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WEB BASED WATER RESOURCE INFORMATION SYSTEM USING SWAT MODEL
Presented bySrishti Singh, B.Tech, Computer Science
and Engineeringand
Dr. Narendra Kumar TiwaryProfessor, Research, ARP & PIM
Water and Land Management Institute, Patna, India
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VISIONOptimum and sustainable utilization of water resourcesby different line departments with active involvement ofstakeholders for efficient and effective management offlood, drought and drinking water.
To develop a comprehensive website for hydro-meteorological data and water resource informationsystem (WRIS) To develop a flood management information system(FMIS) for Bihar stateTo develop a drought management information system(DMIS) for Bihar state
MISSION
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The available river waters would fall short of demand innear future due to increase in the demand for water fordomestic, industrial and municipal uses as a result of thedevelopment of civilization and the growth of cities.The struggle to obtain adequate supplies of water for bothlarge and small communities has continued to the presenttimes.India supports 1/6th of the world population with about1/15th of the world’s land and only 1/250th the world waterresources.India would have to lay serious consideration for fastemerging crisis in water related areas and adopt properstrategies to ensure integrated water resources managementincluding floods and droughts.
INTRODUCTION
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The erratic behaviour of Indian monsoon causes almost eachyear droughts and floods to occur simultaneously, sometimeseven within the same state. The impact of floods is stronger today than ever because ofrapid increase in population and resulting industrial andagricultural development and increasing occupation in theflood plains.The flood damage continues to show an increasing trenddespite the introduction of substantial structural(embankments) and non–structural flood control measuresduring past several decades in the country.It is a big challenge in India to properly moderate floods anddroughts together.
INTRODUCTION
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IMPORTANT FLOOD EVENTS
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Event-1 -The man-made embankments of river Kosi failed andFlooded north Bihar, India during 18 August 2008 434 Deadbodies were found until 27 November 2008
Event-2-In June 2013, a multi-day cloudburst centered on theNorth Indian state of Uttarakhand caused devastating floodsand landslides in the country's worst natural disaster since the200 4 tsunami more than 5,700 people were "presumed dead.Destruction of bridges and roads left about 100,000 pilgrimsand tourists trapped in the valleys
Event-3In September 2014, Heavy Rainfall centered on theNorth Indian state of Jammu and Kashmir caused devastatingfloods and landslides in the country's worst natural disastersince the 1944 Kashmir Flood Disaster. More than 700 peoplewere "presumed dead. Destruction of bridges and roads leftabout more than 100,000 pilgrims and tourists trapped in thevalleys
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Challenge for Water Resource Engineers and Scientists
Today, with modern equipments and radars we shouldbe able to develop a web based water informationsystem for predicting floods (expected inundation) anddroughts much earlier and stop human disasters.
Remote sensing, GIS and mathematical modeling canbe used for developing comprehensive floodmanagement information system and droughtmanagement information system.
SWAT scientists can do this job15-10-2018 6
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Objectives of the present study To develop a web based flood management
information system for Bagmati river basin,Bihar, India Using Remote sensing, GIS and mathematical
modeling for real time flood forecasting and inundationmapping
Downloading hydro-meteorological data formathematical modeling from following websites:
www.imdaws.com/ViewAwsData.aspx, www.hydrology.gov.np/new/bull3/index.php/hydrology/
Station www.fmis.bih.nic.in/Daily_FloodBulletin.html.
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WEBSITES FOR HYDRO-METEOROLOGICAL DATA OF STUDY AREA
www.imdaws.com/ViewAwsData.aspx,
.
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www.fmis.bih.nic.in/Daily_FloodBulletin.html.Real time data can be downloaded during flood season
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Study Area – Bagmati river Basin of Bihar, India
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Description of Study Area
Tributaries of Bagmati
Bagmati river basin is geographically located at 25°15' to27°11'E and 85°15' to 86°20'N in Bihar, India.
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Salient features of the Bagmati Catchment
The river has Himalayan origin and considerable portion of its catchments lie in theglacial region in Nepal. It is, therefore, snow-fed and perennial in flow. Every yearintensively flooded damaging agriculture.Population in Bihar: 5.530Millions,Population density: 1551 persons per Sq Km
Tributaries: Lalbakeya (R), Lakhandei (L)
Drainage Area in Bihar: 6500 Sq Km, Cropped Area in Bihar: 5362 Sq Km ;Totallength of main river in Bihar: 394 Km ;Elevation range 22 - 2913 m
Annual precipitaion of 1255 mm ((80%) within mid June – mid October);Meanannual flows: 2184.4 MCM.
Landuse:Net area under cultivation (67%), miscellaneous trees and groves (4.21%),fallow(16%),
Soil: The terraces in the Terai comprise of clay, sand and gravels. The hills at theflanks comprise conglomerates and thick beds of sand, rock and shoals. 13/
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Hydrological Modelling of Baghmati River Basin by SWAT
Model
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SWAT Model – A Physically Based Model
Equations of mass, energy and momentum are used todescribe the movement of water over the land surfaceand through the unsaturated and saturated zones.
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FROM IMAGES TO INFORMATION…
ANALYSIS
GIS
~ 1:12500 THEMATIC
DISASTER MANAGEMENT APPLICATIONS:
MULTI-LAYER
TABLES/REPORTS
.. ……TO DECISION AND ACTION
HAZARD ZONES
RISKMAP
MAPS
IMAGES
DAMAGEMAP
DROUGHTMAP
FLOODMAP
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METHODOLOGY USED IN PRESENT STUDY1.
1. Watershed delineation using SRTM DEM
2. Formation of HRUS3. Writing input tables4. Runoff generation using Green Ampt
Method5. Using modified SWAT model for real
time flood forecasting application
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(1) DEM – SRTM (90 m resolution)
(2) Landuse – Global USGS (2 M)
(3) Soil – FAO Global soil (5 M)
(4) Rain gauges /Temperaturegauges – IMD
(5)Stream Gauges – CWC
(6) Rainfall data-IMD Data, Aphrodite Gridded rainfall data, real time rainfall data downloaded from websites
Model Set up for Study Area - Bagmati river basinGauge Stations and Stream Networks
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Results and Discussions
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SRTM DEM
Mosaic or Masking if
required
Catchment Extraction
Burning with help of known watershed and river network
Fill Sinks
Direction
Flow Accumulation Network Extraction Drainage Network Ordering
Final Basin Boundary and Drainage map
Watershed Delineation Steps
Sub-watersheds MapStream Networks
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Model Set up (In put Maps)
Study area: Bagmati river basin, Bihar, India Watershed area: 1532353 ha. = 14384 km2
Total number of sub-watershed: 32 (threshold level: 30000 ha)
Number of HRU formation: 206 MULTIPLE HRUs LandUse/Soil/Slope OPTION
:THRESHOLDS : 5 / 5 / 5 [%] Number of calibration points: 1 (Hayaghat)
Soil type Map Land Use Map DEM
HRU Map
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Soil Details
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SEQN SNAM NLAYERS HYDGRP TEXTURE SOL_AWC1 SOL_K1 CLAY1 SILT1 SAND1
3663 3663 2 C LOAM 0.117 35.65 24 35 42
3664 3664 2 C LOAM 0.157 28.52 17 36 47
3682 3682 2 D LOAM 0.175 7.77 24 36 40
3684 3684 2 C LOAM 0.175 13.92 22 38 41
3695 3695 2 C LOAM 0.175 14.96 20 40 40
3743 3743 2 D LOAM 0 6.48 18 44 38
3761 3761 2 C LOAM 0.175 24.73 20 34 46
3808 3808 2 D LOAM 0.175 6.17 21 35 44
3851 3851 2 D CLAY_LOAM 0.137 7.17 27 35 37
Table-6.2 Soil properties
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Flow Hydrograph Daily Simulation
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0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.00
200
400
600
800
1000
1200
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Dis
char
ge in
cum
ecs
1-July Time in days 31-July
Flow Hydrograph of Hayaghat of July-04
RF at Simra
RF at Kathmandu
RF at Nagarkot
RF at Benibad
RF at Hayaghat
HayaOBS
HayaSim
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Valdation for daily flow 2010
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Validation Graph
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ERROR ANALYSIS
Time series analysis of errors in hourly simulations/forecasts has been performed. An ARIMA model developed for forecasting error has been deployed for correcting simulated/forecasted hourly flows. Integration of simulation capability of SWAT model and error forecasting capability by time series analysis has been done for solving the problem of real-time flood forecasting
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Error 2004 Simulation
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-400
-300
-200
-100
0
100
200
300
400
500
1 15 29 43 57 71 85 99 113
127
141
155
169
183
197
211
225
239
253
267
281
295
309
323
337
351
365
379
393
407
421
435
449
463
477
491
505
519
533
547
561
575
589
Dis
char
ge in
cum
ecs
4-July-04 Time in hours 28-July-04
ERROR 4-July-28-July-04
ERROR
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Error 2004 hourly simulation
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-60
-40
-20
0
20
40
60
80
100
120
1 16 31 46 61 76 91 106
121
136
151
166
181
196
211
226
241
256
271
286
301
316
331
346
361
376
391
406
421
436
451
466
481
496
511
526
541
556
571
586
FIRST DIFF OF ERROR 4-July-28-July on y-axix and time in hrs on X-axix
FIRST DIFF
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Error Analysis for hourly Simulation of 2005 Flood Events
ARIMA Model Parameters for error analysis for hourly simulation of year 2005ARIMA Parameters
B1(LAG1)= 0.6056 B2(LAG2)= 0.1792 B3(LAG3)=0.0988
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Effect of error correction
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0
100
200
300
400
500
600
700
800
900
1 10 19 28 37 46 55 64 73 82 91 100
109
118
127
136
145
154
163
172
181
190
199
208
217
226
235
244
253
262
271
280
289
298
307
316
325
334
343
352
Dis
char
ge in
cum
ecs
2-Aug Time in hour 22Aug
Hourly Simulation 2nd August-22nd August-05
OBSSIMCorrectedSimOld
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Real time flood forecasting graph generated by SWAT
model
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FMIS database (1:50,000 scale) and application software
Flood management
Improved flood forecast model
Updated flood manuals
Plans for upgrading hydrologic measurements and telemetry Training
Flood Management Information System (FMIS) FIRST STAGE
Flood website
Inundation simulation model
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FMIS DEVELOPMENT STRATEGY
Identify flood management functions of key agenciesLink
Define information needs
Design information products & analysis tools
Design FMIS – Database and application software
Develop FMIS
Implement and OperateCreate focal point in WRD - FMISC
Assist key agencies to integrate in decision making – institutional arrangements, awareness raising, etc.
Develop interface for flood website
Develop interface with improved flood forecasting software
Develop empirical model for simulating inundation
Disseminate info products, to concerned departments and communities
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Information products to be developed Hydrologic status map Current water level, trend and
forecastImproved preparedness
Flood inundation maps Customized for each state agency Emergency management action
Simulated flood inundation impact
Possible inundation extent, and impact
Early warning for preparedness
Post-flood river configuration & alert
Locate affected and vulnerable sites
Strengthening/ planning flood management works
Seasonal flood summary Summarize flood frequency, duration, and impact area
Build database on flood hazard for mitigation and management
Flood hazard zoning Zoning for hazard, risk and vulnerability
Planning mitigation and long term measures
Need based analysis outputs Thematic and area specific spatial analysis
Specific management needs and action
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PREDICTING FLOOD INUNDATION
The comprehensive approach to forecasting floodinundation may involve the use of a suite of modelsincluding reliable medium range rainfall forecasting in theupstream catchment area in Nepal and in north Bihar;rainfall-runoff modeling to convert rainfall forecast intorunoff forecast; hydraulic routing to downstream areas innorth Bihar; Digital Elevation Modeling (DEM) of floodprone areas; modeling flood inundation from over-bankflow, embankment breach, and drainage impedance, andmodeling duration and depth of flood inundation.
A simpler approach is to correlate u/s rainfall to floodinundation.
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FLOOD WEBSITE
•Review international and national flood sites•Design website based on best features, including interface with FMIS, and linkage with national and international data sources (eg. Satellite based rainfall estimate and forecast)•Develop and implement website using a professional agency•Train FMISC staff in website maintenance
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STRATEGY FOR UPDATING FLOOD MANUAL
Review the existing flood manual, forpossible updation using FMIS outputs.eg. Incorporate annual river configurationmap and table, showing vulnerableembankment reaches and degree of hazard,for improved preparedness
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SUMMARY AND CONCLUSIONS
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Flood management information system has been developed using GIS and Remote Sensing database.
Compressive website for hydrometeorological data for study area has been developed.
Artificial intelligence and machine learning along with smart hardware will make it possible to create a comprehensive water resource information system using SWAT model and GIS data base.
SWAT model has 350 subroutines written in Fortran. Initially it was developed for long term continuous run. But it has been modified for flood forecasting i.eevent modeling
Drought management information system can be developed using SWAT model and GIS database.
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Proposed Institutional framework for FMIS
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Thank You
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