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N OV E M B E R 2 0 1 9
Strengthening Hydromet and Early Warning Systems and Services in GeorgiaA Road Map
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©2019 The World Bank Group1818 H Street NWWashington D.C. 20433, USAInternet: www.worldbank.org
Disclaimer: This report is a product of staff of the World Bank Group with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent.
The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.
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ACKNOWLEDGMENTS _______________________________________________________________________________________ 6
ABBREVIATIONS _____________________________________________________________________________________________7
EXECUTIVE SUMMARY ______________________________________________________________________________________9
1. INTRODUCTION TO THE ROAD MAP AND TO GEORGIA’S GEOGRAPHY, WEATHER, AND CLIMATE _________________________________________________________________16
2. WEATHER, CLIMATE, AND HYDROLOGICAL RISKS _____________________________________________________21
3. SOCIOECONOMIC IMPACTS OF HYDROMET HAZARDS _________________________________________________24
4. ASSESSMENT OF USER NEEDS FOR WEATHER, CLIMATE, AND HYDROLOGICAL SERVICES________25
5. INSTITUTIONAL AND ORGANIZATIONAL ANALYSIS: A BRIEF HISTORY OF THE GEORGIAN HYDROMETEOROLOGICAL DEPARTMENT __________________________________________________27
6. CURRENT STATUS OF GHMD _____________________________________________________________________________30
6.1 SERVICE DELIVERY SYSTEMS _______________________________________________________________________32
6.2 QUALITY MANAGEMENT SYSTEMS __________________________________________________________________36
6.3 CAPACITY BUILDING __________________________________________________________________________________38
6.4 MONITORING AND OBSERVATION SYSTEMS ________________________________________________________39
6.5 ICT SYSTEMS: TELECOMMUNICATION SYSTEMS (DATA EXCHANGE AND DISTRIBUTION SYSTEM, TRANSMISSION) ___________________________________________________________47
6.6 MODELING SYSTEMS _________________________________________________________________________________50
6.7 OBJECTIVE AND IMPACT-BASED FORECASTING AND WARNING SYSTEMS _______________________52
6.8 SUMMARY OF THE CURRENT STATUS OF THE GHMD SYSTEMS ___________________________________57
7. MODERNIZATION OF METEOROLOGICAL AND HYDROLOGICAL SERVICES AND EWS _______________58
7.1 VALUE CHAIN APPROACH ____________________________________________________________________________58
7.2 DEVELOPMENT PARTNERS AND COOPERATION ____________________________________________________62
8. PROPOSED ROAD MAP FOR MODERNIZATION OF THE GEORGIAN HYDROMETEOROLOGICAL DEPARTMENT _______________________________________________________________63
8.1 DELIVERY OF SERVICES ______________________________________________________________________________63
8.2 INSTITUTIONAL STRENGTHENING AND CAPACITY BUILDING ______________________________________69
8.3 MODERNIZATION OF OBSERVATION INFRASTRUCTURE, DATA MANAGEMENT SYSTEMS, AND FORECASTING _______________________________________________72
9. ROAD MAP SCENARIOS __________________________________________________________________________________80
9.1 SCENARIO 1: TECHNICAL ASSISTANCE FOR HIGH-PRIORITY AND IMMEDIATE NEEDS ___________83
9.2 SCENARIO 2: INTERMEDIATE MODERNIZATION _____________________________________________________90
9.3 SCENARIO 3: ADVANCED MODERNIZATION _________________________________________________________95
10. SOCIOECONOMIC BENEFITS OF IMPROVED HYDROMETEOROLOGICAL SERVICES AND EWS ____104
10.1 CONSERVATIVE APPROACH ________________________________________________________________________104
10.2 BENEFITS FROM AVOIDED DISASTER LOSSES____________________________________________________105
10.3 BENEFIT ANALYSIS _________________________________________________________________________________106
TABLE OF CONTENTS
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10.4 VERIFICATION _______________________________________________________________________________________106
10.5 BENEFITS FROM INCREASED PRODUCTION ______________________________________________________107
10.6 TOTAL ANNUAL BENEFITS __________________________________________________________________________107
10.7 COST-BENEFIT ANALYSIS __________________________________________________________________________108
10.8 CONCLUSIONS ______________________________________________________________________________________110
11. CONCLUSIONS AND A WAY FORWARD ________________________________________________________________111
ANNEX 1. REQUIRED TRAINING AREAS ___________________________________________________________________113
ANNEX 2. COMPLETED AND ONGOING PROJECTS _______________________________________________________114
ANNEX 3. SERVICE DELIVERY PROGRESS MODEL _______________________________________________________128
ANNEX 4. OBSERVATION AND TELECOMMUNICATION PROGRESS MODEL _____________________________130
ANNEX 5. MODELING AND FORECASTING PROGRESS MODEL __________________________________________131
ANNEX 6. CLIMATE SERVICES PROGRESS MODEL _______________________________________________________132
ANNEX 7. HYDROLOGICAL SERVICES PROGRESS MODEL ______________________________________________133
REFERENCES _______________________________________________________________________________________________134
Figure 1. Schematic of an NMHS as a system of systems _____________________________________________________13
Figure 2. Physiographic features of Georgia __________________________________________________________________17
Figure 3. Köppen climate classification map of Georgia _______________________________________________________18
Figure 4. Provinces of Georgia ________________________________________________________________________________19
Figure 5. Number of hydrometeorological hazards (2012–2016) ______________________________________________21
Figure 6. Percentage of provincial GDP affected by floods with 10- or 100-year return periods ________________25
Figure 7. NMHS System of systems and subsystems _________________________________________________________31 Figure 8. Development of the meteorological observation network in Georgia _________________________________42 Figure 9. Historical development of the hydrological observation network in Georgia __________________________43 Figure 10. The current ICT system at GHMD __________________________________________________________________49 Figure 11. Schematic of global observing, telecommunication, data processing, forecasting, and dissemination system ____________________________________________59 Figure 12. Hydromet production value chain __________________________________________________________________60
Figure 13. Schematic of NMHS modernization ________________________________________________________________61
Figure 14. Data flow in hydrometeorological services _________________________________________________________62
Figure 15. Service delivery systems of modernized GHMD____________________________________________________64
Figure 16. Monitoring and feedback systems for service delivery _____________________________________________64
Figure 17. Stages and elements of hydrometeorological service delivery _____________________________________65
Figure 18. Quality management systems ______________________________________________________________________70 Figure 19. Technology infusion systems_______________________________________________________________________70
Figure 20. Capacity building __________________________________________________________________________________71
Figure 21. Monitoring and observing systems _________________________________________________________________72
Figure 22. Information and communication technology systems _______________________________________________74
LIST OF FIGURES
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Figure 23. The recommended integrated data center for the GHMD environment _____________________________75
Figure 24. Modeling systems _________________________________________________________________________________76
Figure 25. Forecasting and warning systems _________________________________________________________________76
Figure 26. Annual financial and economic flows of Scenario 3 investment with “realistic” benefits and 5 percent assumed discount rate _____________________________________________________________110
Table 1. Overview of the costs of the three scenarios: Total annual investment, operating, and staff costs ____14
Table 2. Expected outcomes of fully modernizing GHMD ______________________________________________________15
Table 3. Income and expenditure of GHMD ___________________________________________________________________30
Table 4. Examples of primary, secondary, and tertiary hazards cascading from hydrometeorological events ___52
Table 5. Additional staff and staff costs required to implement Scenario 1 _____________________________________88 Table 6. Additional staff and staff costs required to implement Scenario 2 _____________________________________93
Table 7. Additional staff and staff costs required to implement Scenario 3 _____________________________________99
Table 8. Summary of impact of each modernization scenario on GHMD capabilities according to the progress models ____________________________________________101 Table 9. Overview of additional staff requirements and annual staff costs of the three modernization scenarios _________________________________________102 Table 10. Overview of the costs of the three scenarios: Total investment, operating, and staff costs __________103
Table 11. Average annual losses due to natural hazards _____________________________________________________105 Table 12. Triangulation and verification of annual average losses due to hydrometeorological hazards _______106 Table 13. Annual benefits attributed to modernized hydrometeorological services ____________________________107 Table 14. Cost-benefit analysis results for Scenario 1 ________________________________________________________108
Table 15. Cost-benefit analysis results for Scenario 2 ________________________________________________________109
Table 16. Cost-benefit analysis results for Scenario 3 ________________________________________________________109
Table 17. Cost-benefit analysis results: Minimum benefits and 30 percent cost overruns _____________________109
Photo 1. A massive landslide at the conjunction of the Tergi and Amali-Devdoraki Rivers, 2014 _______________23
Photo 2. The historical weather observatory in Tbilisi _________________________________________________________41
Photo 3. Historical archives of the work of Joseph Stalin at the weather observatory of Tbilisi ________________41
Photo 4. Examples of historical data archives _________________________________________________________________46
Photo 5. The telecommunication system at GHMD headquarters _____________________________________________48 Photo 6. The visualization system at the forecast office _______________________________________________________55
Photo 7. Modern public weather service delivery in Indonesia _________________________________________________67
Photo 8. Modern Forecasting office environment in the Australian Bureau of Meteorology ____________________78
LIST OF TABLES
LIST OF PHOTOS
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This report was prepared by the Global Facility for Disaster Reduction and Recovery/World Bank Group as part of the Georgia Disaster Risk Management (DRM) Program. It presents a potential pathway to strengthen the country’s hydrometeorological (hydromet) and early warning systems and services (EWS) in accordance with the needs of the user community. The report is based on a technical evaluation and detailed assessment of the needs and capacities of the Georgian Hydrometeorological Department (GHMD), which as the main service provider in the country issues weather and water-related forecasts and warnings. Other government agencies that are responsible for the provision of advisory services related to weather, climate, hydrology, disaster management, and agriculture to end users are considered key GHMD stakeholders. Among stakeholders, the most important are the Ministry of Environmental Protection and Agriculture (MEPA), the Emergency Management Service (EMS), the Road Department of the Ministry of Infrastructure and Regional Development (MIRD), the Power Engineering Department of the Ministry of Economy and Sustainable Development (MoESD), and various municipalities across Georgia. This report identifies gaps and challenges in the production and delivery of weather, climate, and hydrological information and services, and it proposes a strategy for improving the country’s institutional capacity to save lives and livelihoods and to support social and economic development. The authors consulted a number of government institutions and agencies (including several among those listed above) as well as development partners and donors. The report is the result of a collaboration between the Government of Georgia and the World Bank.
The authors wish to extend their appreciation to and acknowledge the national agencies, ministries, and organizations for their support and assistance in granting access to information, for providing support to the report, and for being available for discussions during the report’s assessment.
For reviewing and improving on the earlier version of the road map, the authors would like to thank Makoto Suwa, Senior DRM Specialist, Melanie Simone Kappes, DRM Specialist, and Arati Belle, DRM Specialist, all of the World Bank; and Milan Dacic, World Meteorological Organization (WMO) Representative for Europe.
This road map was authored by Haleh Kootval, Senior Technical Specialist, Meteorology and Public Weather Service; Andreas Schumann, Senior Technical Specialist, Hydrology; Alice Soares, Senior Technical Specialist, Forecasting; Vladimir Tsirkunov, Lead Specialist; Daniel Kull, Senior DRM Specialist; Tafadzwa Dube, DRM Specialist and Task Team Leader; and Vica Bogaerts, Senior DRM Specialist and Task Team Leader.
Finally, the team is grateful for the financial support received from the Global Facility for Disaster Reduction and Recovery (GFDRR) and its Japan-World Bank Program for Mainstreaming DRM in Developing Countries.
Editing: Anne Himmelfarb
Design: Johanna Mora
Cover photo: Andreas Schumann, World Bank.
ACKNOWLEDGEMENTS
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ABBREVIATIONS
AWS Automatic Weather Station(S)
CAP Common Alerting Protocol
CONOPS Concept of Operations
DRM Disaster Risk Management
ECMWF European Centre for Medium-Range Weather Forecasts
EMS Emergency Management Service
EPS Ensemble Prediction Systems
EU European Union
EUMETSAT European Organisation for the Exploitation of Meteorological Satellites
EUWI+ European Union Water Initiative Plus for Eastern Partnership Countries
EWS Early Warning Systems And Services
FAO Food and Agricultural Organization of the United Nations
FEWS Flood Early Warning System
FFGS Flash Flood Guidance System
FTP File Transfer Protocol
GCF Green Climate Fund
GDP Gross Domestic Product
GFDRR Global Facility for Disaster Reduction and Recovery
GFS Global Forecast System
GHMD Georgian Hydrometeorological Department
GIS Geographic Information System
GSE Georgian State Electrosystem
GTS Global Telecommunication System
ICAO International Civil Aviation Organization
ICT information and communication technology
ISO International Organization for Standardization
IT Information Technology
JICS Japan International Cooperation System
LAM Limited Area Model
LEPL Legal Entity of Public Law
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LiDAR Light Detection and Ranging
m3/s Cubic Meters Per Second
m.a.s.l. Meters Above Sea Level
Mbps Megabit Per Second
MEPA Ministry of Environmental Protection and Agriculture
MFI Météo France International
MIRD Ministry of Infrastructure and Regional Development
MoESD Ministry of Economy and Sustainable Development
MOU Memorandum of Understanding
NEA National Environmental Agency
NCEP National Centers for Environmental Prediction (U.S)
NMHS National Meteorological and Hydrological Service
NOAA National Oceanic and Atmospheric Administration (U.S.)
NWC SAF Satellite Application Facility for Nowcasting
NWP Numerical Weather Prediction
O&M Operations And Maintenance
PWS Public Weather Service
QA/QC Quality Assurance And Quality Control
QMS Quality Management System
RCD Regional Climate Downscaling
SEECOF South East Europe Outlook Forum
SLA Service-Level Agreement
SMEs Small And Medium Enterprises
SOP Standard Operating Procedure
TSMS Turkish State Meteorological Service
UNDP United Nations Development Programme
USAID United States Agency for International Development
WFD Water Framework Directive
WIGOS WMO Integrated Global Observing System
WIS WMO Information System
WMO World Meteorological Organization
WRF Weather Research and Forecasting
ABBREVIATIONS (CONT’D)
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EXECUTIVE SUMMARY
Purpose of the Road Map This analytical work assesses the current capabilities of, as well as the gaps and challenges faced by, the Georgian Hydrometeorological Department (GHMD) in producing and delivering weather, climate, and hydrological (hydrometeorological) products and services based on users’ needs. It provides the government authorities and decision makers in Georgia with a technical strategic framework for improvements in hydromet and early warning systems and services (EWS), to provide socioeconomic benefits to the Georgian population; safeguard their lives, livelihoods, and property; and protect economic investments.
The road map consists of 11 chapters. Chapters 1–3 highlight the climate and hydrological hazards affecting Georgia, their consequent risks, and the socioeconomic impacts on the Georgian people. Chapter 4 provides an assessment of users’ needs for hydromet information. Chapter 5 gives an overview of the institutional and organizational structure of GHMD, while chapter 6 provides an in-depth analysis of GHMD’s current status. Chapter 7 discusses modernization of hydromet and EWS. Chapters 8 and 9 present the road map in detail, along with three proposed successive development scenarios designed to transform GHMD into a technically modern and sound hydrometeorological service by narrowing the gap between GHMD’s current status and the level of services needed for fully discharging its public service mandate. Chapter 10 presents a detailed socioeconomic benefits analysis. Finally, chapter 11 lays out the conclusions and a way forward, and several annexes provide additional details.
IntroductionGeorgia has a total area of 69,700 km² and a very varied topography. It is located in the Caucasus region and is bordered by the Russian Federation to the north and northeast, Azerbaijan to the southeast, Armenia and Turkey to the south, and the Black Sea to the west. Georgia is subdivided into 12 provinces, including the capital Tbilisi.
Mountains cover about 54 percent of the total area, with the highest peak at 5,068.8 m above sea level. The country is crisscrossed by 26,060 rivers. The climate is diverse, with almost all types of climate regimes represented. The country is highly exposed to a wide range of hydrometeorological hazards, including droughts, floods, landslides, mudflows, and avalanches.
Flood monitoring and meteorological observations have a long history in Georgia that dates back to the mid-19th century. The GHMD has been and continues to be the primary source of public hydromet information, warnings, and services in the country.
The collapse of the Soviet Union in 1990 delivered setbacks to Georgia’s hydrometeorological services, leading to degradation of traditional observation networks and—compared with the public services provided by Western European hydrometeorological services—a prevalence of outdated and inefficient technologies in most areas of work. For example, GHMD cannot make the best possible use of Numerical Weather Prediction (NWP) available from the world’s leading centers for weather forecasting and climate Georgia has a total area of 69,700 km² and a very varied topography. It is located in the Caucasus region and is bordered by the Russian Federation to the north and northeast, Azerbaijan to the southeast, Armenia and Turkey to the south, and the Black Sea to the west. Georgia is subdivided into 12 provinces, including the capital Tbilisi.
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With support from donors and development agencies, including the World Meteorological Organization (WMO), World Bank, United States Agency for International Development (USAID), United Nations Development Programme (UNDP), the Czech Republic, Finland, Switzerland, and others, GHMD was partially rehabilitated, and it has been financed with a regular but small budget since 2010. Today, GHMD is a Legal Entity of Public law (LEPL) under the National Environmental Agency (NEA) of the Ministry of Environmental Protection and Agriculture (MEPA) of Georgia. There is no hydrometeorological law in Georgia. However, a general regulation (not passed through the Parliament) on hydrometeorology issued by the minister of environmental protection and agriculture spells out the obligations, functions, and responsibilities of GHMD. The need for and advantages of a national legal framework for meteorological and hydrological operations are elaborated and strongly supported by the World Bank (Rogers and Tsirkunov 2013). As of June 2019, GHMD has a total workforce of 134 employees and 48 consultants. Based on available data, the total budget and operating expenditures of GHMD in 2018 were US$1.48 million, of which approximately US$895,000 was staff costs. The overall trend of reduction of the GHMD budget, from US$1.74 million in 2015 to the proposed US$1.16 million in 2020, is very alarming, as this budget is well below the minimum needed to protect people’s safety and support national development.
GHMD’s key government stakeholder agencies are MEPA, the Emergency Management Service (EMS), the Road Department of the Ministry of Infrastructure and Regional Development (MIRD), and the Power Engineering Department of the Ministry of Economy and Sustainable Development (MoESD). In addition, there are two specialized government aeronautical and marine agencies providing weather services on a full cost-recovery basis.
Large international private firms offer basic weather forecasts to the public through popular mobile applications. However, at present private companies do not seem interested in providing tailored services. This may change in the future with the development of the economy and potential growth of the private sector engaged in hydrometeorology. In such a future environment, the role of GHMD would be to focus on addressing the most pressing needs in order to provide public services, while setting up a regulatory framework with respect to the operation of the private sector. Given the current and projected economic situation, GHMD is expected to continue as the principal public service provider in the medium term (next 8–10 years).
The specialized research institutions in meteorology and hydrology, which were active some 25–30 years ago, appear to be weak now and do not provide any significant support to GHMD operational activities.
Socioeconomic Impact of Hydromet HazardsDisasters originating from hydrometeorological hazards have impacted a high percentage of the territory of Georgia. Losses incurred between 1995 and 2013 as a result of landslides, floods, drought, storms, avalanches, and hail were estimated at approximately US$1 billion. Landslides, debris flows, and mudslides have destroyed irrigation systems, agricultural facilities, and road infrastructure. The severe drought of 2000 affected almost 700,000 people, and its adverse effects reduced gross domestic product by 5.6 percent. Floods are among the most frequent and destructive of disasters and have been the source of fatalities and millions of dollars’ worth of economic loss.
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Services ProvidedGHMD is expected to have the capability and capacity to meet users’ needs by (i) producing, managing, translating, and communicating timely, accurate, and actionable hydromet data and information to stakeholders and end users; (ii) assisting stakeholders and end users in accessing, interpreting, and utilizing the generated data and information; (iii) helping disseminate and respond to warnings for public safety and economic security; (iv) informing planning and decision making for cost-effective investments in national climate-resilient development; and (v) making optimum use of all investments from government and development partners.
The public weather forecasts produced by GHMD for the territory of Georgia are limited to 24-hour, three-day, and seven-day forecasts and 10-day outlooks. No agrometeorological forecasts are produced. Hydrological forecasts are produced for 20 stations for two days ahead on a manual basis. No hydrological model is used to produce forecasts of water levels. Information is disseminated to users via GHMD’s website, a Facebook page on the website of the NEA, and SMS messages to a list of subscribers within the government only. No weather applications have been developed for mobile platforms. GHMD does not have a presence on broadcast media, although it did in the past when it was paid for providing services to the media. There is no direct mechanism for feedback from stakeholders.
This road map uses a series of progress models to measure GHMD’s capacities in several key areas (service delivery, observation and telecommunication, and modeling and forecasting). The Service Delivery Model draws on the model developed by the World Meteorology Organization (WMO 2014); the other two models were developed by the World Bank based on the Service Delivery Model. All these models rate GHMD’s performance on a 1 to 5 scale (Undeveloped to Advanced).
According to the Service Delivery Progress Model of the WMO Strategy for Service Delivery, (WMO 2014), which is based on a scale of 1 to 5 (Undeveloped, Development Initiated, Development in Progress, Developed, Advanced), the current level of GHMD’s meteorological and hydrological service delivery capability is between Levels 2 and 3. In order to ensure that GHMD can deliver services to meet users’ needs, its capability should be at a full Level 4 (Developed). This is the level that the third of the investment scenarios proposed in this road map is designed to meet. (All three scenarios are described in more detail below.) This would put Georgia at a level of service delivery similar to Croatia, a relatively small European country that has developed a strong hydromet and EWS culture.
For comparison, countries that provide services at an advanced level (Level 5) include the United Kingdom, Australia, China, Austria, and Switzerland, among others.
ChallengesThe most important challenge faced by GHMD is that the Government of Georgia may not be fully aware of the value of meteorological and hydrological services for public safety and for weather-, climate-, and hydrology-sensitive economic development. To compete for and optimally use scarce public resources, GHMD must justify the investment of public funds to support its basic infrastructure, operations, and development of services. To demonstrate the benefits to users, however, GHMD must first be able to provide services that satisfy users, which it cannot do unless it has sufficient staff, upgraded forecasting and ICT (information and communication technology) infrastructure, and service provision capability. This is a cycle whereby the gap in GHMD’s available resources and ability to serve its mandate keeps widening.
Other main challenges are listed on the next page.
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OBSERVING NETWORKSGeorgia is in need of a properly designed national meteorological and hydrological network based on users’ requirements.
GHMD’s existing observation network consists of surface meteorological, agrometeorological, road meteorological, hydrological, and snow monitoring stations. No rating curve exists at 50 percent of the hydrological gauges. There is no functioning upper-air monitoring station, which is essential for improvements in forecasts. Remote surface and space-based observations are obtained from three radars (not operated by GHMD) and the EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) satellites via EUMETCast.
As a first step in following best practice and adherence to WMO standards, GHMD requires a careful review of the network to determine the number and location of stations, their purpose, and their current functional capability (e.g., whether they are capable of real-time data transmission). This information is essential to identify gaps and redundancies.
The existing ICT discrepancies and incompatibilities between the observing network and forecasting systems arise mainly from inadequacies in the routing and processing of data and from use of inappropriate forecast model and observation formats. These discrepancies have resulted in less than optimal functioning of the ICT and forecasting systems. To address this issue, the following are the most important priorities: fixing the data format issues, undertaking operational data quality control and direct data archiving in a consolidated data center; and updating computer infrastructure to allow direct access to real-time data.
GHMD’s current observation and telecommunication capability is at Level 2 (Development Initiated) according to the scale of the Observation and Telecommunication Progress Model. In order to deliver services and support forecasting systems at Level 4 (Developed), the capability of the observing and telecommunication systems should be raised to Level 5 (Advanced) by the completion of the proposed Scenario 3. It should be noted that this improvement does not necessarily depend on an expansion of the observation network, but rather on improvement in data quality, accessibility, sustainability, and usage, including sufficient technical and financial capacity for operation and maintenance.
MODELING AND FORECASTING INFRASTRUCTUREThe current modeling and forecasting capability falls between Levels 2 and 3 (Development Initiated and Development in Progress) on the scale for the Modeling and Forecasting Progress Model. In order to deliver services at a Developed level, the capability of the forecasting systems should be raised to Level 4; this would enable the performance of functions as stated in Scenario 3 of the road map.
PROPOSED MODERNIZATION OF HYDROMETEOROLOGICAL SERVICES AND EWSA typical National Meteorological and Hydrological Service (NMHS) is composed of a complex “system of systems,” as shown in figure 1. This generic illustration of a weather, climate, and hydrological system of systems can be used to identify the current status of any NMHS and to visualize investments required in each system, component by component, to achieve a particular level of improvement. The complexity of each system varies depending on the size, level of development, and resources of the individual NMHS. But the system-of-system building blocks are interdependent. Users’ requirements are an essential ingredient for the design and implementation of the entire system. A key requirement is to have staff with the capacity to understand and operate the system. This road map for Georgia uses a system-of-systems approach to arrive at the three scenarios for modernizing the GHMD.
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FIGURE 1. SCHEMATIC OF AN NMHS AS A SYSTEM OF SYSTEMS
Monitoring and Observing Systems
Modelling Systems
Objective and Impact Forecasting and
Warning Systems Service Delivery Systems
Actions, Services, Monitoring and
Feedback Systems
Quality Management Systems
ICT Systems
Technology Infusion Systems
CAPACITY BUILDINGSource: Rogers et al. 2019.A substantial modernization program for any NMHS should include three components, namely (i) enhancement of the service delivery system; (ii) institutional strengthening and capacity building; and (iii) modernization of observation, ICT, and forecasting infrastructure (Rogers and Tsirkunov 2013). The development of this road map is in line with this principle. The activities proposed aim to strengthen the GHMD’s institutional basis: to enhance the existing legal and regulatory framework and to develop the capacity of staff; to technically modernize the observation, ICT, data management, and hydromet forecasting infrastructure, facilities, and procedures; and, most importantly, to improve the delivery of hydromet and early warning services and information to the population and to the sectors most affected by weather, climate, and hydrology—mainly agriculture, transport, energy, and water resources management.
This road map lays out three scenarios for modernization: • Scenario 1: Technical Assistance
• Scenario 2: Intermediate Modernization
• Scenario 3: Advanced Modernization
Each contributes in different and progressively more comprehensive ways, based on the time and resources available to GHMD, to produce and deliver (i) timely warnings of extreme and hazardous weather events and their potential impacts, and (ii) forecasts for operations and planning in weather-, climate-, and hydrology-sensitive economic sectors, particularly agriculture, transport, energy, and water resources management.
There are two possibilities for building and implementing each scenario. The first is that these scenarios could be interdependent and conducted in phases, in which case each would build on the previous one to contribute to the overall goal of modernization. That is, Scenario 2 assumes the accomplishment of objectives in Scenario 1 and builds on them. Similarly, Scenario 3 assumes the achievement of goals in Scenarios 1 and 2 and builds on those. The second possibility is that if resources are made available to undertake the modernization as a stand-alone package, then the chosen scenario will include activities under any subordinate scenario. For example, if resources are made available for Scenario 3, then this scenario will also comprise the activities as described under Scenarios 1 and 2. Similarly, a stand-alone package under Scenario 2 will comprise activities contained in Scenario 1. Below, the cost of Scenarios 2 and 3 is provided both for the phased and the stand-alone approaches. An overview of the costs for the three scenarios—including investment, operation, and staff—is presented in table 1.
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Scenario 1: Technical Assistance. This scenario provides technical assistance over the immediate to short term (two years) for high-priority activities to improve basic public services by introducing high-priority and affordable new technologies and training the staff for heightened capacities and capabilities. The approximate cost of implementing this scenario is expected to be US$1.13 million.
Scenario 2: Intermediate Modernization. This scenario makes investments to modestly improve GHMD’s ability to provide weather and hydrological services that meet the needs of the most important user communities, for example, disaster management, agriculture, transport, and water resources management. In the phased approach, the implementation of this scenario is expected to follow Scenario 1 and would additionally cost US$2.13 million. The stand-alone approach would require a total cost of US$3.26 million invested over four years.
Scenario 3: Advanced Modernization. This scenario should bring GHMD the ability to provide fit-for-purpose data, forecasts, and warning services for the safety of the public, and support to develop the most important socioeconomic sectors. In the phased approach, this scenario is expected to follow Scenario 2 and would additionally cost US$3.72 million to implement. The stand-alone approach would require a total cost of about US$7 million invested over seven years.
TABLE 1. OVERVIEW OF THE COSTS OF THE THREE SCENARIOS: TOTAL ANNUAL INVESTMENT, OPERATING, AND STAFF COSTS
Cost estimates for three
scenarios (US$)(stand-alone
version)
Investments in main GHMD systemsTotal
investment cost
Total annual
operating cost
Total annual staff
cost (expected at the end of scenario)
Hydro Met ICT
Current n.a. n.a. n.a. n.a. 589,355 894,759
Scenario 1 224,000 360,000 546,000 1,130,000 693,751 1,075,335
Scenario 2(including
Scenario 1) 378,000 972,000 1,910,000 3,260,000 784,959 1,217,607
Scenario 3 (including
Scenario 2)1,344,700 2,425,400 3,210,000 6,980,000 1,019,355 1,409,127
Note: n.a. = not applicable.
It is estimated that the total annual GHMD budget by the end of the seven-year implementation period (Scenario 3) should exceed US$2.4 million to make this investment sustainable. This estimate includes an overall operating cost of over US$1 million and GHMD staff costs of about US$1.4 million. To achieve the projected results of Scenario 3, the government will need to meet two main conditions: (i) it must make investment resources from development partners or national projects directly available to support activities of Scenario 3; and (ii) it must significantly increase GHMD staff by recruiting over 90 trained specialists and technicians, and must also allocate additional financial resources to operate the modernized GHMD systems. The second condition entails increasing GHMD staff by about 70 percent and increasing the current GHMD budget by the end of the seven-year period by more than 90 percent; this is challenging but still considered affordable. It is clear that current GHMD staff numbers and skills are inadequate to respond to basic public needs, and that this large expansion in staff capacity is needed to achieve a
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measurable improvement. Alternatives to recruiting a large cadre of permanent staff could be outsourcing (e.g., in ICT and equipment maintenance) and contracting the more sophisticated hydromet modeling and forecasting activities to a more advanced organization while GHMD recruits and trains its own staff. Initial commitments made by MEPA are promising, and an increase of GHMD staff by some 20 persons in three years may be anticipated.
The overall expected outcomes following a full modernization (Scenario 3) are shown in table 2.
TABLE 2. EXPECTED OUTCOMES OF FULLY MODERNIZING GHMD
Hydrological component Outcomes
ObservationsModerate expansion of observation network. Increases in hydrometric capacities to ensure the proper operation of expanded network (discharge measurements, rating curves)
ModelingAdaptation of existing and development of new flood models with an extended hy-drological database, validation and calibration of flood and water balance models, permanent updating to provide results according to user needs
Forecasting Numerical hydrological discharge forecasts for more than 100 gauges and many other points of interests
Hydrological analysesServices such as annual updated flood statistics, water balances, climate change assessments, reports about quantitative hydrology for the implementation of the Water Framework Directive, drought forecasts and monitoring, assessments of anthropogenic impacts on the hydrological conditions
Meteorological component Outcomes
Observations
Support for the operation and maintenance of surface-based remote sensing (Doppler radars)
Moderate expansion of observation network, with support for the operation and maintenance of the expanded network, including upper air
Support for the operation of the calibration laboratory
Use of model products (objective forecast) Enhanced use and adaptation of NWP for forecasting on all time scales
Advancing of impact-based, probabilistic
forecasting and verification
Implementation of real-time forecast process monitoring, quality control of observations; nowcasting; seasonal forecast licenses, dissemination of products; flash flood warning and alert systems; full operationalization of impact-based forecast and warning services; strengthening of end-to-end EWS
Service delivery
Application of all the tools for service delivery, including strategy for service delivery; hydrometeorological user group; Concept of Operations; Memorandums of Understanding and standard operating procedures; new and improved user-tailored products; evaluation of forecast utility and user satisfaction; further improvement of dissemination mechanisms; development of an Agriculture and Climate Advisory Service portal; stakeholder training; public education
ICT component Outcomes
Development of ICT for both met and hydro
Installation and operationalization of a centralized data center; procurement and installation of the full set of the hardware and software required for a modern forecast and warning system; service delivery platform and applications, data management, and dissemination
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SOCIOECONOMIC BENEFITS OF IMPROVED HYDROMET SERVICES AND EWSIt is now a common practice for hydromet service providers to undertake a cost-benefit analysis to secure and optimize the use of investment resources. These analyses have uniformly demonstrated that the benefits of hydromet services are significantly larger than the capital and operational costs needed to modernize, produce, and deliver them.
To optimize investment benefits, the GHMD modernization must focus on delivering services using all possible mechanisms and channels to reach end users, and on ensuring that users can productively apply those services.
Recent assessments have applied different methodologies, as described in Valuing Weather and Climate: Economic Assessment of Meteorological and Hydrological Services (WMO et al. 2015). These include further-refined, sector-specific, and benchmarking approaches.
The cost-benefit analysis indicates that all three proposed investment scenarios are economically efficient, meaning they will produce socioeconomic benefits greater than their costs. In all cases the generated benefits are significantly greater than the costs.
1. INTRODUCTION TO THE ROAD MAP AND TO GEORGIA’S GEOGRAPHY, WEATHER, AND CLIMATE
1.1 The Road MapThis analytical work assesses the current capabilities of, as well as the gaps and challenges faced by, the Georgian Hydrometeorological Department (GHMD) in producing and delivering weather, climate, and hydrological (hydrometeorological) products and services based on users’ needs. It provides the government authorities and decision makers in Georgia with a technical strategic framework for improvements in hydromet and early warning systems and services (EWS), to provide socioeconomic benefits to the Georgian population; safeguard their lives, livelihoods, and property; and protect economic investments.
The road map consists of 11 chapters. Chapters 1–3 highlight the climate and hydrological hazards affecting Georgia, their consequent risks, and the socioeconomic impacts on the Georgian people. Chapter 4 provides an assessment of users’ needs for hydromet information. Chapter 5 gives an overview of the institutional and organizational structure of GHMD, while chapter 6 provides an in-depth analysis of GHMD’s current status. Chapter 7 discusses modernization of hydromet services and EWS. Chapters 8 and 9 present the road map in detail, along with three proposed successive development scenarios designed to transform GHMD into a technically modern and sound hydrometeorological service by narrowing the gap between GHMD’s current status and the level of services needed for fully discharging its public service mandate. Chapter 10 presents a detailed socioeconomic benefits analysis. Finally, chapter 11 lays out the conclusions and a way forward, and several annexes provide additional details.
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1.2 Georgia’s Geographical Features and Weather and Climate Regime
Despite its relatively small area (69,700 km²), Georgia has one of the most varied topographies of the former Soviet republics. It is located in the Caucasus region and is bordered by the Russian Federation to the north and northeast, Azerbaijan to the southeast, Armenia and Turkey to the south, and the Black Sea to the west, with a coastline of 309 km.
The territory of Georgia extends vertically to 5,068.8 m above sea level (the Shkhara peak). The relief of Georgia is characterized by high, medium, and low mountains as well as uplands and plains: mountains cover about 54 percent of the total area, highlands about 33 percent, and valleys some 13 percent. The principal orographic features are the Greater Caucasus Mountains in the north, the Lesser Caucasus range in the south, and the Surami and Imereti ranges, which connect the Greater Caucasus and the Lesser Caucasus. The Kolkhida Lowlands front the Black Sea in the west. Some of the peaks of the main watershed ridge of the Caucasus Mountains in Georgia are higher than 5,000 m above sea level, although about 70 percent of the country lies less than 1,700 m above sea level (figure 2).
FIGURE 2. PHYSIOGRAPHIC FEATURES OF GEORGIA
Source: Elevation data are from U.S. Geological Survey, HYDRO1K database.
Note: m.a.s.l. = meters above sea level.
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The climate of Georgia is characterized by great diversity. Almost all types of climate regimes are represented, with the exception of desert, savanna, and tropical forests. Georgia has an average rainfall of 1,026 mm/year (World Bank 2015). The Likhi range divides the territory into two main regions with dramatically differing climate regimes. Eastern Georgia has a subtropical dry climate, with fairly cold winters and arid, hot summers. The average precipitation varies between 500 and 1,100 mm/year. About 80 percent of the rainfall occurs from March to October, and the longest dry period is about 50–60 days. Droughts are common, and hail occurs in spring and autumn. The temperatures vary between elevation zones. The highest lowland temperatures occur in July (about 25°C), while average January temperatures over most of the region range from 0 to 3°C. Western Georgia has a subtropical humid climate, with mild winters and moderate summers. The average precipitation is between 1,100 and 1,700 mm/year. Drainage of excess water is one of the main problems for agriculture in this part of the country. Average temperatures vary between 5°C in January and 22°C in July (World Bank 2015). In the lowlands of western Georgia and the Black Sea coastal zone, mean annual temperature is approximately 14–15°C, and annual precipitation varies in the range of 1,500–2,700 mm. The alpine zone of the same region contains mountain massifs included in the Greater Caucasus; they rise more than 5,000 m above sea level and are covered with permanent snow and glaciers. There are 734 glaciers in Georgia, all located in the Caucasus Mountains. Their cumulative area is 511 km2 (0.7 percent of the total territory of the country) (Geostat 2017).
There is a need for irrigation in the areas where precipitation is less than 800 mm/year. In the plains of eastern Georgia, mean annual temperature is 11–13°C and annual precipitation is around 400–600 mm; in the mountainous regions annual precipitation increases to 800–1,200 mm. During the last 25 years, the mean annual temperature in western Georgia has increased by 0.3°C, and in eastern Georgia the increase has been 0.4–0.5°C (figure 3).
FIGURE 3. KÖPPEN CLIMATE CLASSIFICATION MAP OF GEORGIA
Source: Grigori Balakhadze. Licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
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The river network in Georgia is unequally distributed: out of 26,060 rivers, whose total length is about 60,000 km, 18,109 rivers are in western Georgia and 7,951 rivers in eastern Georgia. Although the total length of 25,075 rivers (99.4 percent) is 54,768 km, the length of most of the individual rivers is less than 25 km. One Georgian curiosity is the Reprua River in the Gagra District of Abkhazia, which is only 27 m long and possibly the shortest named river in the world. The country can be divided into two main basins: the Caspian Sea Basin in the east and the Black Sea Basin in the west. Almost all rivers of central and eastern Georgia drain to the Caspian Sea, mainly through the Kura River and tributaries, while the rivers of western Georgia flow into the Black Sea, with the Rioni River being the largest. The annual runoff generated within the territory of Georgia is 56.9 km3; taking additional inflow of 9.4 km3 into account, the total annual runoff is 66.3 km3. The rivers of Georgia are fed by glaciers, snow, rain, and groundwater. The country has about 860 small lakes (total area 170 km2) and 44 reservoirs (total area of 163 km2), whose total capacity is 13.3 km³. The reservoirs are mainly used for irrigation and electricity production in hydropower plants in addition to water supply and recreation. There are 12 large hydropower plant reservoirs with 2.4 km³ total capacity and 107 km² total area. In 1995, hydropower supplied 89 percent of electricity. The total capacity represents 5.1 percent of annual runoff in Georgian rivers. The Jvari Dam reservoir in the Enguri River in western Georgia has a capacity of 1.1 km3 and an area of 13.5 km²; at an elevation of 271.5m, it is the world’s third highest dam. For the purpose of irrigation, about 30 dams with a total capacity of 1 km3 have been built, mainly in eastern Georgia. The three largest irrigation reservoirs are all on the Iori River: the Sioni reservoir (0.3 km3), the Tbilisi reservoir (0.3 km3), and the Dalimta reservoir (0.18 km3).
Georgia has a population of 3.7 million, excluding Abkhazia and South Ossetia, with 53 percent of its people living in urban areas. It is a middle-income country with a gross domestic product (GDP) of US$13.965 billion and a GDP per capita that increased from $920 in 2003 to US$3,796.2 in 2015 (World Bank and GFDRR 2017a). The past decade has been marked by a pursuit of broad economic reforms that stimulated capital inflow and investments, improved the business environment and infrastructure, strengthened public finances, and liberalized trade (World Bank 2015).
Georgia is subdivided into 12 provinces, including the capital Tbilisi (comprising 67 districts) as shown in figure 4.
FIGURE 4. PROVINCES OF GEORGIA
Note: Region names correspond to numbers in map as follows (with capital cities in parentheses): 1 = Abkhazia (Sukhumi); 2 = Samegrelo-Zemo Svaneti (Zugdidi); 3 = Guria (Ozurgeti); 4 = Adjara (Batumi); 5 = Racha-Lechkhumi and Kvemo Svaneti (Ambrolauri); 6 = Imereti (Kutaisi); 7 = Samtskhe-Javakheti (Akhaltsikhe); 8 = Shida Kartli (Gori); 9 = Mtskheta-Mtianeti (Mtskheta); 10 = Kvemo Kartli (Rustavi); 11 = Kakheti (Telavi); 12 = Tbilisi.
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Agriculture is a relatively important economic sector in Georgia, despite its modest contribution (estimated at 8 percent) to total GDP. The total cultivable area, which according to Georgian statistics is equal to the agricultural area, was estimated in 1996 at 3 million hectares (43 percent of the country). About 2.2 million hectares are forest, which under the 1978 Forest Code cannot be transformed into agricultural cropped areas. A process of land privatization has been under way since the end of the Soviet period. Agricultural production is generally small in scale, but commercial farming is progressively gaining importance. Of the total 3 million hectares of agricultural land, some 0.7 million hectares are owned and cultivated by private farmers, and 2 million hectares are still owned by the state. Most of the state agricultural land is not cultivated. Only about 30 percent is rented, mainly due to the complicated orography, poor soil, distance from inhabited areas, and damaged irrigation and drainage systems.
During the Soviet era, Georgia exported substantial quantities of high-value agricultural products. Following the breakup of the Soviet Union, however, agricultural production plunged. In the 1990s, the state farms and collectives that had dominated Soviet agricultural production were disbanded, and Georgian agriculture came to be characterized by small- scale subsistence farming. In 2005, the total cultivated area was estimated at 1.07 million hectares. Water and wind erosion, environmentally degrading agricultural practices, and other anthropogenic and natural processes have led to an almost 35 percent degradation of farmland. The contribution of the agricultural sector to GDP has fallen significantly over the last decade and a half, from 22 percent in 2000 to about 8.4 percent in 2010. Nonetheless, agriculture provides a safety net for a large number of people and thus serves a very important social function (FAO and Georgian Ministry of Agriculture 2015). However, many of those employed in agriculture are individual subsistence farmers, lacking in skills and resources to move to the next level of productivity. There are about 640,302 agricultural holdings in Georgia. Agriculture remains a very important employment sector, with over 50 percent of the population engaged in agriculture activities; these activities generate 45 percent of the rural income in Georgia, primarily among self-employed semi-subsistence farmers. There are also some larger commercial farms as well as an agribusiness sector providing rural employment.
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2. WEATHER, CLIMATE, AND HYDROLOGICAL RISKS
Georgia is in a highly disaster-prone region and is exposed to a wide range of weather and climate-related risks such as floods, droughts, landslides and rock falls, avalanches, mudflows, hail, and windstorms. The mountainous terrain and varied elevation in Georgia exacerbate disaster risk, and flooding is the most frequent disaster to occur in the country. There is a growing risk of flooding for almost all river basins in Georgia due to climate change if increasing temperatures result in faster melting of snow in higher elevation zones. The high level of precipitation, characteristic of the rivers in the foothills of the Caucasus, has a significant impact on river hydrology. Landslides are especially intense in mountainous regions and represent the main impetus for economic migration. The National Disaster Risk Reduction Strategy of Georgia (2017–2020) cites mudflows and landslides as frequent hazardous events in Georgia that affect thousands of settlements as well as agricultural lands, roads, pipelines, power transmission lines, etc. (Government of Georgia 2017). There are over 50,000 locations with a high risk of landslides, and up to 3,000 potential mudflow paths have been identified on rivers and tributaries. In the period 1968–2009, approximately 70 percent of the country’s territory experienced geological and hydrometeorological hazards, with economic losses exceeding US$14 billion. These events affected 65 percent of the population. Hail and drought in the eastern part of the country cause especially big losses in Georgia’s agricultural sector, and the frequency and length of these hazards have increased in recent years. The longest drought—lasting six months—was recorded in 2000. Figure 5 provides an overview of the number of hydrometeorological hazards that occurred in Georgia between 2012 and 2016, derived from the National Statistics Office of Georgia.
FIGURE 5. NUMBER OF HYDROMETEOROLOGICAL HAZARDS (2012–2016)
0
Flood and Flash Floods
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40
Natural Hazard
Annual Number
of Events
Storm and Squall Hail Heavy Snow Avalanche
2012
2013
2014
2015
2016
Source: Geostat 2017.
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Georgia is prone to several types of floods, including seasonal, synoptic, and flash floods. Seasonal flooding resulting from snowmelt happens in spring and early summer and is sometimes accompanied by synoptic rain with a large spatial extent and long duration. An example of such an event is the exceptional flood of April 1968, when intensive snowmelt together with rain in the upper River Kura in Turkey caused catastrophic flooding in Georgia. Along the River Kura, bank-protecting structures, roads, railroads, and bridges were destroyed. The flood peak passed the city of Tbilisi, with a water discharge of 2,450 m3/s that far exceeded the river’s hydraulic capacity of 1,800 m3/s (Basilashvili, Tabatadze, and Janelidze 2011). The 1895 and 1922 catastrophic floods on the Rioni River caused death and huge economic damage. On January 21, 1987, the Rioni River breached its northern embankment at the village of Sagvichao. A vast territory was inundated for a long period of time and many settlement areas were flooded, leading to some casualties and huge damage to the local agricultural sector. Flash floods are caused by heavy precipitation, sudden releases from river blockages (e.g. from landslides) acting as massive dams, or glacier melt occurring in mountainous areas and lowlands (photo 1). The National Environmental Agency (NEA) of Georgia recorded 164 flood and flash flood events (approximately 31 percent of all hydrometeorological extreme events) and 24 casualties between 1995 and 2010 (World Bank 2015). The Abkhazia and South Ossetia regions, which at present are not under the control of the Georgian government, are not monitored by the Georgian National Hydrometeorological Department. The flooding risk is especially high in the basins of the Imereti, Samegrelo, Guria, and Mtskheta-Mtianeti Rivers, as well as in territories along the River Kura and the left bank of the Alazani River.
Intense rainfall often initiates mudflows and landslides, resulting in multi-hazard events. One example is the Tbilisi flood of June 13, 2015, in the Vere River, a tributary of the Kura River, which took 19 lives, destroyed housing and highway infrastructure, and flooded the zoo. This multi-hazard event occurred when approximately 100 mm of rain fell on already saturated soil in the space of about four hours, causing not only flooding but hundreds of landslides, which brought trees, rocks, and soil down from the hillsides and into the floodwaters of the Vere River. Upon reaching the City of Tbilisi, the flow was constricted by the tunnel system; consequently, the floodwaters were backed up and the stream occupied its historic floodplain. Before 1995, the average return period of intensive flash floods was five to six years. In the 1995–2013 period, this parameter was almost halved (one event in every two to three years). Before 1995, the average number of floods was three to five per year; since 1995, this number has been between 2 and 20 (World Bank and GFDRR 2017a). floodplain. Before 1995, the average return period of intensive flash floods was five to six years. In the 1995–2013 period, this parameter was almost halved (one event in every two to three years). Before 1995, the average number of floods was three to five per year; since 1995, this number has been between 2 and 20 (World Bank and GFDRR 2017a).
23Landslide is one of the most significant of Georgia’s acute natural hazards. More than 22 percent of the country’s territory is at high risk. It is estimated that 70 percent of 53,000 identified landslide locations are occupied by rural populations. During the last 40 years, dozens of villages have been abandoned due to landslides. The effects of climate change coupled with frequent earthquakes and intensified anthropogenic factors have contributed to an increase in the number of landslides, with disastrous consequences in the regions of Racha-lechkhumi, Adjara, Upper Imereti, and the pre-mountain parts of Samegrelo.
Georgia is also susceptible to mudflows. More than 3,000 locations in various mountain river basins are prone to mudflows (the total area represents 2 million hectares). High-risk mudflow zones contain hundreds of populated places, including cities and settlements. More than 1,500 km of roads and 300 km of railways, as well as oil pipelines and irrigation systems, are at risk. The average annual material damage amounts to roughly US$44 million.
Water erosion processes seriously damage the ecosystems of Georgia and have a significant negative influence on the economy. More than 170,000 hectares of land are impacted by erosion. The use of one hectare of arable land causes the erosion of 150–200 tons of soil, and during periods of high precipitation this figure rises to 3,000–5,000 tons.
In recent years, drought has become a frequent problem in Georgia. Drought-related damages amounted to US$15 million for the years 1995–2008. One example is the drought of 2000, which affected almost 50 percent of the country’s territory and continued for six months. In the past, drought affected Georgia once every 15 to 25 years, but in recent times this interval has been reduced to 5 to 8 years.
PHOTO 1. A MASSIVE LANDSLIDE AT THE CONJUNCTION OF THE TERGI AND AMALI-DEVDORAKI RIVERS, 2014
Credit: GHMD.
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More than 50 percent of the country’s territory is located in avalanche risk zones. At present, 5,000 avalanche locations have been identified that threaten more than 200 populated territories. Observations over the last 40 years have shown that avalanches simultaneously affect various regions in the country once every seven to eight years. Landslides and avalanches pose a substantial threat to the Georgian Military Road, an important road connecting Georgia (Tbilisi), Turkey, and Armenia to Russia, and the road meteorological service in this part of the country has a significant role in protecting the traffic on this road.
The entire Caucasus region is susceptible to various seismological events. Georgia is prone to earthquakes as strong as 8 to 9 on the Richter scale, and it experienced strong earthquakes in 1988.
In its Third National Communication to the United Nations Framework Convention on Climate Change (UNFCCC 2015), Georgia assessed climate change based on observations of 33 stations in its hydrometeorological network for the period 1961–2010. Forecast scenarios for 2021–2050 and 2071–2100 were developed using regional climate model RegCM4. The assessment shows an ongoing increase in average temperatures. Sustainable trends in increased precipitation are observed in western Georgia, especially in mountain areas. This trend shows an increase until 2050, followed by a decrease (except for Batumi, Pskhu, and Mta-Sabueti). Similarly, in eastern Georgia the precipitation trend shows an increase by 2050 of 3–4 percent.
3. SOCIOECONOMIC IMPACTS OF HYDROMET HAZARDS
Over the last 40 years, 70 percent of Georgia has experienced disasters originating from hydrometeorological and geological hazards (World Bank and GFDRR 2017a). Losses incurred between 1995 and 2013 as a result of landslides, floods, droughts, storms, avalanches, and hail were calculated at approximately US$1 billion. Landslides, debris flows, and mudslides have destroyed irrigation systems, agricultural facilities, and road infrastructure. The severe drought of 2000 affected almost 700,000 people, and its adverse effect on agriculture and electricity generation by hydropower stations reduced GDP by 5.6 percent. The most devastating floods in Georgia since it gained independence in 1991 occurred in 1997, when two floods caused a total of seven fatalities and over US$40 million in damage. Flooding in 2012 caused less damage (US$3 million) but affected over 100,000 people. Flooding in 2013 affected close to 25,000 people but caused fairly limited damage. Other floods occurred in 1995, 2004, 2005, and 2011, with fewer than 2,500 people affected and less than US$4 million in damage per event. According to the Post-Disaster Needs Assessment (GFDRR 2015), the June 2015 flooding in Tbilisi caused 20 fatalities, affected over 700 people, and caused over US$20 million in damages. All these events highlight Georgia’s vulnerability to floods. Floods are not always devastating, but they follow each other in quick succession and have a large cumulative effect on the country.
Figure 6 depicts the impact of flooding on provincial GDP. It shows the percentage of annual average GDP affected, with greater color saturation indicating a higher percentage. The bar graphs represent GDP affected by floods with return periods of 10 years (white) and 100 years (black). The horizontal line across the bars also shows the annual average of GDP affected by floods.
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FIGURE 6. PERCENTAGE OF PROVINCIAL GDP AFFECTED BY FLOODS WITH 10- OR 100-YEAR RETURN PERIODS
Source: World Bank and GFDRR 2017b.
4. ASSESSMENT OF USER NEEDS FOR WEATHER, CLIMATE, AND HYDROLOGICAL SERVICES
National Meteorological and Hydrological Services (NMHSs) are public agencies mandated to provide public meteorological and hydrological information and warning services, although some may also provide commercial services.
In preparing this road map for Georgia’s NMHS, several of GHMD’s main stakeholders were consulted regarding their use and requirements for products and services from GHMD. Stakeholders included the Environment and Climate Change Department, Hydro-melioration and Land Management Department of the Ministry of Environmental Protection and Agriculture (MEPA), and the National Crisis Management Centre under the Emergency Management Service (EMS). During in-depth discussions with officials from these agencies, it became clear that these stakeholders require a much broader range of products and information—weather forecasts, climate change projections, flood forecasts, hydromet-related early warnings, drought prediction, avalanche forecasts, and landslide forecasts—than they currently receive from GHMD. In addition to hazard forecasts, stakeholders also require information on the impacts of those hazards in order to better inform and alert the public. They require information at various temporal resolutions, ranging from nowcasting (0–6 hours) in case of flash floods to seasonal and longer-range forecasts for planning and preparedness activities, particularly in the water resources management and agriculture sectors. In addition, they need warnings that are more specific to the locations being impacted by the hazards.
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A specific requirement for additional hydrological information became evident in discussions with MEPA. In 2016, Georgia signed a European Union (EU) Association Agreement that has created a framework for co-operation with the EU. According to this agreement, Georgia will implement the EU Water Framework Directive (WFD) as well as the EU directive on the assessment and management of flood risks (Floods Directive). Within the framework of the European Union Water Initiative Plus for Eastern Partnership Countries (EUWI+), the management of water resources in the Eastern Partnership countries has to be improved, in particular management of transboundary rivers. The specific objective is to achieve convergence of national policies and strategies with the EU WFD, integrated water resource management policies, and relevant multilateral environmental agreements. According to the WFD, Georgia has to set up river basin management plans for the six large river basins in the country by 2024. The insufficient discharge data are a crucial problem for ecological planning.
In order to reverse the dramatic decline in crop production, there is an urgent need to rapidly expand the irrigated areas by rehabilitating irrigation infrastructure and improving the management, operation, and maintenance of working irrigation systems. Extensive development of irrigation infrastructure was undertaken during the Soviet era, which resulted in a total irrigated area of 386,000 hectares by the end of the 1980s. By 2000, it was estimated that only about 160,000 hectares was being irrigated—less than half of the area in the 1980s. Deterioration of the irrigation systems continued for another 10 years, and by 2010, only about 24,000 hectares was being irrigated. As a result of rehabilitation work undertaken between 2012 and 2015, the irrigation infrastructure is expanding once again, and the actual irrigated area increased to 43,000 hectares in 2015. Rehabilitation is projected to continue over the next 5 to 10 years and beyond, with the area equipped for irrigation rising to around 130,000 hectares by 2020 and to around 200,000 hectares by 2025. With the planned changes in the Georgian Water Law, a pricing system for irrigation water will be introduced. This fulfills the WFD requirement for water pricing that includes cost recovery. Water is provided by the Georgian Amelioration Company to the farmer-governed Water User Organizations. The allocation of irrigation water and licensing of water use requires more and better hydrological information. Additional efforts are also needed to ensure a drought monitoring system, as a planned WMO regional center for drought monitoring was not realized.
The National Crisis Management Centre of the EMS recognizes the high relevance of hydrometeorological information for the mitigation of natural disasters. As the center has to combine data and information from many different ministries, a national standard in data exchange is essential. For example, a national standard would make it possible to unify geographic information system (GIS) data from different sources. The existing tools to estimate risks have to be supported by real-time data from several services. An automatic linkage for data access with GHMD is required. The GHMD experts play an important role in contributing to risk assessments through their data (for example, wind forecasts as input for wildfire models), models, and expert knowledge. It is clear that GHMD requires further building and strengthening of its human resources capacity so it can better support the work of the EMS.
In all discussions with users, it became evident that GHMD requires higher capacity to generate products and deliver services tailored to specific user requirements. Since most of the hydromet end users do not fully understand what data and information they need for their respective application areas, or how to apply such information, it is critical that GHMD improve its interactions with users of its products and services: it must understand their current needs in order to respond to them, and it must also be able to anticipate and plan for emerging requirements and potential future users. The user needs will be key to driving the modernization and development of GHMD. The overall level of user satisfaction with the data and products should be significantly improved.
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5. INSTITUTIONAL AND ORGANIZATIONAL ANALYSIS: A BRIEF HISTORY OF THE GEORGIAN HYDROMETEOROLOGICAL DEPARTMENT
Flood monitoring and tracking of weather have a long history in Georgia stretching back for 170 years. The historical evolution of hydromet services in Georgia is briefly described below.
Episodic meteorological observations started in 1832. In 1844, the Tbilisi magnetic-meteorological observatory was established and became the source of regular meteorological observations. Glaciological observations started in 1850; agrometeorological observations started in 1883; and hydrological observations started in 1905. The Meteorological and Hydrological Service was created in the year 1930; aerological observations started in 1931 and marine hydrometeorological observations in 1964. After the collapse of the Soviet Union in 1990, the large hydromet service of the former Soviet republic with approximately 3,000 employees became the State Hydrometeorological Department of Georgia of the Ministry of Environmental Protection and Natural Resources, and it kept that status until 2004. Since 2004 the Georgian Hydrometeorological Department of the National Environmental Agency has been situated within the Ministry of Environmental Protection and Agriculture. With support from donors and development agencies, including WMO, World Bank, U.S. Agency for International Development (USAID), United Nations Development Programme (UNDP), the Czech Republic, Finland, Switzerland, and others, GHMD was rehabilitated and has been financed with a regular budget since 2010. Today, GHMD is a Legal Entity of Public Law (LEPL) under the NEA. NEA implements its activities independently from the public governance bodies but is subject to state control. It includes the following structural units: Administrative Department, Hydrometeorological Department (GHMD), Geological Department, Environmental Pollution Monitoring Department, and Department of Sea Monitoring and Fishery. GHMD is Georgia’s only recognized, responsible, and authorized agency for the provision of hydrometeorological warnings.
Undoubtedly, however, the years since the collapse of the Soviet Union have delivered setbacks to hydrometeorological services in the country, leading to degradation of traditional observation networks and a prevalence of outdated and inefficient technologies in most of GHMD’s work areas. As a result, GHMD does not make the best possible use of Numerical Weather Prediction (NWP) available from the world’s leading centers for short- and medium-range weather forecasts, does not produce forecasts with less than six hours of lead time (nowcasting), which are particularly important for quick-onset hazards such as flash floods, and does not produce seasonal outlooks, which are essential for agriculture and water resources management planning.
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• Prepare and disseminate warnings and notifications in the event of expected natural and human-made disasters and adverse events, such as hydrometeorological or geological disasters and extreme environmental pollution
• Prepare hydrometeorological forecasts for river basins, water bodies, and the Black Sea territorial waters
• Provide meteorological services and support to civil aviation
• Develop environmental databases
• Undertake engineering/ecological assessment of geological processes
• Prepare and disseminate information on the state of the environment; develop and manage a unified information fund on land resources
• Register and track past and ongoing industrial and scientific/geological works
• Develop and update the state water balance and cadastre databases
• Monitor coastal zones
• Promote implementation of Georgia’s international commitments under the competence of NEA
There is no hydrometeorological law in Georgia; a general regulation on hydrometeorology issued by the minister of environment protection and agriculture spells out the obligations, functions, and responsibilities of GHMD. This general regulation is similar to a law but has not been passed through the Parliament. The activities of NEA are as follows:
GHMD is a critical and important department of NEA. It is responsible for the provision of nationwide hydrometeorological services and carries out the following activities:
• Archive and manage current and historical hydrometeorological data
• Prepare statistical parameters of hydrometeorological data
• Provide climate services for construction activities through multiannual data sets
• Determine the areas at risk of flooding due to recurrence of flash floods and floods with different statistical return periods (5, 10, 20, 50, and 100 years); undertake zoning of such territories
• Prepare general and specialized short-, medium-, and long-term weather forecasts
• Prepare warnings on expected risks of adverse hydrometeorological occurrences; issue special forecasts and warnings on the risk of avalanches
• Design hydro-technical facilities of marine infrastructure; forecast water impacts on coastal zones and river banks
• Measure hydrometeorological parameters
• Measure meteorological parameters
• Mount and install meteorological and hydrological observation devices and equipment
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Although the general regulation of MEPA specifies the responsibilities of GHMD, it would be highly desirable for GHMD to have a distinct legal framework to ensure (i) establishment of a legal authority for the mandate of GHMD in providing hazard warnings; (ii) policy guidance on the exchange and use of data and information; and (iii) clarity on the roles and responsibilities of all actors providing products and services related to hydrology and meteorology, including government departments, academia, and private sector, and comprising both national and international entities. The need for and advantages of a national legal framework for meteorological and hydrological operations have been elaborated by the World Bank, which strongly supports their creation (Rogers and Tsirkunov 2013).
As of June 2019, GHMD has a total workforce of 134 employees and 48 consultants, of whom 76 work in areas related to the observation networks and 24 in hydrometeorological forecasting. The number of staff with a bachelor’s degree is 140 (32 male and 108 female), of whom 10 also hold PhDs. Of the remaining 41 staff, 32 have a technical college degree and 9 (acting as observers) hold a high school certificate. Capacity strengthening is needed in the following categories for existing staff (numbers of staff members are indicated in parentheses): staff management (two), meteorologist (six), meteorological technician (two), hydrologist (four), hydrological technician (two), and climatologist/climate services (three).
The improvement of GHMD services has mainly been supported by project-based budget funded by various development partners and more recently by the government. A breakdown of the GHMD main budget items for 2015–2018 is given in table 3. Available data indicate that GHMD total budget and operations and maintenance (O&M) expenditures are decreasing (from US$1.74 million in 2015 to US$1.48 million in 2018), while allocation to staff costs is growing (from 45.7 percent in 2015 to 60.3 percent in 2018). The overall budget allocation for GHMD is below international benchmarks. For instance, in most developed countries, government allocation to the national meteorological agencies is above 0.01 percent of GDP. For Georgia this would mean allocation of more than US$1.6 million for meteorology alone. As a comparison, the budget allocation for the meteorological agencies in Burkina Faso and Mali, Africa countries with similar GDP, was US$2.6 million and US$3.8 million, respectively, a few years ago. Given that hydrological information is very important for Georgia, the government budget for GHMD—which is responsible for providing both meteorological and hydrological information—should be significantly higher than US$2 million under current level of GDP.
The projected transfer of funds from NEA to GHMD in 2019 is US$1,218,980. The total projected overhead budget of NEA for 2019 is US$605,145, of which approximately 54 percent (US$326,778) is expected to be the share of GHMD. In addition, US$192,924 is allocated for the design and construction of the radar tower in 2019. The practice of allocating a specific O&M budget began in 2019, and the total O&M budget of GHMD for 2019 is US$108,000. The previous practice was to make requests to the government for such O&M funds as the need arose. The planned budget for 2020 is US$1,159,068. It should be noted that no budget is allocated for capital replacement. The overall trend of reduction of the GHMD budget, from US$1.74 million in 2015 to the proposed US$1.16 million in 2020, is very alarming and should be reversed. This budget is below the minimum needed to protect people’s safety and support national development. It also means that the proposed investments in the GHMD infrastructure will be unsustainable.
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TABLE 3. INCOME AND EXPENDITURE OF GHMD
YearA. Transfer from NEA to GHMD
(US$)
B. Earned income
(US$)a part of A)
C. Operating expenditures
(US$) additionally allocated
D. Salaries (staff +
contractors) (part of A) (staff
costs as share of total expenditures)
E. Total operating
expenditures (US$)
A + C - D
F. Total GHMD expenditures
(US$) A + C
2015 1,351,115 148,837 392,632 797,745 (45.7%) 946,002 1,743,747
2016 1,400,046 140,543 247,548 771,666 (46.8%) 875,928 1,647,594
2017 1,056,167 184,394 324,754 895,182 (64.8%) 485,739 1,380,921
2018 1,181,126 138,494 302,988 894,759 (60.3%) 589,355 1,484,114
a. The earned income results from data and services provided to users (e.g., from discharge measurements at hydropower stations).
Hydromet data are shared on a cost-recovery basis with those who require it. Until recently this was true for all requests, with the exception of requests for data required for warnings and pollution monitoring. On April 12, 2019, an amendment was made that allows GHMD to share the data for research and educational purposes free of charge. When charges are applied, the amount is agreed upon with the government. In recent years, revenue from charges has provided approximately 7–10 percent of the annual budget of GHMD. The revenue has been shrinking due to a decrease in demand for data, for example, by the operators of hydropower stations. Overall, the current government budget support for GHMD is significantly below the minimum needs required to satisfy public safety and support the main weather-dependent sectors such as agriculture.
6. CURRENT STATUS OF GHMD Modernizing a National Meteorological and Hydrological Service is highly complex and costly. Therefore, such an endeavor should follow a structured and long-term plan based on a sound strategy reflecting the needs of the stakeholders and the end user community.
The first step in the development of such a plan is to study and analyze the current systems comprising the organization. A typical NMHS is comprised of a system of systems, as shown in figure 1. That generic illustration of a weather, climate, or hydrological system of systems can be used to identify the current status of any NMHS and to visualize investments required in each system, component by component, to achieve a particular level of improvement. Each system is composed of a number of subsystems (figure 7). The complexity of each system and its subsystems varies depending on the size, level of development, and resources of an individual NMHS.
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FIGURE 7. NMHS SYSTEM OF SYSTEMS AND SUBSYSTEMS
Note: Blue: Production Systems; Gray: Delivery Systems; Red: Enabling Systems; Yellow: capacity building (internal and external).
Global data system
Surface obs systems
Upper air system
Radar system
Data management and archiving
systems
External data systems
Institutional management systems
Operational management systems
Communication systems
Cloud computing systems
Quality management
systems
Computing hardware and software systems
Data comms systems
ICT systems
Monitoring and observing systems
Global NWP systems
Modeling systems
Regional NWP systems
Limited Area Model system
Nowcasting Model system
Hydro Modeling system
Internal research and development systems
Transition Research to Operations systems
External Research and Development systems
Technology infusion systems
Severe hazard forecasting systems
Objective and impact forecasting and
warning systems
Nowcasting systems
Very short range forecasting system
Short range forecasting system
Medium range forecasting system
Long range forecasting system
Public weather services system
Service delivery systems
G2G Disaster management
service system
G2G Agriculture service system
G2G Water & power management system
G2G and G2B Aviation Services
System
Public-Private cooperative
services systems to key businesses
Service systems for public
Actions, service monitoring and
feedback systems
Service systems for national and
provincial governments
Service Systems for Businesses
Capacity Building
Met/Hydro institutional education and training
Stakeholder institutions training
End user training and outreach
Note: G2G = government to government; G2B = government to business.
The system of systems’ building blocks are interdependent. As has become evident in the case of GHMD, the most important requirement is human resources in sufficient numbers and with the capacity to understand and operate a particular system. This road map uses a system-of-systems approach in the remainder of this chapter to describe in detail the current status of GHMD and to arrive at three possible scenarios for its modernization.
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6.1 Service Delivery SystemsAn extensive culture shift and management change is needed to move Georgia’s hydromet services and early warning systems and services (EWS) to a level that meets the requirements of the general public as well as those of targeted users of particular services.
6.1.1 PUBLIC WEATHER SERVICES SYSTEM
The provision of public weather services (PWS) by GHMD is relatively modest. Each morning (12:00), GHMD produces weather forecasts (precipitation, temperature, and wind) for the territory of Georgia for the actual day plus three days ahead; it updates the forecast each afternoon. In addition, it produces 7- and 10-day outlooks for cities as well as for mountain regions and plain regions in the eastern and western parts of the country. GHMD does not produce nowcasts but uses radar information for forecast updates as required. Forecasts are posted on the department’s website (meteo.gov.ge) in Georgian and English.
The website is the most widely used source of PWS information. Severe weather warnings are also displayed on the website. A number of webcams are installed across the country to provide information on actual weather conditions, but these are not functional. GHMD does not operate an automatic telephone answering system for weather information, but the public can reach the forecasters by phone, and during severe weather the forecasters receive many inquiries from the public. There is a Facebook page on the website of NEA that contains some weather information and that also provides feedback about the weather from time to time, but GHMD itself does not have a presence on social media. SMS messages are disseminated by the ICT division according to a list of subscribers within the government only; no SMS messages are disseminated to the public. No weather applications have been developed for mobile and smartphone platforms. GHMD does not currently have a presence on either television or radio, although it had one in the past when it was paid for providing services to the media. The services to both television and radio stopped when the media stopped the payments. However, there are plans to supply information free of charge to media in the near future. Nevertheless, during severe weather both state and private television reporters often come to the forecast office to interview the forecasters for broadcasting via their respective channels.
There are no uniform thresholds for warnings across the country. Thresholds are varied and are based on strong signals in the models and on guidance from WMO, as well as on GHMD’s considerations of the geographic and climatic characteristics of the country. GHMD conducts no outreach or public education activities, nor does it have any programs or surveys for evaluating user satisfaction. GHMD does not interpret the forecasts or translate them into a form to assist daily decision making by users, and no information is produced on the possible impacts of hazards. GHMD does not forecast sand and dust storms, but it does measure the presence of dust in the air. Rain with dust deposition is becoming more frequent and a topic of interest to journalists. Hence, there is interest in producing sand and dust forecasts for the country. This topic is dealt with by a different department of NEA that is in charge of air quality monitoring. However, GHMD believes that forecasting this phenomenon is its responsibility and that taking on this task will increase its credibility and visibility with the public. The phenomenon is also of interest for climate studies.
GHMD does not implement the WMO competency guidelines specifying the requirements for education and training of personnel in meteorology and operational hydrology, including public weather services.
GHMD requires assistance and guidance in developing PWS, including for dissemination and communication of weather information, work with the media, consultation with users, and solicitation of user feedback. Georgia should establish a comprehensive PWS program that is aligned with the WMO guidance on strengthening hydrometeorological disaster resilience and responding to stakeholder needs.
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6.1.2 DISASTER MANAGEMENT SERVICES SYSTEM
EWS should be enhanced in Georgia. The public’s need for early warning services should be clearly articulated to GHMD, but the end users themselves should also have more knowledge of (and thus capacity to demand) effective services. In the absence of any public outreach, it is not clear how the public would gain this knowledge. Users’ understanding of hydromet data and products needs to be developed so that they can benefit from hydromet services for disaster risk reduction and know what precautions to take for predicted hazard events. The warnings must be received quickly enough to allow end users sufficient time to take the required actions to save their lives and property. Reducing the risk of disasters improves the productivity of socioeconomic sectors and increases well-being.
Georgia has not implemented the Common Alerting Protocol (CAP), which if adopted would allow GHMD to issue alerts and warnings without worrying about the details of the ultimate dissemination mechanism used by the EMS.
GHMD disseminates early warnings through SMS and email. Warnings should be disseminated in a timely manner through multiple dissemination channels so that the public knows where to look for and how to use the information.
The Division of Hydrometeorological Risk Reduction is run with 16 staff at the GHMD headquarters. This division oversees the Section on Coastal Monitoring and Early Warnings as well as the Section on Hydrometeorology and Early Warnings. The main task of the division is monitoring glaciers and hydromet hazards, which includes assessing floods and issuing early warnings of avalanches. At times, the staff of the Section on Hydrometeorology and Early Warnings carries out the monitoring duties together with the Division of Field Expedition.
6.1.3 WATER MANAGEMENT AND FLOOD FORECASTING SERVICES SYSTEM
A National Hydrological Service is an institution that provides information to decision makers about the water (or hydrological) cycle and the status and trends of a country’s water resources. Most typically, it focuses on assessing water resources, including drought monitoring and outlooks as well as flood forecasting and warnings. In most countries, National Hydrological Service functions are dispersed among related water agencies. In Georgia the different departments of NEA have specific responsibilities for monitoring water. The geological department is responsible for groundwater; the hydromet department (GHMD) is responsible for surface water quantities; and the Environmental Pollution Monitoring Department of NEA is responsible for qualitative assessment of surface and groundwater. GHMD is responsible for functions such as modeling, researching, and developing hydrological methodologies to produce information for a variety of purposes, including those identified by WMO and UNESCO (1991) as the purview of NMHSs:
• Assessing the status of water resources (i.e., quantity, quality, and distribution in time and space), the potential for water-related development, and the resources’ ability to meet actual or foreseeable demand
• Planning, designing, and operating water projects
• Assessing the environmental, economic, and social impacts of existing and proposed water resources management practices and planning sound management strategies
• Providing security for people and property against water-related hazards, particularly floods and droughts
• Allocating water among competing users, both within the country and across borders
• Meeting regulatory requirements
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There are new tasks for GHMD resulting from international commitments and approaches, such as the EU WFD, the EU Floods Directive, integrated water resource management, and relevant multilateral environmental agreements. The spatial structuring of the river basin management plans (subdivision into water bodies) requires a rethinking of the monitoring network, which is not done yet. Knowledge of runoff quantities is insufficient, posing a crucial problem for planning. Ecological aspects, water quality problems, licensing of irrigation, and hydropower uses require fuller information than water levels, which are currently the main data category at 90 percent of the gauges, where no rating curves exist. Discharge data are indispensable to fulfill all requirements of modern water management. The missing data strongly limit the options for model-based forecasting, as all hydrological models require discharge data for calibration and validation. The data of the past cannot fill this gap but are very useful for statistical analyses and should be made accessible in a data management system along with quantitative information from the new observation system.
The hydrological forecasts are provided by the Hydrometeorological Forecasting Division in the Section of Hydrological Forecasts. At the moment, no hydrological models are used for flood forecasting. Hydrological and hydraulic models were developed within the framework of the UNDP Rioni River Basin project (Developing Climate Resilient Flood and Flash Flood Management Practices to Protect Vulnerable Communities of Georgia); these have been provided to NEA but have not became operational yet. The human resources capacity at GHMD is not sufficient to ensure operation of these models in real time.
6.1.4 AGRICULTURAL SERVICES SYSTEM
Agricultural production is inextricably tied to climate, making agriculture the most climate-sensitive of all economic sectors. The risks of climate change for the agricultural sector in Georgia are important because most of the rural population depends directly or indirectly on agriculture for their livelihoods.
Agriculturally relevant weather forecasts can yield immediate benefits to farmers, providing information on temperature and precipitation in the short term and facilitating planning over the long term; for example, knowledge of an impending drought can help farmers choose crops and manage irrigation.
Agricultural meteorological services are among the oldest services of GHMD. Until 2003 two different agrometeorology-related divisions existed: the Agro-climate Division, in operation since the 1940s, and the Agromet Forecasting Division, in operation since 1930. The basic product currently being produced is the agrometeorological bulletins based on the normalized difference vegetation index (NDVI) data, but no agromet forecasts are produced because the full range of observational measurements is lacking. Evapotranspiration is computed, but soil moisture is measured directly. In the Soviet era (until 1990), phenological observations were made for different crops. An FAO (Food and Agricultural Organization of the United Nations) project in 2016 installed 10 automatic agromet stations (not to WMO standards). Some crop models are prepared to study the impact of climate change on crops, but this information is not provided to farmers. Frost appears to be the most damaging weather condition for crops, and frost early warning software installed at the Turkish State Meteorological Service (TSMS) uses observations from the 20 GHMD synoptic stations. The warnings are published by TSMS on a website accessible only by GHMD and then published by GHMD on its own website. GHMD would prefer to install the early warning software locally and run and access it directly. However, resources required for this purpose are not currently available. Turkey has promised to install the software but has not yet done so. Studies in crop pest and disease are conducted by the Ministry of Environmental Protection and Agriculture. Every district in Georgia has agriculture extension services that provide farmers with information from GHMD bulletins.
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6.1.5 AERONAUTICAL AVIATION SERVICES SYSTEM
Until the year 2000, aeronautical meteorological services were provided by GHMD. Upon creation of a limited liability entity, this responsibility was transferred to the Georgian Air Navigation (under the Ministry of Economy and Sustainable Development, MoESD). GHMD continued to be the reporting authority to the International Civil Aviation Organization (ICAO), while Air Navigation provided the aeronautical services. In 2007, the Prime Minister decided to transfer all responsibility for aviation, including interactions with ICAO, to Air Navigation, which would operate on a full cost-recovery basis. New equipment was installed at the Tbilisi, Batumi, Kutaisi, and Mestia Airports by Air Navigation. While the Tbilisi Airport office is designated as a meteorological watch office, the other offices provide synoptic observations and issue the routine operational products required for aviation safety. Services are provided for four to five flights per day in Batumi, five to six flights per day in Kutaisi, and about 50 flights per day in Tbilisi. The number of flights in Tbilisi is projected to increase to about 150 per day. The services are provided by a total of 53 staff. The forecasters are university graduates who receive on-the-job training following recruitment.
The Satellite Distribution System (SADIS), installed in 1998, is used for producing forecasts, and two X-band radars operate at Tbilisi and Poti Airports; the radar data are shared with GHMD. There is no upper-air station operating in Georgia at the moment, but if GHMD decides to install such equipment, Air Navigation would be prepared to purchase the data. The new IWXXM (ICAO Meteorological Information Exchange Model), a data format used in aviation for operational exchanges of meteorological information in XML/GML, will be installed by Air Navigation in 2020.
The data exchange between GHMD and Air Navigation was limited until recent times because the former entity was purely public in its operations and the latter purely commercial, but following the lifting of restrictions, they can freely exchange their data.
Air Navigation is fully certified by the International Organization for Standardization (ISO) and carries an ISO-9001: 2015 certification.
6.1.6 MARINE SERVICES SYSTEM
The main objective of GHMD’s Section of Coastal Monitoring and Disaster Prevention is the engineering of the coastline. The meteorological services for marine transport are provided by the Hydrographic Service in the MoESD on a cost-recovery basis. The section monitors the morphodynamic structure of the coastlines and designs protection for those areas. In Batumi and Poti, it also carries out marine observations. Two port meteorological stations have been installed by Japan to monitor sea levels and atmospheric conditions. Coastal inundation maps were produced under past projects, and bathymetry studies of the coastline were conducted. There are no wave and storm surge models, but wave and storm surge forecasts are produced by the Short-Range Forecasting Section. The vulnerable areas of the coastline are studied to produce regulations and recommendations for the government.
6.1.7 CLIMATE SERVICES SYSTEM
Georgia’s natural topography produces very large spatial variations in temperature and precipitation. These large variations underscore the need to develop and improve climate services for different users. Climate records date back to the 1850s, but more comprehensive climate information is required for planning purposes in many sectors— including agriculture, water resources management, and disaster management—and for assessing climate variations and change. Approximately 80 percent of the observational data since 1960 has been digitized, but the historical data gathered since the 19th century until 1960 mostly are in paper form. Some studies on climate change have been carried out using the last 50 years of data, and reports have been produced.
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Climate information is produced according to demand from users; in the construction sector, for example, the information is used to produce the climate building codes required by regulations. Climate indices are prepared routinely. Climate statistics are provided to users on a cost-recovery basis, although some entities—ministries, research institutions, educational institutions, and some international projects based on agreements—receive them free of charge with the proviso that they are not for redistribution to third parties. Climate monitoring reviews are provided to WMO for inclusion in the annual Regional Association VI (Europe) reports on climate. GHMD does not keep a full record of users receiving climatological products.
Activities on regional climate downscaling (RCD) are at a preliminary stage, and staff require training for using these techniques and methodologies. One of the immediate gaps to address is the necessity for a calibration laboratory to ensure the quality of the observations. The government has agreed to allocate budget in 2019 for this purpose. Other gaps to be addressed include regularizing the meteorological data flow, which is an information technology (IT) problem; providing computers at all stations to send the observational data to the relevant subregional offices for preliminary quality control before all data arrive at the headquarters to be quality-controlled; publishing climate monitoring analyses on the Internet; and increasing the number of climate reference stations from the current five. While a meteorological yearbook is prepared, not many information products are generated from the data gathered. Such products are produced only on demand for specific users. The Climate Section should prepare a climate atlas for the country, which would be useful for many clients, but data are not currently available for all parameters, and human resources and GIS capability are not sufficient for this purpose. There are no plans for the development of a national framework for climate services, although Georgia could benefit from one that was in line with the principles of the Global Framework for Climate Services; among other things, a national framework would facilitate planning in the relevant sectors in support of food and water security and health outcomes.
6.2 Quality Management SystemsA quality management system (QMS) is defined as the organizational structures, procedures, processes, and resources needed to develop and successfully manage an organization’s delivery of products and services (WMO 2013). In Georgia, quality control of meteorological data is performed, but spatial quality control is limited by limited hardware and software capacity. A quality control system for improving hydrological data quality has been introduced in GHMD as part of the AQUARIUS system. The introduction of a QMS in GHMD could support the continual enhancement of its products and services by focusing on quality control, quality assurance, and quality improvement. A QMS is implemented by most NMHSs in their provision of services to the aviation sector, in compliance with the requirements of the ICAO. The implementation of QMS as part of the strategy to modernize the GHMD should improve the quality of services and management practices as well as users’ and stakeholders’ perception of GHMD.
6.2.1 INSTITUTIONAL MANAGEMENT SYSTEMSApart from GHMD, there is no other source in the country for the official provision of meteorological and hydrological observations and forecasts (except for aviation and marine navigation). The modernization of GHMD as the main hydromet service provider in Georgia should aim for the provision of optimal weather, climate, and hydrological services. A first important step will be the preparation of a strategy supported by an implementation plan that includes realistic resource allocation (both human and financial) and that involves all relevant ministries and departments, stakeholders, and end users. Currently, there is no user-driven, long-term national strategy to govern the provision of weather, climate, and hydrological services. The absence of such a strategy is reflected in the proliferation of multiple different—and often incompatible technologies—and in an ad-hoc approach to the delivery of services. Observation networks and forecasts
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for use by the aviation sector have been under the control of airports since around 2007 according to the decision of the government. Prior to that, this responsibility was discharged by GHMD. The main reason for the change was a financial decision by the government to locate all revenue-generating institutions in the MoESD. As a result, GHMD has no revenue generated from the aviation sector, which in most countries is an important revenue-generating stream for NMHSs. Improving the legal and regulatory framework, in line with other countries’ NMHSs, will strengthen GHMD’s responsibility and authority for issuing warnings for hydrometeorological hazards and for delivering hydromet services.
6.2.2 OPERATIONAL MANAGEMENT SYSTEMSThe operational management status of GHMD needs to be significantly strengthened in hiring and retention of qualified staff. There is a need to improve capacity building and professional development programs, offer appropriate salaries and incentives, and provide effective services. Overall, Georgia has limited capacity and capability for providing quantitative hydrometeorological information to guide timely and effective decision making.
The situation in Georgia is not unlike that in most developing countries, which report inadequate staff numbers and capacity in meteorology and hydrology. The situation requires urgent attention, especially to establish and maintain an appropriate cadre of professionals in these fields. In almost all cases in the developing world, the necessary institutions for meteorological and hydrological monitoring have been established, but the professional depth and breadth of training and staffing varies. Retention and timely replacement of the trained staff is another major challenge, mainly due to low and noncompetitive salaries. Skilled and qualified staff often leave for better-paying opportunities. This situation is not unfamiliar in Georgia, and any modernization efforts in Georgia need to address these challenges. While GHMD continues to receive donor and government funding to upgrade its observation and monitoring network, along with some limited relevant technology, it struggles to ensure sufficient human capacity to fully utilize new systems and technologies. In some countries, hydromet organizations and the academic sector are not sufficiently engaged, or local universities simply do not offer education in disciplines relevant to meteorological and hydrological services. Although the latter is not the case in Georgia, there is limited scientific exchange between GHMD and academic institutions. This situation is gradually improving, however (see section 6.3.2).
The present capability of GHMD for producing weather and hydrological forecasts does not respond to the needs of stakeholders who require information for short-term operations as well as medium- to long-term planning. Hydrometeorological capacity in Georgia is being developed on a project basis. Some standard operating procedures (SOPs) are in place—e.g., in ICT operations; however, these need to be extended to cover all aspects of GHMD’s operations. The analysis of GHMD’s operational systems reveals low capacity in a number of areas: incomplete digital historical data; limited ICT and data transmission infrastructure; limited capacity in data analysis, quality control, interpretation, use of available NWP models, forecasting, and product development; insufficient human resources, both in numbers and skills; lack of hydromet hazard forecasting services; low capacity in EWS, despite the availability of some service delivery means; an inadequate hydromet service delivery system; and absence of effective communications and engagements between the users and producers of hydromet data and products.
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6.3 Capacity Building
6.3.1 GHMD CAPACITY-BUILDING ACTIVITIESBuilding capacity through training activities and cooperation with other WMO members is indispensable if GHMD’s modernization efforts are to be sustainable. For GHMD to be effective, continued capacity development and access to new skills for new and existing staff are essential. Capacity building is the foundation of any NMHS, as shown in figure 1.
A major challenge for GHMD is to create a professional workforce with the access to training opportunities that will enable them to take advantage of rapid advances in many areas of meteorology and hydrology, particularly advances in information technology and meteorological and hydrological modeling and forecasting. In order to replace retiring staff with workers having the requisite skills, it is essential to provide tailored training programs for a steady supply of meteorologists, hydrologists, engineers, and IT specialists with university degrees (see section 6.3.2). It is critical to provide in-house courses in line with the WMO competency requirements to ensure that as many of the staff as possible become familiar with new meteorological and hydrological tools and software; this training should take place not only within their own working environment, but also at regional or international training facilities, and twinning with more advanced NMHSs should also be pursued. Currently, there are not sufficient staff available for training or retraining who will stay in the department long enough to apply their training. A list of areas where training is required at GHMD is included in annex 1 and could be further expanded as necessary. Currently, there is no structured training plan for technical staff and no access to or use of e-learning materials. GHMD has participated in some WMO or donor-organized training, but it does not organize training financed by its own budget.
Educating stakeholders and partner organizations in the application of hydrometeorological products for decision making is essential. Educating the general public to better understand warnings and probability forecasts is equally important, especially for flooding, which is a major hydrometeorological threat in Georgia; this will help ensure that people have greater awareness of and ability to prepare for floods and other hazards. User education could be undertaken through diverse means, including workshops, flyers, publications, public service videos, and posting of educational materials on the GHMD website. Currently, GHMD does not have a cooperative relationship with the media and does not engage in public outreach.
6.3.2 COLLABORATION WITH ACADEMIAThe role of local universities in creating a hydromet talent pool for the country is critical, and some Memorandums of Understanding (MOUs) with universities are in place. Meteorological and hydrological activities are spread across several academic institutions in Georgia without much coherence and few interactions in common areas of interest. The results of the few research activities carried out by different institutes are not used in GHMD’s operations, since they are not based on the GHMD’s operational requirements and are not supported by regular budget allocations. The Institute of Hydrometeorology (part of the Georgian Technical University) is engaged in atmospheric modeling and in environmental, hydrological, and climatological investigations. Beginning in the early 1950s, the main task of the institute was forecasting and developing methodologies that were used primarily in the Caucasus region of the Soviet Union. Following the collapse of the Soviet Union, the institute became part of the Research Institute of Hydrometeorology and currently is part of the Technical University. Scientists are involved in local area atmospheric modeling—Weather Research and Forecasting (WRF) at 5 km resolution—and weather and climate extreme forecasting. These activities are done in research mode only, and no operational products are produced. In the field of hydrology, the institute works on ice, snow, and avalanches as well as glaciology, including the study of retreating glaciers in Georgia. Main issues in climate and agrometeorology investigated by the institute relate to climate variation and hazards, wind
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and solar power, and agrometeorological forecasts. The institute has produced an atlas of climate and agrometeorology for Georgia, as well as a publication on climate change assessment. It provides all results of its work free of charge, and all its data are published and available in the public domain.
The institute needs to strengthen its staffing, computing capabilities, and ICT infrastructure to carry out all the work that needs to be done. It has a good relationship with GHMD and can access the GHMD data free of charge. Its wealth of detailed information on the mountainous regions could be applied for operational work where relevant.
The researchers at the Institute of Geophysics have developed an atmospheric model over the Black Sea for marine forecasting (currents, temperature, salinity, and density over Georgia and neighboring countries), which is used by the countries in the Black Sea area. The forecasts are available through the Internet. The GHMD data are not used in producing these forecasts. The institute is also interested in mesoscale modeling of the atmosphere and orographic effects in the country. It has developed a dispersion model to determine pollution dispersion from a major smelting facility in Georgia. Its environmental activities include studies of soil degradation due to the use of pesticides, transboundary water pollution, and air pollution modeling for PM10 and PM2.5 particulates. The information from these studies is supplied to the Scientific Fund (Ministry of Education), as well as to Turkey, which receives the transboundary pollution information on a paid-for basis.
In view of the useful contributions that these institutes could potentially make to GHMD’s operations, it is recommended that GHMD pursue a closer collaborative relationship with them. This would promote the exchange of scientific ideas, information, and data, and would facilitate application of research findings to GHMD’s operational work. It is worth mentioning that all modern NMHSs have significant research departments that provide support for operations and develop new methodologies, thus helping to address country-specific hydrometeorological and climate issues.
The Department of Geography at the Tbilisi State University produces up to 10 graduates per year in hydrometeorology and is a good source of potential staff for GHMD. Courses in hydrology include hydrological modeling and GIS, while specialized courses are also offered in meteorology. The university lacks materials, such as modern instrumentation for practical training and literature for students.
Areas of potential collaboration between GHMD and the university include provision of practical training for students at GHMD; PhD students could be trained abroad and then return to teach hydrometeorological disciplines at GHMD. In addition, since GHMD and the relevant academic institutions are all in need of increased computing capabilities, a cost-effective and efficient solution would be to increase affordable computing capacity in one central location (preferably GHMD) for sharing among all the institutions.
6.4 Monitoring and Observation SystemsMeteorological and hydrological observations constitute the first step in producing weather and flood forecasts with proper lead time, as well as providing baseline data for water resources management, drought forecasting, and determination of a long-term climate trend. Depending on their purpose, observing stations record temperature, precipitation, pressure, humidity, evaporation, wind speed, solar radiation, and snow cover depth and density; they also record hydrological regime parameters (water levels, discharges, and reservoir storages) and agrometeorological parameters (soil temperature and soil moisture). Monitoring and observation systems consist of observation stations as well as data management systems (data transmission, telecommunication networks, and data processing and storage).
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6.4.1 GLOBAL DATA SYSTEMGHMD has access to global observational data through the Global Telecommunication System (GTS). It also has access to satellite data via the EUMETCast system of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites).
6.4.2 NATIONAL DATA SYSTEMSThere is no institution in Georgia besides GHMD that has a mandate to collect countrywide meteorological or hydrological observational data (except those for marine and aviation purposes).
Surface Meteorological Observation Network Prior to 1990, over 200 meteorological stations and posts were in operation in the territory of Georgia (figure 8), and the station network density was quite adequate for the country. The monitoring network has been reduced since the collapse of the Soviet Union owing to a large reduction in financial resources. There is a need for a properly designed national meteorological and hydrological network that would meet a variety of user requirements. Based on best practice, these should range from high-precision climate observations, which serve as a reference system to validate weather and hydrological forecasts and support climate change applications, to observations supporting specific sectoral uses (in agriculture, water resource management, transport, energy, and so on). The surface meteorological monitoring network operated by GHMD today consists of a total of 24 automatic weather stations (AWS), eight manual stations, 41 automatic posts (measuring only temperature, humidity, and precipitation), and 10 manual posts. Five of the automatic stations were provided by UNDP, and the rest were bought from the GHMD budget. There are also 10 automatic agrometeorological stations and four automatic road meteorological stations. The majority of automatic posts are manufactured by Vaisala; of these, 20 were provided by UNDP, and the rest were procured from the GHMD budget. There are two lightning detectors donated by Earth Networks, which expected GHMD to purchase more detectors for its network, but this did not happen. The outputs from these lightning detectors are used operationally and significantly contribute to monitoring of high-impact weather events. The GHMD intends to attain the same number of stations as existed in the past (Soviet era), with the addition of certain stations at strategic locations such as the Emergency Management Service or Ministry of Agriculture may require. GHMD does not operate a specific climatological station network, but it operates two tide gauges to measure water level; there are also two moored buoys operated not by GHMD but by the hydrographic services under the MoESD, although these data are not available to GHMD. GHMD does not operate any Global Atmosphere Watch (GAW) stations. Nine automatic synoptic stations participate in the international exchange of data through GTS. The exchanged data are the only data that can be visualized in the Synergie and METCAP systems. With the exception of four meteorological stations, all automatic meteorological and hydrological stations are powered by solar panels.
PHOTO 2. THE HISTORICAL WEATHER OBSERVATORY IN TBILISI
Credit: Haleh Kootval, World Bank.
PHOTO 3. HISTORICAL ARCHIVES OF THE WORK OF JOSEPH STALIN AT THE WEATHER OBSERVATORY OF TBILISI, INCLUDING A PAINTING OF STALIN READING THE SENSORS AT THE
METEOROLOGICAL SCREEN (LEFT) AND WRITTEN RECORD OF STALIN’S OBSERVATIONS (RIGHT)
Credit: Haleh Kootval, World Bank. Credit: Haleh Kootval, World Bank.
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A calibration laboratory existed during the Soviet era but currently there is no such facility. There is a plan to purchase a calibration laboratory in 2019 using the GHMD’s own budget. This will be a critical purchase, since it will provide GHMD with measuring equipment and sensors compliant with international standards.
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The observation network employs both Vaisala and Campbell instruments. While the latter can transmit data in real time, the Vaisala instruments do not have the capability for real-time transmission of observations, since at the time of the purchase, forecasters specified their data requirements on an hourly basis only. Network Manager, a software capable of integrating hydrological and meteorological data, is now required to receive the observation data in near-real time (every minute). GHMD has only one qualified technician and four assistant technicians to deal with the entire array of observing equipment. For optimal handling of all the technical aspects (maintenance and repairs), five more technicians are required (the absolute minimum would be two). GHMD does not use the services of a WMO Regional Instrument Centre.
FIGURE 8. DEVELOPMENT OF THE METEOROLOGICAL OBSERVATION NETWORK IN GEORGIA
Source: GHMD data.
Surface Hydrological Observation Network Many developing countries report having insufficient staff and financial resources to operate and maintain their national hydrological observation network (World Bank and GFDRR 2018a). Automatic stations require continual investment, and they need to be refreshed every 10 to 15 years. Hazard events (such as floods and lightning strikes) or vandalism can damage a station beyond repair, but even limited damages to simple, inexpensive items such as staff gauges are often not repaired. In many cases, straightforward tasks such as routine maintenance are neglected, while data records and validations are lost. A fully functioning NMHS requires ongoing maintenance of hydrological networks, along with the establishment and maintenance of a hydrological information system to enable access to data and information. These issues are familiar in the context of Georgia.
The hydrological observation network in Georgia comprises the hydrometric stations for river stage/discharge and reservoir/lake levels. Water quality monitoring is part of the NEA Department of Environmental Pollution Monitoring. Sediment monitoring sites and groundwater monitoring are the responsibility of the NEA Geological Department. These split responsibilities absolutely require the exchange of data and information for smooth operations of all networks.Surface Water Level/Discharge: The automatic hydrological stations in Georgia collect data on water level, precipitation, air temperature, and relative humidity. These parameters are observed every 15 minutes through data loggers and then downloaded.
Number
Year
0
90
180
1900 1960 20202000
Meteorological Posts
Meteorological Stations
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In 1980, the hydrological network for water level and discharge had its maximum number of stations, with 152 hydrological gauges (see figure 9). It declined after that, reaching 105 stations in 1990 and 21 stations—the minimum—in 2007. With international support and GHMD’s own capacities, it expanded again and in 2015 there were 39 stations. Between 2012 and 2016, the UNDP flood protection project for the Rioni River Basin added 10 automatic hydrological posts to the system (UNDP Georgia 2016). At present, the total hydrological network for surface water consists of 59 hydrological stations—19 manual stations with two observations per day and 40 automatic stations (33 operational). The water levels of two reservoirs used for hydropower generation are also observed.
FIGURE 9. HISTORICAL DEVELOPMENT OF THE HYDROLOGICAL OBSERVATION NETWORK IN GEORGIA
Source: GHMD data.Note: The figure also shows GCF planning for the period 2018–2025.
0
80
160
Number of Hydrological
Stations
Year1900 1940 1980 2025
The planning of the future hydrological network is based on a significant increase in the number of stations in order to return to the number that existed between 1960 and 1980. In discussions within MEPA, it was stressed that the allocation of additional stations has to consider the needs of forecasters, those of the basic hydrological service at GHMD, and those of users, e.g., for implementing the EU WFD.
Besides the water level gauges, GHMD operates five stations where snow depth is recorded, of which only two are operational. These stations are equipped with Campbell SL 500 ultrasonic distance sensors. The plan is to add five more stations and to get information about snow conditions at elevations up to 3,700 m.a.s.l. (the current elevation is 3,200 m.a.s.l.). Through an initiative of GHMD, the existing snow stations have been equipped with gauge boards and webcams A crucial problem for the existing automatic hydrological network is the extremely limited staff available for maintenance. One technician is responsible for ensuring the operability of all GHMD’s automatic stations. In case of failure, it often takes more than a week for the station to be repaired. This lack of staff is especially problematic given GHMD’s responsibility for flood monitoring in Georgia. .
1
3622
40
75
108
148135
148 152
105
5243
2129
3446
55 59
103
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The country’s geomorphological conditions require a high frequency of discharge measurements at many gauges to ensure an update of rating curves; for 25 of the 59 gauges, up to 15 measurements per year must be carried out. However, no rating curves exist at the moment at nearly half of all stations. This serious deficit results from insufficient personnel capacities in the Field Expedition Division of GHMD, which has six staff members and is (among other things) responsible for discharge measurements. The division’s total capacity for discharge measurements is limited to approximately 300 per year, but more than half of this capacity is used for paid services to hydropower plants. The remaining measurements (less than 150) are done at GHMD gauges. The division has special equipment for hydrological measurements, specifically one acoustic Doppler current profiler (ADCP), three propeller-type current meters, and one ultrasonic current meter. According to U.S. Geological Survey recommendations, a control of rating curves requires six to eight measurements per year per gauge. The compilation of new rating curves requires much more data. Considering the experience in similar mountainous regions, setting up completely new rating curves requires a minimum of 12 to 18 measurements per gauge plus hydraulic computations, which have to be based on detailed geomorphological data at gauged sites. Based on these numbers, the current deficit amounts to a minimum of 500 measurements to ensure rating curves at all gauges. Proper prioritization should drive the filling of this gap step by step. After fitting rating curves for all 59 gauges, the annual requirement for hydrometric service would be around 360 measurements. This is close to the existing capacities (300) but requires concentration on gauged sites and an end to the paid service for hydropower plants. Without rating curves, the hydrological service is not able to provide quantitative forecasts, to calibrate and validate hydrological models, to deliver trend analyses for ongoing changes of runoff, or to fulfill other user requirements.
A particular problem is the centralized structure of the hydrometric service, located in Tbilisi. The driving distance to gauges in the western part of the country is more than 500 km. It is impossible to ensure timely discharge measurements during floods, especially for fast-reacting mountainous rivers. Positioning of local hydrometric capacities at the regional hydrometeorological observatories of Adjara, Kolkheti, and Samtkhe-Javakheti could substantially improve this situation. As the calibration and validation of hydrological models has to be based on quantitative discharge data, the hydrometric deficits significantly limit the value of the hydrological observation system.
Surface Water Quality Monitoring: Deterioration of the water quality in rivers affects human health, hydropower generation, livelihoods, the environment, and the economy in general. Increased sediment and nutrient loading in rivers adversely affects the river water quality, which is correlated spatially and temporally to river flows. Climate change further aggravates the problem: prolonged dry spells and high-intensity rainfall contribute to floods, soil erosion, excessive sediment loads in rivers and sedimentation of reservoirs, reduced groundwater recharge, and reduced base flow in rivers. These in turn contribute to further deterioration of the water quality by increasing the pollution concentration. Protecting surface water from pollution and monitoring surface water quality are the responsibility of the NEA Department of Environmental Pollution Monitoring.
Sediment Load Monitoring: The highly dynamic geomorphology in Georgia requires monitoring of sediment loads and riverbed processes. As of the 1990s, no monitoring of sediment loads was being done, while morphological monitoring of riverbed processes is currently carried out by the Field Expedition Division of GHMD.
6.4.3 UPPER-AIR SYSTEMThere are no functioning upper-air monitoring stations in Georgia. Operating and maintaining upper-air stations requires training and significant financial resources.
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6.4.4 RADAR SYSTEMThere are three radars in operation that provide weather information to the GHMD forecasters, none of which is operated by GHMD. They are (i) the X-band Tbilisi Airport radar; (ii) the C-band radar owned by DELTA, the private company that is engaged in hail suppression activities in eastern Georgia; and (iii) the radar located in and operated by Turkey covering the western part (Black Sea) of Georgia and providing graphical displays only. A new C-band radar to be operated by GHMD will be provided by Vaisala through a USAID project to cover the western part of the country. The X-band and C-band radars provide digital data that are not in the standard format. The format of these two radars must be changed to the standard format, and the new C-band radar must also provide data in this format. There is a plan for the installation of two portable X-band radars under the UNDP Green Climate Fund project, which should also provide data in the standard format to ensure a fully integrated radar mosaic over the territory of Georgia. Although radars can be of great help in routine forecasting and in detecting hazardous phenomena, they can be relied upon only if they are properly calibrated. Their cost, operation, and maintenance pose a serious challenge for GHMD under the existing staff and financial constraints. GHMD has only one staff member for radar operations, a forecaster who is being trained in Turkey, but it does not have a radar engineer/technician. Instead, GHMD has agreements with Air Navigation and DELTA to assist with radar-related issues. Technicians need to be trained in radar maintenance, but currently there are no technicians to be trained. The deputy minister has promised to hire a local technician to be trained for radar maintenance. GHMD could adopt a different business model and subcontract radar technicians from DELTA or Air Navigation instead of training its own technicians.
6.4.5 USE OF REMOTE SENSING PRODUCTSCertain parts of Georgia, especially its mountainous regions, do not have sufficient in situ hydromet observing stations to support the reliable provision of EWS and hydromet services. In these sparsely observed regions, satellite data can be particularly useful as a data source that complements in situ systems. Satellite data should be well integrated into the country’s hydromet observing network to ensure maximum benefit and cost-effectiveness.
The development of capacity in this area will allow the use of remote sensing data to produce maps for precipitation, floods, landslides, avalanches, extreme temperature, soil moisture, evapotranspiration, and land cover in Georgia to support agriculture, weather, and hydrological forecasting along with EWS. Georgia is not a member of EUMETSAT but receives data directly from EUMETSAT satellites via EUMETCast. The satellite data are used in forecasting and warning services. GHMD has no special department for managing satellite data and receives the imagery via a meteorological satellite data reception station. Satellite data should also be integrated with other data for visualization in a proper forecaster workstation. The METCAP system provided by Turkey has a satellite display that is used when the EUMETSAT display system is not functioning. However, the METCAP display system is itself not fully reliable due to lack of computing capacity.
6.4.6 DATA MANAGEMENT AND ARCHIVING SYSTEMS: DATA COLLECTION SYSTEM, QUALITY SYSTEM, AND STORAGE AND ARCHIVINGMeteorological and hydrological information, products, and services are only as good as the underlying data and information on which they are based. Hence good systems for managing meteorological and hydrological data are a priority even in resource-constrained environments. The hydromet services of many low- and middle-income countries either do not have access to modern IT systems or are not trained to keep them up to date or make the best use of them. Their data are often held in paper archives or simple spreadsheets. Quality assurance and quality control (QA/QC) of data is another issue in many countries. Modern data management systems embed a data quality management framework, but many NMHSs
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do not regularly control the data quality. For many developing countries, limitations in data collection and management also present a barrier to data sharing among different government departments, even if the protocols for such exchange exist. This situation is familiar in Georgia, which needs to develop an effective systematic means for managing hydromet data and products as well as for sharing warnings or other products among the different organizations. In addition, GHMD needs a comprehensive, reliable, and accessible centralized database as well as proper means for data processing, validation, and communication.
PHOTO 4. EXAMPLES OF HISTORICAL DATA ARCHIVES
Credit: Haleh Kootval, World Bank. Credit: Andreas Schumann, World Bank.
The Division of Database Administration manages the meteorological and hydrological databases. The Czech CLIDATA management system was procured for GHMD by the Czech Development Cooperation and is intended for the quality control and archiving of meteorological data. The CLIDATA system replaced the old CLICOM system and is designed for the Oracle database environment. Metadata are included only partially in the database: the metadata from the Soviet era are currently in paper form (and should be digitized), but the new changes in station status and history can be included digitally, noting that there is a metadata gap of around 20 years (from 1990) in this database. A new version of CLIDATA is needed, but it will have to be paid for by GHMD, which currently lacks the resources. Although climatological and other types of maps were prepared by the CLIDATA/GIS application in the past, such maps are not being prepared with the current version of the system, following the crash of the server in 2017. Currently they are produced outside the CLIDATA environment using GIS, an approach that complicates the task of map production. GHMD recognizes that the system must be updated, but it lacks the donor funding needed to support the Czech experts’ visit to GHMD and the required license fee. There is a possibility of supporting this update through Norwegian government funding. There are also other open source options, such as MCH or Climsoft (supported by WMO), that GHMD may consider.
Data from automatic stations are transmitted in real time and forecasters receive them in real time, but they do not arrive in the CLIDATA management system in real time; they enter the system by manual input via the database specialists. Climate messages could be generated automatically with the updated version of CLIDATA, but currently these are produced manually and transmitted through the GTS. Unfortunately, since the backup data were kept on the same server as the operational server, the crash of the server resulted
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in the loss of two years’ worth of data. This crash highlights the importance of redundancy in the critical ICT infrastructure. Now the backup data are kept on the operational server plus a different backup server. A further complication in the meteorological data management system is that the Vaisala data are in an Access database and not recognized by the Oracle system. Therefore, an intermediate step is required to translate data in the Access database to CSV format before it can be recognized by Oracle.
The hydrological data are managed with the database system WinZPV, also a Czech product, which was obtained in 2012 from the Czech Hydrological Institute to record river water measurements and other information to characterize the river network system. Besides WinZPV, GHMD uses the hydrological data analysis tool HEC-DSSVue, which is a Java-based visual utilities program that allows users to plot, tabulate, edit, and manipulate the data. GHMD uses both software tools to automatically generate reports and other information about hydrological characteristics.
In the framework of a project sponsored by the Norwegian government during the period 2013–2016, all historical hydrological data since the 1930s (water level, discharge, daily data) were digitized, and they are now available in the database system WinZPV. With the introduction of AQUARIUS software, this database will be transferred to the new AQUARIUS system. The digitized time series includes data from up to 464 stations, but observation periods of at least 10 years were recorded only at 155 gauges. Many stations were operating only for three to five years to estimate the potential for hydropower production. Unfortunately, the digitization was done by external contractors, and the process was not subject to proper quality control. Going forward, it will be essential to control and (as necessary) improve the quality of the digitized series step by step. If this cannot be ensured, the value of the digitized runoff data will be limited.
6.5 ICT Systems: Telecommunication Systems (Data Exchange and Distribution System, Transmission)Meteorological data are transmitted from GHMD’s manual stations to the headquarters every three hours using SMS messages. The data from automatic meteorological and hydrological stations and posts are sent in SYNOP and HYDRA codes respectively. Data are stored in the Division of Telecommunications and archived every hour. The database is sent for storage once per month. Pre-processing of data is done in the Division of Telecommunications as the observation data are received from the stations, and corrections are made to any erroneous data before sending them to forecasters. The Section of Meteorology deals with the collection of meteorological data from stations and processes and uploads them into the data management system. The quality control of the historical data (every month) is the task of the Section of Climatology. This means that the forecaster does not use fully quality-controlled data in the forecast production. To address this issue, data should ideally go directly to the centralized server for near-real-time quality control. Processing of current and historical meteorological data is done by the Czech program (CLIDATA), while the WinZPV program (also Czech) is used for hydrological data.
A main problem in the Division of Telecommunications is the Météo France International (MFI) automatic Message Switching System (MSS) TRANSMET, which links the meteorological information systems and ensures connection to the GTS. TRANSMET was purchased together with the Synergie system (also from MFI, circa 2008) and is used operationally by the forecasters. TRANSMET should automatically receive, check, and forward meteorological data and products by connecting with any standard communication device. However, the situation in GHMD makes clear that these automatic functions are not currently available due to the absence of observations in proper BUFR format and models in GRIB2 format. An additional issue to address is the incompatibility of model data resolution with the original setup of the Synergie system. The two major observation systems at GHMD—Vaisala and Campbell—are also incompatible. In addition, some of the computers in the Division of Telecommunications are old and need to be replaced (approximately five desktop computers are needed), and antivirus software is required as part of the rehabilitation of the ICT
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environment. In response to these problems, TRANSMET should be thoroughly reviewed and upgraded. The first priority for the telecommunication system is to fix the formats so that TRANSMET can perform its functions correctly. A second priority is updating the near-real-time meteorological and hydrological data quality control on an operational basis and archiving data directly in a centralized data center. This will allow meteorological and hydrological divisions to have direct access to real-time data.
PHOTO 5. THE TELECOMMUNICATION SYSTEM AT GHMD HEADQUARTERS
Credit: Haleh Kootval, World Bank. Credit: Haleh Kootval, World Bank.
Warnings are distributed by SMS to around 500 government recipients. Forecasts are sent daily to the same recipient list. The Division of Telecommunications is responsible for updating the GHMD’s website.
The data from the Campbell automatic hydrological stations are transmitted hourly via GSM; data from the manual stations are transmitted twice per day by SMS. The majority of automatic posts (35) are equipped with Campbell Radar Water-Level Sensors, but eight stations operate using Vaisala Water-Level Pressure Sensors. All these stations are equipped with data loggers (the Campbell stations use the logger PS 900). The data flow from Campbell stations is based on the Campbell Loggernet system. The near-real-time data are available for forecasters as CSV files. The transfer into the hydrological database WinZPV has been done manually on a monthly basis. The data from Vaisala stations are transferred via FTP by the Meteo Romania Regional Forecast Centre system. The hydrological data are stored in the HYDRA database and are available as Access files. These were stored in WinZPV until 2019, when the WinZPV was replaced with the Water Data Management System AQUARIUS, one of the most powerful platforms available for managing water resources. With the AQUARIUS database system, environmental data from multiple sources will be securely stored for fast, central access.
Data from different sources must use standard formats (e.g., BUFR for AWS data, GRIB2 for model data, etc.). Once this requirement is met, the data for visualization in Synergie, METCAP, or any other system can be integrated. Most of the model data used by NMHSs are now in GRIB2 format, and GHMD’s old forecaster workstations do not read such files. However, the European Centre for Medium-Range Weather Forecasts (ECMWF) has a program to convert GRIB2 to GRIB1 as an intermediary step allowing display in old versions of the workstations. Currently, the GHMD Telecommunication Division has four 24-hour shifts with two engineers per shift, supplemented by three additional engineers during daytime. In addition, there is one IT specialist at NEA (not on shift but on 24-hour call) managing the networking system. Dedicated IT network and database specialists are required at GHMD for maintaining the proper environment for operational activities, networking, and database management systems; otherwise there will be little
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benefit in installing additional observing stations or acquiring better-performing models. The operational (telecommunication, forecaster) Internet bandwidth speeds of 15 Mbps for global data and 20 Mbps for local data will need to be increased for the purpose of downloading products from global and regional centers. The Internet bandwidth for modeling and data management is under control of NEA and is 100 Mbps for local and 40 Mbps for global transmission.
GHMD urgently needs an implementation plan for its ICT system (including infrastructure, human capacity, and software) as part of its complete operational environment, including observations, models, forecasts, and products in an integrated data center (see figure 10).
FIGURE 10. THE CURRENT ICT SYSTEM AT GHMD
Global Surface Observations (Met)
National Surface Observations (Met)
Satellite Data
Radar Data
Global and Regional NWP/EPS
LAM
National Observations
(Hydro)
GTS
LoggerNet & Meteo RFC
EumetCast
FTP
GTS
FTP
LoggerNet & Meteo RFC FTP Hydro
Database
Hydrological Models
HYD
RO
DIV
FOR
ECA
STIN
G O
FFIC
E
FTP
CLI
MAT
E D
IVClimate Database
Note: LAM = limited area model; EPS = Ensemble Prediction Systems.
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6.6 Modeling Systems
6.6.1 METEOROLOGICAL MODELS (GLOBAL AND REGIONAL NWP SYSTEMS)GHMD’s overall use of NWP is limited to older models with low resolutions. Its main weather forecasting model is the French ARPEGE-France model, ARP 0.5, with a coarse 60 km resolution, and ARP 1 (120 km resolution) received via TRANSMET. These are the only functioning models run on the Synergie (2008) visualization system, which was provided by MFI and is used at the forecast office. The Synergie was set up to display the data from ECMWF IFS (Integrated Forecast System, 2.5°), Météo-France Arpege (2.5°, 1.0°, and 0.5°), UK Met Office UM (Unified Model, 1.25°), and NOAA/NCEP GFS (National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction Global Forecast System, 1°). The resolution of all these models is now much higher, as new versions are implemented every nine months or so, and the codes are continuously evolving to take full advantage of the supercomputers, to assimilate data from new observation systems, and to improve the components of the forecast model. However, GHMD has not updated Synergie to allow use of the new data—that is, it has not adjusted the setup of Synergie to accommodate the current model resolutions available on GTS.
GHMD has access to meteograms, via the Internet, for 10 locations provided by ECMWF, according to the ECMWF’s agreement with all WMO members. It also has a METCAP visualization system provided by the Turkish State Meteorological Service, and it has access to other models freely available on the Internet (e.g., ICON from Germany). It does not have access to graphical products from ECMWF and has no access to any digital model data. GHMD would benefit from access to ECMWF data and products in graphical format; this would entail an annual cost of €3,500 (US$3,922), which is the standard cost for a license for image products. Although the ECMWF graphical products provide a significant tool to improve hydromet forecasting, the ultimate goal in forecasting should be access to digital data (e.g., ECMWF data at 9 km resolution, which soon may become 5 km resolution). A software license or membership in ECMWF is required, and extensive training in handling (use and manipulation) of the digital data is essential. The most critical next steps include objective verification of the ECMWF model output over Georgia, and post-processing and calibration to adapt the model for national use. Currently however, GHMD has no storage capacity for output maps from ECMWF. GHMD was interested in becoming an associate member of ECMWF, and in 2008 some discussion was held on this issue; but progress has stalled due to lack of follow-up from the Georgian government.
GHMD does not have enough storage or running capacity for climate modeling. Through discussions with the Georgian Research and Education Networking Association (GRENA), however, the GHMD staff are given computing resources to work on climate issues, although not for daily weather forecasting. Acquiring a high-performance computer may resolve the capacity problems, but it will introduce a significant new problem: lack of qualified staff for its operation and maintenance. At the very minimum, one qualified IT expert with some knowledge of meteorology is needed per shift for the model run management to ensure continuous operation. The current arrangement—one staff member serving the entire NEA’s IT needs—is totally inadequate, and IT issues are the main bottleneck in supporting modeling and forecasting. The capacity of the current server, bought four years ago at a cost of €15,000, is 1 terabyte for storage and 0.5 teraflops of computing capacity for running the models, which is almost full. A low-capacity server and lack of expertise and number of staff to manage the ICT and modeling systems are the main limiting factors in running high-resolution models.
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6.6.2 LIMITED AREA METEOROLOGICAL MODELSGHMD runs a Weather Research and Forecasting (WRF) model using initial and boundary conditions from the GFS model. Data assimilation is not performed because the necessary skilled staff, management of data flow, and IT capacity are lacking. The current computing capacity requires one hour for running the nested 3 km model (a coarse 9 km version of the model is also run). According to the staff, the results are acceptable based on rudimentary subjective verification, but the model is not connected to the Synergie or the METCAP systems and is not used regularly in the forecast office. For a short period (2016–2018), GHMD also ran the COSMO model with 7 km resolution on an experimental basis, but this has been discontinued due to lack of human and infrastructure capacity. GHMD does not run the high-resolution COSMO model (2.8 km), also due to lack of capacity. The products from WRF and COSMO are available from the GHMD modelers and are shared with the forecasters whenever required.
The emphasis on limited area models (LAMs) is often at the expense of full use of the global and regional model guidance. It is far more effective for NMHSs to make full use of the numerical guidance from global centers. Where higher resolution is needed (e.g., for hazard-prone areas or over complex orographic regions), it should be sought on a regional scale with the best available limited area models supported by WMO Regional Specialized Meteorological Centres or by a consortia (WMO 2017), followed by forecast verification and feedback, model post-processing and calibration, model output interpretation, and delivery of services at the national level. This is the so-called cascading forecasting process.
NMHSs should consider running very high-resolution (~1 km or less) convection-permitting numerical models over hazard-prone areas or complex orographic regions, though this should be done only if robust and reliable telecommunications infrastructure (to import the required volumes of data) and large supercomputers are affordable to support models of competitive resolution. Optimal parameterizations of the physical processes, high-quality processing and full data assimilation, and spin-up and cycling issues need to be addressed to make the process successful and sustainable. In addition, a large and expert staff of scientists and computer technicians should be available to develop and maintain such a system 24 hours per day, 365 days per year, in an operational environment. Well-defined SOPs, including a checklist of activities for weather forecasting, are also required to produce forecasts that meet stakeholder and other end user requirements and expectations.
The current freely available model codes were conceived for training and research purposes only; they lack the optimal parameterizations of the physical processes, the configurations tuned for the regions of interest, and the developments required to keep them up to date in terms of science and technology. Therefore, these codes are not well suited for operational use. The notion that lower-resolution locally run models can be equivalent to or better than the global mesoscale models is misguided. Overall the ECMWF’s deterministic model performance is as good as its LAM performance.
6.6.3 HYDROLOGICAL MODELSSeveral hydrological models are available at GHMD. Within the framework of the Norwegian project, a map of 30-year mean annual runoff for Georgia was generated through the application of the HBV model. The map shows local runoff for a spatial resolution of 1 km in units of millimeters of water per year. Within the framework of the UNDP project, hydrological and hydraulic models were provided to GHMD for the Rioni Basin. GHMD occasionally uses the hydrological HEC-HMS model. A hydrodynamic model (MIKE-11) is used for flood wave propagation. Both models are integrated in the Delft-FEWS, a modeling framework provided by the Dutch consulting company Deltares. Within the framework of a technical assistance project managed by the Climate Technology Centre and Network (CTCN) and United Nations Industrial Development Organization (UNIDO), additional hydrological software tools were delivered at the end of July 2018. All software was handed over to the stakeholders during two weeks of training in hydrology and hydraulics. Besides the Apache Open Office program, tools were delivered for handling spatial data (QGIS ArcHydro,
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HEC-GeoHMS), hydrological data (HEC-DSSVue), flood modeling (HEC-HMS 4.2.1), and hydraulic modeling (HEC-RAS 5.0.5); the open data–handling platform Delft-FEWS, which acts as a hydrological forecasting and warning system, was also delivered. The main problem in applying these tools in forecasting is the lack of skilled forecasters and modelers at GHMD. Under the Georgian hydrological conditions, the hydrological and hydraulic models require permanent recalibration and validation, which has to be done by a group of modelers able to change model parameters. This will allow adapting the models by utilizing an extended database and will provide forecasters with opportunities to make the best use of new data sources, such as remote sensing data from satellite or weather radar.
6.7 Objective and Impact-Based Forecasting and Warning Systems6.7.1 SEVERE HAZARD FORECASTING SYSTEMSMany of the hazards affecting Georgia originate from hydromet events such as heavy precipitation or prolonged dry spells. These are primary hazards that lead to secondary and tertiary hazards. For example, floods and flash floods follow specific weather events—heavy rain, fast snowmelt in the early spring, or a combination. Landslides and avalanches are another possible consequence of heavy precipitation. While droughts could result in heat waves and water scarcity, both droughts and frosts will result in damage to or loss of crops and have important impacts on human and animal health. Pest and disease outbreaks may be triggered by drought or excess precipitation. Identifying how certain hazards cascade from others is the first step in progressing from weather forecasts and warnings to multi-hazard, impact-based forecasts and warnings (table 4).
TABLE 4. EXAMPLES OF PRIMARY, SECONDARY, AND TERTIARY HAZARDS CASCADING FROM HYDROMETEOROLOGICAL EVENTS
Event Primary hazard Secondary hazard Tertiary hazard
THUNDERSTORM
• Heavy rainfall• Strong winds• Lightning
• Flash floods• River Floods• Landslides
• Damage to dams and structures, embankments, irrigation and drainage facilities, pumping facilities
• Submerging of fields• Loss of infrastructure
systems and services (shelter, energy, transport, schools, hospitals, communications)
• Widespread economic losses
• Infectious disease• Insect and pest
problems• Sand and silt
deposition• Waterborne diseases• High sediment runoff
into reservoirs
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DROUGHT
• High temperatures• Heat waves
• Less rainfall
• Water scarcity• Low flow • Less inflow• Crop damage
• Forest and surface fires
• High evaporation loss in reservoirs
• Shortage of storage water in reservoirs
• Insufficient diversion in channels
• Salt-affected soil • Food shortages• Energy shortages• Pumping system
difficulties• Air pollution/haze• Smog/dust
Successful impact-based forecasting requires collaboration with others who have the additional expertise, resources, knowledge, and data. Forecasting severe hazards and their impacts requires a well-established weather forecasting system on different time scales.
Spring Flood ForecastingSpring and early summer floods are induced by snowmelt and often combined with synoptic rainfall events. They are typical of the seasonal hydrological regime in Georgia. Under certain initial conditions (median snow depth, high snow density, a significant water equivalent, and high energy input in the form of rain), such events become critical. The seasonal forecasts are based on snow data that are provided by the Field Expedition Division once per season and on statistical relationships (similar to multiple regressions) that date back to the Soviet era. Determining the conditions that aggravate these flood events would require a deterministic forecast based on real-time data and a combination of snow hydrological tools with weather forecasts.
Flash Flood ForecastingFlash floods are a source of death and property loss in Georgia, specifically in the mountainous parts of the country that are vulnerable to these hazards. A WMO/USAID Flash Flood Guidance System (FFGS) was installed at GHMD around five years ago, with support provided by the Turkish State Meteorological Service (TSMS), which is the regional FFGS center for nine countries in the region. GHMD provides its rainfall data to TSMS for ingestion in the system, and after being processed at TSMS, it is displayed at GHMD. However, the system does not recognize the rainfall data from the Georgian network, and thus the flash flood guidance produced for operational work uses data that are available only at the TSMS. TSMS has been approached several times to assist in solving the rainfall data problem, but the problem remains.
Landslide/Mudflow ForecastingIn Georgia mudflow forecasting is the responsibility of NEA and is shared between the Geological Department and GHMD. The location of debris flows (commonly known as mudflows) is highly dependent on very small-scale features of the terrain and the precipitation event. Even though precipitation is the main driver of debris flow generation, prior soil moisture also plays a role. Therefore, in addition to data from the standard weather stations, there is a need for monitoring of soil moisture at different depths.
While it is feasible to forecast floods using basin precipitation estimates, forecasting debris flows (and to a lesser extent flash floods) requires high-resolution precipitation estimates, which are achievable only from radar or satellite observations. Radar data are not available for this purpose in Georgia; however,
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satellite-based precipitation observations in near-real time can help develop such forecasts. Hopefully these will improve and provide the required high-resolution spatial imagery in the future. It should be remembered, though, that debris flows occur in mountainous areas, and it is precisely in those areas that ground-based radar observations tend to have problems from the blocking effect of the mountains.
Avalanche ForecastingAvalanches cause death and property damage in Georgia, impacting transportation infrastructure in particular. The main factors in avalanche generation include snow depth and profile, fresh snowfall, and wind speed and direction.
Avalanche monitoring is done at GHMD by the Hydrometeorological Warnings Section. Two road meteorological stations have been installed along the Military Road (joining Tbilisi to the Russian border), and data from meteorological posts and webcams are collected along this road. In addition, data are also collected from three high-mountain stations, with snow sensors and observers on the manual stations, and by some snow sensors installed in winter resorts. Based on the analyzed data, if the conditions that create a risk of avalanches exist, GHMD issues a warning for the Military Road with a lead time of three hours, so that the road can be closed. Based on the warnings, the resorts and the military may set off avalanches on the mountains. General warnings about avalanches are posted on the GHMD website when the meteorological conditions are conducive for their generation. Information about all avalanches collected by the Hydrometeorological Warning Section is used to produce national statistics by the Ministry of Internal Affairs. Given that avalanches tend to recur in the same geographical areas, it is possible to prioritize locations for new stations.
Drought ForecastingGHMD should develop the capability for monthly and seasonal long-range weather forecasting through application of RCD methods to provide detailed and accurate representation of localized extreme climate events. It should also train staff in techniques for downscaling of climate models. With the development of RCD, collaboration between GHMD and the Ministry of Environmental Protection and Agriculture should enable the development of an effective drought forecasting service covering meteorological, agricultural, and hydrological droughts. A drought monitoring system was developed through a Slovakian project that was completed recently, and it will likely be implemented shortly. Soil moisture and land degradation are used as indicators of drought.
6.7.2 VERY SHORT- AND SHORT-RANGE WEATHER FORECASTING SYSTEMSTo produce meteorological forecasts, GHMD accesses data via the MFI Synergie system (the main tool) and uses the meteograms available on the ECMWF password-protected website. A plain-language two-day weather forecast for Tbilisi and the eastern and western parts of the country, which is issued twice daily, is the output of GHMD’s short-range forecasting system. An outlook for 7 and 10 days is also prepared. The daily forecasting routine includes the examination of EUMETSAT imagery; analysis and hand drawing of the data received from Moscow (plotted by the Synergie system); data from the Tbilisi Airport and the DELTA radars, as well as the imagery from the Turkish radar; the METCAP display of observations; the meteograms from ECMWF (10 locations); the global model outputs available on the Internet; and the displays provided by the Synergie system.
Although not a member of EUMETSAT, Georgia is a cooperating state and so has access to EUMETSAT products. The METCAP displays observations from only three AWSs, which were included in the system in 2012. The METCAP system is used mainly to look at the graphics from the Turkish radar, as it does not function as a real visualization system in a forecaster workstation environment. The problem is that the system was set up some time ago, and the adjustments to keep it relevant have not been made.
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The observations are updated every three hours. The METCAP system is mostly used in the spring and summer and for early warning. The meteograms generally produce good results except during the spring to summer transition season, which produces severe weather conditions, including hail in the eastern part of the country, that are usually difficult to predict.
Nowcasting would be possible using 15 products of the EUMETSAT Satellite Application Facility for Nowcasting (NWC SAF), which are extrapolated for one hour and updated every 30 minutes. Extracting this information for some geographic areas is planned but not yet implemented. The Modeling Section is trying to apply these tools for future use, but support from NWC SAF is required for their proper implementation and integration into the centralized database for visualization by the forecaster workstation.
For daily temperature and precipitation in 15 cities, subjective verification is done in a qualitative manner (low, medium, high) only. The accuracy rate is reportedly 70–80 percent. Temperature accuracy rate in the +2°C to -2°C range is reportedly high, sometimes as high as 90–100 percent, but the forecasters use their own experience to correct the model output. The forecasts are typed out and are produced in the form of information bulletins. Another information bulletin is issued for three days ahead for six regions according to their elevation. Warnings are included in the same bulletins and are placed at the top of the forecast page.
PHOTO 6. THE VISUALIZATION SYSTEM AT THE FORECAST OFFICE
Credit: Haleh Kootval, World Bank.
There are no regular or formal consultations and discussions among modeling and forecasting staff, although the two groups have some informal exchange from time to time. An implementation plan needs to be developed for the upgrade/replacement of the visualization system (forecaster workstation). Currently, the Forecast Division is unable to properly use data in the forecaster workstation to allow integrating and overlaying of data from various sources; instead, individual displays are used. Since the current versions of the visualization tools (Synergie and METCAP) do not allow any interventions by GHMD staff, GHMD should call on the manufacturers to upgrade the existing systems, ensuring that further development by GHMD is possible in the future.
The current work environment is not the most efficient for effective operational purposes. The entire weather forecasting process at GHMD needs to be reviewed and modernized following the practices of the more advanced forecasting centers. SOPs should be developed to guide the work of all forecasters in a standard manner and to ensure the forecast office’s effectiveness and efficiency.
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6.7.3 MEDIUM- AND LONG-RANGE WEATHER FORECASTING SYSTEMSMedium-range forecasts cover up to 10 days ahead. Long-range forecasts are monthly and seasonal forecasts that are required for planning purposes in different sectors; they are available on several websites. The ECMWF website includes EUROSIP products, which are multi-model seasonal forecasts from the ECMWF, Met Office, Météo-France, U.S. NOAA/NCEP, and Japan Meteorological Agency. The WMO Lead Centre for Long-Range Forecast Multi-Model Ensemble (https://www.wmolc.org/) provides access to the 12 Global Producing Centers for Long-Range Forecasts. A global climate model can provide reliable prediction information on a scale of around 1,000 km by 1,000 km, covering what could be a highly diverse landscape (e.g., ranging from mountains to flat coastal plains), with varying potential for droughts, floods, or other extreme events. Regional climate downscaling, which provides projections with much more detail and more accurate representation of localized extreme events than global climate models, is needed to support more detailed impact and adaptation assessments and planning in Georgia.
Four GHMD staff members work in the medium- and long-range forecasting division and produce forecasts for 10 days using the GFS model (accessed through the Internet) and ECMWF meteograms. These forecasts are included in the daily short-range forecast bulletins. Monthly forecasts are produced using statistical descriptions of weather for the next 30 days and are updated each 10 days. For seasonal forecasts, GHMD participates in and uses outcomes of the South East Europe Outlook Forum (SEECOF) and Mediterranean Outlook Forum (MEDCOF). In the summer season the forum meetings are face-to-face, and in the winter season they are online. GHMD does not access products from Global Producing Centers, and in the absence of any downscaling techniques, the SEECOF maps are the only source of seasonal forecasts in Georgia. The products from SEECOF are distributed only to those who request them, and they are not widely disseminated within the government ministries. Verification of long-range forecasts is conducted only for those locations that are included in the forecast bulletins, and according to GHMD the results are reportedly quite good. The verification results are not published, and no statistics are produced based on the results.
6.7.4 HYDROLOGICAL FORECASTING SYSTEMSMuch hazard-related loss and damage could be avoided if the people likely to be affected by the event were warned in advance. For many developing countries, the absence of such a warning system using modern forecasting and dissemination systems is a major issue. In producing hydrological forecasts, close collaboration between meteorologists and hydrologists is essential. Reliable hydrological forecasts require meteorological data in the form of quantified estimates of observed and forecast precipitation and temperature, dew point, wind speed and direction, and solar radiation, as well as river levels, river discharge, and snow conditions (snow cover area and snow-water equivalent). In addition, weather forecasts on various time scales are required: up to 14 days for rain-induced flood forecasts, several weeks for snowmelt-induced floods, two to four weeks for reservoir management, and monthly and seasonally for droughts. Too often these data and products are provided to hydrological forecasters as inputs for hydrologic modeling as an afterthought, without consideration of required data formats, timeliness, and delivery methods. The situation in Georgia is much more favorable, since meteorology and hydrology reside in the same department (GHMD), making these considerations relatively straightforward to address.
Hydrological forecasts are produced by GHMD for high-flood-risk and normal situations. In the case of high flood risk, forecasters get real-time precipitation data and prepare their forecasts using their knowledge and experience. Regular forecasts are provided for 20 stations for two days ahead. As rating curves exist for only five of these gauges, the forecasts are based on water levels only and specify their future ranges in centimeters. There are two thresholds against which the forecast is compared: the warning level and the level of disaster. The forecasters consider qualitative rainfall (low, medium, high) forecasts only. The warnings will be interpreted for a certain region according to the expected increase of water
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levels at relevant regional hydrological stations. The forecasts of water levels result from the knowledge and experience of the forecasters, as no hydrological model is used for this purpose. Seasonal forecasts are provided for the period April to June. The flood peak in m3/s is specified for 16 gauges. Average flows are provided for the period April to July. These forecasts are based on snow data, provided by the Field Expedition Division, and statistical relationships (similar to multiple regressions) that date back to the Soviet era. The introduction of hydrological models is strongly limited by an insufficient database (no rating curves) and the lack of staff qualified to calibrate and validate these models.
Besides forecasts, GHMD provides regional hydrological information, which is stored in an ArcGIS system containing maps, graphs, photos, and text files. Despite the modern IT tools, the content is based mainly on analyses that date back to the 1970s. The new hydrological information has not yet been integrated. The system includes many empirical formulas from Soviet hydrology, but their current relevance is uncertain as the climatic conditions as well as other physical characteristics have changed over time.
6.8 Summary of the Current Status of the GHMD SystemsFigure 1 in this road map presents the system-of-systems concept in the structure and functioning of a modern NMHS, while figure 7 shows the details of the subsystems within each system. Based on the analysis of GHMD’s current system of systems in producing and delivering meteorological and hydrological products and services, the approximate capabilities for each main GHMD system have been estimated using a series of progress models—for weather and hydrological service delivery, for modeling and forecasting, and for observation and telecommunication systems. The progress models use a scale of 1 to 5 (Undeveloped, Development Initiated, Development in Progress, Developed, Advanced).
The current level of the service delivery capability of GHMD is assessed to be between Level 2 (Development Initiated) and Level 3 (Development in Progress). In order for GHMD to be able to deliver services to meet users’ needs, its capability at the end of the Scenario 3 intervention (see chapter 9) must be at a full Level 4 (Developed). This increase would put Georgia at a level of service delivery similar to Croatia, a relatively small European country that has developed a strong hydromet and EWS culture. As a comparison, countries that provide services at an advanced level (Level 5) include the United Kingdom, Australia, China, Austria, and Switzerland, among others.
GHMD’s current modeling and forecasting capability falls between Level 2 (Development Initiated) and Level 3 (Development in Progress) in the Modeling and Forecasting Progress Model. In order to deliver services and perform functions as stated in Scenario 3 of the road map, the capability of the forecasting system should be raised to Level 4 (Developed). This improvement would put Georgia at a level similar to a country such as Croatia or Serbia.
The current observation and telecommunication capability is at Level 2 (Development Initiated) in the Observation and Telecommunication Progress Model. In order to deliver services and support forecasting at a Developed level, the capability of the observing system should be raised to Level 5 (Advanced) by the time Scenario 3 is complete. It should be noted that this improvement does not necessarily depend on an expansion of the observation network, but rather on the improvement in data quality, accessibility, sustainability, and usage, including sufficient technical and financial capacity for operation and maintenance. Such an improvement would put Georgia at a level similar to a country such as Malaysia.
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7. MODERNIZATION OF METEOROLOGICAL AND HYDROLOGICAL SERVICES AND EWS
7.1 Value Chain ApproachThe GHMD meteorological and hydrological forecasting and warning services need to be modernized beyond the current observation and data-gathering systems in order to provide fit-for-purpose services to all users. A well-planned and organized NMHS should play a key role in EWS. Producing and disseminating warnings that are targeted to the impacted areas and populations is the main mandate of any NMHS. In the future, NMHSs will collaborate with relevant government organizations to provide impact-based forecasting and warning services. The public will need to be educated and the emergency management authorities trained on the potential impacts of severe hydrometeorological events so they can take protective actions.
Modernizing an NMHS is a complex, time-consuming, and costly task in any country. To cite two examples: the modernization of the U.S. National Weather Service and the Japan Meteorological Agency both took many years and cost hundreds of millions of dollars. The modernization of the hydromet service in Slovenia, a country one-third the size of Georgia, was completed in 2015 and cost €33 million. Thus before proposing modernization activities for GHMD, it would be reasonable to briefly describe the main elements of a well-functioning NMHS.
The operation of an NMHS in any country is based on observations and data collection; data processing; telecommunications; preparation of forecasts, warnings, and climate advisories; and dissemination of forecasts and other specialized information, through the media and other channels, to users (figure 11). These functions are carried out through the combination of many networks, centers, and hubs at different scales—global, regional, and national—that form the intricately interconnected world of global hydrometeorology. The three components of observations, telecommunications, and data processing and forecasting together comprise the WMO World Weather Watch system.
The Global Observing System is extremely complex and perhaps one of the most ambitious and successful instances of international collaboration in the last 100 years. The system consists of a multitude of individual observing systems owned and operated by many national and international agencies. The Global Telecommunication System is the communications and data management component that allows the World Weather Watch to collect and distribute information critical to its processes. The GTS is implemented and operated by the NMHSs of WMO members and by intergovernmental organizations, such as ECMWF and the EUMETSAT. The GTS also supports other programs, facilitating the flow of data and processed products to meet WMO members’ requirements in a timely, reliable, and cost-effective way. It ensures that all members have full access to meteorological and related data, forecasts, and alerts. The Global Observing System has evolved into the WMO Integrated Global Observing System (WIGOS) and the GTS has expanded into the WMO Information System (WIS).
The Global Data Processing and Forecasting System encompasses all forecasting systems operated by WMO members. It enables members to make use of the advances in NWP by providing a framework for sharing data related to operational hydrology, meteorology, and oceanography. The main support for the exchange and delivery of these data is the WIS.
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FIGURE 11. SCHEMATIC OF GLOBAL OBSERVING, TELECOMMUNICATION, DATA PROCESSING, FORECASTING, AND DISSEMINATION SYSTEM
Source: Rogers and Tsirkunov 2013.Note: RTH = regional telecommunication hub. The compilation of different systems of observation, telecommunication, data pro-cessing, forecasting, and dissemination is based on the WMO World Weather Watch system.
The value of NMHSs’ products and services is manifested in the way they are used by the recipients. The generation of meteorological and hydrological value can be depicted in a value chain linking the production and delivery of services to users’ decisions and the outcomes and values resulting from those decisions (WMO et al. 2015); see figure 12. Potential value is added at each link of the chain as services are received by users and incorporated into or considered in decisions. Value-adding processes involve tailoring services to more specialized applications and decisions (i.e., making the information more relevant) or expanding the reach of an information product to ever-greater audiences (e.g., public, decision makers, and clients). In a modernized, well-functioning NMHS, every link in this chain is strong,
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helping to deliver value to the society at the end of the chain. In contrast, in a less developed NMHS, the chain often stops at observation or forecasting without a robust modeling, ICT, and service delivery capability. A broken link somewhere in the value chain would result in production of suboptimal value for the society, and in the worst case, no value at all.
FIGURE 12. HYDROMET PRODUCTION VALUE CHAIN
HYDROMET SERVICES PRODUCTION AND VALUE CHAINS
Processing & Data Management
Weather Climate Water
Observations Modelling Forecasting Service Delivery
Research & Development
Weather Climate Water
Communication Processes
Processing & Data Management
Weather Climate Water
Observations Modelling Forecasting Service Delivery
Research & Development
Service Production
Value-Adding Processes
Basic & Specialized Services
NMHS & Commercial Providers
User Decision & Actions
Outcomes
Value Benefits & Costs
Source: WMO, WBG, GFDRR, & USAID (2015). Valuing Weather and Climate: Economic Assessment of Meteorological and Hydrological Services. WMO-No. 1153. Geneva, Switzerland.
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Modernizing NMHSs cannot be done piecemeal, but it can be implemented in a phased approach stretched over a number of years, as long as the initial plan takes into consideration every component of every system and the level of improvement needed. The implementation process should be transformative, ensuring that the NMHS can deliver the services and products stakeholders expect (Rogers et al. 2019). These include new technologies for observation and data recording, data validation, and archiving, as well as modern tools for forecasting, dissemination, and communication of products and services (figure 13).
FIGURE 13. SCHEMATIC OF NMHS MODERNIZATION
Modernisation of
NMHS
Information Utilization and Decision Making
Data Synthesis and Analysis (incl.
modelling, forecasting)
Data Sensing and
Recording
Information Dissemination
Data Validation and
Archiving
Monitoring Networking Design Based on User
Requirements
Source: Courtesy of Andreas Schumann, World Bank.
Network design has to be an ongoing process based on user needs, with new stations established and existing stations discontinued as program priorities and funding evolve. Selecting the best technology for data sensing at a given location is a very complex task. There are many technologies available, and for each combination of these technologies, numerous vendors and products are available. Network operators must consider additional factors such as reliability, reporting accuracy, costs, operation and maintenance requirements, durability, and site specifications. Data management ensures the proper storing, validating, analyzing, and reporting of vast amounts of data and establishes the validity of the data by providing evidence of compliance with QMS. Finally, no investment in technology can compensate deficits in human capacities; hence continuous training of staff is essential. Figure 14 gives an overview of the flow of data and information in modern hydrometeorological services.
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FIGURE 14. DATA FLOW IN HYDROMETEOROLOGICAL SERVICES
User Community
Data for Operational Purposes
Natural Meteorological and Hydrological Characteristics
Objectives
Technologies, depending on• Reliability• Accuracy• Control and Maintenance• Specific Local Site Factors• Costs of Ownerships
Network Design• Program Priorities• New Stations• Closure of Stations
Data Collection
Data Management System
Meteorological and Hydrological Information e.g., forecasts, statistics, real-time data
Dissemination of Information
Source: Courtesy of Andreas Schumann, World Bank.
The socioeconomic benefits of modernization will be manifested in improved risk management and decision making, for both weather-related disasters and economic development. These benefits will be especially evident in the case of floods, which have the biggest impact on poor and vulnerable populations. Improving the forecasting and early warnings for hydrometeorological hazards will help build resilience in communities and sectors at risk. A substantial modernization program for any NMHS should typically include three components: (i) enhancement of the service delivery system; (ii) institutional strengthening and capacity building; and (iii) modernization of observation, ICT, and forecasting infrastructure (Rogers and Tsirkunov 2013). The activities proposed in the subsequent chapter are in line with this principle. They aim to strengthen the GHMD’s institutional basis: to enhance a legal and regulatory framework and to develop the capacity of staff; to technically modernize the observation, ICT, data management, and hydromet forecasting infrastructure and facilities; and, most importantly, to improve the delivery of hydromet and EWS to the population of Georgia and weather-dependent sectors.
7.2 Development Partners and Cooperation Various donors and development partners have initiated numerous projects aiming to strengthen EWS and hydromet services (or achieve related goals) in Georgia. Annex 2 lists 21 such projects, based on information provided by GHMD. Two of these are ongoing, while the rest have been accomplished. While the objectives of the projects are stated, there is no clear information about their outcome or impact on the
Quality Management System
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organizations or the populations where they were implemented (it is known, however, that the four road sensors were installed under the two Czech projects).
Assuming that the objectives of the projects were achieved, some improvement of capacity was provided to the stated beneficiaries. However, in the absence of a proper national strategy for improving EWS and hydromet services, insufficient coordination among the various donors and recipient agencies has led to a piecemeal approach and has created a disjointed system, where separate components are poorly, if at all, connected. Such a system creates major operational and management challenges for GHMD in areas where it is directly involved. It is therefore crucial that projects give due consideration to the recipient agency’s absorbing capacity, both in terms of the operation and maintenance cost of the systems and the availability of sufficient skilled staff. It is likewise crucial that any planned initiatives should build upon the activities and achievements of ongoing projects that fit within an overall national plan. Any new project for modernizing GHMD could benefit from consolidating the achievements of the previous activities and coordinating its proposed activities with ongoing initiatives. The implementation of the GCF-funded project FP068 (Scaling-up Multi-Hazard Early Warning System and the Use of Climate Information in Georgia) and other development partner initiatives provide an excellent opportunity for such a coordinated approach.
8. PROPOSED ROAD MAP FOR MODERNIZATION OF THE GEORGIAN HYDROMETEOROLOGICAL DEPARTMENT
Recognizing that cultural change in institutions takes time (Rogers and Tsirkunov 2013), this road map represents the first step in a planned long-term engagement on hydromet modernization. The resulting project needs to lay a strong foundation that can be developed over time. Moreover, the government authorities need a stronger understanding of the role that GHMD can play in many areas of the development of the country.
A modernization program for any NMHS should include the three interrelated groups of activities or components cited in the previous chapter: (i) enhancement of the service delivery system; (ii) institutional strengthening and capacity building; and (iii) modernization of observation, ICT, and forecasting infrastructure. These components are described below for GHMD.
8.1 Delivery of ServicesGHMD should evolve from a data-providing organization to a demand- and user-driven, knowledge-based organization that emphasizes service provision across many socioeconomic sectors. Proper capacity building for the staff of GHMD—enabling them to take ownership of the investments in new equipment and technologies and use their new knowledge effectively—requires time and patience. The service delivery system of GHMD should be able to meet the needs of various users who require different services from their national service provider; more specifically, it should include a service monitoring and feedback system (figures 15 and 16).
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FIGURE 15. SERVICE DELIVERY SYSTEMS OF MODERNIZED GHMD
FIGURE 16. MONITORING AND FEEDBACK SYSTEMS FOR SERVICE DELIVERY
Service Delivery Systems
Public Services System
G2G Disaster Management
Services System
G2B & G2G Transport Services System
G2G Agricultural
Services SystemG2G Water
and Power Management
System
G2G & G2B Climate Services System
Public-Private
Cooperative Services
to Key Business System
Source: Rogers et al. 2019.Note: G2G = government to government; G2B = government
to business. Not all users and stakeholders are identified here; others include aviation, marine, road, and rail services.
Actions, Service Monitoring,
and Feedback Systems
Monitoring and Feedback System
for Public Services
Monitoring and Feedback System for Businesses
Monitoring and Feedback System
for National and Provincial
GovernmentSource: Rogers et al. 2019.
In many countries, some of the challenges relate to a gap between providers and users of hydrometeorological services, which leads to miscommunications and misunderstandings. To overcome this gap, it is essential to create and deepen the understanding of who the users are, what they need, and how NMHSs can meet those needs. It is critical that the design and updating of monitoring networks be coordinated with the user community, so as to achieve an integrated network that supports users’ requirements for services. It is encouraging to note that some effort has been made in Georgia to identify users and their requirements for hydrometeorological information. An integrated national policy for meteorological and hydrological services will make it possible to deliver these services and target users more effectively.
The objective under this component of the road map is to enhance the GHMD’s service delivery systems by developing a national strategy for service delivery; enhancing public weather and hydrological services; strengthening end-to-end EWS, including impact-based forecast and warning services; developing agriculture and climate advisory services; and creating a national framework for climate services. These actions provide for the implementation of a systematic upgrade of the weather, climate, and hydrology-related end-to-end services provided to all agencies, communities, and individuals. The WMO Strategy for Service Delivery and Its Implementation Plan provide in-depth and step-by-step guidance to enhance and develop service delivery (WMO 2014). The strategy describes a continuous cycle of four stages that define the framework for service delivery, and it identifies six elements that detail the activities required for high-quality service delivery (figure 17).
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FIGURE 17. THE FOUR STAGES OF A CONTINUOUS AND CYCLIC PROCESS FOR DEVELOPING AND DELIVERING SERVICES
Service Design and Development
DeliveryUser Engagement
and Developing Partnerships
Evaluation and Improvement
The six elements necessary for moving towards a more service-oriented culture are:
Evaluate user needs and decisions1
Link service development and delivery to user needs
2
Evaluate and monitor service performance and outcomes
3
Sustain improved service delivery4
Develop skills needed to sustain service delivery
5
Share best practices and knowledge6
Source: WMO 2014.
Annex 3 shows the Service Delivery Progress Model as illustrated in the WMO Strategy for Service Delivery and Its Implementation Plan. It should be noted that this model is applicable to all types of services provided by NMHSs.
Such a shift to user-based products and service delivery requires a mechanism to facilitate communication and understanding between the meteorological and hydrological service providers and the user sectors. Establishing a hydrometeorological user group is a useful tool for this purpose. The user group needs
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to develop and implement a strategy for service delivery with the engagement of service providers, stakeholders, and end users. The strategy should outline users’ needs; priorities for needed products and services; design and generation of those products and services; dissemination of products and delivery of services; evaluation of the impact of the new products and services on the country; and improvement of products and services (WMO 2014). Since user needs change periodically, existing and potential new users should be surveyed on a regular basis. NMHSs need to engage with the public and more specialized users, and especially to educate them about how to make the best use of scientific endeavors. It is essential that a user database be maintained and updated, and that the products and services required by users become part of GHMD’s strategic planning.
While GHMD houses both a Hydrology Division and a Meteorology Division, a holistic response to user requirements will entail establishing a structured collaborative approach between them. Under this approach, the Hydrology Division could provide the following (WMO 2008, 2009):
• Water-related data and observations obtained from the hydrological observing network
• Water-related information, such as a comprehensive assessment of national water resources, the statistics of flood events, or maps of spatial/temporal trends
• A monitoring service designed to provide very specific data or information at a particular location for a particular user (e.g., to indicate when the remaining discharge, influenced by water extractions, falls below a specified minimum value)
• Information on of water-related phenomena and water resources
• Advice on decision making, where information is developed into recommendations for response to certain conditions (e.g., an evolving drought)
• A model- and database-driven methodology to estimate water balances, developed through joint interdisciplinary efforts of experts in geo-informatics, hydrology, meteorology, and water management, and requiring an exchange of information between sectors and capacity building of staff
Similarly, the Meteorology Division might provide the following:
• Weather-related data and observations from the meteorological observing network that provide specific data at a particular location on agreed atmospheric elements, based on established practices by WMO
• Weather forecasts at various time scales (nowcasting, very short, short, medium, and long range based on available capacity) to meet user needs; and severe weather warnings
• Advice on the impact of weather conditions (both severe and routine) on different stakeholders and decision-making guidance for users
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8.1.1 STRENGTHENING PUBLIC WEATHER, CLIMATE, AND HYDROLOGICAL SERVICESThe public weather service is the main channel used by NMHSs for coordinating with the public, the media, and the sectors impacted by weather and climate. It is the principal interface between the technical providers of weather and related products and their users. It interprets and translates technical meteorological forecasts and other information into socially and economically relevant and understandable information, and it provides this information to the public at large and various sectors for decision making. In most countries, all forecasts and warnings are disseminated from the NMHS via various channels, including the mass media, the Web, and increasingly social media. This information includes both weather and hydrological warnings and forecasts. Under a PWS program, GHMD should partner with key stakeholders to develop and implement SOPs for producing and communicating fit-for-purpose services. SOPs are especially important in the case of warnings, since they help ensure that messages are consistent among partners and stakeholders and thus permit clear decision making and timely action. Implementing PWSs and hydrological services effectively at GHMD would ensure that all users receive timely information on all time scales available. Implementing formal and regular feedback mechanisms should also be part of GHMD’s delivery of public weather and hydrological services.
The wide dissemination of hydrometeorological forecasts and warnings to all users is a key element of modern hydrological services. For GHMD, an essential tool in this regard is its website, which provides access to important meteorological and hydrological information needed by the user community. GHMD should also consider developing color-coded information, which is often the most effective way of communicating warnings.
PHOTO 7. MODERN PUBLIC WEATHER SERVICE DELIVERY IN INDONESIA
Credit: Haleh Kootval, World Bank.
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8.1.2 DEVELOPING A COMPREHENSIVE NATIONAL DROUGHT MONITORING PROGRAM
GHMD needs to develop more-comprehensive agriculture and climate advisory services, including a drought monitoring program that coordinates information and knowledge between meteorology and hydrology and that establishes the drought magnitude and impact information required by most farmers in Georgia. The drought monitoring program should be developed by GHMD in collaboration with MEPA, whose requirements are essential in defining drought forecasts and information linked with decision making.
8.1.3 DEVELOPMENT OF A NATIONAL FRAMEWORK FOR CLIMATE SERVICES
A national framework for climate services is defined as a coordinating mechanism enabling the development and delivery of the climate services required at national and local levels. Most modern NMHSs have developed such a framework, guided by the Global Framework for Climate Services and involving practicalities and specifics for the actual delivery of climate services at the national level. A national framework involves the key national institutions (if other than NMHS) collecting and compiling climate observations and other climate-related data sets, as well as those undertaking relevant research and providing tailored information, products, and expert advice. In Georgia, the major activity under such a framework would potentially include support to major sectors such as agriculture, water management, energy, and disaster risk management (DRM).
8.1.4 AVIATION REGULATED SERVICES IN THE REPUBLIC OF GEORGIA
Until the year 2000, aeronautical meteorological services were provided by GHMD (Section 6.1.5). In 2007, all responsibility for aviation, including interactions with ICAO, was transferred to Air Navigation, which operates on a full cost-recovery basis. When this change was made, GHMD was not permitted to enter into arrangements for fee-based services. Currently, the monitoring and provision of aviation services are carried out by SAKEAERONAVIGATSIA Ltd. These services include the management of air traffic movement, provision of communication systems and lightning detection, aeronautical meteorological services and aeronautical information services. In parallel, GHMD provides services to the public and is in the process of modernizing its services.
It should also be noted that GHMD is currently permitted to enter into fee-based service delivery arrangements with clients.
Although aeronautical meteorological services are conducted independently from the NMHS in a few countries, it is not a best practice, especially for a relatively small country such as Georgia. In Europe (the EU countries and Turkey), only five of twenty-eight aeronautical meteorological services operate independently of the NMHS. Since the NMHS is responsible for the provision of core services to a variety of users, the proportion of core services allocated to aeronautical meteorological services should be relatively small; however, the revenue from aviation services could assist in the further development of GHMD capacities.
Another important factor to consider is that the forecasting services are anticipated to be substantially upgraded with the ability to access and use the most advanced forecasting techniques. This will be an opportunity for aviation forecasting services to benefit from these upgrades – which in turn will tend to improve efficiency by increasing the utility of the forecasts. An important consideration is the ability to minimize the impact of adverse weather events across Georgia’s entire airspace and provide safe and efficient routing guidance. This would require access to the NMHS’s core services.
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• Comprehensive, high-quality, and robust observational networks• Efficient data collection and management and rapid information exchange• State-of-the-art ICT and fit-for-purpose computing facilities within operational and maintenance
capabilities• Sophisticated data analytics schemes and powerful simulation and forecasting models• Improved understanding of meteorological and hydrological phenomena through ongoing
scientific and operational research• Expertise in delivering forecast and warning services based on impacts of hydrometeorological
phenomena, in partnership with relevant government organizations• Effective tailoring of services to user needs
8.2 Institutional Strengthening and Capacity Building8.2.1 INSTITUTIONAL STRENGTHENING
Most developing countries need to develop strategic policies that ensure effective integration of water resources and DRM. In isolation from broader water resources concerns, DRM cannot be effective in mitigating the loss of life and livelihoods due to droughts, floods, and climate change (World Bank and GFDRR 2018).
The main objectives of NMHSs are to provide information on weather, climate, and hydrological conditions for safety in the air, on land, and at sea; to mitigate natural disasters; to provide services to weather-sensitive economic sectors; and to support national development (WMO et al. 2015). A modern NMHS performs these functions by means of the following:
• Effective dissemination systems that use multiple channels to assure the widest dissemination of warnings, forecasts, and advisory information, and that engage social scientists as required for increased impact of communication to communities
• Efficient and transparent public and private service delivery arrangements• Effective communication of the science and practice of meteorology and hydrology, including
limitations, uncertainties, and applicability of the science and related technologies• Enhanced legal and regulatory framework • Capacity building across the entire NMHS and for users and stakeholders• Improved methodologies and algorithms for use of meteorological, hydrological, and related
information in decision making.
Modern NMHSs focus on understanding the user value chain to better understand what users need, what decisions they make, and how they apply information related to weather, climate, and hydrology to minimize risk and to benefit the society as a whole (see section 7.1). When service delivery improves, users gain confidence in the capability of the NMHS, which leads to improved relations with users and increased demand for services. In addition, better services to government agencies and departments result in greater recognition of the NMHS as a provider of vital services supporting the economy and society. This enables the NMHS to build a more convincing case for investment to sustain and further improve the range and quality of services.
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FIGURE 18. QUALITY MANAGEMENT SYSTEMS
Institutional Management
Processes and Systems
Quality Management
SystemsOperational
Management Systems
Source: Rogers et al. 2019.
For modern NMHSs seeking to maximize the return on investment by ensuring optimum use of resources, a Concept of Operations (CONOPS) is a powerful tool. A CONOPS provides a conceptual overview of the system and subsystems of an NMHS (Figure 1) and describes the operation of the system from different stakeholders’ viewpoints. It provides important information for the design, procurement, implementation, operation, maintenance, and replacement of that system. The CONOPS is intended to support the evolution of a fully integrated, modernized, and functional NMHS that provides the level of services required by its users and stakeholders.
At the moment, GHMD’s activities mainly focus on observation and data collection. Producing varied forecasts and delivering services—by taking advantage of current technological and scientific progress and applying best practices and standards—are not the strong points of the department. The step from data collection to information production demands a strengthening of the rest of the system of systems in an integrated manner (as shown in figure 1); more specifically, modeling, forecasting, and service delivery systems must be supported by the QMS (figure 18), technology infusion systems (figure 19), and capacity building (figure 20). The institutional strengthening component of this road map will call for investing in improved institutional arrangements at GHMD with the goal of enhancing its performance in line with international best practices.
FIGURE 19. TECHNOLOGY INFUSION SYSTEMS
Technology Infusion Systems
Commercial Off-
The-Shelve Systems
Transition of Research and
Development into Operational Systems
External Research and Development
Systems
Internal Research and Development
SystemsSource: Rogers et al. 2019.
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Quality management systems, which are at the heart of a well-run organization, apply equally to operation of the various service delivery and production systems and to the overall management of the organization.
8.2.2 CAPACITY BUILDING
Capacity building underpins the human resources within any NMHS and within the main NMHS users and stakeholders. GHMD must build capacity to ensure that its efforts to modernize are sustainable; this step is indispensable and serves as a foundation for other systems and functions (as shown in figure 1). For a strong and effective GHMD, all staff must have continuous access to new skills through provision of short- and long-term training courses at home and abroad. On-the-job training is essential. A major challenge for GHMD is creating a strong professional meteorological and hydrological workforce. It is essential to have a steady supply of meteorologists, hydrologists, and related specialists at the BSc, MSc, and higher educational level with the ability to perform at the required levels. In this regard, strengthening the hydromet programs at national universities is critical, as these are the main sources for GHMD staff at present and likely to remain so in the foreseeable future (figure 20).
FIGURE 20. CAPACITY BUILDING
Capacity Building
NMHS Institutional Education Training
Stakeholder Institutional Training
Source: Rogers et al. 2019.
End-User Training and Outreach
Educating stakeholders and end users in the application of hydrometeorological products for decision making is equally needed. The end users’ inability to understand and interpret weather and climate products for decision making in economic sectors is a limiting factor, and user education should be implemented to overcome this gap. Educating the public to better understand warnings and probability forecasts, so they are aware of and able to prepare for disasters, is very important for effective use of information, especially for flooding, which is a major hydrometeorological threat in Georgia. User education should include workshops, open days to encourage visits by the public, and school visits, as well as distribution of flyers, publications, and public service videos and posting of educational materials on the GHMD website.
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8.3 Modernization of Observation Infrastructure, Data Management Systems, and Forecasting
This component aims to ensure that meteorological and hydrological observations networks are well functioning and interoperable. It further focuses on modernizing data management, communications, and ICT systems; improving weather and hydrological forecasting processes and numerical prediction systems; and refurbishing offices and facilities. Modernization of each system should be broken down to manageable packages for phased implementation (figure 21).
FIGURE 21. MONITORING AND OBSERVING SYSTEMS
Source: Rogers et al. 2019.
Monitoring and Observing
Systems
Global Data
Systems
National Data Systems• In situ observing systems
• Radar and other remote sensing systems
• External data systems — social media, private networks
Note: Monitoring and observing systems have two distinct subsystems. The first is the global data system, which includes all of the information received via the WMO Information System or the Global Telecommunication System and data from unique sources, such as satellite products from specific providers. The second is the national data system, which is a combination of observation networks supported by different entities—public and private, and crowdsourced data associated with social networks.
8.3.1 METEOROLOGICAL OBSERVATION INFRASTRUCTURE
The increasing risk of floods and droughts due to climate change will require better forecasts and response. Infrastructure modernization should focus on rehabilitation of the existing synoptic network to safeguard compatibility of and interoperability between different types of equipment and sensors; it also should introduce a higher degree of automation of observations to improve nowcasting and very short-range forecasts. Concerning the expansion of observing stations, it is necessary to point out that a ground-based observation network provides only moderate value for money from a weather and climate perspective. Access to satellite technology can now provide good analysis of snowpack and water resources relevant for many sectors. A ground-based observational network increases in value when assimilated into a common information layer through NWP, as it then offers a richer, more usable, sector-specific output for forecasters; it also gains in value when used as ground truth to calibrate radar data. Thus single (or even multiple) ground observations from an area of interest do not represent the full picture unless they are used as part of a common information layer. This road map strongly encourages any planned expansion or reorganization of the network to carefully assess the future needs for data and consider the requirements of users and constraints of the operators. Regular preventive maintenance by trained personnel once the network expansion has been undertaken will be a major condition for success—and under current conditions also a main constraint for GHMD.
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8.3.2 HYDROLOGICAL OBSERVATION INFRASTRUCTURE
Currently, the hydrological activities of GHMD are mainly focused on observation and data collection. Due to insufficient human capacities (quantitative and qualitative), the hydrological services cannot benefit in an appropriate way from many results of previous programs and projects initiated to strengthen those services. The existing capacities for operation and maintenance of GHMD’s observation network are insufficient, and this gap between requirements and existing capacities will widen further in the near future with further proposed installations of observation stations. Between the year 2008 and 2018, the number of stations nearly tripled, increasing from 21 to 59. Even if the hydrological network delivers water levels at 59 gauges, the value of this information is low, as rating curves exist at just over half of the stations. This deficit results mainly from the insufficient capacities of the Field Expedition Division of GHMD. It is responsible not only for discharge measurements but also for the acquisition of snow data (snow depth, snow density, and water equivalent) at the beginning of the snowmelt season, as well as inventory of glaciers and geodetical works, e.g., the analysis of geomorphological riverbed processes. Approximately 50 percent of its activities in the field of discharge measurements are provided as a paid service of NEA to hydropower plants. The remaining discharge measurements (approximately 150) at GHMD gauges are insufficient to fulfill the basic requirements of the existing hydrological network. Despite high investments to extend the observation system, limited human capacities hamper GHMD’s ability to take advantage of technological and scientific advances. The step from data collection to information production requires a strengthening of basic services such as ICT and data quality management, and a significant increase in capacities in technical support and technology infusion systems. Regular preventive and operational maintenance programs for all equipment need to be in place before any further modernizations of the network. This step also requires capacities for the calibration of hydrological instruments (e.g., current meters).
The extent and speed of network expansion should be proportional to GHMD’s capacity in operating and maintaining the stations. This capacity can be assessed through the operational status of existing automatic stations. Real-time information is critical for the fast-responding watersheds (with areas of less than 200 km2) and for flash flood forecasting. A revision of the operating procedures is necessary to consider the needs at different locations as a result of new demands, such as from the EU WFD or EU Floods Directive. The need for operational data at the existing stream gauge sites and for data loggers should be assessed, for instance, with regard to the new pricing system of irrigation.
Strengthening the status of data logging and transmission will allow the provision of reliable end-to-end data communication, the delivery of forecast and warning services to users, and the implementation of operational deterministic flood models. WMO’s recommended guidelines (WMO 2008) on establishing O&M programs for NMHSs should be taken into consideration. In a modernized hydrological observing system, all new stream gauge installations should also include recording rain gauges in the contributing watersheds. Real-time access to this rainfall data should be established and telemetry added to ensure that the data are automatic and operational at all times to trigger flash flood warnings.
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8.3.3 DATA MANAGEMENT, COMMUNICATION, AND ICT SYSTEM
A readily accessible historical database of hydrological and meteorological parameters is urgently needed to develop a range of warning and forecast services related to extreme weather and flood events that impact many sectors of Georgia’s economy. The modernization and expansion of GHMD’s observation network and improvement in its forecasting and service delivery will require significant improvements in ICT capacity (figure 22). A number of components are needed to establish a modern software/hardware environment: communications equipment and computers; harmonized database management systems for weather, climate, and hydrological data, including servers, software, web access, and social media; and remote sensing and GIS, including the satellite downlink. Such an environment will provide efficient and timely collection of data from the observational network and will speed up reception and processing of information products from leading international centers, making higher-resolution products and more information available to GHMD forecasters (figure 23).
FIGURE 22. INFORMATION AND COMMUNICATION TECHNOLOGY SYSTEMS
Source: Rogers et al. 2019.
Information and Communication
Technology Systems
Data Communication
Systems
Computer Hardware and Software
Systems
External Cloud Computing Systems
Telecommunication Systems
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FIGURE 23. THE RECOMMENDED INTEGRATED DATA CENTER FOR THE GHMD ENVIRONMENT
Global Surface Observations (Met)
National Surface Observations (Met)
Satellite Data
Radar Data
Global and Regional NWP/EPS
LAM
National Observations
(Hydro)
GTS
LoggerNet & Meteo RFC
EumetCast
FTP
GTS
FTP
LoggerNet & Meteo RFC
Note: DB = database; WS = workstation; SD = service delivery.
CENTRALIZED DATACENTER
Clima DB
Hydro DB
Forecaster WS
OPERATIONS
Model
SD Platform
(…)
Clima DB
Hydro DB
Forecaster WS
DEVELOPMENT & BACKUP
Model
SD Platform
(…)
HYDRO DIV
MET DIV
FORECASTING OFFICE
8.3.4 METEOROLOGICAL FORECASTING
Numerical Weather Prediction (NWP), including Ensemble Prediction Systems (EPS), coupled to an extensive in situ and remote sensing observational network (satellite, radar, upper air, and ground), underpins the information layer of an NMHS and is a foundation of modern forecasting (figure 24). It is a cost- and resource-intensive business limited to a few centers, because at its fully developed mode, it requires multimillion-dollar supercomputer infrastructure (with associated research and technical support). While limited area models are within the reach of many countries, it is arguable whether they are an appropriate approach, given the capability and resolution of current and near-future global and regional models. Since Georgia has the possibility of becoming a member state or a cooperating state of the ECMWF, it would have access to the best available NWP/EPS.
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FIGURE 24. MODELING SYSTEMS
Modeling Systems
Global NWP Systems
Regional NWS Systems
Source: Rogers et al. 2019.
Hydrological Modelling Systems
Limited Area Modelling Systems
Moreover, different model outputs from various global and regional centers are accessible to nearly all countries. As part of their NMHS modernization strategies, developing countries must receive the best possible training to allow them to extract optimum benefit from all the available and accessible tools. Modern forecasting and warning systems cover all time scales from the immediate (nowcasting) to climate time scales. Each range is often a specialization of particular forecasters. For example, severe hazard forecasting may be the responsibility of flood forecasters, tropical cyclone forecasters, drought forecasters, or a combination of these and other experts (figure 25).
FIGURE 25. FORECASTING AND WARNING SYSTEMS
Objective and Impact Forecasting and
Warning Systems
Nowcasting System/Flash Flood Guidance
Very Short-Range Forecasting System
Hydrological Modelling Systems
Limited Area Modelling Systems
Short-Range Forecasting System
Severe Hazard Forecasting System
Source: Rogers et al. 2019.
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Current forecasting at GHMD is based on output from the Synergie and METCAP systems, tools designed to be a complete working environment for the operational forecaster. Blending the in situ, remote sensing, and model data produces three-day forecasts plus 7- and 10-day outlooks for a number of cities in Georgia. No objective verification of forecasts is performed, although some subjective verification of forecast precipitation and temperature is performed against observations. No nowcasts or long-range forecasts are produced. As part of the longer-term modernization plans for GHMD, it is necessary to establish a comprehensive process for operational weather forecasting as is practiced in a well-functioning modern national forecast center. Such a modernization process will allow access to NWP/EPS digital data and products (short-, medium-, extended-, and long-range forecasts) from a global center (e.g., ECMWF) as well as access to the required software for data handling (license acquisition); it will also enable NWP post-processing and calibration (model output adjustment to country conditions) and production of regional and site-specific forecasts. This process, which requires an uninterrupted broadband Internet, allows moving from deterministic prediction to EPS. This shift is absolutely critical for estimating the uncertainty in the weather forecasts and the most likely outcomes, as well as the likelihood of an extreme event. Instead of running the NWP model once to produce a deterministic forecast, the model is run many times from very slightly different initial conditions to produce a probabilistic forecast. The range of different solutions in the forecast allows access to the uncertainty in the forecast and to the level of confidence in a deterministic forecast. The EPS is used to produce probabilistic forecasts and allows the application of techniques for impact-based forecasting, which is very important for decision making.
While access to the ECMWF global model digital data (9 km resolution) will represent a great step forward for GHMD, it should be noted that the required license costs €42,000 (approximately US$51,400) per year. An even better approach is for GHMD to become a member state of the ECMWF, which would provide GHMD with full access to digital data (including archive), as well as to the ECMWF supercomputing facilities and associated training. It should be noted that the ECMWF membership costs include an entry fee of US$264,000 plus an annual fee of US$60,000. Other tools for the modernization of forecasting include up-to-date software for the existing forecaster workstations (METCAP and Synergie), implementation of real-time data management, forecast process monitoring and verification, NWP post-processing, nowcasting, and impact-based forecasting techniques. Training is required in the use and interpretation of these products and processes, as well as in the overall forecasting process supported by SOPs.
In addition to the short-range forecasts, there is a need to develop monthly and seasonal long-range forecasts. GHMD should be able to access long-range forecasts, for example on the ECMWF website, and on the WMO Lead Centre for Long-Range Forecast Multi-Model Ensemble (at https://www.wmolc.org/), which provides access to long-range forecasts from 12 Global Producing Centers. Eventually, GHMD should also develop expertise in RCD techniques, which will allow it to provide high-resolution climate information on a national scale and with much greater detail and more accurate representation of localized extreme events.
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PHOTO 8. MODERN FORECASTING OFFICE ENVIRONMENT IN THE AUSTRALIAN BUREAU OF METEOROLOGY
Credit: Haleh Kootval, World Bank.
• Establishment of a network of automatic or manual hydrometric stations linked to a central control by some form of telemetry to collect real-time data for the prediction of flood severity
• Provision of rainfall forecasts (quantity and timing), for which NWP models are necessary
• Flood forecasting model software linked to the observing network and operating in real time
• Preparation of forecast information and warning messages, including expected impact
• Dissemination and communication of such messages, including what action should be taken
• Interpretation of the forecast and flood observations to determine impacts on communities and infrastructure
• Response to the warnings by the agencies and communities involved
• Review of the warning system and improvement as necessary after a flood event.
8.3.5 HYDROLOGICAL FORECASTING AND HYDROLOGICAL INFORMATION SYSTEM
Flood forecasting and warning as a focused activity in the hydrometeorological sector is a relatively recent development. This may be evidence of the growing seriousness of flood impacts, and the risks posed by floods to both financial investments and areas of increased population. Flood forecasting requires an understanding of both meteorological and hydrological behavior for the particular conditions of the country. While the ultimate responsibility for flood forecasting lies with the appropriate government agencies at a national level, the information on predicted flooding needs to be made available at more localized levels, such as a river basin or a center of population. To form an effective real-time forecasting system, the basic structures need to be linked together in an organized manner. The main components of a modern and well-functioning national flood forecasting and warning system include the following:
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Many rivers normally pass over flood-affected areas and therefore river management will contribute to managing flood risk.
MEPA’s decision to implement the EU Floods Directive means that in the future, MEPA will be required to specify both hydrological flood hazards (in the form of hazard maps) and the resulting risks of flooding for the population and property. Thus, flood forecasting, flood statistics, and hydrological and hydraulic modeling have to be connected. Currently the capacities for deterministic modeling at GHMD are not sufficient. As described previously, GHMD has several models available, but their operational use is hampered by two constraints: insufficient discharge and geodata for calibration and validation of models, and insufficient human capacities.
Introduction of model-based hydrological forecasting in Georgia is crucial to respond to requirements from many users and to improve the timeliness and quality of hydrological forecasts. GHMD needs to allocate additional capacities in hydrological modeling; a High-Performance Computing Cluster is especially important as a precondition of improving EWS and water management strategies, establishing flood and drought risk management, and extending water management systems and optimizing their operation. It will be necessary to evaluate hydrological simulation models for usability in the Georgian context and to select and acquire adequate models. The existing statistical tools for forecasts that may be employed in Georgia will continue to be in use in the near future, but these tools have weaknesses. Deterministic snow models can be used as an alternative to statistical models with the help of high-resolution satellite data (e.g., snow cover, snow depth, and water equivalent in snow). By introducing new hydrological models and software packages for short- and longer-term flow forecasting (which have been tested in other mountainous countries), and by enhancing technical capacities for modeling, a higher quality of forecasts can be ensured. Other simulation models for water resources systems should be tested for setting up water balances and planning for water resources allocations, river basin water management, and prognoses of future conditions. An important task will be evaluating the effects of climate change on rainfall and streamflow by deterministic models driven with plausible climate change scenarios. Selection of a modeling system should include the availability of training, documentation, technical support, and calibration.
In addition, as the accuracy and reliability of meteorological models and quantitative precipitation forecasts increase, a 24-hour, seven-day-a-week flood watch alerting advisory could be added. A Doppler radar would be essential to specify the location of storm cells, to estimate the spatial differences in rainfall intensities, and to provide input data for flash flood alert systems. To be effective, flood early warning should provide adequate lead time so that institutions and communities at risk can undertake preparatory and mitigating actions.
Integrated river basin management, which is a key element of the WFD, would be useful for various purposes, including flood forecasting, irrigation management, and reservoir operations. It requires improved communication with other departments of NEA (e.g., on water quality issues) and with water managers. In competing situations (e.g., between hydropower and irrigation), runoff forecasting at different time scales can be used to manage the water resources in an effective manner. During floods the reservoir operation could ensure minimum impact resulting from extreme runoff downstream of the reservoir and save water for drier times of the year. Such forecasting will require advanced technology such as digital elevation models and the effective use of available tools such as GIS. Besides forecasts, the hydrological component of GHMD has to provide information about the inventory of surface waters in Georgia. This includes flood and drought statistics, characteristics of the water balance in the past and the future, information about the hydrological conditions at benchmark stations, and operational data for water management. Currently, the hydrological service is based mainly on data and information derived during the Soviet era and is still using the methodologies of that period. Another (small) part of GHMD tries to implement new methodologies, such as hydrological models, but has very limited human capacities and
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suffers from a lack of data (e.g., digital elevation data or discharge data). A small number of well-educated people who work on these issues make great effort to introduce new methods—for example, by adapting mathematical forecasting models or applying new technologies such as GIS, satellite data, and others. At the same time, traditional methods, inherited from the past, still need to be applied to provide the basic service. The potential of a new digitized network cannot be realized due to the limited human capacities. This constraint has led to the existence of two parallel hydrological information systems: the paper-based hydromet service and the digital one. The very low number of hydrological stations with rating curves is symptomatic of this situation. Despite high investments to expand the observation system, limited human capacities hamper GHMD’s ability to take advantage of these technological and scientific advances.
Existing best practices and standards can be utilized in delivering services, but the insufficient technical capacities in modeling, ICT, and maintenance of the stations and equipment limit their applicability. This is especially the case for application of hydrological models, hydrological assessments, hydrological forecasting, and information management. The step from data collection to information production requires a strengthening of basic services such as ICT, QMS, capacity building, and technology infusion systems.
In summary, the modernization of hydrological forecasting and information at GHMD should provide new hydrological tools and information as follows:
Seasonal forecasts, based on remote sensing data and snow modeling, including technical facilities such as servers, software licenses, training, quality management, dissemination of products
River and flash flood warning and alert systems, including technical facilities such as new sensors (e.g., water level recording based on radar precipitation stations with data automatic transfer), weather radar data, data transmission systems, visualization interfaces with servers and hydrological models, software licenses, training, quality management, and dissemination of results
River basin management based on operational water balances for the main river basins, including data from the main water users and water management facilities
9. ROAD MAP SCENARIOSThe road map for Georgian hydrometeorology and EWS considers several questions:
• How well the long-term strategy of GHMD—the single national hydromet service provider—is aligned with the expectations of the government and people of Georgia
• What future needs for data and information users will have
• How to ensure GHMD has the tools to match the expectations of the government and people of Georgia
• How to design a business plan that capitalizes investments in GHMD’s modernization to provide sustained, high-quality, value-for-money public and commercial services throughout Georgia
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The above considerations have shaped the road map’s three development scenarios, which are based on realistic possibilities and ultimately aim to transform GHMD into a technically modern and sound hydrometeorological service by narrowing the gap between its current status and the level of services that are needed for fully discharging its public service mandate. Each scenario contributes in different and progressively more comprehensive ways, based on the time and resources available, to a system capable of producing and delivering (i) timely warnings of extreme and hazardous weather events and their potential impacts; and (ii) forecasts for operations and planning in weather and climate-sensitive economic sectors, particularly agriculture, transport, and water resources management.
Taking account of the forthcoming implementation by UNDP of the GCF-funded project FP068 (Scaling-up Multi-Hazard Early Warning System and the Use of Climate Information in Georgia), along with the efforts of various development partners supporting the hydromet agenda, scenarios 2 and 3 of the road map introduce the most critical and efficient elements of the observational network and forecast production and delivery systems. The intention of including these scenarios in the road map is to offer the government the opportunity to potentially maximize the synergies between the World Bank’s proposed activities and those of UNDP and other development partners.
Scenario 1: Technical Assistance. This scenario provides technical assistance for high-priority activities to improve basic public services by introducing affordable new technologies into GHMD and training GHMD staff for heightened capacities and capabilities (immediate to short term: two-year duration). The success of this assistance requires some basic investments and additional staff to implement the new technologies.
Scenario 2: Intermediate Modernization. This scenario makes investments to modestly improve the ability to provide weather and hydrological services that meet the public service needs of the most important user communities, including disaster management, agriculture, transport, and water resources management (medium term: four-year duration).
Scenario 3: Advanced Modernization. This scenario makes investments to bring GHMD the capabilities for providing fit-for-purpose data, forecasts, and warning services for the safety of the public, and support to develop the most important socioeconomic sectors (long term: seven-year duration).
The first two scenarios build up the capacity of GHMD to discharge its public service responsibilities. The third provides the opportunity to build on the capacity of public weather and hydrological services to provide additional tailored services, either alone or in partnership with other institutions.
The steps outlined in this road map to modernize GHMD are based on extensive discussions with the staff of the various divisions and offices of GHMD and key stakeholders. These discussions reveal gaps between the requirements of the user community and the capabilities of GHMD to respond to those needs. The proposed steps are meant to guide the transformation of GHMD to a fit-for-purpose organization, with standards for delivering products and services that are at the highest possible level, and with the ability to discharge public service duties to the satisfaction of the users. Clearly, GHMD strives to provide users with diverse, high-quality products offering broad coverage. However, in doing so, it faces major challenges in these areas: (i) ensuring sufficient numbers of well-trained technical staff; (ii) having access to appropriate technical assistance and guidance; (iii) ensuring that its capacity keeps pace with and meets the ever-growing demand for its services; and (iv) securing adequate and sustained funding.
GHMD should clearly demonstrate to the government authorities the importance of access to essential modern tools and technologies—for observation, data processing and forecasting infrastructure, and delivery of services and advisory guidance to users. It should also rigorously argue the case for the expected social and economic benefits of the services it could provide (by reducing losses from floods and other hazards) given adequate
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government support for its operations.
To compete for and optimally use scarce public resources, GHMD must justify the need for improving its operations and thus the investment of public funds to support its basic infrastructure and suite of services. To demonstrate the benefits to users, however, GHMD must first be able to provide fit-for-purpose services to the satisfaction of those users, which it cannot perform without a substantial upgrading of its forecasting and ICT infrastructure and its services capability. This is a vicious cycle whereby the gap in GHMD’s available resources and its ability to serve its mandate keeps widening.
This road map and the scenarios it presents offer GHMD a systematic basis for setting strategic and forward-looking priorities to improve its service delivery capability, given available (and potential future) financial and human resources. Future challenges may include the impacts of climate change with resulting increases in the frequency and intensity of natural hazards as well as the emergence of new technologies and economic evolution in the country.
Based on users’ requirements, it is clear that GHMD should produce more relevant, location-specific, well-articulated, and usable information, not only on hazards but on their impacts on target areas and population. It is no longer sufficient for the department to provide hydrological information on the basis of old data and methods dating back to the Soviet era, or for its main activities to be analyses of observational data and production of statistical information alone. This assumption has been the basis of the different scenarios proposed in this road map. Certain steps can be taken quickly and with rather limited investments to enhance the utility of weather-, climate-, and hydrology-related information for users. Examples include training the GHMD technical staff to access, understand, and use readily available products and guidance from various regional and global centers for improved forecast and warning services; streamlining the forecasting and IT procedures and practices; and developing regular means of user communication and feedback. Essential tools such as computers and servers will be needed for some essential improvements. Other changes may require a series of actions over medium or long time scales and require more substantial investments. One example is introducing capacities for hydrological modeling.
It bears repeating that the modernization of GHMD should be guided by three main components: (i) enhancement of service delivery; (ii) institutional strengthening and capacity building; and (iii) modernization of observation infrastructure, data management systems, and forecasting.
The development of a Concept of Operations as a living operational plan will be essential to guide and support the transformation of GHMD. The CONOPS is based on the principle of a system of systems (figure 7) and proposes various alternatives, depending on the level of financial and human resources and other constraints, for the transformation of each individual system. The provision of the best possible products and services requires a full modernization program. This will form Scenario 3 of this road map and will aim to bring GHMD’s capabilities for providing data, forecasts, and warning services up to those of a well-functioning developing country NMHS that is able to meet the needs of a wide spectrum of users. The CONOPS is particularly useful in understanding the impact of any new activity in the existing system, including identifying the need for additional resources for operations and maintenance.
The alternatives, however, should be considered for each system if there are not sufficient resources to provide this full modernization. It will be necessary to prioritize the most important changes in the systems and to consider where the program should be scaled back in favor of those priorities. The solution may be to trim down from the full modernization to a relatively modest improvement in services, carried out in consultation with users and matched with a corresponding reduction in their expectations. This is Scenario 2 in the road map: an intermediate level of investment to achieve a modest improvement in capabilities
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for providing weather, climate, and hydrological services to meet the public service needs of the most important users, such as disaster management, agriculture, transport, and water resources management. Finally, if there are not enough resources for a moderate modernization, it will be necessary to choose an alternative that provides a minimum basic improvement through technical assistance. This is Scenario 1 in this road map and represents a set of high-priority activities. It focuses on improving basic public weather and hydrological services, strengthening the GHMD staff’s capacity to access and use available tools and techniques, and introducing basic affordable new technologies. In this way the CONOPS will guide the process through considering a whole range of alternatives and finally choosing the one that is both affordable and able to provide the best possible services to users.
There are two possibilities to build and implement each scenario. The first is that these scenarios could be interdependent and conducted in phases, in which case each builds on the previous one to contribute to the overall goal of the modernization. That is, Scenario 2 assumes the accomplishment of objectives in Scenario 1 and builds on them; and Scenario 3 assumes the accomplishment of objectives in Scenarios 1 and 2 and builds on those. The second possibility is that if resources are made available to undertake the modernization as a stand-alone package, for example, under Scenario 3, then this scenario will also comprise the activities as described under Scenarios 1 and 2. Similarly, a stand-alone package under Scenario 2 will comprise also activities contained in Scenario 1. The cost of scenarios 2 and 3 is provided for both the phased and the stand-alone approaches.
In the World Bank’s experiences of NMHS modernization in other countries (Rogers and Tsirkunov 2013; Rogers et al. 2019), a very beneficial strategic approach is the use of international advisors who work alongside the local staff. Such advisors could provide Georgian employees of GHMD with practical ongoing advice, guidance, and assistance as long as is needed in the implementation of the different scenarios to ensure that the required capacity and expertise are built in different divisions of GHMD.
The three scenarios of modernization of GHMD are presented below.
9.1 Scenario 1: Technical Assistance for High-Priority and Immediate Needs
This scenario includes high-priority activities needed to achieve critical minimal capabilities for improved weather, climate, and hydrological services (focused on improving basic public services by strengthening GHMD’s capacity in using and interpreting available and accessible tools and technologies and introducing basic affordable new technologies). Activities focus on developing a national strategy for service delivery; establishing a hydrometeorological user group; developing a CONOPS to guide the design of activities for Scenario 1; establishing/strengthening a collaborative approach for service provision to key government stakeholders; training; introducing near-real-time QA/QC of GHMD’s own observations; accessing and using NWP/EPS data and products from other centers; initiating an objective verification of NWP data and products from other centers against GHMD’s own observations; enhancing use of remote sensing products for hydrological services; initiating basic long-range forecasting and hydrological forecasting; procuring basic computing and communication equipment as required; and revising seasonal river forecast methods. While the list below is indicative of the wide range of activities that may be considered for development/enhancement of the various functions of GHMD under Scenario 1, the actual activities included under this scenario are deemed the most urgent and those that will result in major improvements in each particular component of the hydromet system (forecasting, ICT, service delivery, etc.). The implementation of this scenario should be completed within two years.
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Strengthening institutional capacity can be achieved through these means:
1. Developing an initial CONOPS to guide design of activities for different systems under this scenario
2. Developing a business plan to capitalize the investment in GHMD’s modernization to provide sustained, high-quality, value-for-money public and fee-based services throughout Georgia
3. Assisting GHMD in developing a legal and regulatory framework, potentially including enactment of a law on hydrometeorology, based on the existing general regulation on hydrometeorology
Strengthening service delivery can be achieved through these means:
1. Developing and implementing a national strategy for service delivery based on the WMO Strategy for Service Delivery and Its Implementation Plan (WMO 2014). The WMO strategy defines the various stages and elements of a continued process for developing and delivering services, and it guides NMHSs through the steps in assessing and improving their current service delivery. For GHMD, the initial step includes assessing its current level of service delivery using the Service Delivery Progress Model of the WMO Strategy document (annex 3), followed by close consultation with GHMD’s key stakeholders (in DRM, agriculture, water resource management, transport) to gather their requirements. The next stages will involve designing the required services and delivering them to the user sectors.
2. Establishing closer collaboration with disaster management, by (for example) establishing/strengthening SOPs, conducting joint exercises, providing mirror computers for display of weather information as seen by the forecaster, and attaching a meteorologist to the disaster management office during severe weather events, for improved EWS.
3. Applying the national strategy for service delivery and CONOPS in developing initial SOPs for operating the critical existing and new equipment; in the review and needed improvements of forecast production; and in service delivery for both meteorological and hydrological functions.
4. Establishing a hydrometeorological user group to develop and enhance different services and to improve coordination among service providers and improve interaction with and response to users.
5. Initiating/strengthening a quality management system across the GHMD institutional and operational systems.
6. Initiating the provision of information and services in collaboration with key government stakeholders and agencies responsible for water management, irrigation, energy (hydropower), climate change impact assessments, transport, and emergency management.
7. Increasing dissemination channels for enhanced provision of PWS and hydrological services.
8. Initiating the process of transferring all responsibility for the provision of information and services to the aviation sector from SAKEAERONAVIGATSIA Ltd to GHMD.
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Improvement of short and medium-range weather forecasting can be achieved through these means:
1. Streamlining the forecasting processes, procedures, and functions
2. Training forecasters to build on current capabilities to enhance the understanding and maximize the use of NWP/EPS data and products for short- to medium-range forecasts from leading global centers (e.g., ECMWF, GFS, UK); training in the operation and maintenance of the forecasting systems, including the use of any new techniques taught during the training
3. Initiating an objective verification of NWP data and products from other centers against GHMD’s own observations
4. Introducing improved techniques for verification of public forecasts
5. Training staff in EPS and the concept of probabilistic forecasting and its benefits
6. Training staff in the concept and basic application of impact-based forecasting through interpreting forecasts and adding other information to demonstrate the impact of weather and associated hazards (initial and follow-up training)
7. Purchasing license for access to graphical products from a global center (e.g., ECMWF)
8. Using all relevant data as effectively as possible for optimum forecast production
9. Upgrading the tools for visualization and manipulation of data and products by forecasters
Improvement of long-range weather forecasting can be achieved through these means:
1. Training staff to build up knowledge and understanding of concepts related to long-range forecasting
2. Providing access to and use of products from Global Producing Centers for long-range forecasts
3. Tailoring long-range forecasts for specific applications and users
4. Introducing concepts of climate models and downscaling
Improvements in ICT can be achieved through these means:
1. Urgently addressing the issue of ICT bottlenecks, which are a main source of problems in monitoring, forecasting, and service delivery systems, and preparing an implementation plan for the ICT system (infrastructure, human capacity, software) for a complete operational environment including observations, models, forecasts, and products in an integrated data center
2. Converting all data into a standard format required for functioning of an integrated ICT system, covering the needs of the meteorological and hydrological divisions as well as the requirements for improved data exchange between them
3. Upgrading the Internet bandwidth
Support to the observing network can be achieved through these means:
1. Training in calibration of the data from the newly acquired Doppler radar (2019) and in the use and interpretation of radar products
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2. Training in the use of facilities of the new calibration laboratory (2019)
3. Training in managing and maintaining observation networks
Improvements of the hydrological services can be achieved through these means:
1. Establishing the basis for quantitative hydrology by setting up rating curves for all hydrological gauges and by providing discharge data together with water levels, to ensure an extension of the hydrological service from the provision of water levels to corresponding discharges
2. Improving the automatic flow of quantitative hydrological data by a joint data management system, including quality-controlled historical data
3. Ensuring the components of the existing heterogeneous data management system (consisting of components from Campbell and Vaisala) are linked with the AQUARIUS system that will be implemented in future
4. Validating hydrological tools and methods dating back to the Soviet era to specify the needs for new methodologies that provide updated hydrological information for the following aspects of water management:
• Knowledge of water resources
• Statistical characteristics of hydrological time series
• Analyses of the current hydrological situation and forecasts of the hydrological conditions in near future
• Forecasts and real-time data of hydrological extremes (floods, droughts)
• Assessments of impact of water management activities and land use changes on hydrological conditions
• Assessments of hydrological impacts of climate change, based on monitoring and simulations
5. Strengthening the application of GIS through a common database using QGIS software (freeware) and through access to global information systems such as Google Earth Engine IDE (GEE), Amazon AWS, Microsoft ModisAzure, and others
6. Flood forecasting and flood risk management, specifically to improve hydrological flood forecasts by operationalization of conceptual hydrological models with direct integration of real-time data through automatic data assimilation; estimation of forecasting uncertainties by using discharges instead of water levels
7. Implementation of impact-based forecasting by specifying critical water levels at points of interests together with local authorities responsible for EWS
Taking into consideration the current staffing capacity of GHMD, the most urgent items in the comprehensive list above have been selected for the implementation of this scenario. However, as mentioned before, if resources allow, the items below could be revised and expanded. The cost of various components of Scenario 1 is shown below.
For improved institutional capacity, estimated total funding of US$66,000 is needed, as follows:
1. Advisory services, including training, to assist GHMD in developing a CONOPS for Scenario 1 to guide design of activities (one month, US$22,000)
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2. Advisory services, including training, to assist GHMD in developing a business model (1 month, US$22,000)
3. Advisory services to assist GHMD in developing a legal and regulatory framework based on the existing general regulation on hydrometeorology (one month, US$22,000)
For improved meteorological services, estimated total funding of US$294,000 is needed, as follows:
1. Advisory services to assist GHMD in understanding and documenting stakeholders’ detailed requirements (meetings, workshops, and surveys); establishment of a baseline for user satisfaction with the current GHMD services through conducting a user-based assessment; development of a national strategy for service delivery and application of the CONOPS (2 months, US$44,000)
2. Training and advisory services for streamlining the forecasting processes, procedures, and functions; introduction of EPS and probabilistic forecasting; forecaster training to understand and use available global and regional NWP data and products and to perform forecast verification (nine months over two years, US$198,000)
3. Training for GHMD forecasters and DRM on the principles and practices of impact-based forecast and warning services (four two-week sessions over two years, US$44,000).
4. Purchase of graphical (not digital) product license from a global center (US$4,000 per year).
For improved hydrological services, estimated total funding of US$224,000 is needed, as follows:
1. Advisory support for operationalization of the outcome of the Rioni project as a starting point for the installation of a flood forecasting center at GHMD. This includes training for new staff, advisory services to organize data flows, and dissemination of forecasts (two months, US$44,000).
2. Significant expansion of hydrometric capacities of GHMD to establish rating curves at all registering gauges (including the gauges used in the Rioni project). This requires additional staff, equipment, and vehicles to ensure the provision of a database essential for implementing hydrological models and forecasts (given that the existing database has been rendered outdated by climate change at many locations) (additional staff, two vehicles, and three current meters, US$92,000).
3. Advisory services to implement model-based forecasts in operational hydrological services through an integrated hydrological monitoring and forecasting system that considers existing and future data availability and (in cooperation with end users) the need for additional hydrological information, differentiated between operational purposes (forecasts and observations, transmitted in real-time) and the basic network. These services are essential for long-term monitoring of hydrological conditions and water resources assessments in future (three months over one year, US$66,000).
4. Advisory services to assist in the initial development of CONOPS to guide design of activities of a hydrological forecasting center (one month, US$22,000).
For improved ICT-related systems, estimated total funding of US$546,000 is needed, as follows:
1. Advisory services and training for increasing the dissemination channels for PWS and hydrological services, including implementation of CAP at GHMD and disaster management (one month over three months, US$22,000)
2. Procurement of computers, including special furniture, and basic software to establish two forecaster desks (US$20,000)
3. Advisory services to improve infrastructure, human capacity, and software, including training to address the issue of ICT bottlenecks due to incompatible data formats; data transmission; near-real-time QA/QC procedures and archiving; and development of SOPs for the main ICT operations (six months, US$132,000)
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4. Selection and procurement of the most suitable visualization system, including hardware, software, and training for the forecast office for integration of all meteorological observations and model data (US$298,000)
5. Advisory services to develop an integrated system for data transfer, quality control, and data storage and management under consideration of the needs of embedded hydrological models by analyses of the required flow of data and information, including linkages with meteorological forecasts (hydrological component of the ICT) (two months, US$44,000)
6. Upgrade of Internet bandwidth (US$30,000)
To fully realize the benefits of the technical assistance offered in this scenario, an increase in staff is recommended, as shown in table 5. With an estimated average remuneration cost of GEL 1,200 (US$456 as of February 12, 2019) per month per person and the required addition of 33 persons to the current GHMD staff, the additional staff cost for the implementation of this scenario is US$180,576 per year. Note that the same remuneration cost has been applied for both technicians and forecasters/engineers: this should be adjusted for the actual costs of each category. The source of the additional staff is not fully clear at the moment. While some specialists will graduate from universities, some staff may come from government agencies or be contracted from the private sector. The latter requires setting up a regulatory framework for contractual/partnership arrangements.
The activities proposed in this scenario will strengthen the capabilities of GHMD to discharge its basic public functions.
TABLE 5. ADDITIONAL STAFF AND STAFF COSTS REQUIRED TO IMPLEMENT SCENARIO 1
Position Scenario 1Engineers/ Scientists (Number)
Technicians (number)
expenditures (US$)
additionally allocated
Personnel costs
(US$/year)Remarks
1 Observation 2 2 21,888Increase in hydrometric capacities to ensure the proper operation of the existing network (discharge measurements, rating curves)
2 Modeling 3 0 16,416
Adaptation of existing models (derived from the results of the Rioni project) to an extended hydrological database; validation and calibration, additional computational nodes within the model; permanent updating
3 Forecasting 1 0 5,472 Step-wise replacement of manual forecasts by numerical forecasts during floods
4 Hydrological Analyses 3 0 16,416
Services such as annual updated flood statistics, water balances, climate change assessments, reports about quantitative hydrology for the implementation of the Water Framework Directive
Total Hydrology 9 2 60,192
HYDROLOGY
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5
Observation
2 3 27,360 Operation and maintenance of surface-based remote sensing (Doppler radar)
6 0 5 27,360 Operation and maintenance of the existing network
7 0 2 10,944 Operation of the calibration laboratory (met and hydro)
8Use of model
products (objective
forecasting)
3 0 16,416
Wider use of global and regional NWP data and products and initiation of many forecasting tools such as EPS and probabilistic forecasting. These are essential to bring the forecasting capabilities up to an acceptable level.
9
New forecasting
methods (impact-based, probabilistic)
2 0 10,944
Implementation of the outcome of the review of the forecast production procedure, from data stage to delivery stage, including impact-based forecasting and seasonal forecasting. These are essential steps for modernizing the forecasting practices.
10 Service delivery 2 0 10,944
Establishment of the foundation for service delivery (which is very limited now) through tools such as a strategy for service delivery; CONOPS; QMS; increased dissemination channels for PWS and hydrological services, including implementation of CAP; hydrometeorological user group. Outreach and user education represent the first step in building capability of GHMD as a service provider.
Total Meteorology 9 10 103,968
METEOROLOGY
11 Observation 3 0 16,416Data management (both met and hydro); ICT system, better data utilization; maintenance of the dissemination systems
Total ICT-Related 3 0 16,416
Total Hydromet 21 12 180,576
ICT-RELATED
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The total cost of activities under Scenario 1 is US$1.13 million. The biggest impact under this scenario is expected to be the strengthened institutional and staff capacity, enhanced delivery of weather and hydrological services, and improved forecasting and ICT capabilities. Using the progress models for various components of GHMD, the service delivery capability is expected to be raised to a full Level 3 (Development in Progress); the modeling and forecasting capability is expected to be raised to Level 3 (Development in Progress); and the observing and telecommunication capability is expected to reach between Levels 2 and 3 (between Development Initiated and Development in Progress).
9.2 Scenario 2: Intermediate ModernizationThis intermediate investment scenario aims to improve capabilities to provide weather, climate, and hydrological services to meet the needs of the most important public service users, such as disaster management, transport, agriculture, and water resources management. As explained earlier in this chapter, the scenario could be implemented either under a phased approach that builds on Scenario 1, or as a stand-alone scenario. As presented below, it is assumed that this scenario builds on the activities of Scenario 1, which are not repeated here. However, if this scenario is chosen for stand-alone implementation, then the cost of investment for activities under Scenario 1 should be added to this scenario.
Under Scenario 2, the following set of potential activities may be undertaken:
1. Revising and further developing a national strategy for service delivery (already initiated)
2. Revising and further developing a business plan (already initiated)
3. Further establishing closer collaboration with disaster management for improved EWS
4. Establishing a hydrometeorological user group and revising and further developing the CONOPS to guide the Scenario 2 activities
5. Maximizing the utility of the meteorological observation network following the introduction of new equipment such as weather radar for application in (e.g.) hydrological forecasting
6. Linking the observing systems (hydrological and meteorological), data management, and modeling systems in a common format to avoid problems of various ICT systems
7. Enhancing training in EPS and probabilistic forecasting
8. Enhancing training in impact-based forecasting
9. Initiating long-range forecasting and hydrological forecasting for different forecast periods
10. Procuring computing and communication equipment for modeling and forecasting
11. Maximizing the utility of the hydrological network by obtaining quantitative hydrological data for water management and other key stakeholders
12. Enhancing the use of remote sensing products for hydrological services
13. Operationalizing quantitative hydrological forecasts by establishing a hydrological forecasting center to apply numerical models for forecasts at hot spots
14. Assessing the state of water resources in the country, including through a database of water uses and their impacts on hydrological conditions
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15. Training in scenario-based drought forecasting and links with seasonal meteorological forecasts
16. Training to establish modern methods to regionalize flood statistical assessments, which are based either on rain events and hydrological models or statistical analyses of long observation series
17. Training stakeholders and end users to build their understanding and capacity in using hydromet information
18. Strengthening systems for monitoring and feedback.
The budget for this scenario should include the estimated cost of any new equipment, tools, instrumentation, and software. The O&M budget for this scenario (approximately 10 percent of the initial capital expenditure) should be used for, among other things, spare parts, consumables, fuel, increased communication, power, and other operating costs. It is expected that the implementation of this scenario (combining activities included in Scenario 1) should be completed within four years.
In addition to the survey of the observation and the ICT systems to specify the existing gaps and outdated and incompatible components, the rest of the technical infrastructure of GHMD should also be examined to introduce new technical equipment and methodologies. The most urgent items among the comprehensive list above have been selected for the implementation of this scenario.
For strengthening institutional capacity, estimated funding of US$22,000 is needed, as follows:
1. Advisory services for updating the CONOPS to guide design of activities under Scenario 2 (one-half month, US$11,000)
2. Advisory services for revising and further developing a business plan for Scenario 2 (one-half month, US$11,000)
For improved meteorological services, estimated total funding of US$590,000 is needed, as follows:
1. Advisory services and training to support the development of a QMS in GHMD, which includes the design and implementation of a standardized QMS (following international good practice) and preparation of GHMD for potential certification under International Organization for Standardization (ISO) Standard ISO 9001. As part of this activity, a gap analysis would be carried out to identify which clauses of ISO 9001 are not being fully applied (or applied at all) by GHMD, and then develop remedial actions and procedures (up to seven months, US$150,000).
2. Advisory services for further development of the forecaster environment using the visualization system (e.g., development of a dashboard for the forecaster workstation) and related training (two months, US$44,000).
3. Advisory services, including training, for downscaling of climate models and initiating seasonal forecasts (one month, US$22,000).
4. Advisory services, including training, for post-processing of NWP output (three months, US$66 000).
5. Advisory services, including training, to advance the implementation of EPS, probabilistic forecasting, and impact-based forecasting to an intermediate level; also including on-the-job support (six months over one year, US$132,000).
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6. Advisory services, including training, for further engagement with users through strengthening of monitoring and feedback systems and tools (surveys) and enhanced training of stakeholders and end users (one month over 12 months, US$22,000).
7. Advisory services to assist GHMD in conducting workshops with DRM to define warning thresholds and update knowledge of stakeholder needs (one month over 12 months, US$22,000).
8. Advisory services to assist GHMD in conducting workshops and developing a prototype warning system with DRM based on likelihood and severity of impact, using common color coding for warning thresholds for all hazard impacts (three months over two years, US$66,000).
9. Advisory services to assist GHMD in conducting workshops and developing SOPs for all partners involved in the delivery of the impact-based forecast and warning services (three months over two years, US$66,000).
For improved hydrological services, a total of US$154,000 is needed, as follows:
1. Advisory services to ensure the linking of real-time data, Numerical Weather Prediction, and climatological data with hydrological and hydraulic models in a central server (Delft-FEWS) and a tailor-made design of hydrological forecaster interfaces (two months, US$44,000)
2. On-the job training for advancing hydrological analyses at ungauged sites by several methods (two months, US$44,000)
3. On-the-job training for impact-based drought forecasting (data analyses, modeling, utilization of seasonal meteorological forecasts) within the Delft-FEWS environment (two months, US$44,000)
4. On-the-job training for snow modeling using remote sensing data to improve seasonal flood forecasts (three months, US$66,000)
For improved ICT-related systems, estimated total funding of US$1,364,000 is needed, as follows:
1. Design, procurement, and installation of a centralized data center for integration and automation of the meteorological and hydrological data flow, and for data storage and visualization, including advisory services and training (nine months, US$800,000)
2. Acquiring membership in ECMWF* plus five years of annual fees (US$564,000, including entry fee of US$264,000 plus annual fee of $60,000)
To fully realize the benefits of the technical assistance offered in this scenario, an increase in staff is recommended, as shown in table 6. With an estimated cost of US$456 per month per person and the required addition of 59 trained staff to the existing GHMD staff, the implementation of this scenario requires an additional US$322,848 per year in staff costs.
* According to the ECMWF website, “By bringing together resources from across its Member and Co-operating States, ECMWF serves its community by providing world-leading weather forecasts, specialist software, and the largest meteorological data archive in the world. An extensive educational programme facilitates scientific collaboration and equips Member States to make the most of ECMWF’s products. Member and Co-operating States receive ECMWF’s numerical prediction data in real time to prepare forecasts for their end users. They can access ECMWF’s basic computing facilities, the meteorological archive, and temporary tape storage. Member States also have access to the supercomputers for their own post-processing activities, and permanent tape storage.” ECMWF, “What We Do,” https://www.ecmwf.int/en/about/what-we-do.
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TABLE 6. ADDITIONAL STAFF AND STAFF COSTS REQUIRED TO IMPLEMENT SCENARIO 2
Position Scenario 2Engineers/ Scientists (Number)
Technicians (number)
expenditures (US$)
additionally allocated
Personnel costs
(US$/year)Remarks
1 Observation 4 4 43,776Increase in hydrometric capacities to ensure the proper operation of the existing network (discharge measurements, rating curves)
2 Modeling 4 0 21,888
Adaptation and extension of flood models to other gauged basins with an extended hydrological database, validation and calibration of flood and water balance models, additional computational nodes within existing model, and permanent updating to provide results according to user needs
3 Forecasting 2 0 10,944 Complete replacement of manual forecasts by numerical forecasts
4 Hydrological Analyses 4 0 21,888
Services such as annual updated flood statistics, water balances, climate change assessments, reports about quantitative hydrology for the implementation of the Water Framework Directive, drought forecasts, and monitoring assessments of anthropogenic impacts on hydrological conditions
Total Hydrology 14 4 98,496
HYDROLOGY
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5
Observation
3 6 49,248 Operation and maintenance of surface-based remote sensing (Doppler radar)
6 0 7 38,304 Operation and maintenance of existing network, plus addition of new equipment
7 0 2 10,944 Operation of the calibration laboratory
8Use of model
products (objective
forecasting)
6 0 32,832
Advancing the implementation of EPS for probabilistic forecasting, and use of other modeling tools from advanced centers for short-and medium-range forecasting, including digital model data
9
Advancing impact-based, (probabilistic
forecasting and verification)
3 0 16,416Enhanced implementation of impact-based forecasting, better data use for improved forecasting and objective verification; seasonal forecasting
10 Service delivery 4 0 21,888
Intermediate service delivery CONOPS for Scenario 2; QMS, enhanced monitoring and feedback systems and training of stakeholders and end users
Total Meteorology 16 15 169,632
METEOROLOGY
11ICT-related for
both hydro and met
10 0 54,720
Total ICT-Related 10 0 54,720
Total Hydromet 40 19 322,848
ICT-RELATED
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The total cost of activities under Scenario 2 (phased approach) is US$2.13 million. A stand-alone approach would increase the cost of this scenario to US$3.26 million. The impacts of activities under this scenario are expected to be incremental improvement in institutional and staff capacity, enhancement in the delivery of weather and hydrological services, improvement in forecasting and ICT capabilities, and increased capacities for the proper operation of the existing network and data utilization. Using the Progress Models for various components of GHMD, the service delivery capability is expected to increase to between Levels 3 and 4 (between Development in Progress and Developed); the modeling and forecasting capability is expected to reach between Levels 3 and 4 (Development in Progress and Developed); and the observing and telecommunication capability is expected to reach Level 4 (Developed).
9.3 Scenario 3: Advanced ModernizationScenario 3 presents the investment needed to bring GHMD up to the level of a well-functioning modern NMHS, with capabilities for providing data, forecasts, and warning services that meet various users’ needs, in addition to meeting the obligations for public service provision.
This scenario follows a phased approach and is built on Scenarios 1 and 2. As previously indicated, a stand-alone approach is a second possibility; this would assume that activities described under Scenarios 1, 2, and 3 are rolled into one scenario, the implementation of which would require up to seven years. This is the reason for including the full explanations for the three modernization components in sections 9.3.1–9.3.3. Under the phased approach to Scenario 3, most of the effort is expended for the full utilization of all the systems that are in place and expected to result in increased capabilities in forecasting, ICT, data access, service delivery, and quality management systems, as well as optimal utilization of the observing system.
9.3.1 ENHANCEMENT OF THE GHMD SERVICE DELIVERY PROCESS In developing and implementing a national strategy for service delivery, it is essential that users of meteorological and hydrological information and services are included in product planning and design from the outset and that the derived information and services respond to user needs. An action plan with well-defined milestones would then be created for responding to the unfulfilled user requirements. The establishment of a hydrometeorological user group would be a useful mechanism for this purpose. The user group should be supported through the following means:
Enhancement of GHMD’s service delivery process will focus on the improvement of public weather, climate, hydrological, and agrometeorological services. It will include among other things and as required the following: further enhancement and implementation of a national strategy for service delivery as described above; development of new and improvement of an existing set of basic and specialized user-tailored products, including evaluation of forecast utility and user satisfaction; development and operationalization of CAP capability at GHMD (if not implemented yet) to standardize the production and dissemination of warnings; improvement of mechanisms that disseminate information to communities; pilot testing and operationalization of impact-based forecast and warning services in selected vulnerable districts/cities; strengthening of end-to-end EWS, including a regular post-event review process; development of an Agriculture and Climate Advisory Service portal, including provision of hardware and software; and development of a digital library of climate-relevant information. In addition, based on an evaluation of
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opportunities for GHMD to initiate public-private engagement, strategies will be developed to introduce new sustainable business models, for example, fee-based service provision and outsourcing of modeling activities (e.g., updating of models).
The estimated budget under this scenario will cover the cost of any new equipment, tools, vehicles, instrumentation, software, and refurbished facilities. As in the intermediate modernization option, the O&M budget under this scenario should be used for proper life-cycle management of observation infrastructure and facilities, which in this scenario will also require greater staff support. This effort includes the supply of spare parts, consumables, and fuel; coverage of the increased communication, power, and other operating costs; and quality control/quality assurance procedures. Considering that the GHMD operations under this scenario will be based on the broad use of more sophisticated instruments (e.g., Doppler radar), modern technologies, and research, the GHMD workforce should be further strengthened by hiring more qualified staff and offering continued technical training (see table 7).
9.3.2 INSTITUTIONAL STRENGTHENING AND CAPACITY BUILDINGUnder this scenario, the key national, provincial, and local government agencies must work in close cooperation if forecasting and warning services are to be fully effective. The interdepartmental relations also need to be strengthened through regular contacts and communication channels. Roles and responsibilities of each agency must be sufficiently well defined to avoid ambiguities, especially during severe weather-related events. A QMS will be established across the entire institutional and operational systems of GHMD to develop and implement management of the organization’s delivery of products and services. There will also be a need to establish formal communication mechanisms involving all stakeholders. Establishment of MOUs among service providers and key stakeholders will help pave the way for associated negotiations and agreements. SOPs will enable GHMD to codify how alerts, warnings, and other operational products are issued. They will also enable stakeholders to define their responses to the various levels of alerts and warnings, thereby improving the response to meteorological and hydrological hazards. SOPs should be constructed to align with WMO guidelines and global good practices.
Institutional strengthening and capacity building will aim to improve the performance of GHMD in line with international best practices through various means: development of a new CONOPS aligned with Scenario 3; improvement of a legal and regulatory framework for GHMD operations; improvement of the GHMD internal management system, including human resources planning and management as well as strengthening and completion of the quality management system; evaluation of GHMD’s opportunities to develop a new business strategy for more sustainable operations; development of technical capacity and education through a training plan for GHMD to build/enhance the skills required to cope with the innovation, modernization, and sustainability of the enhanced systems (e.g., on-the-job training, training at other institutions, twinning with developed NMHSs, fellowships, higher degree courses); enhancement of
• Establishing a coordination platform and communication channels between the service providers and users to support modernization, effectiveness, and sustainability of the services
• Supporting users to identify their respective data, product, and service needs
• Proposing improvements to existing products and services, or development of new products and services, to meet needs
• Developing the capacity of users to maximize the benefits of data, products, and services
• Supporting awareness and outreach programs targeted at decision makers and sector users to highlight the benefits of the services
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national educational institutions’ capacity to provide rigorous hydromet education and training; stakeholder training; public education and outreach; further development of GHMD’s website, publication of bulletins and annual reports, and work with schools; and cooperation with universities and research institutes.
One example of institutional strengthening through the regulatory framework would be establishing a mandate for providing hydrological planning tools. The operation of the hydrological network and the description of the current hydrological conditions and short- or longer-term forecasts are important activities of GHMD. To transform the hydrological data into information, new hydrological planning tools are needed. For this purpose, GHMD’s responsibilities for countrywide assessments of hydrological conditions—in the form of water balances, hydrological data for flood risk management, drought forecasts and warnings, and other derived information—have to be specified as a priority.
9.3.3 MODERNIZATION OF OBSERVATION INFRASTRUCTURE, DATA MANAGEMENT SYSTEMS, AND FORECASTINGModernization of the observation infrastructure, data management systems, and forecasting is a substantial undertaking. The road map considers the need for a modernized data processing system, including communication and computer equipment for storage, archiving, processing, and visualization for weather, climate, and hydrological data (servers and workstations), as well as data management systems for weather, climate, and hydrological data (servers, software, web access, and social media). Meteorological and hydrological modernization, including the required training and capacity building, may entail GHMD’s use of internationally available products where possible to achieve economic efficiency. Examples include satellite products, NWP/EPS data and products and required software for data handling (i.e., license), and flood forecasts from the Global Flood Awareness System (GloFAS) operated by the ECMWF. Other essential requirements include uninterrupted broadband Internet, equipment for weather forecasting (including forecaster workstation software products, real-time forecast process monitoring, and quality control of observations), nowcasting using radar data, seasonal forecasts based on remote sensing data and snow modeling (including servers, licenses for software, training, quality management, and dissemination of products), flash flood warning and alert systems (including technical facilities for collecting data from new sensors), operational water balances for the main river basins, and refurbishment of GHMD facilities and offices. It should be noted that this list is neither exhaustive nor mandatory. It is meant mostly to provide guidance and reflection on what may be needed in Georgia for modernizing GHMD’s infrastructure and technologies with the ultimate goal of improving hydromet service provision to the Georgian population.
This scenario includes the expansion of current technologies, including observation, forecasting, ICT, etc. It is normal practice for O&M costs to be 10–15 percent of the initial capital expenditure.
The technical investments are specified as follows:
For improved hydrometeorological services, including ICT-related systems, estimated total funding of US$3.72 million is needed, as follows:
1. Building on the ICT design (centralized data center), procurement and installation of the full set of the hardware and software required for a modern forecast and warning system; a service delivery platform and applications, including data management, dissemination, and service delivery (US$1.17 million)
2. Revision and updating of CONOPS for Scenario 3 and development of additional SOPs, to include the requirements for both GHMD and disaster management; operationalization of impact-based forecast and warning services (five months, US$110,000)
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3. A moderate expansion of the existing observation network to represent fit-for-purpose coverage of the country, including six synoptic AWS; seven agromet AWS; 24 AWS met posts; one upper-air station; four total lightning detection sensors; and 22 automatic hydro posts, including establishment of sediment load monitoring (US$1.23 million)
4. Refurbishment of GHMD facilities and offices (US$150,000)
5. Upgrading of instrumentation and transport for improved quality and effectiveness of field operations (US$220,000)
6. Fostering of cooperation with universities and research institutes to provide support to GHMD on priority issues (US$200,000)
7. On-the-job training of staff to support the implementation and application of upgrades for meteorological components, including user engagement and feedback (US$360,000)
8. On-the-job training of staff to support the implementation of countrywide NWP downscaling and hydrological models with different components according to climatic conditions; procedures for model upgrade, calibration, and validation (US$280,000)
To fully realize the benefits of the technical assistance offered in this scenario, an increase in staff is recommended, as shown in table 7 With an estimated average cost of US$456 per month per person and the required addition of 94 trained staff, the implementation of this scenario requires additional an US$514,368 per year in staff costs. We assume that this amount will be added to the current allocation of about US$1 million for GHMD staff, increasing total staff cost to US$1.5 million.
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TABLE 7. ADDITIONAL STAFF AND STAFF COSTS REQUIRED TO IMPLEMENT SCENARIO 3
Position Scenario 3Engineers/ Scientists (Number)
Technicians (number)
expenditures (US$)
additionally allocated
Personnel costs
(US$/year)Remarks
1 Observation 8 8 87,552Increase in hydrometric capacities to ensure the proper operation of widely extended network (discharge measurements, rating curves)
2 Modeling 36 0 32,832
Adaptation of existing and development of new flood models with an extended hydrological database, validation and calibration of flood and water balance models, permanent updating to provide results according to user needs
3 Forecasting 3 0 16,416Numerical hydrological discharge forecasts for more than 100 gauges and many other points of interests
4 Hydrological Analyses 8 0 43,776
Services such as annual updated flood statistics, water balances, climate change assessments, reports about quantitative hydrology for the implementation of the Water Framework Directive, drought forecasts and monitoring, assessments of anthropogenic impacts on the hydrological conditions
Total Hydrology 25 8 180,576
HYDROLOGY
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5
Observation
3 6 49,248Support for the operation and maintenance of surface-based remote sensing (Doppler radars)
6 0 12 65,664 Support for the operation and maintenance of the expanded network, including upper air
7 0 4 21,888 Support for operation of the calibration laboratory
8Use of model
products (objective
forecasting)
10 0 54,720 Enhanced use and adaptation of NWP f or forecasting on all time scales
9
Advancing impact-based, (probabilistic
forecasting and verification)
5 0 27,360
Implementation of real-time forecast process monitoring, quality control of observations; nowcasting; seasonal forecast licenses, dissemination of products; flash flood warning and alert systems; full operationalization of impact-based forecast and warning services; strengthening of end-to-end EWS
10 Service delivery 6 0 32,832
Application of all the tools for service delivery, including strategy for service delivery; hydrometeorological user group; CONOPS for this scenario; MOUs and SOPs; new and improved user-tailored products; evaluation of forecast utility and user satisfaction; further improvement of dissemination mechanisms; development of an Agriculture and Climate Advisory Service portal; stakeholder training; public education
Total Meteorology 24 22 251,712
METEOROLOGY
11ICT-related for
both hydro and met
15 82,080
Total ICT-Related 15 0 82,080
Total Hydromet 64 30 514,368
ICT-RELATED
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The total cost of activities under Scenario 3 (phased approach) is US$3.72 million. A stand-alone approach to Scenario 3 would require an expenditure of US$6.98 million. The activities under this scenario are expected to result in improvements in all systems of GHMD and to bring them up to the level of a modern NMHS, with capabilities for providing data, forecasts, and warning services to meet various users’ needs. Using the Progress Models for various components of GHMD, the service delivery capability is expected to reach a full Level 4 (Developed); the modeling and forecasting capability is similarly expected to reach a full Level 4 (Developed); and the observing and telecommunication capability is expected to reach Level 5 (Advanced) as shown in table 8.
TABLE 8. SUMMARY OF IMPACT OF EACH MODERNIZATION SCENARIO ON GHMD CAPABILITIES ACCORDING TO THE PROGRESS MODELS
Current Situation
Scenario 1: Technical
Assistance
Scenario 2: Intermediate
Modernization
Scenario 3: Advanced
Service Delivery
Between Level 2 (Development
Initiated and level 3 Development in
Progress)
Level 3 (Development in Progress)
Between Level 3 (Development
in Progress) and Level 4 (Developed)
Level 4 (Developed)
Observations and ICT
Level 2 (Development
Initiated)
Between Level 2 (Development
Initiated) and Level 3 (Development in
Progress)
Level 4 (Developed)
Level 5 (Advanced)
Modelling and Forecasting
Between Level 2 (Development
Initiated) and Level 3 (Development in
Progress)
Level 3 (Development in Progress)
Between Level 3 (Development
in Progress) and Level 4 (Developed)
Level 4 (Developed)
The estimated investment cost of Scenario 3 is about US$7 million. It is estimated that the total annual GHMD budget by the end of the seven-year implementation period should exceed US$2.5 million, including overall operating cost of over US$1 million and staff cost of about US$1.5 million. Tables 9 and 10 present the additional number of staff and staff costs, and the investment, total operating, and staff costs, respectively.
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TABLE 9. OVERVIEW OF ADDITIONAL STAFF REQUIREMENTS AND ANNUAL STAFF COSTS OF THE THREE MODERNIZATION SCENARIOS
Personnel Hydrology Meteorology ICT Total
Currenta 134 staff plus 48 contractors n.a. n.a. n.a. 182
Staff cost (US$) n.a. n.a. n.a. 894,759
Scenario 1
Engineers/scientists 9 9 3 21
Technicians 2 10 0 12Additional staff costs 60,192 103,968 16,416 180,576
Scenario 2(including
Scenario 1)
Engineers/scientists 14 16 10 40
Technicians 4 15 0 19Additional staff costs
(US$)98,496 169,668 54,720 322,848
Scenario 3(including
Scenario 2)
Engineers/scientists 25 24 15 64
Technicians 8 22 0 30Additional staff costs
(US$)180,576 251,712 82,080 514,368
Total annual staff cost at the
end of 7-year implementation
period
1,409,127
a. Based on expenditures at the end of 2018.Note: n.a. = not applicable.
To achieve the projected results of Scenario 3, two main conditions will need to be met: (i) the government must be able to direct available investment resources from existing development partner or national projects or programs to support activities of Scenario 3 aimed at modernization of GHMD observation, ICT, and forecasting infrastructure and improvement of service delivery; and (ii) the government must be able to significantly increase GHMD staff by recruiting over 90 trained specialists and technicians, and allocating additional financial resources to operate the modernized GHMD systems. The second condition, which entails more than a 90 percent increase in the current GHMD budget by the end of the seven-year period, seems to be the most challenging but is still considered affordable.
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TABLE 10. OVERVIEW OF THE COSTS OF THE THREE SCENARIOS: TOTAL INVESTMENT, OPERATING, AND STAFF COSTS
Cost estimates for various scenarios
(US$) (stand-alone
version)
Investments in main GHMD systems
Total investment
costs
Total annual
operating cost
Total annual
staff cost (at the end
of scenario)
Hydro Met ICT
Current n.a. n.a. n.a. n.a. 589,355 894,759
Scenario 1 224,000 360,000 546,000 1,130,000 693,751 1,075,335
Scenario 2(including
Scenario 1)378,000 972,000 1,810,000 3,260,000 784,959 1,217,607
Scenario 3 (including
Scenario 2)1,344,700 2,425,400 3,210,000 6,980,000 1,019,355 1,409,127
Note: n.a. = not applicable.
The O&M costs were calculated based on an average of 10 percent of the capital investment, as follows:
1. The current O&M costs for the hydrology and meteorology equipment were calculated based on the number of existing stations and posts and the unit costs of all equipment.
2. The O&M costs for Scenario 1 were calculated based on the current costs plus the cost of the Doppler C-band radar.
3. The O&M costs for Scenario 2 were calculated based on accumulative costs of Scenario 1 plus the cost of hardware described in the activities under that scenario.
4. The O&M costs for Scenario 3 were calculated based on accumulative costs of Scenario 2 plus the cost of equipment included in the expanded network and computer hardware described in the activities under that scenario.
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10. SOCIOECONOMIC BENEFITS OF IMPROVED HYDROMETEOROLOGICAL SERVICES AND EWS
For a potential public investment to be justified, the socioeconomic benefits it will produce should be compared to the costs involved. The application of cost-benefit analysis to modernizing hydrometeorological services was explored in WMO et al. (2015), which also outlined different methodologies (and challenges) for quantifying benefits and costs related to weather, climate, and water information services. This study found that in general, investing US$1 in hydrometeorological services and EWS results in at least US$3 in socioeconomic benefits (defined as a 3:1 benefit/cost ratio), and often far more.
10.1 Conservative ApproachCost-benefit analysis for disaster and climate risk management is often challenged by a lack of data and information. Further, as indicated in the IPCC’s (2012) SREX report, there are several complexities and uncertainties inherent in quantifying disaster risk management that are compounded by climate change. Cost-benefit analysis is also challenged in handling intangibles and—of particular importance for extreme events—in discounting future impacts.
Therefore, to build confidence in and robustness of a cost-benefit analysis of hydrometeorological services, a transparent and conservative approach is warranted (Kull, Mechler, and Hochrainer 2013). All assumptions and their supporting analyses are here reported. Where a range of potential analysis inputs is generated, the most “conservative” values are taken, meaning that for a range of potential benefits the lowest value is used. This approach results in the analyzed net present value and benefit/cost ratio representing the lowest threshold of expected economic effectiveness; most likely the truly realized economic efficiency will be greater than what is reported here.
From the outset three key conservative assumptions must thus be noted:
1. Only reductions in the short-term direct impacts of weather and climate-related processes are considered; long-term indirect impacts (such as health) are not included.
2. The analysis does not consider future population growth and development that will be protected by this investment; the economy at risk is considered the same as the most recent World Bank data on GDP (2017).
3. Disaster risk is based on past experience and therefore not adjusted for potential climate change impacts.
These assumptions all further contribute to a conservative estimate of the investment’s economic effectiveness.
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TABLE 11. AVERAGE ANNUAL LOSSES DUE TO NATURAL HAZARDS
Hazard Average Annual Loss
% GDPa US$ 2017
Mudflow 0.359 54,161,500
Landslide 0.271 40,815,500
Flood 0.125 18,917,700
Hail 0.045 6,737,800
Wind 0.027 4,146,300
Avalanche 0.014 2,073,200
Total 0.841 126,852,000
Source: CENN 2010.a. Calculations are based on World Bank figure of US$15.081 billion for Georgian GDP in 2017.
10.2 Benefits from Avoided Disaster LossesConsidering the stochastic nature of disasters, common practice for cost-benefit analysis of disaster risk management is to determine the average annual losses due to disasters (Kull, Mechler, and Hochrainer 2013). This represents the averaging of all potential losses over time to quantify the expected economic burden per year. When sufficient data are available, the average annual loss is calculated as the area under a loss frequency curve, which is a common metric indicating the exceedance probability of the full potential range of losses per year (for example from the yearly flood to the 100- or 200-year flood).
Given current limitations of disaster loss data in Georgia, average annual losses are taken directly from the Atlas of Natural Hazards and Risks of Georgia (CENN 2010), translated into percentage of GDP, as shown in table 12.
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Considering the similarities of assessing and managing the risks of floods, mudflows, and landslides, these can be combined to create a single loss category of “flood,” with a total annual average loss of 0.76 percent of GDP, or US$113.9 million in 2017 values. Similarly, hail and wind form a single category of “storm,” with a total annual average loss of 0.07 percent of GDP, or US$10.9 million in 2017 values. For the purposes of this analysis, avalanche risk is considered negligible in terms of overall national hydrometeorological risk and economic impact.
More recent but lower-resolution assessments estimate the average annual GDP affected by floods at US$300 million (World Bank and GFDRR 2017b), correlating with 2.58 percent of GDP, while the risk profile published by UNISDR (2019) is much lower at 0.39 percent of GDP. A similar previous lower-resolution study estimated the average annual losses from all hydrometeorological disasters as 0.99 percent of GDP (World Bank 2008). The average annual loss of 0.76 percent of GDP, based on CENN (2010) and reported above, is therefore considered to be at the lower, i.e., more conservative, end of this range, as shown in table 13.
TABLE 12. TRIANGULATION AND VERIFICATION OF ANNUAL AVERAGE LOSSES DUE TO HYDROMETEOROLOGICAL HAZARDS
Average annual loss (% of GDP) Hazard Source
0.39 Flood UNISDR 2019
0.76 Flood CENN 2010
0.84 All hydromet CENN 2010
0.99 All hydromet World Bank 2008
2.58 Flood World Bank and GFDRR 2017b
Note: This analysis uses CENN (2010) as a conservative estimate.
10.3 Benefit AnalysisSubbiah, Bildan, and Narasimhan (2009) provides guidance on the level of damage reduction that can be achieved through early warning, which ranges from 5 percent to 90 percent, depending on the items at risk and provided lead times. While a 20 percent reduction is often assumed as an average reduction in economic losses attributable to early warning, contextually relevant experience indicates a more conservative range of 5–8 percent is more appropriate, for example 8.5 percent in Russia (World Bank 2005) and 10 percent for floods in southeastern Europe (World Bank 2008). This aligns with a conservative approach; for the current analysis, 5 percent is applied for flood risk reduction, equaling US$5.7 million in annual benefits, and recognizing the shorter lead times, 2 percent is applied for hail and wind storms, equaling US$220,000 in annual benefits.
10.4 VerificationConsidering the limited data availability, a benchmarking methodology is here employed to verify the results, following Hallegatte (2012) and based on a country’s GDP. Hallegatte (2012) found that on average, well-functioning, modern EWS reduce disaster-related asset damages by between 0.003 percent and 0.017 percent of GDP. The study therefore concludes that the potential benefit of an investment in
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EWS is the difference between the current protection provided by the country’s existing systems and the potential reduction in asset damages if the system is modernized.
Under this benchmarking methodology, Georgia would be considered a lower-middle-income country with a relatively weak system and would therefore be assumed to currently capture only 20 percent of the potential damage reduction benefits of hydromet early warning. Potential benefits would thus be calculated as the difference between the potential reduced losses—between 0.003 percent and 0.017 percent of GDP, assuming Georgia corresponds to the global benchmark—and the actual reduced losses, which in this case would be 20 percent of that value. The results for Georgia range up to US$2.1 million in average annual reduced losses.
The benchmarking methodology indicates that estimates of annual benefits from reduced flood and storm losses are of a similar order of magnitude. Recognizing some discrepancies, likely due to Georgia being more exposed to hydrometeorological hazards than the global average, a sensitivity analysis is also pursued to identify the impact of reduced benefits on the overall economic assessment.
10.5 Benefits from Increased ProductionIn addition to diminishing disaster losses, modernized hydromet systems can significantly enhance economic productivity. Because information is lacking, a benchmarking approach is used to estimate potential benefits to economic productivity from modernized hydromet services in Georgia.
Hallegatte (2012) finds that about 25 percent of the world GDP is generated in climate-sensitive sectors, i.e., agriculture, mining and energy, construction, and transport. Modernized hydromet and warning systems can benefit these sectors in many ways, ranging from immediate warnings and seasonal advisories to infrastructure design and spatial planning. A conservative global benchmark is that modern forecasts add value of 0.1 percent to 1 percent in weather-sensitive sectors.
In Georgia, climate-sensitive sectors represent about 35 percent of the economy (Geostat 2018). Applying the Hallegatte (2012) benchmarking approach results in annual benefits in production of US$5.2–52.0 million per year. To avoid double-counting and again pursuing a conservative approach, the lower end of the range is used in this analysis. However, considering the frequency of droughts in Georgia, this must be considered extremely conservative.
10.6 Total Annual BenefitsTable 14 summarizes the benefits attributed to improved hydrometeorological services for this analysis, including the bounds of values used for sensitivity analysis. Maximum value for reduced disaster losses assumes 20 percent reduction of annual losses.
TABLE 13. ANNUAL BENEFITS ATTRIBUTED TO MODERNIZED HYDROMETEOROLOGICAL SERVICES (US$)
Benefit Minimum value “Realistic” value Maximum value
Reduced flood losses 2.5 million 5.7 million 22.8 million
Reduced storm losses 0 220,000 2.2 million
Increased productivity 5.2 million 5.2 million 28.7 million
Total 7.7 million 11.12 million 53.7 million
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The three investment scenarios described in chapter 9 will not only incur different costs but will also bring the GHMD’s services to different levels. To reflect this in the socioeconomic benefit assessment, the average capacity increase expected from each scenario is used to prorate the total potential benefits listed in table 14. The values are as follows: Scenario 1 = 39 percent (of potential benefits of a perfect system listed in table 14), Scenario 2 = 57 percent, and Scenario 3 = 77 percent.
10.7 Cost-Benefit AnalysisComparing the costs and benefits of the project over time can show the relative value of the planned investments. While cost-benefit analysis provides a useful process and resultant metrics to help steer investment decision making, however, it should not be the only factor considered.
While the implementation phase of the scenarios ranges from two to seven years, this analysis assumes that the project impact is 20 years. Investment disbursements are assumed to occur equally across the scenario durations. Additional O&M costs due to modernization thus increase linearly as cumulative project investments are made, reaching a constant maximum the year after the investment scenarios are completed. Benefits in terms of reduced disaster damages and increased production are also assumed to increase linearly, starting to be realized from the second year and reaching a constant maximum the year after the investment scenarios are completed.
Cost-benefit analysis utilizes a discount rate to represent societal preference for consuming in the present as opposed to saving and consuming in the future. A discount rate of 0 percent indicates no preference between now and in the future, while a discount rate of 15 percent represents a high preference for spending now. In this analysis a discount rate of 5 percent is applied, representing an understanding that future costs and benefits are relatively important in comparison to the current situation (in keeping with concerns regarding climate change). However, 0 percent and 15 percent discount rates are also applied for sensitivity analysis.
Tables 15–17 show the results of the analysis for the following cost-benefit metrics:
• Net present value: Present benefits minus present costs. If the net present value is greater than 0, then the investment is considered economically effective.
• Benefit/cost ratio: Present benefits divided by present costs. If the benefit/cost ratio is greater than 1.0, then the investment is considered economically effective.
TABLE 14. COST-BENEFIT ANALYSIS RESULTS FOR SCENARIO 1
Net present value (US$ millions) Benefit/cost ratio
Discount rate 0% 5% 15% 0% 5% 15%
Total costs 3.4 2.7 2.0
Minimum benefits 5.6 3.0 0.9 1.1 1.1 1.1
“Realistic” benefits 26.7 16.6 8.0 1.7 1.7 1.6
Maximum benefits 273.4 175.2 91.9 8.2 8.0 7.6
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TABLE 15. COST-BENEFIT ANALYSIS RESULTS FOR SCENARIO 2
Net present value (US$ millions) Benefit/cost ratio
Discount rate 0% 5% 15% 0% 5% 15%
Total costs 6.8 5.3 3.8
Minimum benefits 23.2 12.4 3.8 1.5 1.4 1.2
“Realistic” benefits 55.6 32.6 13.7 2.3 2.1 1.8
Maximum benefits 435.7 268.4 128.7 10.9 10.2 8.8
TABLE 16. COST-BENEFIT ANALYSIS RESULTS FOR SCENARIO 3
Net present value (US$ millions) Benefit/cost ratio
Discount rate 0% 5% 15% 0% 5% 15%
Total costs 13.3 9.7 6.3
Minimum benefits 38.1 19.1 4.7 1.7 1.6 1.2
“Realistic” benefits 81.8 45.1 16.4 2.6 2.3 1.9
Maximum benefits 593.7 349.6 152.4 12.4 11.1 8.9
To further test the sensitivity of the analysis, the realistic benefit assumption for all three scenarios is analyzed using an assumption that the costs are 30 percent higher than estimated. The results are shown in table 18.
TABLE 17. COST-BENEFIT ANALYSIS RESULTS: REALISTIC BENEFITS AND 30 PERCENT COST OVERRUNS
Net present value (US$ millions) Benefit/cost ratio
Discount rate 0% 5% 15% 0% 5% 15%
Scenario 1 15.4 9.1 3.8 1.3 1.3 1.2
Scenario 2 42.5 23.9 8.7 1.7 1.6 1.4
Scenario 3 66.2 34.7 10.6 2.0 1.8 1.4
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The importance of reliable long-term budget availability is reflected in figure 26, which shows the first 10 years of financial and economic flows for Scenario 3, assuming “realistic” benefits and a discount rate of 5 percent. The first years of investments result in a negative net present value, but as more and more investments come online, the net present value becomes positive, despite increased operations and maintenance costs. Once the project is completed (in Year 7), the annual costs and benefits remain constant, with the cumulative net present value increasing year on year. The relatively small operations and maintenance costs leverage the Scenario 3 investment to deliver significant benefits far into the future.
FIGURE 26. ANNUAL FINANCIAL AND ECONOMIC FLOWS OF SCENARIO 3 INVESTMENT WITH “REALISTIC” BENEFITS AND 5 PERCENT ASSUMED DISCOUNT RATE
Costs
Benefits
Cumulative net present value
0
5
10
Year
US$ (Millions)
-5
15
1 2 3 4 5 6 7 8 9 10
10.8 ConclusionsThe cost-benefit analysis indicates that all three proposed investment scenarios are economically efficient, meaning they will produce socioeconomic benefits greater than their costs. In all cases the generated benefits are significantly greater than the costs; for example, in the worst-case scenario with realistic assumed benefits and 30 percent cost overruns the benefit/cost ratios for all investment scenarios are over 1.2. For what are considered the most realistic assumptions, the benefit/cost ratios for all scenarios are over 1.5.
Considering the very conservative approach and assumptions applied throughout the analysis, the results are considered robust. Hallegatte et al. (2017) found that globally, universal access to EWS would almost double the benefits of reducing asset losses by also reducing “well-being” losses. These less tangible well-being benefits—for example, contributions to poverty reduction—are not considered in this analysis, again suggesting that the analysis very likely underestimates the benefits from the proposed investments. In addition, the saving of lives, which is a primary benefit of EWS, is not considered in the analysis. This is omitted due to the moral implications and sensitivities of assigning economic values to human lives, even
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with “neutral” approaches such as value of a statistical life (VSOL). This omission further contributes to the conservative nature of the analysis.
As weather and climate impacts increase, the net present value and benefit/cost ratio of the proposed investments will also increase. This is because early warning provides benefits that are not limited by thresholds; whether a flood is a 25-year or a 50-year event, early warning still reduces impacts similarly (as opposed for example to levees or other structural measures, whose design thresholds are at some point exceeded).
As the Georgian population and economic productivity grows, EWS will continue to provide benefits. New developments and investments will also benefit from improved forecasting and early warning, as opposed (again) to structural flood control, where new levees may need to be built to protect new developments. The fact that these two factors (climate change and population/economic growth) were not incorporated in the analysis again points to an underestimation of the actual project benefits.
While all three investment scenarios are economically efficient, the analysis shows that Scenario 3 is more efficient than Scenario 2, which itself is more efficient than Scenario 1. At the same time, Scenarios 2 and 3 deliver significantly higher absolute benefits to Georgia. Considering that such higher-level investments are relatively low in cost, are economically efficient, protect lives and property, and contribute to economic development and resilience, they should be considered for priority financing.
11. CONCLUSIONS AND A WAY FORWARDThe strategic steps needed to modernize hydrometeorological products and services in Georgia are primarily driven by the needs of the user community. Extensive discussions with the management and technical staff of GHMD and key stakeholders dealing with the country’s most pressing issues, such as emergency management and response, water management, and agriculture, have revealed that those needs are not being fully met. At present, the activities of GHMD are mainly focused on observation and data collection, with some forecasting and limited service delivery. Due to a lack of resources since the 1990s, GHMD has fallen behind in accessing up-to-date technologies and tools for producing forecasts and in using best practices and standards to deliver services. Addressing these issues will require a joint approach involving stakeholders and GHMD, one that fully considers all meteorological and hydrological elements of a well-planned department and that includes a clear strategy and goals and means of achieving those goals.
GHMD has limited early warning capacity for issuing warnings of severe weather events; it produces no agrometeorological forecasts and runs no hydrological or hydraulic models, which are necessary for flood forecasting. GHMD’s use of Numerical Weather Prediction is limited to producing basic public weather forecasts. It has no technical means to produce nowcasts needed for warnings; it does not use climate models and does not produce seasonal outlooks or climate projections.
Stakeholders clearly need the entire infrastructure of GHMD to be modernized. To produce fit-for-purpose services, GHMD needs to reach the level of a modern middle-income country NMHS. This implies building a robust data management system; a forecasting system with capabilities to produce forecasts on all time scales (from very short-range to long-range and seasonal forecasts) as well as impact-based forecasts; hydrological services and flood forecasting; an ICT system capable of transmitting, processing, and storing data from all the different components of the observing network in a harmonized and efficient manner; and an effective service delivery system.
GHMD is currently a dominating source of public hydromet information and services in the country and will continue to hold this position at least in the medium term (8–10 years). Although large international private
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firms now offer basic weather forecasts distributed on popular mobile applications, there is no obvious indication at the present that national private companies are interested in entering this sector. Of course, this may change in the future with the potential growth of the private sector engaged in hydrometeorology. In such a future environment, the focus of GHMD would be on meeting the most pressing needs in order to provide public services, while setting up a regulatory framework with respect to the operation of the private sector.
Meteorological and hydrological activities are spread across several institutions in Georgia without much coherence and with few interactions in common areas of interest. The specialized research institutes in this area that were active some 25 to 30 years ago appear to be weak now and do not provide any significant support to GHMD operational activities. There is a potential mutual benefit in closer collaboration with academia, mainly the Georgian Technical University, the Geophysics Institute, and the Tbilisi State University, whose work is mainly directed to research that is not then transformed to operations. In view of the factors cited above, the assessment and modernization of GHMD has been the main focus of this road map.
An estimate of the current staffing number is 182 (staff and consultants), at a cost of US$894,759 per year.
Three scenarios to modernize GHMD have been presented in this road map, with two possible approaches to implementation: a phased approach in which each scenario builds on a previous one, or a stand-alone approach. The level of complexity and required resources is different in each scenario, as shown below.
Scenario 1: Technical Assistance. This scenario provides technical assistance for high-priority activities to improve basic public services by introducing affordable new technologies into GHMD and training GHMD staff for heightened capacities and capabilities (immediate to short term: two years). The implementation of this scenario requires an additional 33 staff and staffing cost of US$180,576 per year. The investment cost of this scenario is estimated at US$1.13 million, and the annual operating cost is US$693,751.
Scenario 2: Intermediate Modernization. This scenario makes investments to modestly improve GHMD’s ability to provide weather and hydrological services that meet the public service needs of the most important user communities, for example, disaster management, agriculture, transport, and water resources management. In the phased approach, the implementation of this scenario is expected to follow Scenario 1 and would additionally cost US$2.13 million. The stand-alone approach would result in a total cost of US$3.26 million (scenarios 1 + 2) over the medium term (four years). The implementation of Scenario 2 requires an additional 59 staff at a cost of US$322,848 per year and an operating cost of US$784,959 per year.
Scenario 3: Advanced. This scenario makes investments to bring GHMD the capabilities for providing fit-for-purpose data, forecasts, and warning services for the safety of the public, and support to develop the most important socioeconomic sectors. In the phased approach, this scenario is expected to follow Scenario 2 and would additionally cost US$3.72 million to implement. The stand-alone approach would result in a total investment cost of US$6,980,440 (scenarios 1 + 2 + 3) over the long term (seven years). The implementation of Scenario 3 requires an additional 94 staff at a cost of US$514,368 per year and an operating cost of US$1.02 million per year.
It is estimated that the total annual GHMD budget by the end of the seven-year implementation period will exceed US$2.4 million, including overall operating cost of over US$1 million and staff cost about US$1.4 million. This budget estimate is based on very conservative assumptions (e.g., about labor cost) and may not be sufficient to fulfill main public functions.
The cost-benefit analysis indicates that all three proposed investment scenarios are economically efficient, meaning they will produce socioeconomic benefits greater than their costs. In all cases the generated benefits are significantly greater than the costs.
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To achieve the projected results of Scenario 3, two main conditions will need to be met: (i) the government must be able to direct available resources from existing projects to support activities of Scenario 3 aimed at modernizing GHMD observation, ICT, and forecasting infrastructure and improving service delivery; and (ii) the government must be able to significantly increase GHMD staff by recruiting over 90 trained specialists and technicians, and must allocate additional financial resources to operate the modernized GHMD systems. The second condition, which entails about a 90 percent increase in the current GHMD budget by the end of the seven-year period, seems to be the more challenging but is still considered affordable.
Developing a Concept of Operations is essential for the detailed planning and implementation of each scenario.
ANNEX 1. REQUIRED TRAINING AREASThe following list indicates areas for which NMHSs generally require training. The precise details of training for GHMD will be defined at the time of designing implementation of the different scenarios presented in this road map. Other areas may be added to this list as needed.
• Project management
• Change management/leadership training
• Technical skills to support meteorological and hydrological observing networks
• Instruments and sensors maintenance
• Enhanced skills in weather forecasting using numerical prediction models (including Ensemble Prediction Systems) on all time scales from very short- to long-range forecasting
• Enhanced skills in weather monitoring based on in situ and remote sensing observational data; enhanced skills in nowcasting through blending of these observational data with NWP outputs to extrapolate to the immediate future
• Enhanced skills in operating a flood forecasting center
• Enhanced skills in flood forecasting using numerical models
• Enhanced skills in deterministic seasonal forecasting using snow models
• End-to-end early warning production and delivery
• Impact-based forecasting and warning services, including for hazards such as floods, landslides, avalanches, and droughts
• Verification and statistics methods for model evaluation
• Database management
• IT management
• Skills for delivery of public weather and hydrological services, including user/stakeholder consultation, communication, negotiation, and feedback gathering
• Enhanced skills in climate prediction using numerical methods
• Public education and outreach
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ANNEX 2. COMPLETED AND ONGOING PROJECTS
Program/
project titleDonor/
implementer
Status (Including
implementation period)
Involved organization/ beneficiary
Budget Description
1 Enhanced Preparedness of Georgia Against Extreme Weather Events
Czech Development
Agency (CzDA)
Accomplished (2011–2015)
NEA €568,900 The main outcome of the project is increased capacity of NEA in forecasting meteorological and hydrological threats in Georgia in order to reduce or mitigate the negative impacts of such threats. Achieved results:
• Extension of network of automatic meteorological stations and posts (8 automatic meteorological stations, 4 meteorological posts, 7 hydrological posts)
• Extension of observation network of automatic hydrologic gauges
• Functional meteorological database, data processing systems
• Functional hydrological database
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2 Developing Climate Resilient
Flood and Flash Flood Management
Practices to Protect Vulnerable
Communities of Georgia
Adaptation Fund/UNDP
Accomplished (2012–2017)
NEA, Municipalities
US$5.06 million
The project objective is to improve resilience of regions of Georgia that are highly exposed to hydrometeorological threats, which are increasing in frequency and intensity as a result of climate change. The project will help the governments and the population of the target region—the Rioni Basin—to develop adaptive capacity and embark on climate-resilient economic development. The project comprises three main components:
1. Floodplain development policy introduced to incentivize long-term resilience to flood/flash flood risks
2. Climate-resilient practices in flood management developed and implemented to reduce vulnerability of highly exposed communities
3. Early warning system in place to improve preparedness and adaptive capacity of population
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3 Assessment of Hydropower
Resources of Georgia
Ministry of Foreign Affairs
of Norway/ Norwegian Water
Resources and Energy
Directorate (NVE)
Accomplished (2013–2016)
Ministry of Energy of
Georgia, NEA
€1,792,800 The project envisages creating an electronic system to assess rivers’ energy potential in Georgia. The system will make it possible to calculate and electronically register the energy potential of water resources and rivers within the country’s territory. After introduction of the program and based on the processed information, the Ministry of Energy of Georgia will analyze new hydrological data and elaborate investment plans to implement relevant projects.The framework of the project also envisages digitizing all hydrological data available at the NEA and providing corresponding technical and software support to the agency. After accomplishment of the project, the river energy potential database will be handed over free of charge to NEA, which will manage the database.
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4 Prevention & Preparedness
towards Natural Disasters in Mestia
Municipality (in the framework of “Strengthening the prevention
and preparedness
systems,” phase 2)
Swiss Development Cooperation
(SDC)
Accomplished (2014–2015)
Mestia Municipality,
NEA
SwF 625,000 The project assesses the natural disaster risks related to water, climate, and weather in Mestia Municipality. The following outcomes are sought for the territory of Mestia Municipality (Mestia community, settlements of Chuberi, Mulakhi, Becho, Nakra, and Ushguli):
• Determination of risks of landslides, mudflows, stone and snow avalanches, floods, and flash floods
• Determination of propagation zones and compilation of risk maps for the mentioned phenomena, zoned according to the risks
• Development of recommendations for preventive measures
• Following the recommendations will allow Mestia Municipality to reduce disaster risks and will support the municipality’s sustainable development.
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5 Anti-flood Early Warning and Prevention Systems
in Georgia: Special Focus on Kabali and Duruji Rivers
Ministry of Foreign Affairs
of Poland, Department of Development Cooperation (PolishAid)
Accomplished (2014–2015)
Kvareli and Lagodekhi
Municipalities, Ministry of Internal
Affairs, Civitas Georgica, NEA
US $125,000
The project objectives are as follows:
• Creating an early warning system on Duruji and Kabali Rivers
• Elaborating crisis management plans for Kvareli and Lagodekhi Municipalities
• Conducting training to increase the skills of the representatives of respective services of Kvareli and Lagodekhi
The results of the project are as follows:
• Rehabilitated and extended network of the automatic hydrological stations in the Kabali and Duruji Rivers and the most vulnerable tributary of the Alazani River (3 automatic hydrological gauges)
• Installed forecasting technological lines for the Kabali and Duruji Rivers and the tributaries (12) of the Alazani River
• High-resolution and successful outputs provided by models
• Issued timely and effective early warnings in the region
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6 Japan’s Non-Project Grant Aid for Provision
of Japanese SMEs’ Products (FY 2013)
Government of Japan
Accomplished (Package
1—2014–2016; Package 2—2016–
2018)
NEA, Japan International Cooperation
System (JICS)
¥200 million
This program envisaged procurement of Japanese SME products by JICS for delivery to NEA by successful tenderers. The goal was to improve NEA’s monitoring capacities. The following results were achieved:
• 3 air quality monitoring stations were installed in Tbilisi.
• 2 automatic weather stations for the harbor were installed in Poti and Batumi seaports.
• 4 automatic river water-level measuring stations were installed on the Khobistkali, Natanebi, Bzhuzha, and Gubazeuli Rivers.
• Data collection and management systems were installed at NEA’s headquarters.
7 Modernization of Hydrometeorological
Services in Georgia
Czech Development
Agency (CzDA)/ expert
Radim Tolasz
Accomplished (April–June 2015)
NEA €30,000 This project is a study of the hydromet system as the basis for hydromet modernization.
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8 Increasing Meteorological
Safety of TRACECA Corridor
Czech Development
Agency (CzDA)/ Glomex MS,
S.R.O.
Accomplished (June-December
2015)
NEA/Roads Department of
Georgia
€110,000 The project aims at mitigating negative impacts of dangerous meteorological phenomena on traffic safety in the TRACECA (Transport Corridor Europe-Caucasus-Asia) corridor in the vicinity of the Rikoti Pass. It seeks to make drivers using this corridor more aware of the occurrence of dangerous hydrometeorological phenomena.The project includes installation of 1 road meteorological station, personnel training in maintenance and operation, and provision of essential know-how for advanced short-term weather forecasting and its applications to road meteorology. These activities will be carried out by Czech contractors and NEA staff.
9 Feasibility Study and Technical Expertise for the Radar Integration
into the Meteorological Network of the Agency
(NEA)
Swiss Development Cooperation (SDC)/expert Ljubov Liman
(Finnish Meteorological
Institute)
Accomplished (July–August
2015)
NEA €30,000 Based on the feasibility study by the qualified expert, the project aims at preparing the technical-economic justification for integrating meteorological radar into the agency’s current meteorological network.
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10 Feasibility Study and Technical Expertise for
the Radar Integration into
the Meteorological Network of the Agency (within
the framework of GCP/GEO/004/AUT - Capacity Development of the Ministry of Agriculture of
Georgia: Improved Policy Making and Effective
Implementation of the Strategy for Agricultural Development
(Contribution to ENPARD Georgia
Program)
FAO/expert Fadi Karam
Accomplished (September–
October 2015)
NEA €20,000 Based on the feasibility study by the qualified expert, the project aims at preparing the technical-economic justification for integrating meteorological radar into the agency’s current meteorological network.
11 Strengthening Capacity of the National
Environmental Agency in
Monitoring and Forecasting of Flood Risks in
Tbilisi Area
Ministry of Foreign Affairs of the Republic
of Poland/Polish Development Cooperation
Accomplished (September–
December 2015)
NEA €29,740 Within the framework of the project, the National Environmental Agency will purchase hydrometeorological equipment to strengthen its capacities in monitoring and forecasting of flood risks in the Tbilisi area.The following equipment will be purchased:
• Rainfall measurement stations (3)
• Geodetic receiver (1)• Remote-controlled
air system with high-definition camera to collect hydrometeorological data (1)
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12 Subproject in the Framework
of Strengthening DRR Capacities in
Georgia
UNDP Georgia
Accomplished (2015–2016)
NEA US$525,000 (allocated amount for NEA:
US$39,690)
The project intends to develop multi-hazard (hydrological and geological) maps for major hot-spot river basins in Tbilisi, particularly the Gldanis Khevi Basin (for geological hazard risk mapping) and Vere and Gldanis Khevi Basins (for hydrological hazard risk mapping and flood zoning). The work uses hydraulic and hydrological models, with a list of recommended measures for reduction of multi-hazard risks.
13 Japan’s Non-Project Grant Aid for Provision of Japanese SMEs’
Products (FY 2014)
Government of Japan
Accomplished (2015–2016)
NEA ¥100 million
The program envisaged procurement of Japanese SME products by JICS for delivery to NEA by successful tenderers. The goal was to improve NEA’s monitoring capacities, in particular its use of different laboratory and field equipment.
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14 Study of Hydraulic Modeling against
Floods—2nd Stage: Support to the Competence and Readiness
of Georgian Institutions—1st
Module
Ministry of Foreign Affairs of the Republic
of Poland, Polish Development Cooperation/
Polish Center for International Aid
(PCPM)
Accomplished (June–December
2016)
NEA US$58,048 The aim of the project was developing institutional capacities of NEA and its staff in hydraulic modeling. The specific objectives of the project were as follows: 1. Consultations by
Polish specialist on own work of dedicated NEA employees on basic 1D modeling of Aragvi River (below the Zhinvali Dam) and next 5 Kakheti rivers (northern Alazani inflows)
2. Advanced training in 1D modeling—MIKE-11 complicated functions: bridge break or dam break scenario on the example of Aragvi/Zhinvali, rivers with changeable catchments
3. Training on LiDAR scanning data usage
4. Institutional support to NEA: ARC GIS purchase
5. Institutional support to NEA: library creation and equipment
15 Increasing Safety of Transport Corridors in
Georgia through Development of
Road Meteorology
Czech Development
Agency (CzDA/ GEOTEST
Accomplished (2016–2017)
NEA/Roads Department of Georgia
€120,000 The project aims at mitigating negative impacts of dangerous meteorological phenomena on traffic traveling in the TRACECA and Georgian Military Road corridors.The project includes installation of 3 road meteorological stations, personnel training in maintenance and operation, and capacity-building activities for further development of road meteorology in Georgia.
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16 Study of Hydraulic Modeling against
Floods—2nd Stage: Support to the Competence and Readiness
of Georgian Institutions—2nd
module
Ministry of Foreign Affairs of the
Republic of Poland, Polish Development
Cooperation/ Polish Center for International Aid
(PCPM)
Accomplished (May–December
2017)
NEA, Dusheti and
Mtskheta Municipalities
Zl 826 481 (allocated budget for
NEA— financial: US$8,000;
in-kind: US$86,200)
The aim of the project is to build the human and institutional capacity of the National Environmental Agency for hydraulic modeling. The objectives of the project are as follows:1. Improving quality
of hydrological and geological data in NEA databases
2. Improving NEA employees’ competence in data processing from LiDAR scanning
3. Increasing selected NEA employees’ competence in 2D river modeling and drawing of related conclusions
4. Improving NEA employees’ skills in presenting results of their work in Georgia as well as abroad
5. Raising awareness of local and state authorities and various stakeholders of flood risks related to Aragvi River in Zhinvali-Mtskheta section
6. Enriching meteorological station network in Georgia (Barisakho and Shatili villages)
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17 Monitoring and Assessment of the Impact of Droughts on Water Resources and Their Effective
Use in Georgia
Slovak Agency for International
Development Cooperation (SlovakAid)
Accomplished (2017–2018)
NEA €89,735 (allocated amount for NEA: €20,070)
The main objective of the project is improving knowledge of drought impact on the water resources and their protection and sustainable use. More specifically, the following will be achieved:• The overall improvement of the monitoring and assessment of drought in Georgia• Elaborated proposal of the institutional and organizational structure for drought management and development of an early warning system in Georgia
18 Adaptation of the Remote Sensing
Methods in Water Resources
Management and Assessment
of Extreme Hydrometeorological Situations in Georgia
Slovak Agency for International
Development Cooperation (SlovakAid)/
Slovak Hydro-meteorological
Institute (SHMÚ)
Ongoing (2017–2019)
NEA €95,025 (allocated amount for NEA: €25,825)
The following objectives will be achieved by the project:• Overall improvement
of extreme hydrometeorological situations by monitoring and assessment of their impact on Georgia’s water resources and vulnerable zones
• More effective use of remote sensing data; capacity building for cooperation and sustainable use of water resources and civil protection in Georgia
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19 Preschool Infrastructure Assessment and Support to Georgian Institutions’ Readiness to Respond to Natural
Disasters and Fire
Ministry of Foreign Affairs of
the Republic of Poland,
Polish Development Cooperation/
Polish Center for
International Aid (PCPM)
Ongoing (2018–2019)
(accomplished for NEA May–
September 2018)
Civitas Georgica,
NEA
Zl 630,990 (including allocated budget
for NEA of US$8,815)
The following are within the project (2018–2019):
1. Infrastructure assessment related to flood risk at schools located in flood zones of 5 Kakaheti rivers (Avaniskhevi, Chelti, Intsoba, Shromoskhevi, and Lopota) will be conducted; recommendations for technical and organizational improvements will be delivered to schools and relevant municipalities. NEA’s task: preparing and presenting flood zones to the assessment team
2. Infrastructure assessment of kindergartens related to readiness against natural hazard risks (flood, landslides, wind, avalanche) will be conducted for 5 municipalities: Mtskheta, Tianeti, Dusheti, Kazbegi, and Gardabani; recommendations will be delivered to kindergarten management and municipalities. NEA’s task: risk description and assessment for the preschool objects under assessment
3. Kindergartens will be equipped with safety equipment (fire extinguishers, smoke detectors, evacuation plans, etc.).
4. Kindergarten administrators, teachers, and parents will be assessed and trained in safety and disaster risk reduction.
5. Kindergarten infrastructure standards for preventing negative consequences of natural hazards and fire will be elaborated and delivered to relevant state institutions for approval; such standards should be elaborated by already existing legislation.
6. Final conference presenting the results of the project and elaborated infrastructure standards will be organized.
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20 Assessment of Suitable Flood
Mitigation Measures in Tbilisi
Climate Technology
Center & Network/
Hydroc, NGO Environment
and Development
Accomplished (2017–2018)
NEA US $247,000
Flash floods and mudflows occurring on small rivers as a result of heavy rains impact various parts of Tbilisi, causing heavy damage and/or human casualties. Recommendations are needed in order to determine appropriate actions to prevent disastrous consequences of possible floods of the Tsavkisiskhevi River within Tbilisi (as part of climate change adaptation).
21 Renewable Energy -
Hydropower - Hydrology -
Climate (within institutional cooperation
between the Norwegian
Water Resources and Energy Directorate
(NVE), MoESD, MEPA,
Georgian State Electrosystem
(GSE), Georgian Technical University (GTU), and
National Environmental Agency (NEA)
Ministry of Foreign Affairs of Norway/
Norwegian Water
Resources and Energy Directorate
(NVE)
Ongoing (2018–2023)
Ministry of Energy
of Georgia
(now within
MoESD), NEA
NKr 30,833,668
The overall objective of the project is to improve the utilization of Georgia’s renewable energy resources for economic development of the country. In order to reach the overall project goal, which is establishment of relevant data and technical capacity for rational planning and development of Georgia’s renewable energy resources and to draft the Renewable Energy Law of Georgia, the following cooperation areas are foreseen:
1. MSc program at Norwegian University of Science and Technology (NTNU) for Georgian students
2. Five short-term courses for employees of MoESD, GSE, and NEA
3. Analysis of climate change impact on runoff and hydropower production
4. Hydrological and meteorological data management system (hydro generation forecast, hydropower plant operation in free market conditions)
5. Modeling tools for water resources management
6. Road map for power market development
7. Grid integration study Georgia–Turkey (with reserve sharing, market coupling)
8. Draft Renewable Energy Law of Georgia
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ANNEX 3. SERVICE DELIVERY PROGRESS MODEL
The Service Delivery Progress Model is adapted from the WMO Strategy for Service Delivery and Its Implementation Plan (WMO 2014). The model can be used as a tool for assessing an NMHS’s level of development and for creating an action plan to improve service delivery. Full details can be found in http://www.wmo.int/pages/prog/amp/pwsp/documents/WMO-SSD-1129_en.pdf.
Undeveloped Development, Initiated
Development in Progress Developed Advanced
Strategy Element 1:
Evaluate User
Needs and Decisions
The users and their requirements for products or services are not known.
Users are known, but no process for user engagement exists.User requirements for service delivery are not well defined.
Users are able to contact the NMHS and their feedback is recorded.There are some formal processes for integrating the feedback received into the development of services.User requirements are defined with limited documentation.
NMHS seeks input on an ad hoc basis from users to facilitate the development of services.Requirements are defined in documents agreed upon with the user but are not routinely updated.
An ongoing dialogue is maintained with users regarding their needs and the services they receive.Requirements are defined in documents agreed upon with the user and routinely updated using feedback from users.
Strategy Element 2: Link service development and delivery
to user needs
No concept of service exists; products are simply issued.
Services do not adapt to changing user needs and new technology.Products are documented with limited descriptive information.
Services are developed and changed as technology allows, but engagement with users is ad hoc.Products and services are documented, and the information is used to inform management of changes.
User feedback is used to inform management of changes and development of services.Products and services are consistently documented. Service-level agreements (SLAs) are defined.
Users are consulted to facilitate development of products and services.The service defined in the SLA is agreed upon with the user based on user consultation.
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Undeveloped Development, Initiated
Development in Progress Developed Advanced
Strategy Element 3:
Evaluate and monitor
service performance
and outcomes
No measures are in place for assessing performance, in terms of either accuracy or service delivery.
Some measures of development are in place.The verification of accuracy and/or service delivery takes place, but no systematic process exists to use this information to improve the service.
Measures of verification and service delivery are in place but are not informed by user requirements.
User requirements are used as data for performance measures.Findings are used to identify areas for improvement.Subsequent actions are taken in an ad hoc manner.
Measures of performance are based on user needs, which are regularly reported and consistently used to inform decisions on improvements.
Strategy Element 4:
Sustain improved service delivery
No concept exists of service delivery principles.
The concept of service delivery has been introduced and an assessment of current status has been undertaken.
An action plan has been created to improve the current level of service delivery, and resources have been identified to implement it.
The action plan is being implemented to improve service delivery, and the outcomes are being monitored.
The status of service delivery is reviewed on a regular basis.The action plan evolves in response to the outcome of the reviews.
Strategy Element 5:
Develop skills needed
to sustain service delivery
No concept or communication of service delivery principles exists.
No formal training in service delivery is provided, though service delivery principles are informally communicated.
Most staff of the NMHS are aware of the importance of service delivery.Some formal training is provided.
All members of staff are fully aware of the importance of service delivery.Formal training is provided. There is an ad hoc process for staff to offer ideas for improvements to service delivery.
There is a culture of providing best possible service delivery.Innovative ideas are routinely integrated into the continual service improvement process.
Strategy Element 6: Share best
practices and knowledge
NMHSs are encouraged to share best practices in service delivery through formal training, twinning, mentoring and other methods.
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Undeveloped Development, Initiated
Development in Progress Developed Advanced
Observations and
Telecommunications
NMHS has very few manual synoptic stations and hydrological stations. It does not share station data on the Global Telecommunication System (GTS).
NMHS has the capacity to support a synoptic meteorological network and hydrological network; it shares these data on the GTS; and it has sufficient staff to maintain its observing networks.
Automation of observing network with quality control is routine. NMHS accesses satellite data with (e.g.) the capacity to derive precipitation estimates. The observing network is sustainable with sufficient budget for operations and maintenance. The vertical structure of the atmosphere may be routinely measured.
Observations extend to smaller scales and include ground-based remote sensing techniques, such as radar. The NMHS may be able to take and integrate observations from other parties.It may access observations by outsourcing its observing requirements.
NMHS conducts research, introducing new observational technologies and techniques as needed. The observing network is comprehensive and sufficient to meet main user needs, incorporates external observations from other suppliers, for example, agro-meteorological network operated by a Ministry of Agriculture or hydrological network operated by a Ministry of Energy or Water Resources.
ANNEX 4. OBSERVATION AND TELECOMMUNICATION PROGRESS MODEL
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ANNEX 5. MODELING AND FORECASTING PROGRESS MODEL
Undeveloped Development, Initiated
Development in Progress Developed Advanced
Modeling and Forecasting
Systems
NMHS provides up to a two-day deterministic forecast based on graphical forecast products retrieved from different Web sources. There is no verification of forecasts. The NMHS does not operate forecasting on a 24-hour, seven-day-a-week basis; and warnings are not issued.
NMHS can provide at least a three-day deterministic forecast based on access to global and regional NWP data and products available on the GTS and/or graphical products available from WMO Regional Specialized Meteorological Centers; monitors the current weather and hydrological system; has basic data-processing and archiving systems; and carries out subjective forecast verification. There is no research and development, and the quality management system is rudimentary. The NMHS may not operate forecasting on a 24-hour, seven-day-a-week basis. Warnings are limited.
The NMHs can provide zero- to five-day forecasts using global and regional deterministic NWP and EPS data and products from Global Producing Centers; issues nowcasts and very-short-range forecasts of up to 12 hours based on extrapolating NWP and blending remote-sensing observations; is able to monitor major rivers and generate short-term flow and flood forecasts; has protocols for emergencies, back-up of data and products, and off-site storage facilities; carries out verification and post-processing; has some R&D and a QMS. The NMHS operates forecasting on a 24-hour, seven-day-a-week basis.
LAM systems are available locally or through regional centers. Using local data assimilation, high-resolution short time scale forecasts are produced with emphasis on zero to six hours for extreme events. The forecasting system extends from zero to at least seven days based on a combination of global, regional, and national deterministic NWP and EPS data and products. The NMHS has the capacity to manipulate digital data and to tailor forecasts to specific users; operates a multi-hazard warning system; generates seasonal streamflow outlooks and specialized hydrology products; and has full R&D capability. There are well-established relationships with partner agencies.
NMHS has an extensive research program and introduces new forecasting technologies and techniques; has the capacity to support requirements of other NMHSs; and is able to run global, regional, and national NWP and EPS systems. Forecasts of weather and hydrological impacts on specific sectors are routine and generally developed with users of these forecasts. The NMHS has a well-developed education and training unit.
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Undeveloped Development, Initiated
Development in Progress Developed Advanced
Climate Services
NMHS may operate a limited national climate observing system; collects data in paper form; retrieves climate data from different sources to generate national climate products; participates in regional climate outlooks; and has very limited or no interaction with users. Typically, NMHSs in this category do not have staff dedicated to carrying out climate services.
NMHS designs, operates, and maintains national climate observing systems; manages data, including QA/QC; develops and maintains data archives; monitors climate; oversees climate standards; performs climate diagnostics, climate analysis, and climate assessment; disseminates climate products; participates in regional climate outlooks; interacts with users; and performs the functions of national climate centers providing basic climate services. Staff are proficient in climate statistics, homogeneity testing techniques, and quality assurance techniques.
NMHS has the capacity to develop and/or provide monthly and longer climate predictions, including seasonal climate outlooks, both statistical and model-based; is able to conduct or participate in regional and national climate outlook forums; interacts with users in various sectors; adds value from national perspectives on the products received from Regional Climate Centers and in some cases Global Producing Centers for long-range forecasts; conducts climate watch programs; and disseminates early warnings. Staff are proficient in developing and interpreting climate prediction products and in assisting users in the uptake of these products.
NMHS generates subseasonal to seasonal forecast products, develops specialized climate products; downscales long-term climate projections as well as interprets annual to decadal climate predictions; covers all the elements of climate risk management (risk identification; risk assessment, planning, and prevention; services for response and recovery from hazards; information relevant to climate variability and change; and information and advice related to adaptation); builds societal awareness of climate change issues and provides information relevant to policy development and a national action plan. Staff have knowledge of climate modeling and methods for downscaling/calibration, risk and risk management, and financial tools for risk transfer.
NMHS has research capacities and runs global and regional climate models (subseasonal to decadal and longer); and works with sector-based research teams and develops application models, software, and product suites for customized climate products. Staff have multi-disciplinary modeling and statistical expertise and can downscale/calibrate global scale information to regional and national levels. The NMHS is able to receive and respond to user requirements for new products.
ANNEX 6. CLIMATE SERVICES PROGRESS MODEL
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Undeveloped Development, Initiated
Development in Progress Developed Advanced
Climate Services
NMHS may operate a limited national climate observing system; collects data in paper form; retrieves climate data from different sources to generate national climate products; participates in regional climate outlooks; and has very limited or no interaction with users. Typically, NMHSs in this category do not have staff dedicated to carrying out climate services.
NMHS designs, operates, and maintains national climate observing systems; manages data, including QA/QC; develops and maintains data archives; monitors climate; oversees climate standards; performs climate diagnostics, climate analysis, and climate assessment; disseminates climate products; participates in regional climate outlooks; interacts with users; and performs the functions of national climate centers providing basic climate services. Staff are proficient in climate statistics, homogeneity testing techniques, and quality assurance techniques.
NMHS has the capacity to develop and/or provide monthly and longer climate predictions, including seasonal climate outlooks, both statistical and model-based; is able to conduct or participate in regional and national climate outlook forums; interacts with users in various sectors; adds value from national perspectives on the products received from Regional Climate Centers and in some cases Global Producing Centers for long-range forecasts; conducts climate watch programs; and disseminates early warnings. Staff are proficient in developing and interpreting climate prediction products and in assisting users in the uptake of these products.
NMHS generates subseasonal to seasonal forecast products, develops specialized climate products; downscales long-term climate projections as well as interprets annual to decadal climate predictions; covers all the elements of climate risk management (risk identification; risk assessment, planning, and prevention; services for response and recovery from hazards; information relevant to climate variability and change; and information and advice related to adaptation); builds societal awareness of climate change issues and provides information relevant to policy development and a national action plan. Staff have knowledge of climate modeling and methods for downscaling/calibration, risk and risk management, and financial tools for risk transfer.
NMHS has research capacities and runs global and regional climate models (subseasonal to decadal and longer); and works with sector-based research teams and develops application models, software, and product suites for customized climate products. Staff have multi-disciplinary modeling and statistical expertise and can downscale/calibrate global scale information to regional and national levels. The NMHS is able to receive and respond to user requirements for new products.
Undeveloped Development, Initiated
Development in Progress Developed Advanced
Hydrological Services
The NMHS may operate and maintain a very small hydrological observation network; collect data in paper format; and have very limited or no interaction with users. Typically, staff of NMHSs in this category are not trained in hydrology.
Functions of NMHS may include operation and maintenance of a small hydrological observation network; hydrological data management, with basic hydrological data processing, archiving, and communication system; little or no backup/off-site storage; and some interaction with users of hydrology data and products. There is no research and development, and a rudimentary quality management system. There are no relationships with partner agencies.
The NMHS is able to operate and maintain a hydrological observational network to monitor major rivers, and take and integrate some hydrological observations from other parties. The NMHS operates an interoperable hydrological data management system and has well-established protocols for emergencies, backup of hydrological data, and minimum off-site facilities. The NMHS carries out water-level and flow monitoring and is able to generate short-term flow forecasts (low flows), flood forecasting, and hydrological data products for design and operation of water supply structures. There is a small research and development unit and a quality management system. There are some relationships with partner agencies.
The NMHS operates and maintains a comprehensive hydrological observational network to monitor major and some smaller rivers, and takes and integrates most of the hydrological observations from other parties. The NMHS operates a well-developed interoperable hydrological data management system and has well-established protocols for emergencies, backup of hydrological data, and off-site facilities. The NMHS carries out water -level and flow monitoring, and is able to generate short-term flow forecasts (low flows), flood forecasting, and hydrological data products for design and operation of water supply structures. The NMHS is also able to generate seasonal streamflow outlooks and specialized hydrology products. There is a research and development unit; and a well-established quality management system. There are well-established relationships with partner agencies.
In addition to the foregoing capabilities, the NMHS has an extensive research and development program; and strong relationships with partner agencies, taking a leading role in advice and decision support. NMHS has the ability to generate customized hydrological products, and to develop hydrological application tools.
ANNEX 7. HYDROLOGICAL SERVICES PROGRESS MODEL
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