Modelling_Hydroinformatics.pdf

8/10/2019 Modelling_Hydroinformatics.pdf

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MODELLING IN WATER

MANAGEMENT&

HYDROINFORMATICS

Content

Introduction Hydroinformatics (HIS) Historical context of HIS Definition of Hydroinformatics Influence of HW and SW on development of HIS Simulation models cornerstone of HIS Data for HIS Information systems and HIS Practical HIS - role or consultant Future Trends

Prague Flood in 2002


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rague oo pro ec on 8/2002 mobile flood control

Prague Flood protection 8/2002 mobile flood control

Prague 2002 - modellingWater Levels

2D flood model of Prague - flood 8 / 2002


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Teoretical fundaments ofHydroinformatics

Hydraulics (physics of aquatic systems) long tradition fundamental scientific discipline

Hydrology technological discipline Computational hydraulics (Abbott - 1969)

Def.: scientific discipline integrating hydraulics,numerical mathematics, numerical methods andprogramming into unified framework

Informatics Ecology, Biology, Chemistry

Goals of Hydroinformatics To provide predictive tools for analysis of aquatic

component of living environment To verify effects of interventions into ecosystems using if-

then scenarios To integrate protection of living environment in the

engineering business To provide managerial tools for complex aquatic systems To optimize investment policy To offer training of-line systems (operational games) To support other technological areas (e.g. GIS, Expert

systems, DSS) To provide foundation for legislations To optimize engineering design work

Hydroinformatic system (HIS)Set of interconnected tools acting as one unified

system and comprising substantial volume of

information and knowledge in digital form originatingmainly from hydraulics hydrology results of applied research area of law and legislation area of social and economic espects protection of environment (EIA) informatics data collection and monitoring

Hydroinformatic System (HIS) = Decision Support System (DSS)


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User

Information systemsGeografic

information

systems

Databases Knowledge

bases

Pollutionsources

Models

Transportprocesses

Waterquality

Ecology

Decision Support systems

Socio-economicimpacts

Impact ofenvironment

Strategicscenarios

Userinterface

(GUI)

Hydroinformatic System (HIS)

Conditions for Formation ofHydroinformatics

Development of computational hydraulics-simulation models

Foundation of information technology Trend for management of complex systems Development of data acquisition, monitoring and

methods for data collection and analysis Need for communication among distinct scientific

and engineering disciplines Need for presentation technologies (animations)

Impacts of personalities (Abbott, Cunge, Ionescu,Price, aj.) Effects of institutions (NHL, DHI, DH, Hr, IAHR,

IAHS)

Conditions for Formation ofHydroinformatics

Dynamics of

economical processes

New

technologies

Protection ofliving environment

Restrictedfinancialsources

Managementand

planning in urbandrainagearea

Dynamics of

economical processes

New

technologies

Protection ofliving environment

Restrictedfinancialsources

Management

and planning in

Water utilities


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Historical development of HIC Hardware development personal computers

1980 - IBM PC .. ..

2005 Intel = 2 Core processors

Software development operational systems (unification) application software -(text editors, tabular processors, graphical

modules) specialized SW - simulation models standard databases connected to GUI existence systm grafick podpory

Increasing use of simulation models in practicalengineering life

Historical development of HIC

Generations of simulation tools

1.generation - calculation of formulas - analog

2.generation - one-off models 60s, big labs

3.generation more general matematical models 70s, variability ofinputs

4.generation - menu-driven system technology based on PC, DOS,weak graphics, low standardization 80s 90s

5.generation - today UNIX x WINDOWS, DB, quality graphics, GIS,server client

6. generation - future (KBS, UI), RTC, max safety, ?

Simulation model

the Core of HIS system

RDBMSRDBMS


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Conceptual Models

Deterministic Models

Stochastic models

Simulation - modelling

Application of concept, that substitute for natural process ( nonlinearreservoir)

Mathematical solution of differential equations describing the natural

process (hydrodynamic equations, continuity equation)

Based on solution of natural processes by means of statistical

methods

Models are tools able to simulate long term behaviour of physical

system by means of interpretation of dominant proccesses

digital copy of a physical system (1, 2, 3D)

simulation of physical processes important for the for

the studied phenomena (non stationarity, dynamics, continuity)

ForecastsForecasts::WhatWhat happenshappens,, whenwhen..............

Deterministic Simulation Models

Q

xb

H

xx+ = 00

2

gAix

ygA

x

A

Q

t

Q=++

+ EgAi

the same response to outer impuls like in nature

difficult to obtain input

data

QQ

Q

hh

hh

Simulation Model like virtual reality


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Simulation modelsDefinition

program (digital code) model (tool for user able to simulate reality) matematical model x physical model

simulationtool

Model build :

1. problem definition 2. schematization (space and time) 3. governing equations 4. dependend, independent variables 5. empirical and complementary formula 6. algoritmization of task 7. boundary and initial conditions 8. calibration 9. verification 10. simulation

Modular structure of simulation model

Water Quality

Sediment Transport

Hydrodynamics

Rainfall-Runoff

Advection-Dispersion

Flood Forecasting

River Catchment

Precipitation

Receiving water

i

t

t

Q

Rainfall-runoff processes


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Rainfall

Algorithm

Runoff from

catchment

Rainfall

Lossmodel

RainfallExcess

Routingmodel

Runoff fromcatchment

Evapo-transpiration

Interception Storage

Unsaturated Zone

Ground watertransfers

Depression Storage

Runoff fromcatchment

Saturated Zone

CatchmentChannelStorage

precipitation

Black Box models Physical process models

Loss-routing models

Rainfall-Runoff Processes

System descriptionLooped network (1D, 1D+)2D horizontal mesh

Hydraulic phenomenaBackwater effectsFlood RoutingWave propagationEnergy dissipation

Hydraulic Structures Weirs Culverts Bridges

Regulation Gates Pumping Control Structures Dambreak Failures

Hydrodynamic Processes

Hydroinformaticsand

Data

RDBMSRDBMS


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Need of information for optimalmanagement in complex systems

Dealing with information is one of the key factors for mastering

of problems in complex systems. (Ratzek, 1992)

"Since post-industrial organisations will be faced withincreasing environmental complexity and turbulence,organisations need to process information and make

decisions will be substantially increased", (Huber, 1984).

Information technology is the basic tool, used by organizations,

to make forecasts, cope with the environmental changes and to

adjust to them (Malone & Rockart, 1993)

Current state of data

Increasing demandon integrated solution Impactof Information Technology Focus on living environment

Increasing demand on data (quality and quantity) Increase in cost for data collection, update and archiving Need for quick and cheapdata exchange Demand on continual data update and maintenance

Changes in data reguirements

Change in approach to water related problems

Current state of data sources

Large spectrum and volume of data Only a part of the data in a digital form (IS) Variousspecialized information systems Various proprietary data structures, formats, data guality Communications using export/import routines

Data for Simulation model Structural data

Pipe (X,Y,Z, length, DN, roughness, slope, ) Manhole (X,Y,Z1,Z2, diameter, inlet, outlet)

Structures (pump, CSO, basin, gates, ) Catchment areas (size, slope, impermeability, inhabitnts)

Processes Data (time series) Water consumption data Flow data (v, h, Q) Water quality data (O2, NH4, NO3, P) Precipitation (i)

Operational data Gates manipulation, pump QH,

Parameters in model


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topological data for the river channel(cross sections, objects)

topological data for the river inundation(inundation profiles, objects in inundations photo, DMT)

hydrological and hydraulic data(roughness, Q-H curves, manipulation rules for the objects,

precipitaion, water level and flow time series)

Data needs for simulation model

flooding

water quality

sediment transport

dam break

Data requirements are stronglyinfluenced by the type of simulation:

Additional data sources

-750000 -745000 -740000 -735000

-1054000

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1

- 7 5 00 0 0 00 0 - 74 5 0 00 0 0 0 - 740000000-1060000000

-1058000000

-1056000000

-1054000000

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-1050000000

-1048000000

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Untitled

1-1-1990 16-5-1991 27-9-1992 9-2-1994 24-6-1995 5-11-1996 20-3-1998

0.0

5.0

10.0

15.0

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25.0

30.0

35.0

[m] Flags

355 372445

513 475523 534 427419

0

100

200

300

400

500

199019911992199319941995199619971998

h[mm]

Users of data

Private consulting companies

Simulation

model

GIS, CAD

RDBMS

Specialised

tools

GIS

CAD

Owners

RDBMS

Governmental

officesRDBMS

Researchorganisations

Simulation

models

Specialised

tools

Water utilities

GIS

CAD RDBMS


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kan_pkt

kanal_pkt_MS

kak_lin

kak_pkt

kak_lin

kak_pkt

kan_lin

kan_pkt

kak_lin

kan_lin

kak_pkt

kan_pkt

Ms_No

weir

kan_pkt

kan_lin

FROM kanal_pkt_MS

TO kan_pkt

kanal_pkt_MS

kan_pkt

kan_pkt

kan_lin

kanal_pkt_MS

kan_lin

kan_pkt

kan_lin

kan_pkt

NEWMANHOLE

kan_lin weir

kak_weir

kak_weir

kanal_pkt_MS

kan_pkt

kanal_pkt_MS

kan_pkt

kak_weir

go to Eryl'steam

go to GISteamDATABASEcorrected

/PROGRAMSOFIYSKAVODA/

kan_lin

kan_pkt

HORISONTAL, VERTICAL

PLANANDPHOTO

INSIMULATIONM ODEL

USETHEMES

SAVEAS

CUTTHEME

COPYFIELDS

-FILLFIELD

JOINTABLES

WITHDATA"B"

INGISTHEMES

ENTERDATA"A"FORMANHOLE

GIS\U+0442\U+0435\U+043C\U+0438:HASRIGHTLOCATION

MOVEMANHOLES

SITUATIONPLANIN CADFORMAT

FROM MANHOLESURVEY

EXCELLTABLECREATETHEME

FORCOLLECTORKAKACH

GISTHEMES

YES

NODOESMANHOLE

VERIFICATION

EXISTIN GIS IN GIS THEMES

CREATE

VERIFICATION

DOESMANHOLE

NO

YES

VERIFICATIONOFNUMBERS

CUTTHEME

SAVEAS

FROM MANHOLESURVEY

EXCELLTABLE

FROMMANHOLE SURVEY

FROMMANHOLE SURVEY

SITUATIONPLANIN CADFORMAT

FROM MANHOLESURVEY

EXCELLTABLE

SAVEAS

CUTTHEME

CORRECTLOCATION

OFMANHOLES

INGISTHEMES

RUNAVENUESCRIPTS

TRANSFERMEASURED

DATAINGI STHEMES

INGISTHEMES

CORRECTPROBLEMS

RUNAVENUESCRIPTS

connectivity checks

aqva base

DOESMANHOLE

VERIFICATION

HASRIGHTLOCATION

YES

NO

START

1CONTRACT

MS-GISTRANSFER

2 CONTRACT

MS-GISTRANSFER

START

2 CONTRACT

INDATABASE

/PROGRAMSOFIYSKAVODA/

FILLDATAFROM

Contractordata

Single dataevaluation

DataConnectivity

check

Field datacheck survey

GIS dataVerification

Simulationmodelling

Other sourcedata

Data manipulation aspect

Integration of data (GO HM Prahy)

Integration of data (Sofia DAP)


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Data volumes Sewer system - LIDS, 20M

Digital reference map of Prague, ArcInfo , 100M

Digital map of Prague, DGN, 48M

Ortophoto map of Prague, JPG, 77M, DMT of Prague (10x10 m, 30 cm ) , 240M

Cartographic map of Prague, TIF, 80M

Groundwater levels, grid 30m x 30 m, MGE, 20M

9 years historical rainfall serie in 7 sites, ASCII, 5M

Development plans

Prague land register

maps of vegetation, protection zones

Measurement data (19i, 19Q, 25H)

Hydroprojekt,a.s.

Data volumes

Rainfall data - Gandalf, 500M

Matematical model of sewer system, MOUSE , 5000M

Matematical model of rivers, MIKE11, 2000M

Catchment data, PE, impervious areas, Mapinfo, 500M

Simulation results MOUSE, MikeView, 20000M

Simulation results MIKE11, MikeView, 10000M

Interpretation of data

Sewer data ?

Population data ? +

X

X

Hydraulic data ?

Adristic sea

Baltic sea

?

?

Designmethods

Evaluationmethods?


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X1,Y1

X2,Y2X1,Y1

X2,Y2

X1,Y1

X1,Y1

X1,Y1

L2 X2,Y2

L1

X1,Y1


structurestopology

Relative distancesMeasurements


start

SCADA

ModelsInspections

GISCAD

Integration and openness


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Unproductive, time consuming work bringing higher probability of random

or systematic errors and difficulties in a long term data maintanance.

! WRONG DECISIONS !

Data communication problems

Data formats - vektor x raster data, ASCII x BIN x RDB,Data structure time series, summer/winter time, objects

Data conversions - topology of network, coordinate systems, unitsWork with data data volumes, data management, changes, updateGeneral topics quality of source data, costs, units, formats, SW a

HW errors

PODBABARUZYNE

LIBUS

UHRINEVES

KLEMENTINUM KARLOV

BRANIK

7 locations time serie 1990-1998 Average rainfall: 450 mm/year

Average year for simulations: 1994

Historical rainfall series

1 -1 -1 99 0 1 6- 5- 19 91 2 7- 9- 19 92 9 -2 -1 99 4 2 4- 6- 19 95 5 -1 1- 19 96 2 0- 3- 19 98

0.0

5.0

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35.0

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355372

445

513475

523 534

427419

0

100

200

300

400

500

1990 1991 1992 1993 1994 1995 1996 1997 1998

h[mm]

9-2-1994 31-3-1994 20-5-1994 9-7-1994 28-8-1994 17-10-1994 6-12-1994

0.0

2.0

4.0

6.0

8.0

10.0

12.0

[m] Flags

415

458

406

537

492

447

483

Example rainfall data

Hydroprojekt,a.s.

Example rainfall dataMeasured rainf all 6.7.1999 1730 1830

D13

D19D14

D01

D03

D04D05 D06

D02

D17

D18

D10D07

D11D12

D15 D08

D09D16

17:30:00

6-7-1999

1 7: 45 :0 0 1 8: 00 :0 0 1 8: 15 :0 0

0.0

10.0

20.0

30.0

40.0

50.0

[m] Flags

D01

17:40:006-7-1999

17:50:00 18:00:00 18:10:00 18:20:00

0.0

10.0

20.0

30.0

40.0

[m] Flags

D14

17:30:00

6-7-1999

1 7: 45 :0 0 1 8: 00 :0 0 1 8: 15 :0 0 1 8: 30 :0 0

0.0

10.0

20.0

30.0

40.0

50.0

[m] Flags

D02

17:30:00

6-7-1999

17 :4 5: 00 1 8: 00 :0 0 1 8: 15 :0 0

0.0

10.0

20.0

30.0

40.0

[m] Flags

D03

17:30:00

6-7-1999

1 7: 45 :0 0 1 8: 00 :0 0 1 8: 15 :0 0

0.0

10.0

20.0

30.0

40.0

50.0

[m] Flags

D04

17:30:00

6-7-1999

17:40:00 17:50:00 18:00:00 18:10:00 18:20:00

0.0

10.0

20.0

30.0

40.0

50.0

[m] Flags

D05

17:30:00

6-7-1999

1 7: 45 :0 0 1 8: 00 :0 0 1 8: 15 :0 0

0.0

10.0

20.0

30.0

40.0

50.0

[m] Flags

D06

17:30:00

6-7-1999

1 7: 45 :0 0 1 8: 00: 00 1 8: 15 :0 0

0.0

5.0

10.0

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25.0

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35.0

40.0

[m] Flags

D07

Hydroprojekt,a.s.


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Example Rainfall dataProcessed rainfall intensities - 6.7.1999

17 30 17 48 17 51 17 53

17 55 17 57 18 01 18 06

Hydroprojekt,a.s.

Catchment data Catchment delineation, areas

snow elevation zones

Hydrological and meteorological data Water level and Discharge hydrographs

Rainfall amounts

Evaporation

Snow cover

Temperature

etc.

Hydrological data

Databases

Topographical DataTopographical Data:

River cross-sections Flood plain topography Channel & Flood plain

roughness Structure geometry

Time Series DataTime Series Data: Boundary conditions, Calibration and Verification Additional data-type:

Q-h boundary data

b (storage width)

h (elevation)

flood plain flood plainchannel

Time

Discharge [m3/s]


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Topography data Cross section data (all the same DATUM !!) Flodplains data (width, volume, area, DEM,..)

Aerial/Satelite/Radar images of flood extents Reservoirs data (control strategy, spillways ...) Structures description (control strategy, geometry ...) data in geographical coordinates background maps

Hydraulic data Water level and Discharge hydrographs Rating curves Peak water level during significant events (used for

calibration and verification)

etc.

Hydrodynamic data

GIS and other IS Geografical information systems

ESRI MAPINFO INTERGRAPH

GIS what is it for? Graphical presentation of geographically distributed data graphics is based on databaseorientedinformation Tools for topological data presentation, processing and analysis

Priority for user: firstly: data analysis and pilot project for data collection and

definition of requirements for IS

Hydroinformatics and

Project


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Role of consultant

Engineer coordinator: Information into the numbers, symbols and codes Interpretationof results

E tica laspect Communication between specialists on definedplatform

HIS expert:

Specialized teams - multidisciplinary character of work Experts in hydraulics, hydrology, chemistry; ecologists mathematitians IT experts Communications and measurement experts

Problem Formulation

Phase C+D Phase E

Phase F

MOUSE NAM runoff model

MOUSE HD,AD model

MIKE11 river model

1,4

0,83,2

2

2,2

0

3 , 6

0,85

1,6

5

2,4

2

,8

0,4

1,5

1,6

MIKE11 Vltava river model

MOUSE HD, AD sewer model


1,4

0,83,2

2

2,2

0

3 , 6

0,85

1,6

5

2,4

2

,8

0,4

1,5

1,6

1,4

0,83,2

2

2,2

0

3 , 6

0,85

1,6

5

2,4

2

,8

0,4

1,5

1,6

1,4

0,83,2

2

2,2

0

3 , 6

0,85

1,6

5

2,4

2

,8

0,4

1,5

1,6

MIKE11 Vltava river model

MOUSE HD, AD sewer model


BLACK BOX treatment plant model

MIKE11 rivermodel


MOUSE HD,AD model

MOUSE HD,AD model

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[m]

D

C B

KSB

M

BS

A

112B

F2

F3

modr

Jih

Barr

Stod

Solid

JM

Po%%232

D1

BS1

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KSB

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modr

Jih

Barr

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Solid

JM

Po%%232

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BS1

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KSB

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Solid

JM

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BS1

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[m]

V123

V165

V166

V167

B

A_O21A

A_O11A

M_0 A_O4A A_O9AA_O10A

A_O13A

A_O2A

A_O1A

A_O14A

A_O16A

A_O18A

A_0

A_O20AA_O20A

A_O15A

B_O11B

B_O5B Os

Os

Os

P2

Vl

System Schematisation


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Model

Monitoring19 flowmeters

24 water level meters

19 rain gauges

3 WQ samplers

1 2 : 0 04 - 7 - 1 9 9 7

0 0 : 0 05 - 7 - 1 9 9 7

1 2: 00 0 0:0 06 - 7 - 1 9 9 7

1 2:0 0 0 0: 007 - 7 - 1 9 9 7

0 . 0 0

0 . 0 5

0 . 1 0

0 . 1 5

0 . 2 0

0 . 2 5

0 . 3 0

0 . 3 5

0 . 4 0

0 . 4 5

0 . 5 0

0 . 5 5

0 . 6 0

0 . 6 5

0 . 7 0

0 . 7 5

[ M 3 / S E C ] T i m e s e r i e s o f D I S C H A R G E B R A N C H E S ( 1 _ 0 4 0 7 . p r f )

simulan model

Model Calibration


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21/28

Totalinflow to the city

Total CSO production

Total WWTP production

Impact parameter BSK5[t/year]

CHSK[t/year]

NL[t/year]

N tot[t/year]

N-NH4+[t/year]

P tot[t/year]

Total inflow to the city 8 700 62 500 44 500 47 500 270 400

Total impact from CSOs 430 1 100 640 107 60 20

Total impact from WWTP 3 700 12 600 5 800 4 100 950 250

BOD

3%

29%

68%

Amonia

21%

5%

74%

Phosphorus

60%

3%

37%

Analysis and interpretation of results

From To Qmax No MaxT[hour]

OK_56K 963114 1.8 7 1.3

OK_57K 9815155 1.5 4 1.2

OK_70K OK_70KO 9.9 17 2.5

RN V_RN 9.6 10 3.1

OK_71K 539015 0.2 2 0.6

OK_72K 544029 3.8 5 1.3

OK_73K B9 0.0 0 0.0

OK_75K OK_75KO 1.0 13 1.7

OK_77K 0 0.2 6 1.2

OK_78K 479073 0.0 0 0.0OK_79K B4 0.0 0 0.0OK_80K OK_80KO 0.0 0 0.0OK_81K OK_81KO 0.0 0 0.0OK_83K OK_83KO 1.0 1 0.3

From To TotT[hour] Sumamax. SumaTot.

OK_56K 963114 3.5 3500 6400OK_57K 9815155 2.6 3150 5100OK_70KOK_70KO 15.2 37 700 102 800

RN V_RN 15.8 36400 87000OK_71K 539015 0.8 150 250OK_72K 544029 3.5 8500 14100

OK_73K B9 0.0 0 0OK_75KOK_75KO 8.7 2500 6900OK_77K 0 3.0 270 500OK_78K 479073 0.0 0 0OK_79K B4 0.0 0 0OK_80KOK_80KO 0.0 0 0OK_81KOK_81KO 0.0 0 0OK_83KOK_83KO 0.3 600 600

Analysis and interpretation of results

DHI Software Suite

++


22/28

MOUSE sewer model

AQUAbase graphical DRBMS

RAINGEN rainfall simulator


23/28

Gandalf - monitoring

MIKE View - postprocessing

MIKE NET water supply


24/28

MIKE 11 1D river model

MIKE 21 2D flooding

Mike Urban


25/28

Mike Basin

Integrace nstroj Hydroinformatiky

Flood plainCombining 1D & 2Dmodels, i.e.MOUSE & MIKE 21

Integration of hydroinformatic tools

MIKE FLOODDetailed flood plain modelling

Combines 1-D and 2-D modelling

Detailed urban flood modelling

River

Water

Wastewater


26/28

3D models

MIKE SHE

FLUENT

Framework for real-time modelling & DSS applications

IMS

SCADA or telemetrysystems

Economic Systems(like Microsoft Navision -SAP)

MOUSE MIKE11 MIKE NET Third party modelling software

DIMS

RADARDIMS

DIMS

Communication

SCADASCADA

MOUSEEFOR

MIKE11/21

DIALOGMIKE NET

DIMS


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Operational Dashboard

Dashboard: Web interface tosensors, alarms, data, andhydraulic models.

For further information go to: www.HarmoniT.com or email: [email protected] 80

Project aims and objectives

To build a model linking mechanism for:

run time data exchange between models, databases & tools

In order to:

improve ability to model complex scenarios

Estuary

Surface runoff

Groundwater

Evaporation

Precipitation

Coast

EvaporationFloodsFloods

PlanningPlanningReservoir yieldReservoir yield

DroughtsDroughts

Aquifer yieldAquifer yield

Water qualityWater quality

EcologyEcology

Climate changeClimate change

Ecology

Flow

??

EcologyFlow

SCADA

Models

Inspections

GISCAD

Future trends ???


28/28

Pros of Hydroinformatics

Better knowledge of water system

Better (cheaper and more effective)decisions

Positive effect on living environment

Effective use of investments

Cons of Hydroinformatics

price of HIS systems (SW and HW)

complexity of HIS systems

garbage in garbage out effect

dramatic change of approach

Scientists from company RAND created model of home computer", howit would look

like in 2004. ..

From "Popular Mechanics" - 1954:

Modelling_Hydroinformatics.pdf

Documents

Transcript of Modelling_Hydroinformatics.pdf