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Introduction to Hydroinformatics - presentation for UNESCO-IHE students (v16)

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Introduction to Hydroinformatics - presentation for UNESCO-IHE students.

Text of Introduction to Hydroinformatics - presentation for UNESCO-IHE students (v16)

HydroinformaticsModelling and information systems for integrated water management

Programmewithadifference

Dr. Dimitri P. Solomatine Professor of Hydroinformatics1

WaterWater is an important constituent of the meteorological cycle Pressure on water resources Consequences of climate change Need for conservation and sustainability of potable water resources Need for better information and predictions - to understand and to manage water

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Managing water resourceswater-related decisions is difficult to test on large-scale experiments, hence importance of computer-based

modelling and forecasting

solutions

control of water resources must be based on optimal management of water needs a lot of data and information from various sources need for Computer-based modelling, Information and Communication Technology (ICT) tools

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Hydroinformaticsmodelling, information and communication technology, computer sciences applied to problems of aquatic environment with the purpose of proper management

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Q Q 2 h + gA gAS o + gAS f = 0 + t x A x

Modelling

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ModellingComputer-based model isa simplified description of reality an encapsulation of knowledge about a particular physical or social process in electronic form

Hydroinformatics integrates

data, models, people

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Generations of modelling: a bit of history1. Computers used as calculation devices of analytical expressions 1950sno friendly interfaces

2. Mainframe computers used to solve differential equations numerically 1960-70scustom-built models

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Generations of modelling3. Production of modelling packages/systems for wide class of problems 1980-90sdeveloped user interfaces production lines of models (modelling shells) refinement of solution methods promotion of standards more clients more profits more enhancements

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Generations of modelling4. Mass production of modelling systems for PCs 1990sprovision of products, not projects access by non-specialists high standards of robustness and consistency ease of use via the sophisticated user interfaces involvement of software engineering and IT specialists integration with supporting tools and facilities

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Generations of modelling. The fifth generation as we understand it now5. Hydroinformatics systems 1990sModelling as a central interface betweendomain data (monitoring stations, weather radars, remote sensing) and human decision maker

Domain knowledge encapsulators Integration of various types of models Alternative, non-process-based modelling paradigms (data-driven modelling) Potential of integration with artificial intelligence 5th generation modelling = CH AND AI (but this has not happen yet)D.P. Solomatine. Introduction to Hydroinformatics

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Hydroinformatics system: typical architectureUser interface

Judgement enginesDecision support systems for management

Fact enginesPhysically-based models Data-driven models

Data, information, knowledge

Knowledge inference enginesKnowledge-base systems

Observations, Communication

Real worldD.P. Solomatine. Introduction to Hydroinformatics

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Position of HydroinformaticsInstrumentation ICT Computing AI Modelling Water Engineering Hydrology

Systems sciences, Optimisation Management

Environment

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Encapsulation of knowledge related to waterTacit (implicit) knowledge embedded within a person Words, texts, imagesprinted stored in electronic media

Mathematical modelsformulas algorithms algorithms encapsulated in computer programs (software)

Integrated systems encapsulating all of above

Hydroinformatics systems

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Hydroinformatics system: flow of informationData Models Knowledge Decisions Decision support Earth observation, Numerical Weather monitoring Prediction Models Data modelling, Access to integration with modelling hydrologic and results hydraulic models

Map of flood probability

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Hydroinformatics systems in flood managementData Models Knowledge Decisions

Map of flood probability

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Models are indispensable in dealing with floods

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Sobek modelling software (Delft Hydraulics) in designing urban master planvisulaizing potential floodings:

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Hydroinformatics systems for flood warning: MIKE FloodWatchMIKE Flood Watch (Danish Hydraulic Institute), a decision support system for real-time flood forecasting:advanced time series data base MIKE 11, for hydrodynamic modeling MIKE 11 FF, real-time forecasting system, ArcView, Geographical Information System (GIS)

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Hydroinformatics systems for flood warning: MIKE FloodWatch

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Flood warning systems: Piemonte case study

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Architecture of a hydroinformatics system for flood warning in Athens, Greece (IHE project)Meteorological Models Hydrologic/ Hydraulic Models Connector to Hydrologic/ Hydraulic Model

Trigger

Decision Tree Module

GIS Module

DSS MAIN INTERFACE Internet, telephone lines

Database Module

Connector to Telemetric data storage Telemetric Data

Communication Module (Email, FTP)

Post flood evaluation and documentation module

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Flood warning system interface, developed by Hydroinformatics participant

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Warragamba Dam, AustraliaWarragamba Dam - 65 km west of Sydney in the Burragorang Valleyprovides the major water supply for Sydney Warragamba River flows through a 300-600 m wide gorge, about 100 m deep before opening out into a large valley. This allows a relatively short and high dam to impound a vast quantity of water.

A dam break of the Warragamba Dam would be a major disaster. SOBEK (Delft Hydraulics) software was used for simulation Introduction to Hydroinformatics D.P. Solomatine.

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Warragamba Dam, Australia Simulation of the dam break with SOBEK, Delft HydraulicsThe animation shows the simulation results. They may be used for disaster management, evacuation planning, flood damage assessment, urban planning

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Use of 2-dimensional modelling in Jamuna bridge project, Bangladeshconstruction of a 4 km bridge and several river training works for guiding the flow to pass under the bridge Danish Hydraulic Institute (DHI) carried out a study of the river morphology to enable the contractor to take the preventive or remedial measures (MIKE 21 modelling system was used)

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Eutrophication modelling of a tidal lagoon in Bali, Indonesia

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Example: Eutrophication modelling of a tidal lagoon in Bali, IndonesiaTurtle Island is an enlargement of the existing Serangan Island at the entrance to Benoa Bay; three artificial lagoons are planned for leisure crafts and beaches at the order of Penta Ocean Construction Co. LTD, DHI performed modelling for water quality in terms of rooted benthic vegetation, macroalgae, concentrations of phytoplankton, nutrients and oxygen MIKE 21 EU (eutrophication) model was used; various scenarios were analysed. The concentration field of Chlorophyll is shown; the area is strongly influenced by tidal flushing and dries out during each tidal cycleD.P. Solomatine. Introduction to Hydroinformatics

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Example of Integrated Modelling: a Case Study for Sonso Lake, Colombia(Masters study of Mr. Carlos Velez performed together with the experts from Delft Hydraulics)

Problem: 70% of the surface area of this shallow lake is covered by an invasive macrophite Water Hyacinth Causes:Nutrients pollution from agricultural use of land Lack of sustainable management of the lake

Methodology:Integrated modelling of Water Hyacinth growth (ecological water flow model)

Results: the developed model makes it possible to analyse alternatives to manage the Water Hyacinth infestation D.P. Solomatine. Introduction to Hydroinformatics

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Ecosystem Integrated Model: a Case Study for Sonso Lake, ColombiaDeveloped by Carlos Velez. Supervisors: A. Mynett, L. Postma, A. v. Griensven Solar Radiation 2 Sobek Rural Sobek Rural 1 DELWAQ 1D2D Hydro dynamic Water Quality 3 5 6 5 7 Velocity Water Depth Flow 4 6 8WATER SURFACE

16 Norg Porg 14 12 15 13 Water Hyacinth

Water Volume

9 10 NH4 11 PO4 NO3 9

Ecosystem

Organic Matter Settled Water Hyacinth Model (coded using SOBEK RURAL Open Process Library)PROCESSES 1. Input / Output 2. Rainfall 3. Evapotransp

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