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S. Nativi, P. Mazzetti, L. Bigagli and M. Mancini
Case Study #2:A DSS for Flash Flood
Bringing together Geo-science systems and Decision Makers
Ontology mapping issue
Expanding Horizons 2003 UNIDATA/UCAR
Boulder (CO) 23-27 June 2003
Rationale- Flash-Flood Early Warning estimate is a complex task
requiring a wide set of geospatial data providing information about current and future values of heterogeneus parameters (hydrological and not)
- Most common sourcesRaingauge networks Satellites Weather radars Local Area Models GIS
- Generally speaking, Decision Makers are NOT computer scientists or Hydraulics Engineers.
- A DSS to be effective needs to express results according to Decision-Makers ontology.
The Service-OrientedApproach
GISDatasets
WeatherDatasets
ForecastedDatasets
Geo DATA PROVIDERS
USERCOMMUNITIES
HUMAN INTERACTIONServices
MODEL/INFORMATIONMANAGEMENT
Services
DATA/INFORMATION
CO-OPERATIONServices
PROCESSING/TASKServices
DEVICE RENDERINGServices
Current Situation PresentationFuture Situation Presentation
Single Situation Analysis
Information Resources Synchronising ServicesHeterogeneous Content Consolidation Services
Protocol Adapting Services (to Geo-RI Interfaces)Binding Adapting Services (e.g. Marshalling services)
Hydrological Parameter Generation ServicesDecision Making Parameter Generation Services
Device Adaptation services
The Starting Scenario: main issues
Organization:- Data sources were managed by many different data providers;Technology:- Data were accessed through different communications protocols and they
were encoded in proprietary formats;Content:- No specific pre-processing for flash flood early warning was available;Semantic:- Information was expressed according to data providers (scientists,
researchers,…) or hydrologists conceptual models;Presentation:- Data were visualized through legacy applications that were not
specifically designed for flash flood early warning problem;
The Starting Scenario: overview
Decision-makers can access a lot of information, but they can utilize only a small part of them, effectively.
Our approach for a DSSThe DSS is made up of two maincomponents.
ExpertSystem
Decision Maker
Raingauge Network(Measured precipitation)
LAM(Forecasted precipitation)
!
Ancillary Data(GIS layers)
MARTE network
RAMS Model
Tuscany RegionGIS
PresentationSystem
Enriched and ContextualisedSituation Rendering
Presentation and Graphical Enrichment Info
SituationReport
The first component act as an ExpertSystem:
1. It extracts useful information from data sources;
2. It integrates and processes the information (according to a specificmodel);
3. It provides a “standard” and “open” situation report.
A second component acts as a PresentationSystem:
1. It carries out proper presentation of the situation report.
2. It enriches the presentation with useful graphical and presentation features.
3. It contextualises the rendering according to the client device configuration
An operational implementation:the MIMÌ System
ExpertSystem
Decision Maker
Raingauge Network(Measured precipitation)
LAM(Forecasted precipitation)
!
Ancillary Data(GIS layers)
MARTE network
RAMS Model
Tuscany RegionGIS
PortalSystem
Enriched and ContextualisedSituation Rendering
Presentation and Graphical Enrichment Info
SituationReport
Decision Maker
MARTE network
RAMS model
???
Ancillary Data(GIS layers)
-MARTE system: a ground-based sensors network providing data every 15/30 minutes, in a legacy format. It is managed by the National Hydrographic Service.
-RAMS system: a Local Area Model providing forecasted precipitation data for the Tuscany Region. It works out one map per hour within 48 hours forecasting time. Maps are provided in legacy binary format along with a metadata text file. It is managed by the Regional Laboratory for Applied Meteorology.
The three Ontology Views
Expert System
Decision-makersOntology
HydrologyOntology
Hydrogeologicparameterextraction
Decision-makingparameterextraction
Domain specifc
Ontologies
RAMS forecastedprecipitation data
MARTE measuredprecipitation data
other data
DSSClient
Application
Domain OntologyTo be effective the system needs to express results according tothe Decision-Makers ontology.
Decision Maker
Portal
SituationReport
!
Sub-basinsection status
AlarmThreshold
Generally speaking, Decision Makers are NOT computer scientists or Hydraulics Engineers
Decision Maker
Portal
??
AntecedentMoisture Content
Rainfall Event shape
0
20
40
60
80
100
120
140
160
180
200
East West North
4th Qtr
3rd Qtr
2nd Qtr
1st Qtr
EffectiveNot effective
The Ontology Integration issue
Hydrology Conceptual Model
(Simplified View)
(Simplified View)
DSS ConceptualModel
Hydrogeological Model
An Hydrogeological Model developed by the Polytechnic of Milan is the core component of the expert system.
It defines the procedures to extract information from the input data and generate the hydrological outputs which are mapped to the DM’s concepts(Conceptual Model).
- Briefly, the expert system tasks are:
- To update the situation (sub-basins critical sections status) each time a measured map(from MARTE) or a forecasted map (from RAMS LAM) is available;
- To aggregate the rainfall on each sub-basin;- For each sub-basin, to check the existence of a rainfall event according to the value of the
aggregated rainfall;- For sections with active events, to compute and compare the cumulated rainfall with a
threshold, based on hydrological parameters;- To manage sectionstatus, each section is in one of three possible status (no event, event
without warning, event with warning);- To achieve the model output: a summary of the situation (sections status, rainfall series,…)
Computational Architecture- Component-based approach;- Multiplatform approach;
- Extensible solution;- Distributed solution
Middleware
ClientApplication
Info/DataResources
Expert System PresentationAdapter
ContentCollector
Presentation System
MIMÌ Technology baseline
Adopted technologies:
- Java Platform (J2SE, J2EE, J2ME, Java Web Start);- Web Service technology
– XML/XSD; XSLT;– SOAP/HTTP(S); HTTP/HTTPS;– WSDL;
- SVG;
DSS Implementation
Expert System
Raingauge Network Data(Real Time Data)
Local Area Model(Forecasting Data)
Hydrological Expert System(Situation Information Generator)
Web Server(Situation Information Publisher)
Thick Client Application(Expert Decision-makers)
Presentation System
LegacyData
LegacyData
GIS Data(Time-invariant Data)
LegacyData
Intranet
Internet
MARTE System RAMS System National Authority GISHydrographicNational Centre
Tuscany RegionalMeteo-Laboratory
National Arno BasinAuthority
Hydrogeological ModelPolytechnic of Milan
Web Servers(Presentation Information
Publishers: e.g. River Network, DEM, etc.)
XSDXML
XSDXML
XSDXML
XSDXML
ContestualisedPresentation
Server
Thin Client Application(Decision-makers)
XSDXML SVG
HTML
Internet
- Expert System– Hydrological Model
Implementation– Ontology Mapper
- Presentation System– Content Collector– Contestualised
Presentation Adapter
- Client Application– Thick Client– Thin Client– Mobile Client
DSS Implementation
- Expert System– Hydrological Model
Implementation– Ontology Mapper
- Presentation System– Content Collector– Contestualised
Presentation Adapter
- Client Application– Thick Client– Thin Client– Mobile Client
Expert System
Raingauge Network Data(Real Time Data)
Local Area Model(Forecasting Data)
Hydrological Expert System(Situation Information Generator)
Web Server(Situation Information Publisher)
Thick Client Application(Expert Decision-makers)
Presentation System
LegacyData
LegacyData
GIS Data(Time-invariant Data)
LegacyData
Intranet
Internet
MARTE System RAMS System National Authority GISHydrographicNational Centre
Tuscany RegionalMeteo-Laboratory
National Arno BasinAuthority
Hydrogeological ModelPolytechnic of Milan
Web Servers(Presentation Information
Publishers: e.g. River Network, DEM, etc.)
XSDXML
XSDXML
XSDXML
XSDXML
ContestualisedPresentation
Server
Thin Client Application(Decision-makers)
XSDXML SVG
HTML
Internet
MIMÌ Human-System Interaction Model
The Java-based thick client is specifically designed for decision-makers showing DMs ontology information in a user friendlymanner.The GUI is based on typical use-cases defined in collaboration withthe final users;
In particular:
-Only the sections status for a given time is normally visible;-User can select the reference time choosing to view the measuredsituation or one of the forecasted situations;-Uuser can inspect a specific section obtaining charts of cumulatedand aggregated rainfall
Thick Client
2) View the real-time measured situation
Its satus isreported by the shape and the
colour
CriticalSections
Thick Client3) Select and view a real-time forecasted
situation
Just select oneand the
forecasetdscenario isdiplayed
AvailableForecastedSituations
Thick Client4) Inspect a basin section for a potentially
dangerous forecasted situationAggregated
Rainfall
Threshold
CumulatedRainfall
Green = forecastedBlue = measured
Cell-Phone Client
XHTML enabledDevice
The nextforecastedsituation
At the Sub-basin level
The presentsituation
At the Sub-basin level
S. Nativi, P. Mazzetti, L. Bigagli and G. Villoresi
University of Florenceand IMAA-CNR
The Presentation System
To leverage interoperability and extend the DSS
Decoupling Content from Presentation Info
Towards the Cooperative work
Expanding Horizons 2003 UNIDATA/UCAR
Boulder (CO) 23-27 June 2003
To decouple Contentand Presentation
information
Expert System
Raingauge Network Data(Real Time Data)
Local Area Model(Forecasting Data)
Hydrological Expert System(Situation Information Generator)
Web Server(Situation Information Publisher)
Thick Client Application(Expert Decision-makers)
Presentation System
LegacyData
LegacyData
GIS Data(Time-invariant Data)
LegacyData
Intranet
Internet
MARTE System RAMS System National Authority GISHydrographicNational Centre
Tuscany RegionalMeteo-Laboratory
National Arno BasinAuthority
Hydrogeological ModelPolytechnic of Milan
Web Servers(Presentation Information
Providers: e.g. River Network, DEM, etc.)
XSDXML
XSDXML
XSDXML
XSDXML
ContestualisedPresentation
Server
Thin ClientApplication Mobile Client Application
(Decision-makers)
Internet
XSDXML
Content Information
Content Information
Presentation Information
Presentation Information
Device-dependedRendering Expert System
Thick Client Application(Expert Decision-makers)
Portal System
Web Servers
ContestualisedPresentation
Server
Internet
XSDXML
XSDXML
XSDXML
XSDXML
XSDXML
HTMLSVG XSDXML
Tag-language Java Object Internet
Collector
Inf
or
ma
tio
n R
es
ou
rc
es
Cl
ien
t A
pp
lic
ati
on
s
Adapter
XSDXML
Thin ClientApplication Mobile Client Application
(Decision-makers)
•Sub-basin Situations•Raingauges Situations
•Basin critical sectionsMetadata
•Basin DEM
•Basin River Network
Device-dependedRendering Expert System
Thick Client Application(Expert Decision-makers)
Portal System
Web Servers
ContestualisedPresentation
Server
Internet
XSDXML
XSDXML
XSDXML
XSDXML
XSDXML
HTMLSVG XSDXML
Tag-language Java Object Internet
Collector
Inf
or
ma
tio
n R
es
ou
rc
es
Cl
ien
t A
pp
lic
ati
on
s
Adapter
XSDXML
Thin ClientApplication Mobile Client Application
(Decision-makers)
Content
Info Assessment
Content
Info Assessment
Content + Presentation
Info Rendering
Content + Presentation
Info Rendering
ComputationalComponents
Content
Info
Thick Client Application(Expert Decision-makers)
XSDXML
XSDXML
Internet
Collector
XSDXML
DeviceConfiguration
ConsolidatedReport
SVG <TAG>HTML
J
XSDXML
XSDXML
Cl
ien
t A
pp
lic
ati
on
s P
or
ta
l S
ys
te
m
Adapter
XSLT
SVG
SVG
Presenta
tion Inf
o
Web Service HTTP Service
XSDXML
XSLT
Thin ClientApplication Mobile Client Application
(Decision-makers)
Sub-basin Situations
RaingaugesSituations
Basin critical sectionsMetadata
Basin DEM
Basin River Network
Implemented Presentation Services
- Global Situation Service– The presentation of the present and future situations for all the
basin sections
- aSituation Service– The presentation of a given situation for all the basin sections
- aSection Evolution Service– The presentation of the present and future situations for a
given basin section
Only Thick and Thin Clients
Only Thick and Thin Clients
All ClientsAll Clients
All ClientsAll Clients
Global SituationService
Thick Client Application(Expert Decision-makers)
Thin Client Application(Decision-makers)
XSDXML
XSDXML
Internet
GlobalSituationCollector
XSDXML
DeviceConfiguration
GlobalReport
XSDXML
Cli
en
t A
pp
lic
ati
on
s P
or
tal
Sy
ste
m
Thick ClientAdapterXSLT
Thin ClientAdapterXSLT
XSDXML
SVG SVG
SVGHTML
Web Service HTTP Service
XSDXML
XSLT
PresentationProxy
Thin Clients need an HTTP-based
Presentation Proxy
Demo Components Deployment
Expert Proxy(TOMCAT)
port: 8080
Client Device
PresentationProxy
(TOMCAT)port: 8080
PresentationServerport: 8004
Internet
Adapter ServiceProxy
Internet Collector
Web ServiceCollector
Application
SOAP message HTTP/GET/POST Message
Web Browser
AdapterWeb Service
AdapterApplication
Internet
SituationReportServlet
SituationReportCollector
SituationReportServiceManager
Expert SystemProxy
Internet
Expert SystemApplication
Web Services
ServerWeb Services
Server
Servlet Server
Servlet Server
Servlet Server
Servlet Server
Any Device
Web BrowserAny Device
Web Browser
Low-level Access Services- Web Service
– SOAP Message– XML/XSD
- HTTP Service– HTTP GET/POST Message
Operative System
Servlet Engine
Internet
Web ServiceProxy
Internet
SOAP Engine
Web Service AdapterApplication
SOAP message HTTP/GET/POST Message
Web Browser
Mobile Clients Demo
- Demo: aSituationService
- Client application is any device Web Browser- Presentations are personalised for:
– PDA– Smart Phone– Cellular Phone
Exercises
1. Use a general purpose SOAP Client to access the Collector and Adapter web services
• http://localhost:8004/glue/src.wsdl• http://localhost:8004/glue/srsm.wsdl
2. Add a Presentation Resource (SVG fragment)• The Tuscany Region boundary
![Flash Flood Risk Estimation of Wadi Yutum (Southern Jordan ...tional for flash flood risk assessment. El-Maghraby et al. [54] employed morphometric analysis to evaluate the flash flood](https://img.pdfslide.us/doc/110x75/5f63b02dfde39d7cc462b8d3/flash-flood-risk-estimation-of-wadi-yutum-southern-jordan-tional-for-flash.jpg)
