Technical Assistance Consultant’s Report...And two river basins of Balochistan, namely, Mula and Zhob river basins were nominated as the pilot areas. Figure 1-1 shows the project

Technical Assistance Consultant’s Report

Project Number: 48098-001 November 2018

Islamic Republic of Pakistan: Balochistan Water Resources Development Project (Financed by the Japan Fund for Poverty Reduction)

Final Report

Prepared by: Techno-Consult International (Pvt.) Ltd. (Water Division)

Karachi, Pakistan

For: Irrigation Department, Government of Balochistan, Pakistan

This consultant’s report does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents. (For project preparatory technical assistance: All the views expressed herein may not be incorporated into the proposed project’s design.)

Balochistan Water Resources Development

Project Preparatory Technical Assistance

(TA 8800-PAK)

Water Resource Information System

Applying Remote Sending and GIS Technology

November 2016

The Government of Balochistan

Final Report

Remote Sensing and GIS Team

Balochistan Water Resources Development Project

Final Report

i

Table of Contents

1 Introduction .................................................................................................................... 1

1.1 Background............................................................................................................. 1

1.2 Project rationale and objectives .............................................................................. 1

1.3 Project area ............................................................................................................ 1

1.4 Project preparation.................................................................................................. 2

1.4.1 Vision & strategy .............................................................................................. 3

1.4.2 Consultants' mobilization ................................................................................. 4

1.4.3 Resource mobilization ...................................................................................... 4

1.5 Report-in-hand ........................................................................................................ 4

2 Water Resource Information System (WRIS) ................................................................. 5

2.1 Overview ................................................................................................................. 5

2.2 Concept .................................................................................................................. 5

2.3 Architecture............................................................................................................. 6

2.4 Information layer ..................................................................................................... 6

2.4.1 Satellite information ......................................................................................... 6

2.4.2 Ground observation data and associated information ...................................... 7

2.5 System design ...................................................................................................... 14

2.5.1 WRIS ............................................................................................................. 14

2.5.2 Satellite data processing ................................................................................ 16

2.6 WRIS Operational Model ...................................................................................... 18

2.7 WRIS User Access Levels .................................................................................... 19

3 WRIS Institutional Framework ...................................................................................... 21

4 Satellite Information layer ............................................................................................. 23

4.1 Overview ............................................................................................................... 23

4.2 Agro-meteorological information ........................................................................... 24

4.2.1 Precipitation ................................................................................................... 24

4.2.2 Soil Moisture .................................................................................................. 25

4.2.3 Solar Radiation .............................................................................................. 27

4.2.4 Land surface temperature .............................................................................. 29

4.2.5 Normalized vegetation index .......................................................................... 30

4.2.6 ET-index and Evapotranspiration ................................................................... 32

4.3 Warning information .............................................................................................. 35

4.3.1 Heavy precipitation warning based on probable precipitation ......................... 35

4.3.2 Land water index (LWI) .................................................................................. 38

4.4 Agro-meteorological information (high-resolution map) ......................................... 39


Final Report

ii

4.4.1 Vegetation Index (Landsat-8) ......................................................................... 39

5 Training Plan in the PPTA ............................................................................................ 41

5.1 Overall Planning ................................................................................................... 41

5.2 The detailed contents regarding WRIS.................................................................. 41

6 Recommendations for the next step ............................................................................. 42

6.1 Overview ............................................................................................................... 42

6.2 As for the systems architecture ............................................................................. 42

6.3 As for the water resource monitoring information .................................................. 42

6.4 As for capacity development aspect ...................................................................... 42


Final Report

iii

List of Figures

Figure 1-1: Project Area ........................................................................................................ 2

Figure 1-2: WRIS Components and application field ............................................................. 3

Figure 2-1: Concept of WRIS ................................................................................................ 5

Figure 2-2: Concept of WRIS architecture ............................................................................. 6

Figure 2-3: Proposed System Architecture(PPTA Stage) .................................................... 14

Figure 2-4: Internal Architecture for PostgreSQL ................................................................. 15

Figure 2-5: Data Sources & Services offered by GeoServer ................................................ 16

Figure 2-6: Processing follow of satellite information ........................................................... 17

Figure 2-7: WRIS Proposed Operations Structure ............................................................... 18

Figure 2-8: WRIS User Access Levels and User Privileges ................................................. 20

Figure 3-1: Balochistan Institutional Arrangement ............................................................... 22

Figure 4-1: Distribution map of accumulated precipitation for half-month ............................ 24

Figure 4-2: Time series graph of accumulated precipitation for half-month .......................... 25

Figure 4-3: Distribution map of soil moisture ....................................................................... 26

Figure 4-4: Time series graph of soil moisture..................................................................... 27

Figure 4-5: Distribution map of solar radiation ..................................................................... 28

Figure 4-6: Time series graph of solar radiation .................................................................. 28

Figure 4-7: Distribution map of land surface temperature (LST) .......................................... 29

Figure 4-8: Time series graph of Land Surface Temperature (LST) .................................... 30

Figure 4-9: Distribution map of Normalized Vegetation Index (NDVI) .................................. 31

Figure 4-10: Time series graph of Normalized Vegetation Index (NDVI) ............................. 32

Figure 4-11: Distribution map of ET-index ........................................................................... 34

Figure 4-12: Distribution map of Evapotranspiration (ETa) ................................................... 34

Figure 4-13: Time series graph of Evapotranspiration (ET) ................................................. 35

Figure 4-14: Heavy precipitation warning (1 hour) ............................................................... 36


Final Report

iv

Figure 4-15: Heavy precipitation warning (3 hours) ............................................................. 36

Figure 4-16: Heavy precipitation warning (12 hours) ........................................................... 37



Figure 4-19: Land water Index map ..................................................................................... 38

Figure 4-20: Landsat-8 vegetation index (NDVI) ................................................................. 40


Final Report

v

List of Tables

Table 2-1: Proposed GIS Layers & Access Level from Satellite Information .......................... 8

Table 2-2: Proposed GIS Layers & Access Level from Ground Observation Data and Associated

Information ............................................................................................................................ 9

Table 2-3: Data source of satellite information .................................................................... 17

Table 4-1: Satellite Information ........................................................................................... 23

Table 5-1: Proposed Training Course ................................................................................. 41


Final Report

vi

Acronyms

ACD – Agriculture and Cooperative Department

ADB – Asian Development Bank

AMSR2 – Advanced Microwave Scanning Radiometer 2

AMSU – Advanced Microwave Sounding Unit

API – Application Program Interface

BWRDP – Balochistan Water Resources Development Project

DMSP – Defense Meteorological Satellite Program

EA – Executing Agency

EORC – Earth Observation Research Center

ET – Evapotranspiration

FAO – Food and Agriculture Organization of the United Nations

GCOM – Global Change Observation Mission

GCOM-C – GCOM - Climate

GCOM-W1 – GCOM 1st - Water

GIS – Geographical Information System

GMI – GPM Microwave Imager

GoB – Government of Balochistan

GPM – Global Precipitation Measurement

GSMaP – Global Satellite Mapping of Precipitation

ID – Irrigation Department

IR – Infrared

IRSA – Indus River System Authority

JASMES – JAXA Satellite Monitoring for Environmental Studies

JAXA – Japan Aerospace Exploration Agency

JBIC – Japan Bank for International Cooperation

LP DAAC – NASA Land Processes Distributed Active Archive Center

LST – Land Surface Temperature

LWI – Land Water Index

MODIS – Moderate Resolution Imaging Spectroradimeter

NASA – National Aeronautics and Space Administration

NDMA – National Disaster Management Authority

NDA – National Drainage Program

NDVI – Normalized Difference Vegetation Index

NOAA – National Oceanic and Atmospheric Administration

OGC – Open Geospatial Consortium

ORDBMS – Object-Relational Database Management System


Final Report

vii

P&D – Planning and Development

PCO – Population Census Organization

PDMA – Provincial Disaster Management Authority

PMD – Pakistan Meteorological Department

PPTA – Project Preparatory Technical Assistance

RESTEC – Remote Sensing Technology Center of Japan

RS – Remote Sensing

SUPARCO – Pakistan Space &Upper Atmosphere Research Commission

SSMIS – Special Sensor Microwave Imager/Sounder

TCI – Techno-Consult International (Pvt.) Lid

TMI – TRMM Microwave Imager

TRMM – Tropical Rainfall Measuring Mission

USGS – United States Geological Survey

WFS – Web Feature Service

WMS – Web Map Service

WR – Water Resource

WRIS – Water Resources Information System

1

1 Introduction

1.1 Background

1. Government of Balochistan (GoB) in collaboration with Asian Development Bank (ADB)

has envisioned a Water Resources Development Program comprising rapid assessment of four

basins namely, Hingol, Mula, Pishin Lora and Zhob river basins and selecting two basins for

further detailed study. Based on the study, development works (sub-projects) shall be proposed

and implemented. ADB also decides to apply remote sensing and GIS technology to monitor the

water resources in Balochistan, which is the biggest province in Pakistan and its population

density quite low. Through the PPTA, Remote Sensing Specialists from Remote Sensing

Technology Center of Japan (RESTEC) and GIS specialist from Exponent Engineers (Pvt.)

Limited are required to design and develop Water Resources Information System (WRIS) with

applying remote sensing and GIS technology.

1.2 Project rationale and objectives

2. The project will improve land and water resources, agricultural production and farm

income of 10,000 rural households by (i) bringing 10,000 ha of new land under cultivation; (ii)

improving 20,000 ha of irrigated land; and (iii) protecting 1,500 ha of watersheds. The project will

(a) construct new small dams and flood irrigation (spate) systems; (b) improve 300 km of canals,

drains, and karezes (subsurface water channels); (c) develop a satellite-based water information

system; and (d) build capacity of the local communities, the Irrigation Department (ID), and the

Agriculture and Cooperative Department (ACD).

3. As part of the project, WRIS for Balochistan to collect and share freely available satellite-

based water resources data and other ground-based data collected and maintained by the

Irrigation Department (ID), Government of Balochistan in cooperation with other relevant agencies

will be developed.

1.3 Project area

4. An initial survey1 by the water resource specialist (firm) was completed. And two river

basins of Balochistan, namely, Mula and Zhob river basins were nominated as the pilot areas.

Figure 1-1 shows the project area and two pilot areas.

1 Balochistan Water Resources Development Project, Inception Report prepared by Techno - Consult International

(TCI), April 2016.


Final Report

2

Figure 1-1: Project Area Background Image is a topographic map.2 Red and blue shaded areas shown Mula and Zhob river basin, respectively.

1.4 Project preparation

5. As a part of the preparation phase, ADB defined the functions of WRIS to be equipped. In

the start, a freely available satellite-based water resources information such as precipitation, soil

moisture, and land surface temperature will be collected and shared by the WRIS in collaboration

with Japan Aerospace Exploration Agency (JAXA). The WRIS will have a user interface using

GIS for sharing the collected data among stakeholders. The system will integrate the satellite-

based remote sensing data, the ground observation data and associated information into the

same system (Figure 1-2), and visualize the data with base maps for geographic information

management and data analysis. Users can browse and find information and data in a cross-

thematic manner in more intuitive ways than with a keyword search, and easily measure

geographic features such as the size of the impact area and precipitation volume in the target

area.

2 Data source: NASA SRTM v3

Mula River Basin

Zhob River BasinBalochistan

https://earthdata.nasa.gov/nasa-shuttle-radar-topography-mission-srtm-version-3-0-global-1-arc-second-data-released-over-asia-and-australia


Final Report

3

Figure 1-2: WRIS Components and application field

1.4.1 Vision & strategy

6. For good design and development of WRIS, the integration of GIS and Remote Sensing

technology is one of the key factors of WRIS. And the following points should be highlighted.

i. Appropriate design for the lead time of information delivery

ii. Selection of satellite data source with reasonable cost

iii. Adjust the format of the outputs in accordance with EA and IA’s requirements.

iv. Easy-to-use design as a Geographic Information System (GIS).

7. To develop WRIS on this PPTA, the team for WRIS will be formed as a virtual sub-team

in PPTA. The members of RS&GIS team are bellow;

i. Hideyuki Fujii (Remote Sensing Specialist 1, the team leader of RS&GIS team)

ii. Tsugito Nagano (Remote Sensing Specialist 2)

iii. Ashar H. Lodi (GIS Specialist)

8. At the beginning stage of this PPTA, the design work of WRIS is led by the combination

of a top-down approach and a bottom-up approach. Since available resources from satellite-

based remote sensing data are limited and it takes a certain amount of time to clip and optimize

to Balochistan from the global scale data, the satellite data component of WRIS is developed

based on the remote sensing consultant’s consultancy. On the other hand, the dialogue with future end-users is immense to collect the ground data to be managed in WRIS. So, the RS&GIS

team will proceed with the work with mature communication with parties concerned, including the

implementing agency and the executing agency.

1. Flood & Drought Hazard Assessment

2. Basin Water Resource Assessment

3. Socioeconomic Assessment

SatelliteInformation

GroundObservation

Data

AssociatedInformation

WRIS (Water Resources Information System)

Application

Project Web

Portal

System Improvement based on user’s needs


Final Report

4

9. At the final stage of this PPTA, collecting end-user’s opinions/feedbacks to the prototype

of WRIS developed is necessary to evaluate the potential benefit of WRIS and to consider the

strategy to the loan phase.

1.4.2 Consultants' mobilization

10. The RS&GIS team mobilized March 2016, as per a submitted work plan, and started work

on the assigned tasks. Fujii and Nagano joined the inception workshop at Islamabad and

discussed with EA’s representative on his visit to Japan. Simultaneously, Lodi introductory visited

and had with various related officers of Balochistan ID and Planning and Development (P&D).

Back in the Project Office at Karachi, team professionals started collecting and reviewing the

pertinent data and information.

1.4.3 Resource mobilization

11. Mobilization of resources shall be matched to the needs and timings of the planned

activities.

1.5 Report-in-hand

12. This report (Final Report) introduces the WRIS, briefly describes the approach of system

design, system development and data collection. The approach and method for various activities

leading to the completion of the ‘project preparation’ have been presented in later sections of this

report.

5

2 Water Resource Information System (WRIS)

2.1 Overview

13. WRIS will be designed for monitoring for water resource management in Balochistan to

assist IA’s decision making. WRIS will have the capability to handle multiple data sources

including (i) satellite information, (ii) ground observation data and (iii) associated information. To

handle this information, GIS technology will be used.

14. WRIS will act as a data/information sharing platform among stakeholder departments

within the Government of Balochistan (GoB) and/or stakeholders out of Balochistan Province. The

agreed institutional arrangement enabling stakeholder departments to share information

seamlessly is discussed in detail in Section 3 of this report.

2.2 Concept

15. The concept of WRIS is to make a scalable system. Therefore, it is designed to be scalable

to include other participating departments both within and outside Balochistan in the future. The

initial participating departments include the Irrigation Department and Agriculture Department of

GoB and Pakistan Council of Research in Water Resources (PCRWR).

Figure 2-1: Concept of WRIS

Irrigation Department

Agriculture and Cooperative

Department

Relevant Agencies

PCRWR

(National Focal)

Data Sharing

WRISWater Resources Information System

A platform for data collection & sharing

COMSAT(Sever Hosting)

Space Agencies

Satellite data(Open & Free)


Final Report

6

2.3 Architecture

16. There are three scales of area coverage at (i) Balochistan level, (ii) River basin level and

(iii) Sub-river basin level. It is expected that at present the information at the project level shall be

partially available, however, the GIS architecture shall be designed in the way that this information

can be incorporated as this becomes available over time. However, the stakeholder departments

at GoB shall be responsible for all such updates.

17. To keep WRIS simple to use for end-users, WRIS is designed as a web-based application.

Furthermore, to ensure long term sustainability of WRIS it is designed as independent of any

commercial software platform. Therefore, WRIS is developed using open source development

platforms such as MySQL, PostgreSQL, OpenLayers, etc as stated in section 2.5.

Figure 2-2: Concept of WRIS architecture

2.4 Information layer

18. Table 2-1 and Table 2-2 describe the further description of proposed GIS Layers from the

data sources.

2.4.1 Satellite information

19. At the sub-river basin level, high spatial resolution information with ten-meter scale is

required. If the GIS & RS team prepare and develop this information, the main consulting firm

(TCI) will be able to assess water availability and water use. Then, the results of their assessment

can be also layers of WRIS. By comparing water availability/use maps with various layers in

WRIS, it will be helpful for water resources management.

20. Spatial resolution of freely available satellite data differs depending on the

dataset/satellite. Landsat-8, which is commonly used as free data, has 30m resolution with 16-

day revisit. But high temporal frequency information derived from satellites has a very coarse

Balochistan Level

River Basin Level

Sub-River Basin Level

Satellite (map)

Satellite (time series graph)(high-reso. map)

Ground data

Associated infor.

Ground data

Associated infor.

Ground data

Associated infor.

Satellite (time series graph)


Final Report

7

resolution. For example, the resolution of hourly precipitation data is 0.1 degree by 0.1 degree

(approx.11km x 10km in latitude x longitude direction).

21. Coarse resolution information will be useful with appropriate usage and area coverage

scales. Details of satellite information are described in Table 4-1.

2.4.2 Ground observation data and associated information

22. Presently, not significant data has been received from stakeholder departments, however

it is envisaged that data shall be received soon. Moreover, WRIS is under development and will

be completed within the stipulated timeline for this PPTA. It is however envisaged that whatever

data is received until the end of this PPTA shall be incorporated in WRIS and the remaining data

shall be incorporated by stakeholder departments themselves after their training and capacity

building is performed.


Final Report

8

Table 2-1: Proposed GIS Layers & Access Level from Satellite Information

Data Class Layer ID

Proposed Layer Name GIS Access Availability

Balochistan Level

Basin Level

Sub-Basin Level

Agro-meteorological information (map)

S1 Precipitation √

S2 Precipitation ratio (ratio to the average year)

√

S3 Soil Moisture √

S4 Soil Moisture ratio (ratio to the average year)

√

S5 Solar Radiation √

S6 Solar Radiation anomaly (difference from the average year)

√

S7 Land Surface Temperature √

S8 Land Surface Temperature anomaly (difference from the average year)

√

S9 Vegetation Index √

S10 Vegetation Index anomaly (difference from the average year)

√

S11 ET index √ √

S12 ET index anomaly (difference from the average year)

√ √

S13 Evapotranspiration (proposed by RS consultant)

√ √

S14 Evapotranspiration anomaly (proposed by RS consultant)

√ √

S15 Heavy rain warning √

S16 Inundation area (Land water index)

√

Agro-meteorological information (time series graph)

S17 Precipitation √ √

S18 Solar Radiation √ √

S19 Soil Moisture √ √

S20 Land Surface Temperature √ √

S21 ET index √ √

S22 Vegetation Index √ √

Agro-meteorological information (high-resolution map)

S23 Vegetation index (Landsat-8)

√ √


Final report

9

Table 2-2: Proposed GIS Layers & Access Level from Ground Observation Data and Associated Information

Data Class Layer ID

Proposed Layer Name

GIS Access Availability Probable Data Source Data Availability Status as of Nov. 15, 2016

Balochistan Level

Basin Level

Sub-Basin Level

Hydrological data and information (for 18 river basins in Balochistan)

G1 Watershed boundary data

√

Information for 5 basins including BWRD project available presently with TCI

G2 River channels

√

Information for 5 basins including BWRD project available presently with TCI

G3 River cross section data

√ Information only

available for localized locations for selected schemes from TCI

Information received only Location Name, Discharge Cusecs and Name of 100 Major / Minor River from Irrigation Department

G4 Topography (if data available other than free-open data such as SRTM)

√

G5 Soil type map

√

Information only available for localized locations for selected schemes from TCI

G6 River discharge / flow

√

From hydrological Year Books (Water Resources Planning Development & Monitoring Directorate Balochistan)


Final report

10

Data Class Layer ID

Proposed Layer Name


Balochistan Level

Basin Level

Sub-Basin Level

G7 Ground water level

√


G8 Dam operation records

√

G9 Specification of Dams

√

G10 Potential dam sites

√


Information received only Location (Coordinates) and Name of 100 Dams from Irrigation Department

G11 Inventory of hydrological observation stations, its specification and available data

√

From hydrological Year Books (Water Resources Planning Development & Monitoring Directorate Balochistan

Meteorological data (hourly data)

G12 Air temperature √

May be available from Metrological Department & Metrological Stations from Irrigation Department

G13 Humidity √

G14 Wind speed √

G15 Wind direction √

G16 Solar radiation √


Final report

11

Data Class Layer ID

Proposed Layer Name


Balochistan Level

Basin Level

Sub-Basin Level

G17 Precipitation √

G18 Air pressure √

G19 Soil moisture √

Meteorological facility (meta data)

G21 Observation site information / photograph

√

May be available from Metrological Department & Metrological Stations from Irrigation Department

G22 Ambient surrounding

√

G23 Sensor specifications,

√

G24 installed condition, √

G25 maintenance records,

√

G26 other information on meteorological facility

√

Cropland data and information

G27 Cropping map

√

Information only available for localized locations for selected schemes from TCI & Partial datasets may be available from Agriculture Department

Information received but unable to plot/overlay because data does not have coordinate

G28 Crop calendar for each crop

√

G29 Yield amount / Production records

√

G30 Amount of irrigated water

√

Information only available for localized


Final report

12

Data Class Layer ID

Proposed Layer Name


Balochistan Level

Basin Level

Sub-Basin Level

Irrigation data and information

G31 Irrigation operation records

√

locations for selected schemes from TCI & Partial datasets may be available from Agriculture Department

G32 Boundary data of irrigation area

√

G33 Irrigation method (map)

√

G34 Irrigation networks (canal, collector drain pump station, well, etc..)

√

G35 Status of Irrigation facility (Pump system, irrigation water channel, etc.)

√

G36 Management rule and policy

√

G37 Information of farmers' organization

√

Baseline topographic data at 1:50,000 or better scale maps

G38 Settlements √

Information may be available from Population Census Department, Provincial Disaster Management Authority (PDMA) & TCI Office

G39 Political boundaries √

G40 Road networks √

G41 River networks √

G42 Contour

√

G43 Spot height

√


Final report

13

Data Class Layer ID

Proposed Layer Name


Balochistan Level

Basin Level

Sub-Basin Level

G44 Land cover / land use classification

√

Socioeconomic information

G46 Overview of agricultural organization

√


G47 Community / village area & population

√

G48 School, health center, evacuation shelter, etc.

√

G49 Poverty condition

√

G50 Indigenous people (if any)

√

Water related disaster records

G51 Past inundation data/maps

√

May be available from Provincial Disaster Management Authority (PDMA).

G52 Past drought data/maps

√

G53 Inventory of dyke break

√


Final Report

14

2.5 System design

2.5.1 WRIS

23. The system design is performed considering two stages (PPTA Stage & Future Stage) for

the project. Since the level of governmental involvement from GoB and the budget allocation for

two stages are different, therefore this strategy of the system design is adopted.

24. This two-stage strategy shall also give time and understanding to GoB for a better

understanding of WRIS and include and cooperate with more and stakeholder departments.

25. The current section presents system development for both the stages, however at this

stage this document focuses more on suggesting system architecture in the PPTA stage.

26. The major considerations for system design at this stage shall be given to the following:

i. Minimum development and maintenance for IT support from stakeholder

departments.

ii. Use of open source technology for system development, deployment and hosting.

27. Based on the above it is proposed to use PostgreSQL Server for hosting all vector layers

and Data and GeoServer to host all raster datasets. For development it is recommended that

OpenLayers API for developing web-engine for WebGIS. The proposed system architecture is as

given in Figure 2-3.

Figure 2-3: Proposed System Architecture (PPTA Stage)


Final Report

15

28. The following discussion introduces PostgreSQL, GeoServer and OpenLayers.

29. PostgreSQL often also referred as Postgres, is an object-relational database management

system (ORDBMS) with an emphasis on extensibility and standards-compliance. As a database

server, its primary function is to store data securely, supporting best practices, and to allow for

retrieval at the request of other software applications. It can handle workloads ranging from small

single-machine applications to large Internet-facing applications with many concurrent users. It’s an open source service.

Figure 2-4: Internal Architecture for PostgreSQL3

30. GeoServer is a Java-based software server that allows users to view and edit geospatial

data. Using open standards set forth by the Open Geospatial Consortium (OGC), GeoServer

allows for great flexibility in map creation and data sharing. GeoServer allows you to display your

spatial information to the world. Implementing the Web Map Service (WMS) standard, GeoServer

can create maps in a variety of output formats. GeoServer is built on Geotools an open source

Java GIS toolkit. GeoServer also conforms to the Web Feature Service (WFS) standard, which

permits actual sharing and editing of the data that is used to generate the maps. Others can

incorporate your data into their websites and applications, freeing your data and permitting greater

transparency.

3 Reference: https://www.slideshare.net/oddbjorn/Get-to-know-PostgreSQL

Disk buffers

Tables

Kernel disk buffers

Disk Shared

postmaster

(daemon)

postgres

(backend)

postgres

(backend)

postgres

(backend)

Server processes Client

Client

application

Client

libraryqueries and result sets

initial connectionand authentication

https://www.slideshare.net/oddbjorn/Get-to-know-PostgreSQL


Final Report

16

Figure 2-5: Data Sources & Services offered by GeoServer4

31. OpenLayers is an open source JavaScript library for displaying map data in web

browsers. It provides an API for building rich web-based geographic applications similar

to Google Maps and Bing Maps. OpenLayers a free mapping library, is integrated into GeoServer,

making map generation quick and easy.

2.5.2 Satellite data processing

32. Satellite data collection and processing are also performed by using open source software

based on Linux system. Processing follow of satellite data consists of 4 stages as shown in Figure

2-6; (i) data collection, (ii) processing, (iii) visualizing, and (iv) archiving.

33. Each specification of satellite data such as data providing method and file format is

different respectively, according to data provider. WRIS downloads satellite products from each

data provider in an appropriate method and processes/visualizes the dataset for Balochistan.

Data processing and visualizing are performed using open source software such as GDAL5 and

GMT.6

34. Table 2-3 is a list of the data sources of satellite information. Almost of satellite data are

automatically downloaded except evapotranspiration data and Landsat-8 data at the time of

writing. They are on-demand products. RS specialists are still discussing an effective method to

collect them and will fix this issue by the end of December 2016.

4 Reference: https://eatlas.org.au/node/300 5 https://gdal.org 6 http://gmt.soest.hawaii.edu

Vector filesShapefile

DatabasePostGIS, Oracle,

and others

ServersWFS, ArcSDE

Raster dataGeoTiff, NetCDF,

and others

Data Sources Services

Vector filesShapefile, GML2

and others

Styled mapsPNG, GIF,Geotiff

and others

Raster dataGeotiff, ArcGrid

and others

Web Feature Service

Web Map Service

Web Coverage Service

https://eatlas.org.au/node/300

https://gdal.org/

http://gmt.soest.hawaii.edu/


Final Report

17

Figure 2-6: Processing follow of satellite information

Table 2-3: Data source of satellite information

Item Data source

Precipitation (GSMaP)

JAXA GSMaP; https://sharaku.eorc.jaxa.jp/GSMaP/index.htm

Soil Moisture (AMSR2)

GCOM-W/AMSR2 data is supplied by G-Portal at JAXA, https://gportal.jaxa.jp/gpr/.

Solar Radiation (JASMES)

JAXA Satellite Monitoring for Environmental Studies (JASMES); https://kuroshio.eorc.jaxa.jp/JASMES/

Land surface temperature (MODIS)

MODIS product was retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/tools/data-pool/.

Vegetation index (MODIS)

MODIS product was retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/tools/data-pool/.

Evapotranspiration and ET-index

Evapotranspiration products are provided by University of Miyazaki and Nagasaki University under activities of JAXA GCOM-C project.

Land water index (AMSR2)

Land water index is derived from the GCOM-W L1 product provided by JAXA GCOM-W project, which is supplied by G-Portal at JAXA, https://gportal.jaxa.jp/gpr/..

Vegetation index (Landsat-8)

Landsat-8 data produced by the U.S. Geological Survey https://www.usgs.gov/land-resources/nli/landsat

JAXA

NASAUSGS

Otherdistributer

Data Provider

datacollection

Processing(preliminary data)

✓ Subset- Decode- Gridding

✓ Statistical analysis

✓ etc.

Visualizing(secondary data)

✓ Map

✓ Time series graph

✓ etc.

WRISarchiving

https://sharaku.eorc.jaxa.jp/GSMaP/index.htm

https://gportal.jaxa.jp/gpr/

https://kuroshio.eorc.jaxa.jp/JASMES/

https://lpdaac.usgs.gov/tools/data-pool/

https://lpdaac.usgs.gov/tools/data-pool/

https://gportal.jaxa.jp/gpr/

https://www.usgs.gov/land-resources/nli/landsat


Final Report

18

2.6 WRIS Operational Model

35. After several discussions with ADB and the present WRIS stakeholders (i.e. Irrigation &

Agriculture Departments of GoB and PCRWR) along with the RS&GIS Team, it is suggested and

agreed that WRIS shall be hosted at COMSATS Data Centre in Islamabad. COMSATS shall

ensure that the WRIS Server shall remain up and running.

36. To facilitate continuity of WRIS hosting services in the future, PCRWR shall enter into a

formal Service Level Agreement (SLA) with COMSATS and shall also take responsibility for web

hosting payments to COMSATS. This way PCRWR shall also act as a National Level Facilitator.

With this arrangement, WRIS could also be expanded to other provinces in the future. Based on

the above, the operational model for WRIS was decided and presented in Figure 2-7.

Figure 2-7: WRIS Proposed Operations Structure

37. To ensure sustainability at the provincial level and ensuring that all provincial stakeholder

departments keep on contributing to WRIS. Additionally, to ensure that new departments keep on

adding at the provincial level as contributors a provincial level facilitator is also proposed. This

department shall be either Planning and Development (P&D) Department, Information

Technology (IT) Department or any department to be decided by the provincial government.

However, it is recommended that at the provincial level the P&D Department should be given this

role. This is because the P&D Department controls development funds of all departments and

this way all departments shall abide by their commitment of participation.

ID

AD

Stakeholder Departments

PCRWR(National focal)

COMSAT(Server Hosting)

PMD

National

Facilitator

Regional

Administrator

Balochistan

Partner Other users(In Future)

WRIS

Other

Participating

Departments


Final Report

19

38. It is also recommended that a provincial facilitator and the national facilitator should sign

an MOU with the existing and new participating departments to ensure their commitment to

participate in the future.

2.7 WRIS User Access Levels

39. WRIS is designed to have various access levels for different users as shown in Figure 2-8.

There would be 4 types of users to WRIS, these are as follows;

i. Administrators / Facilitators Level:

The user shall be a power user and shall have the right to create, delete, modify and

give access to other users. This role is reserved for all stakeholder departments that

are contributing in WRIS. Every participating department shall have an administrator,

which can create other primary or secondary users, however any participating

department shall only be able to create such users at a respective departmental level

only. For example, Irrigation department shall be an administrator for the Irrigation

Department data and users. The irrigation department can create sub-users (either

primary or secondary levels) but would not be able to create any user in any other

department.

ii. Primary Registered Users:

The primary user shall be the one who will be able to view, download and upload data

in WRIS. This user shall have to be pre-registered. A user belonging to a particular

department shall be a primary user for data belonging to the same department.

iii. Secondary Registered Users:

The secondary level user will be the user that will be able to view and download data

from WRIS. The user also has to be registered as a user. These users will be users

belonging to other contributing departments. For example, the Agriculture department

users shall be secondary level users of the Irrigation Department. These users could

also be registered users such as universities, consultants, researchers, etc.

iv. Public / Unregistered Users:

This will be the basic level user of WRIS and shall only be able to view WRIS Data.

This user doesn’t have to get registered to access and see information on WRIS. This

way any user coming to WRIS website shall be facilitated. This user role shall be given

to the general public; these users shall be able to see data in WARIS.


Final Report

20

Figure 2-8: WRIS User Access Levels and User Privileges


Final Report

21

3 WRIS Institutional Framework

40. The institutional aspects are absolutely necessary to ensure the success of any

information system in a country like Pakistan. The project duration is too short to think about

sustainability. Several initiatives of this sort have been planned and have failed including many in

water sector.

41. The most important was the National Drainage Program (NDP) at a cost of US$ 750 million

by the World Bank, ADB and JBIC – 1997-2004. The institutional reforms failed badly resulting in

failure of the entire project.

42. The P&D Department in provinces is an institution dealing with coordination among

sectors. The success of the BWRDP would also depend on how effective role P&D Balochistan

can play to have effective participation of ID and ACD.

43. Learning from previous examples and after several discussions with stakeholders at the

ADB Workshop in October 2016, it was decided that to make an effective and sustainable

framework for WRIS and a provincial level facilitator would be absolutely necessary.

44. The role of the provincial facilitator shall be to sign Memorandums of Understanding

(MoUs) with the stakeholder (participating) departments making it mandatory for the participating

department to keep dataset belonging to their respective department updated in WRIS. It should

be ensured that the facilitator department is a contributing department. This is necessary because

no department should feel to be under any other development.

45. During the ADB Workshop in Quetta in October 2016, it was discussed that for Balochistan

this role could either be given to P&D Department or IT Department. The decision lies with the

GoB to select either of the departments. However, knowing the governmental structure in

Pakistan, the RS&GIS Team suggest that this role should be given to P&D Department, as all

provincial departments get their project budget approvals from this department and this way the

P&D Department will have an upper edge to compel participating departments to keep their

datasets up to date all the times.

46. It was also decided that each participating department shall be the Primary Level user of

their own department and shall have all the rights to make other users within their own

department. The other departments shall be secondary level users of one department. This way,

all departments shall remain autonomous with respect to their particular datasets and they will

have an MOU for data sharing with a facilitator. This way WRIS sustainability seems to be bitterly

ensured.

47. The same structure could also be replicated in all the provinces if WRIS is to be

implemented at the national level in the future.


Final Report

22

48. For future phases of WRIS a national facilitator is also proposed, the role of this national

facilitator shall sign MOUs with the provincial facilitator departments and other national level

organizations such as PMD, NDMA, etc.

49. The proposed institutional set up is presented in Figure 3-1.

Figure 3-1: Balochistan Institutional Arrangement

WRIS Network at Federal Level - WRIS Facilitator Knowledge InstitutionPCRWR

Federal Data Collecting Institutions IRSA, PMD, WAPDA

WRIS - Balochistan FacilitatorP&D Department

Data Collecting Institutions

ID

Data Collecting Institution

ACD

23

4 Satellite Information layer

4.1 Overview

50. A summary of satellite information is shown in Table 4-1. There are three groups of layers

with map information, time-series graph, and high-resolution map. The map information and the

time-series graph will be provided at Balochistan level and at river/sub-river basin level. The high-

resolution map will be also provided at river/sub-river basin level

51. The agro-meteorological information consists of half-month average or composited

products including precipitation, soil moisture, solar radiation, land surface temperature (LST),

vegetation index, evapotranspiration index (ET-index), and evapotranspiration, which are useful

to monitor of agro-meteorological environment. In addition, heavy precipitation (rain) warning

information based on the occurrence probability of precipitation and daily inundated information

are provided.

Table 4-1: Satellite Information

Item Update Grid size ContentStatus

(collected data period)

Agro-meteorological information layers: map (current and anomaly)

precipitation twice a month 0.1deg mesh(approx. 10x11km)

15 days accumulated Mar 2000 – Sep 2016

soil moisture twice a month 15 days average July 2002 – Sep 2016

solar radiation twice a month 0.05deg mesh(approx. 5x5.5km)

15 days average July 2002 – Sep 2016

Land surface temperature twice a month 15 days average July 2002 – Sep 2016

vegetation index twice a month 250m resolution 15 days composite Feb 2000 – Aug 2016

ET-index twice a month 1km resolution 15 days average 2015 (basin level)

Evapotranspiration (ET)( proposed by RESTEC )

twice a month 1km resolution 15 days accumulated 2015 (basin level)

heavy rain every 1h0.1deg mesh(approx. 10x11km)

Probable Precipitation(1hour, 3hours, 12hours 24hours, 72hours precp.)

Jan 2015 –Sep 2016

Inundation area

(Land water index)once a day land water index (daily) July 2012 – Sep 2016

Agro-meteorological information layers: time series graph (current year and average year)

precipitation twice a month

River basin level and sub-river basin level

15 days accumulated Mar 2000 – Sep 2016

soil moisture twice a month 15 days average July 2002 – Sep 2016

solar radiation twice a month 15 days average July 2002 – Sep 2016

surface temperature twice a month 15 days average July 2002 – Sep 2016

vegetation index twice a month 15 days composite Feb 2000 – Aug 2016

ET-index twice a month 15 days average

Agro-meteorological information layers: high resolution map (current)

Vegetation index (Landsat-8)

Every 16-days(data available onlycloud-free area)

30m mesh for river/sub-river basin

Snap shot 2013 - 2015


Final Report

24

4.2 Agro-meteorological information

4.2.1 Precipitation

52. Overview: GSMaP 7 provided by JAXA/EORC is used for precipitation information.

GSMaP is an hourly global rainfall map available four hours after observation provided by the

JAXA Global Rainfall Watch System. The system is based on the combined microwave-infrared

algorithm using GPM-Core/GMI, TRMM/TMI, GCOM-W/AMSR2, DMSP series SSMIS, NOAA

series AMSU, MetOp series AMSU, and Geostationary IR developed by the GSMaP (Global

Satellite Mapping of Precipitation) project.

(1) Map

53. The WRIS provides two types of maps, the accumulated precipitation and its anomaly

information, every half-month with a 0.1x0.1-degree mesh grid (approx.11km x 10kmin latitude x

longitude direction). The anomaly information for accumulated precipitation is defined as the ratio

of target year to the average year during the same time span. The value of average year is

calculated using archived data for 16 years from April 2000 to March 2016.

54. Figure 4-1 shows an example of an accumulated precipitation map (left) and its anomaly

information map (right). In the accumulated precipitation map, the red color means a large amount

of accumulated precipitation and the blue color means a small amount of it. In the anomaly

information map, green and blue color mean that accumulated precipitation is more than the

average year. The value of 100% is the same as the average year and the value of 1000% is ten

times the average year.

Figure 4-1: Distribution map of accumulated precipitation for half-month Half-month accumulated precipitation (left) for 16-31 Jul. 2015 and its ratio to the average year (right) in Balochistan

7 Reference: GSMaP user guide https://sharaku.eorc.jaxa.jp/GSMaP/guide.html

https://sharaku.eorc.jaxa.jp/GSMaP/guide.html


Final Report

25

(2) Time series graph

55. WRIS also provides time-series graphs of the half-month accumulated precipitation for the

specific river or sub-river basin, which contains 3 lines of the target year, the selected year in the

past and an average year (the averaged value of half-month accumulated precipitation for 16

years). Each line is shown by red, blue and gray, respectively in the graph. So, the user can

understand the target year anomaly using comparisons between the red line and blue or gray

lines. For instance, if the plus discrepancy is large, this means that the target year should be an

unusual year and there is a possibility of having a flood.

Figure 4-2: Time series graph of accumulated precipitation for half-month Sep.2014 - Nov.2015 (blue), Sep.2015 - Nov.2016 (red) and Average Year (gray) of the accumulated precipitation in the Mula River Basin

4.2.2 Soil Moisture

56. Overview: Surface soil moisture, which is derived from satellite observation using a

microwave radiometer, is used. The microwave radiometer observes natural radiation from the

land surface transmitted across the atmosphere at the multi-frequency band. The radiation in the

microwave region varies with the existence of water in the soil, vegetation, and atmosphere. Soil

moisture can be estimated based on the frequency characteristics in the microwave region. WRIS

uses a soil moisture product provided by JAXA8.

57. Notes: Soil moisture is not estimated in the area along the coast. Values tend to have a

high estimate around a water body, and a low estimate in the forest and mountain areas.

8 Reference: http://sharaku.eorc.jaxa.jp/AMSR/doc/alg/13_alg.pdf

https://sharaku.eorc.jaxa.jp/AMSR/doc/alg/13_alg.pdf


Final Report

26

(1) Map

58. WRIS provides two types of maps, surface soil moisture and its anomaly information,

every half-month with a 0.1x0.1-degree mesh grid. The anomaly information for soil moisture is

defined as the ratio of the target year to the average year during the same time span. The value

of the average year is calculated using archived data for 14 years from August 2002 to July 2016.

59. Figure 4-3 shows an example of soil moisture and its anomaly information. In the soil

moisture map, blue color means a high value of the soil moisture content (wet condition) and the

red color means a low value of the soil moisture content (dry condition). In the anomaly information

map, green and blue colors mean wetter than the average year. For example, the blue color

means 300% which is 3 times the average year. And the orange and red colors mean drier than

the average year.

60. Notes: Satellite-based soil moisture values are too high around water areas and too low

in the forest and mountain areas. So, we cannot use the soil moisture information in those areas.

In addition, satellite-based soil moisture values in rice paddy field areas during the planting

season may also be too high since paddy fields are flooded and the soil moisture value in those

areas may not be useful.

Figure 4-3: Distribution map of soil moisture Averaged soil moisture for 1-15 Aug.2015 (left) and its ratio to the average year (right) in Balochistan


61. WRIS provides time-series graphs of the half-month average of the soil moisture for the

specific river or sub-river basin. The time-series graph contains 3 lines of the target year, the

selected year in the past and the average year (the averaged value of soil moisture for 14 years).

Each line is shown by red, blue, and gray, respectively. So, the user can understand the target

year anomaly using comparisons between the red line and blue or gray lines. For instance, if the


Final Report

27

plus discrepancy of the half-month average soil moisture is big, this means that the target year

should be an unusual year and there is a high possibility of having a drought. If the minus

discrepancy is big, this means that the target year should be an unusual year and there is a

possibility of having an inundation caused by heavy rain.

Figure 4-4: Time series graph of soil moisture Sep.2014 - Nov.2015 (blue), Sep.2015 - Nov.2016 (red) and Average Year (gray) of the soil moisture Mula River Basin

4.2.3 Solar Radiation

62. Overview: Solar radiation means the downward short-wave radiation at the land surface,

which is derived from reflectance of visible light observed from Terra/MODIS and Aqua/MODIS.

Solar radiation data provided by JAXA/EORC is available in the WRIS.

(1) Map

63. WRIS provides two types of maps, solar radiation and its anomaly information, with a

0.05x0.05-degree mesh grid. The anomaly information for solar radiation is defined as the ratio

of the target year to the average year during the same time span. The value of the average year

is calculated using archived data for 16 years from April 2000 to March 2016.

64. Figure 4-5 shows an example of solar radiation map (left) and its anomaly information map

(right). In the solar radiation map, red color is a high solar radiation value (400w/m2) and the blue

color is a low solar radiation value (0 w/m2). In the anomaly information map, orange and red color

mean more sunshine than the average year (red = 200%, 2 times the average year) and the green

and blue color is less sunshine.


Final Report

28

Figure 4-5: Distribution map of solar radiation Averaged solar radiation for 1-15 Aug. 2015 (left) and its ratio to the average year (right) in Balochistan


65. WRIS also provides time-series graphs of the half-month average of solar radiation for the

specific river or sub-river basin. The time series graph contains 3 lines of the target year, the

selected year in the past and average year (the averaged value of solar radiation for 16 years).

Each line is shown by red, blue, and gray, respectively. For instance, if the minus discrepancy of

the red line is big, it means an unusual year and there is not enough sunshine.

Figure 4-6: Time series graph of solar radiation Sep.2014 - Nov.2015 (blue), Sep.2015 - Nov.2016 (red) and Average Year (gray) of the solar radiation in Mula River Basin


Final Report

29

4.2.4 Land surface temperature

66. Overview: The Land surface temperature (LST)9 shows how hot the “surface” of the Earth would feel to the touch in a particular location. From a satellite’s point of view, the “surface” is whatever it sees when it looks through the atmosphere to the ground. It could be the soil surface,

the grass on a lawn, the leaves in the canopy of crops and forest, the surface of a water body, or

the roof of a building. Thus, the land surface temperature is not the same as the air temperature

that is included in the daily weather report.

67. The LST is estimated from satellite data observed in the thermal-infrared light. The WRIS

uses the daily average based on observation data by Terra/MODIS and Aqua/MODIS which are

provided by USDA.

68. Notes: This information is provided for a cloud-free area because LST cannot be obtained

in a cloud-covered area.

(1) Map

69. The WRIS provides two types of map, land surface temperature map and its anomaly

information map, every half-month with a 0.05 x 0.05-degree mesh grid. The anomaly information

for LST is defined as the difference of target year from the average year during the same time

span. The value of the average year is calculated using data archived for 14 years from August

2002 to July 2016.

70. Figure 4-7 shows an example of LST and its anomaly information. In the LST map, red

color is a high value of LST (340K) and the blue color is a low value (240K). In the anomaly

information map, orange and red colors mean warmer than the average year (max. +15K) and

green and blue colors mean colder than the average year (min. -15K).

Figure 4-7: Distribution map of land surface temperature (LST) Averaged LST for 1-15 Aug. 2015 (left) and its anomaly from the average year (right) in Balochistan

9 Reference: NASA USGS LP-DAAC https://lpdaac.usgs.gov/products/mod11c1v006/

https://lpdaac.usgs.gov/products/mod11c1v006/


Final Report

30


71. WRIS provides time-series graphs of the half-month average of LST for the specific river

or sub-river basin. The time-series graph contains 3 lines of the target year, the selected year in

the past, and the average year (the averaged value of LST for 16 years). Each line is shown by

red, blue, and gray, respectively. For instance, if the minus discrepancy of the target year is high,

it means an unusual year and it is too cold.

Figure 4-8: Time series graph of Land Surface Temperature (LST) Sep.2014 - Nov.2015 (blue), Sep.2015 - Nov.2016 (red) and Average Year (gray) of the land surface temperature in Mula River Basin

4.2.5 Normalized vegetation index

72. Overview: Normalized Difference Vegetation Index (NDVI) is used as the vegetation

index. The NDVI is a simple graphical indicator to show vegetation activity, and is derived from

satellite data observed at the red visible band (R) and near-infrared band (NIR). Although the

chlorophyll in the plant strongly absorbs visible light for use in photosynthesis, the cell structure

of the plant strongly reflects near-infrared light. The difference between R and NIR increases with

increasing vegetation activity. A high NDVI value shows high vegetation activity; a low NDVI value

shows low vegetation activity. The WRIS uses NDVI product provided USDA

73. Notes: NDVI is a qualitative value. This information is composited together during a

specific period to create a nearly cloud-free image showing maximum greenness because NDVI

cannot be obtained in a cloud-covered area.


Final Report

31

(1) Map

74. WRIS provides two types of maps, NDVI and its anomaly information, every half-month

with a 0.05 x 0.05-degree mesh grid. The anomaly information for NDVI is defined as the

difference of target year form the average year during the same time span. The value of the

average year is calculated using data archived for 16 years from April 2000 to March 2016.

75. Figure 4-9 shows an example of NDVI map and its anomaly information map. The value

of NDVI typically lies on the range from 0 to 1 for the land. The low value of NDVI means less

vegetation and the high value of NDVI means much vegetation and its high activity. If a water

body is there, NDVI may take a minus value. In the anomaly information map, green and blue

color mean higher NDVI than the average year and orange and red color mean lower NDVI than

the average year.

Figure 4-9: Distribution map of Normalized Vegetation Index (NDVI) Composited NDVI for 1-15 Aug. 2015 (left) and its anomaly from the average year (right) in Balochistan


76. WRIS provides time-series graphs of the half-month average of NDVI for the specific river

or sub-river basin. The time-series graph contains 3 lines of the target year, and the selected year

in the past, and the average year (the average value of NDVI for 16 years). Each line is shown

by red, blue, and gray, respectively. For instance, if the minus discrepancy of the red line is big,

it means an unusual year and there will not be good growing conditions.


Final Report

32

Figure 4-10: Time series graph of Normalized Vegetation Index (NDVI) Sep.2014 - Nov.2015 (blue), Sep.2015 - Nov.2016 (red) and Average Year (gray) of the Normalized Vegetation Index in Mula River Basin

4.2.6 ET-index and Evapotranspiration

77. Overview: The evapotranspiration (ET) can be considered as an indicator of field water

availability in the cropland. If enough irrigation water is supplied to cropland field, it will promote

the growth of crops and then will be consumed more as the evapotranspiration from soil surface

and crops. If irrigation water is insufficient for growth of crops, the evapotranspiration is

suppressed.

78. In the inception report, ET-index10 was listed in the WRIS satellite information. ET-index

(ETin x) is a simple graphical indicator to show the degree of evapotranspiration in the cropland

field. In addition, the RS specialists propose the evapotranspiration (ETa ) for the satellite

information. The ETa is a total amount of evapotranspiration from the field.

79. The relationship between ETa and ETin x can be expressed by the following equation: ETa = ETin x × ET0 (1)

80. Where, ET0 is defined as the evapotranspiration from a reference surface, which is a well-

watered hypothetical grass surface. The ET0 represents an index of climatic demand and is

calculated from only weather data. Most of the effects of various meteorological conditions are

incorporated into the ET0 estimate. The evapotranspiration in the actual cropland differs distinctly

from the ET0 as crop status and moisture conditions are different from the reference surface. The

10 Reference: Tasumi, M., Kimura, R., Moriyama, M., Allen, R.G., Fujii, A. (2012). Estimation of global ET-Index from

satellite imagery for water resources management, Proc. of SPIE Vol. 8524, Land Surface Remote Sensing, pp. 85240K1-10

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/8524/85240K/Estimation-of-global-ET-Index-from-satellite-imagery-for-water/10.1117/12.976283.short?SSO=1




Final Report

33

effects of characteristics that distinguish field crops from the grass are integrated into ETin x. The ETa is calculated by multiplying ET0 by ETin x. 81. The ET-index is derived from the satellite remote sensing data and other field data based

on the ET-index algorithm (Tasumi, M el. al., 2013)10 which was developed for global estimation.

This algorithm was adopted by Japan Aerospace Exploration Agency (JAXA) to produce a

research product of GCOM-C satellite. This algorithm can be also applied to the Moderate

Resolution Imaging Spectroradimeter (MODIS) data and other satellite data. The ET-index

product will be provided by University of Miyazaki and Nagasaki University.

82. Notes: The ET-index algorithm was developed to monitor cropland field over the flatland

area. It will need further studies to apply the ET-index algorithm to mountainous area. ET0 was

calculated based on daily meteorological data provided by Global Surface Summary of the Day

(GSOD), NOAA.

83. This information is provided for a cloud-free area because ET-index cannot be obtained

in a cloud-covered area.

(1) Map

84. WRIS will provide a half-month ET-index and actual ET map with approx. 1km mesh grid

for the river basin level. WRIS will also provide their anomaly information (ratio to the average

year) map.

85. Figure 4-11 shows an example of ET-index map (left) and its anomaly information map

(right) in the Mula river basin. In the ET-index map, blue color means high ET-index value which

shows much evapotranspiration. In the anomaly information map, green and blue color mean

higher ET-index than the average year and orange and red color mean lower ET-index than the

average year. Figure 4-12 is the same as Figure 4-11 but this shows evapotranspiration (ETa). 86. Note: There are two areas shown in Figure 4-11 and Figure 4-12. The white line indicates

a Mula river basin, which was made by digitizing basin map shown in Figure 3.3 of Inception

Report prepared by the water resource specialist (TCI). This will be replaced by the correct

boundary data. On the other hand, the black line shows a downstream area of Mula river, where

has an altitude of below 110m. This area corresponds to Figure 4-13.


87. WRIS provides a time-series graph of the half-month average of the ET-index and

evapotranspiration (ETa) in a specific river or sub-river basin. This time-series graph contains the

target year with the previous year and climate value (the average value of the same period

information in several years). Figure 4-13 shows an example of time-series graph of ETa.


Final Report

34

Figure 4-11: Distribution map of ET-index Averaged ET-index (left) for 1-15 Sep. 2015 (left) and its anomaly from the average year (right) in Mula River Bain

Figure 4-12: Distribution map of Evapotranspiration (ETa) Averaged ETa for 1-15 Sep. 2015 (left) and its anomaly from the average year (right) in Mula River Bain


Final Report

35

Figure 4-13: Time series graph of Evapotranspiration (ET) Sep.2010– Nov.2011 (blue), Sep.2014 – Nov.2015 (red), and Average Year (gray) of the Evapotranspiration in the downstream area of Mula river where has an altitude of below 110m.

4.3 Warning information

4.3.1 Heavy precipitation warning based on probable precipitation

88. Overview: A heavy precipitation area is identified by probable precipitation, in which the

precipitation is higher than the probable precipitation with a 5-year return period and a 10-year

return period.

89. Probable precipitation (or rainfall) is a statistical parameter based on hydrological

frequency analysis with historical precipitation data. The probable precipitation is defined as “the theoretically greatest depth of precipitation for a given duration that is physically possible over a

particular drainage area at a certain time of year” (American Meteorological Society, 1959). It is

often used for a design of hydraulic structures. Heavy precipitation may be considered the kingpin

that determines the size of hydraulic structures regulating the flow to and in watersheds, culverts,

sewers, dams, and spillways. In situations in which the risk of the structure's failure must be

minimized, the probable precipitation is considered in determining the size of the structure.

90. Notes: In this system, the probable precipitation is used as the criterion value for heavy

precipitation.

(1) Accumulated precipitation information and Probable precipitation information

91. WRIS provides an accumulated precipitation map and probable precipitation map for 1

hour, 3 hours, 12 hours, 24 hours and 72 hours to be selected by the user with a 0.1 x 0.1 degrees

mesh grid as shown in figures from Figure 4-14 and Figure 4-18. In the accumulated precipitation

map (left), the red color indicates a high volume of accumulated precipitation and the blue color


Final Report

36

indicates a low volume of it. Thus, a red color area may have a chance of facing a flood. In the

probable precipitation map (right), the red color means that the current rain rate is exceeding the

rain rate of 10 years and the yellow color is exceeding the 5-year return period. Thus, since a red

color area has such a heavy precipitation at one time, it may have a chance of facing a flood with

severe damage.

Figure 4-14: Heavy precipitation warning (1 hour) 1 hour accumulated precipitation (left) and Anomaly probability information (right)

Figure 4-15: Heavy precipitation warning (3 hours) 3 hours accumulated precipitation (left) and Anomaly probability information (right)


Final Report

37





Final Report

38

4.3.2 Land water index (LWI)

92. Overview: The Land Water Index (LWI) is a simple graphical indicator to show the degree

of extension of the water surface area, which is based on the polarization characteristics of

microwave emissivity at the Earth’s surface. The LWI is defined as the polarization difference

normalized by the sum of vertical and horizontal polarization. A difference in emissivity on a land

surface between both polarizations is larger at the water surface than at the soil surface. So, the

LWI value becomes larger in the area in which a more widespread water surface is lying.

93. Polarization response characteristics, however, depend on the land cover type. For

example, polarization difference becomes larger at the smooth surface than at the rough surface.

Vegetation will reduce the difference between both polarizations. To minimize such crosstalk

effects and emphasize the wetland area, WRIS also provides the anomaly information of LWI.

94. Notes: The LWI is a qualitative value.

(1) LWI map

95. WRIS provides a daily LWI map with a 0.1 x 0.1 degrees mesh grid. The LWI has a good

correlation with inundated areas. The color legend shows the land water index information which

has a correlation with the inundation area and the blue color is a high index value (0.1) and the

white color is a low index value (0.0). A blue color area that is equal to or more than 0.1 of the

land water index means that it may be an inundated area. Based on our experience, if the water

index value at a point is 0.1, that point is covered with land surface water.

96. Notes: Because a standing water area also has a high ratio with the blue color in the land

water index map, the user should check the time series of the land water index map to remove

standing water areas like a lake, shrimp farm, etc. Even so, there is still the possibility of having

the blue color in the land water index map for rice crop areas during the planting season.

Figure 4-19: Land water Index map (Land Water Index observed on 25 Feb. 2015 and its anomaly from the average year (right) in Balochistan)


Final Report

39

(2) Land water index anomaly information map

97. WRIS also provides a daily land water index anomaly information map with a 0.1 x 0.1

degrees mesh grid. This anomaly information is a comparison between the present index value

and the 10 years’ average value of the same period. The color legend shows the ratio index of

land water and the blue color is a high ratio and the red color is a low ratio. A blue color area

means that it may be an inundated area.

98. Notes: Because a standing water area also has a high ratio with the blue color in the land

water index map, the user should check the time series of the land water index map to remove

standing water areas like a lake, shrimp farm, etc. Even so, there is still the possibility of having

the blue color in the land water index map for rice crop areas during the planting season.

4.4 Agro-meteorological information (high-resolution map)

4.4.1 Vegetation Index (Landsat-8)

99. Overview: Normalized Difference Vegetation Index (NDVI) is used as the vegetation

index. The NDVI is a simple graphical indicator to show vegetation activity, and is derived from

satellite data observed at the red visible band (R) and near-infrared band (NIR). Although the

chlorophyll in the plant strongly absorbs visible light for use in photosynthesis, the cell structure

of the plant strongly reflects near-infrared light. The difference between R and NIR increases with

increasing vegetation activity. A high NDVI value shows high vegetation activity; a low NDVI value

shows low vegetation activity.

100. Notes: NDVI is a qualitative value. This information is provided for a cloud-free area

because NDVI cannot be obtained in a cloud-covered area.

(1) Map

101. WRIS provides snapshot images of NDVI with the resolution of 30m. Figure 4-20 shows

an example of Landsat-8 NDVI map. The value of NDVI typically lies on the range from 0 to 1 for

the land. The low value of NDVI means less vegetation and the high value of NDVI means much

vegetation and its high activity. If a water body is there, NDVI may take a minus value.


Final Report

40

Figure 4-20: Landsat-8 vegetation index (NDVI) Mula river basin, 8 August 2015

41

5 Training Plan in the PPTA

5.1 Overall Planning

102. Overall planning including WRIS part is defined in the report written by Water Resource

Specialist (Dr. Shahid) and this report refers it as the master.

5.2 The detailed contents regarding WRIS

103. From the technical point of view, a certain amount of basic training regarding Remote

Sensing and GIS for a better understanding of WRIS. Table 5-1 are the contents proposed. The

detailed course design will be defined in the collaboration with the Water Resource Specialist.

Table 5-1: Proposed Training Course Name of Trainers RS-GIS team members

(Dr. Fujii, Mr. Nagano and Mr. Ashar) Title Basis of WRIS Course Outline 1 - Introduction of WRIS

2 - WRIS Remote Sensing Data (Theory w/ hands on) 3 - WRIS Ground Observation & Administrative Data 4 - Guidance of WRIS operation 5 - Hands on – demonstrating WRIS operation 6 - Discussion to improve WRIS

Participant Number TBD Duration of course 2 days Type of Training On-job Short-term Training Lead Department Irrigation Department Other Departments Agriculture and Cooperative Department Pre-requisite for Training Adequate Knowledge and Practice in MS Excel, Database

Development, Internet Data Downloading, etc. Required Qualification BSc/MSc in Civil or Agricultural Engineering or Computer

Science or Information Technology


Final Report

42

6 Recommendations for the next step

6.1 Overview

104. Through the activities by WRIS team, the demonstration version of WRIS was developed

and demonstrated at Quetta successfully. For the next steps, the following items should be

considered.

6.2 As for the systems architecture

105. As proposed in this report, considering the process for satellite data, it is ideal that the

centralized WRIS node maintained as a country scale and distributed to each federation since its

data volume is large and it is hard to process by the desktop computing level. However, since

WRIS team recognizes that the end-user of WRIS is GoB and the loan will be processed for them.

So, the detailed discussion among all parties related to satellite data is necessary for ideal

systems design.

6.3 As for the water resource monitoring information

106. Designed WRIS can handle both various satellite-based information and ground-based

information related to water resources. However, the ground-based information is limited to “static” information and it does not contain any “live” monitoring data from ground observation tools such as rain gauges, Automatic Weather Stations and water gauges for groundwater systems. In

particular, considering the limited capacities of satellite-based information to monitor the

groundwater, the input from water gauges are immense to WRIS for Balochistan.

6.4 As for capacity development aspect

107. WRIS is designed as an easy-to-operate system. The end users can handle it with basic

web-based operations. However, it is crucial to understand the detailed aspects of satellite-based

information since it contains a certain amount of limitations compared with the ground-based

information. However, to conduct the intensive lectures related to satellite-based remote sensing

technologies, it is hard to prepare appropriate resources at Balochistan. So, conducting the

training at the country which has advanced technology for satellite-based remote sensing

technology should be considered in the next step.

Documents

Technical Assistance Consultant’s Report...And two river basins of Balochistan, namely, Mula and Zhob river basins were nominated as the pilot areas. Figure 1-1 shows the project