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Remote Sensing and GIS Application in
   Water Resources Management

                   By
           Dr. S.P. Aggarwal
            spa@iirs.gov.in


    Indian Institute of Remote Sensing
    (National Remote Sensing Centre)
   ISRO, Dept. of Space, Govt. of India
                  Dehradun
Indian scenario
           Water Resources of India – A Glance

    Average Annual Rainfall                         - 4000 billion cu.m.
Natural Runoff                                      - 1953 billion cu.m.
( Surface & Ground Water)
Estimated Utilisable Surface Potential              - 690 billion cu. m.
Ground Water Resource                               - 432 billion cu. m.
Available Groundwater Resource for Irrigation        - 361 billion cu. m.
Net Utilisable Ground Water Resources for Irrigation - 325 billion cu. m.
Groundwater provision for Domestic, Industrial       - 71 billion cu. m.
and Other

                                          About 1700 liter/person/day



 Source : ICID NEWS, March, 2000
Problem!
Spatial variation
  120 mm to 12000 mm
Seasonal Variation
  Rainy season: 70%-90%
Annual variation
  Some times drought year
  some times wet year
Solution!
Water Resources Management
For effective Water Management we need

          Near real time hydrological information
          Temporal information : Seasonal variation
          Spatial information: Point v/s Spatial
          Synopticity : think globally and act locally
Remote Sensing provides

          Near real time hydrologic information : within few
          hours to few days
          Temporal : 30 minutes to few days
          Spatial information :1 Meter to few km. spatial
          resolution
          Synoptic coverage: 25 km to 800 km. or more

Geographic Information System is used …..
          Develop spatial database
          Integrate databases ( remote sensing , topographic,
          Socioeconomic etc . ) and develop water resources management
          strategies through SDSS
Imaging capability of India

                   Imaging
                  ‘Hot spot’    Met/Ocean
                               Observation

                                                         communication




                                                 All weather
   High                                           mapping
resolution
 imaging




                  Laser
             Terrain Mapper                  Real Time
                                             Mapping
1999
       1995/1997
                                                                 2003

   IRS-1C/1D LISS-3 (23/70M,                              RESOURCESAT-1
   STEERABLE PAN (5.8 M);               INSAT-2E CCD      LISS3 - 23 M; 4 XS
         WiFS (188M)                 (1KM RESOLUTION;      LISS4 - 5.8 M; 3-
                        1996         EVERY 30 MNUTESS)            XS          2005
    1994                                                   AWIFS - 70 M; 4-
                     IRS-P3
                                                                  XS
                     WiFS MOS          1999                   CARTOSAT - 1
        IRS-P2       X-Ray                                 PAN - 2.5M, 30 KM,
                                           IRS-P4                   F/A
        LISS-2
                                     OCEANSAT OCM, MSMR                     2007
 1988/91

IRS-1A/1B LISS-1&2 (72/36M,
                                    INDIAN
                                                                      CARTOSAT-2
    4 BANDS; VIS & NIR)            IMAGING                             PAN – 0.8M

              1982                 SYSTEMS                     2009

           RS-D1               IMAGING IMPROVEMENTS                      MEGHA-
1979                             1KM TO 0.8 M RESOLUTION                TROPIQUES
                                 GLOBAL COVERAGE
                                 APPLICATION-SPECIFIC
   BHASKARA
OBSERVATION CAPABILITY
                         INSAT –                                 IRS LISS-3
                         VHRR/CCD



EVERY 30 MIN. IMAGING EACH
                                         EVERY 22 DAYS IMAGING


                             IRS – OCM                            IRS – PAN


                                                                 towards….
EVERY 2 DAYS IMAGING                     EVERY 5 DAYS IMAGING




                         IRS – WiFS
                                                                 CARTOSAT
                                                                    +AIR-
                                                                   BORNE
EVERY 5 DAYS IMAGING                                              SENSORS
OPERATIONAL APPLICATIONS


•   Flood Mapping & Management
•   Snowmelt Runoff moelling
•   Hydrological modelling
•   Irrigation water Management
•   Drought Monitoring
•   Rain Water Harvesting
Flood Inundation Mapping
and Damage Assessment
Near Real-Time Flood
Inundation Mapping
Flood Damage
Assessment
Flood Risk Zone
Mapping
Flood forecasting and
Spatial Warning
System
1998 Brahmaputra Floods -Basinwise monitoring
                                     Assam
                                     State




                                     Water Resources Group,NRSC
         08 Sept, 1998 IRS-1C WiFS
1998 Brahmaputra Floods - Inundation extent
Marigaon District                            Marooned village




           <-- Flood inundation




10 Sept, 1998 IRS-1D WiFS         13 Sept, 1998 IRS-1D WiFS
 Inundated area 34,240 ha          Villages affected 465

                                         Water Resources Group,NRSC
1998 Brahmaputra Floods - Damage to road network
             Part of Marigaon district

Pre-Flood                                                DuringFlood




                                         <--Marooned village



                                          <-- Flood inundation



  IRS-1D PAN 03 March, 98                IRS-1C PAN 08 Sept, 98
29 Oct-6gmt
28 Oct-3gmt
 30Oct-9gmt
   Oct-9gmt
   Oct-6gmt
   Oct-3gmt

                          SUPER CYCLONE
                            OVER ORISSA
                                  COAST
                         INSAT IMAGES
                         SHOWING THE
                         CYCLONE MOVEMENT
                         DURING 28 OCT TO
                         30 OCT, 1999




               …...AND THE AFTERMATH
              • NEARLY 3.75 LAKH Ha. INUNDATED

              • ROAD, POWER AND COMMUNICATION
                NETWORKS SEVERELY AFFECTED IN 10
                COASTAL DISTRICTS
Iirs overview -Remote sensing and GIS application in Water Resources Management
3D VIEW OF FLOOD RISK ZONES OF ALLAHABAD CITY




                                          100Year
                                          79.00mt
                                          50
                                          25 Year
                                          10Year
                                           5
Snow Melt Runoff Modelling
Snow cover depletion

15/05/98   15/06/98   12/10/98   28/11/98   04/12/98   14/02/99




25/05/99   25/06/99   14/07/99   27/09/99   28/10/99   22/11/99
September - I
                                                                                     August - II
                                                                                     July - III
                                                                                     July - I
                                                                                                      zone 10
                                                                                     June - II
Snow Cover Depletion Curves




                                                                                     May - III
                                                                                                      zone 9
                                                                                     May - I
                                                                                     April - II
                                                                                     March - III




                                                                                                      zone 8
                                                                                     March - I
                                                                                     February - II




                                                                                                      zone 7
                                                                                     January - III
                                                                                     January - I




                                                                                                      zone 6
                                                                                     December - II
                                                                                     November - III
                                                                                     November - I
                                                                                     O ctober - II
                              100

                                    90

                                         80

                                              70

                                                   60

                                                        50

                                                             40

                                                                  30

                                                                       20

                                                                            10

                                                                                 0
                                               Snow cover [% ]
Iirs overview -Remote sensing and GIS application in Water Resources Management
SRM calculation
           The basic equation of SRM model is

      Qn+1 = [CSn an (Tn + ΔTn) Sn+ CRn Pn] A·10000 (1-kn+1)+ Qn kn+1
                                              86400

   T, S and P are variables to be measured or determined each day. CR, CS, lapse
   rate to determine T, TCRIT, k are parameters which are characteristic for a given
   basin.

As an Example for a basin of an elevation range of 1500 m. It is sliced in three
   elevation zones A, B and C of 500 m each, the model equation becomes

Qn+1 = {[cSAn · aAn (Tn + ΔTAn) SAn + cRAn · PAn] + AA86400
                                                      * 10000

         [cSBn · aBn (Tn + ΔTBn ) SBn + cRBn · PBn ] + AB* 10000
                                                           86400

   [cSCn · aCn (Tn + ΔTCn ) SCn + cRCn · PCn ] +AC* 10000 )} + Qn ·kn+1
                                                 (1-kn+1
                                                   86400

In this project all the model parameters are derived as 10 daily average values and
    used to compute the 10 daily average runoff.
Dv(%)=1.8




                                                                                                                          Dec ember II
                                                                              estimated
                                                                                           real




                                                                                                                          Nov ember II
                                                                                                                          O c tober II
Martinec-Rango SRM (1998-1999)




                                                                                                                          September II
                                                                                                                          Augus t II
                                                                                                                          J uly II
                                                                                                                          J une II
                                                                                                                          May II
                                                                                                                          April II
                                                 • Snow Cover Area




                                                                                                                          Marc h II
                                                 • Temperature
                                                 • Precipitation




                                                                                                                          February II
                                                                                                                          J anuary II
                                                                                                                          Dec ember II
                                                                                                                          Nov ember II
                                                                                                                          O c tober II
                                                                                                                          September II
                                                                                                                          Augus t II
                                                                                                                          J uly II
                                                                                                                          J une II




                                     240
                                           220
                                                  200
                                                        180
                                                              160
                                                                        140
                                                                              120
                                                                                          100
                                                                                                  80
                                                                                                       60
                                                                                                            40
                                                                                                                 20
                                                                                                                      0
                                                              discharge [m /s]
                                 3
Martinec-Rango SRM (calibration 2000-2001)




                                                                                                                               September - I
                                                                                       measured
                                                                                                  estimated
                                                                                                              Dv(%)=15.3




                                                                                                                               August - II
                                                                                                                               July - III
                                                                                                                               July - I
                                                                                                                               June - II
                                                                                                                               May - III
                                                                                                                               May - I
                                                                                                                               April - II
                                                                                                                               March - III
                                                                                                                               March - I
                                                                                                                               February - II
                                                    Year: 1998




                                                                                                                               January - III
                                                                                                                               January - I
                                                                                                                               December - II
                                                                                                                               November - III
                                                                                                                               November - I
                                                                                                                               O ctober - II
 180

                                             160

                                                   140

                                                                 120

                                                                       100

                                                                             80

                                                                                  60

                                                                                         40

                                                                                                       20

                                                                                                                           0
                                                                  Discharge [m3 /s]
Hydrological Modelling
Introduction
Hydrological System

        Input                      Output
                          System




       Input: Rainfall
       System: Watershed/Basin
       Output: Runoff
LOCATION OF KULSI BASIN
DRAINAGE MAP OF KULSI BASIN
DIGITAL ELEVATION MODEL OF KULSI BASIN
ASPECT MAP OF KULSI BASIN
Land use/ Land cover
   Change study
     (1991 to 2002)
Satellite Data
   (26-11-1991)
Satellite Data
   (17-02-2002)
LAND USE/LAND COVER MAP OF KULSI BASIN FOR THE YEAR 1991
LAND USE /LAND COVER MAP OF KULSI BASIN FOR THE YEAR 2002
Land use/ Land cover statistics for the year 1991 & 2002


LULC            1991              2002             Difference
                Sq. Km             Sq. Km          Sq. Km

Dense Forest    849.38            823.17           -26.21 (2621 Ha)
Open Forest     235.09            249.17           14.08
Agriculture     490.44            502.23           11.79
River/Streams   21.32             21.32            -
Hydrologic Simulation
Daily Simulated and observed
                         Runoff (2002)
                                                 Date
                 1   24 47 70 93 116 139 162 185 208 231 254 277 300 323 346 369 392
             0                                                                         100
                                                                                       90
            50
                                                                                       80
                                                                                       70
           100
                                                                                       60
Rainfall




                                                                                             Rainfall
           150                                                                         50    Simulate Runoff
                                                                                       40    Observed Runoff
           200
                                                                                       30
                                                                                       20
           250
                                                                                       10
           300                                                                         0
Impact of LULC Changes
     on hydrology
      (1991 to 2002)
Impact on Runoff

             160
             140
             120
Runoff(mm)




             100                                 Simulated Runoff (mm )
                                                 for 1991
              80
                                                 Simulated runoff (mm ) for
              60                                 2002
              40
              20
               0




                                             v
                n




                                l

                                      p
                    ar

                         ay

                              Ju




                                          No
              Ja




                                    Se
                    M

                         M




                              Month
Impact on Sediment Yield

                         1.4
 Sediment Yield (T/Ha)




                         1.2
                          1                                    Monthly Sediment
                         0.8                                   Yield for 1991
                         0.6                                   Monthly Sediment
                         0.4                                   Yield for 2002

                         0.2
                          0



                                                           v
                            n




                                            l


                                                    p
                                ar


                                     ay


                                          Ju




                                                        No
                          Ja




                                                  Se
                                M


                                     M




                                          Month
Comparison
       Forest          Rain          Runoff             Sediment
                                                        Yield


       849.38 sq. km   957mm         75 mm
1991   (53 %)                        (7.8%)


       823.17 sq.km    2915 mm       505 mm
2002   (51.5%)                       (17.3%)

       Model is run for same rainfall
       849.38 sq. km   2915 mm       777.5 million M3   2.41 t/ha
1991   (53 %)
                        Increased Runoff: 27.1 million Cub. M
       823.17 sq.km    2915 mm       804.6 million M3   3.88 t/ha
2002   (51.5%)
one of the worst natural disasters

causes extensive damage to food
grain production

widespread desert condition in the
long run

affects social and economic life of
millions of people every year




               Water Resources Group,NRSC
NATIONAL AGRICULTURAL DROUGHT ASSESSMENT AND MONITORING SYSTEM
                            (NADAMS)



       GROUND SYSTEM                         SATELLITE SYSTEM




                       CROP                         VI           VI
RAINFALL   ARIDITY                 LANDUSE
                     CALENDAR                   STATISTICS      MAPS




                           GEOGRAPHIC
                       INFORMATION SYSTEM




                       DROUGHT BULLETIN
                           AND MAP
NATIONAL AGRICULTURAL DROUGHT ASSESSMENT &
       MONITORING SYSTEM ( NADAMS )
            NOAA BASED VEGETATION INDEX




                                                  ANDHRA
                                                  PRADESH




                                                     ADILABAD
                                                   DISTRICT, A.P




                                 DISTRICT & MANDAL-WISE
                                      ASSESSMENT
                                     Water Resources Group,NRSC
India




NOAA-AVHRR based NDVI - August 1999


                      Andhra Pradesh




 IRS-WiFS based NDVI - August 1999

                                        Water Resources Group,NRSC
IRRIGATION WATER
MANAGEMENT: RS GIS
      Approach
Schematic diagram of an irrigation
           command

                  D
                       D

  River
          Main canal

  DAM         F


          M       D    D
Part of Upper ganges canal as
        seen by satellite
IRS 1D Pan(5.8)
Cartosat 1(2.5 m)
Bhimgauda barrage thru quickbird (65 cm)
Branching of canals
Superpassage
Complex…..why?
Crop type
Crop growth stage
Canal network
Rainfall
Soil map
Indian Imaging System – Till now
   1979/81                           1999/2003
             BHASKARA –1 /2        Overall               INSAT-2E
             VIDICON,                             VHRR, CCD (1 km)
             SAMIR                 Mapping
                                                         INSAT-3A
                                                        VHRR,CCD

                                    1999
   1988/91        IRS-1A & 1B
                              •Crop Type        IRS-P4 (Oceansat– 1)
                  LISS-1&2                            OCM (360m)
                  (72/36m) •Crop Condition
                                                        MSMR
                              •Crop acreage
                                      2001
   1994                         Estimation
                                      IRS-P5(Cartosat-1)
                                                  TES
                    IRS-P2                           PAN (1m)
                    LISS-2

   1996                         Canal2003
                  IRS-P3       Network        IRS-P6 (Resourcesat-1)
                  WiFS,                            LISS 3 (23m)
                                                   LISS 4 (5.8m)
                  MOS X-Ray
                                                   AWiFS (55m)
                                    2005&7
   1995/1997
                                 •Canal
                                                 IRS-P5(Cartosat-1)
                      IRS-1C/1DAlignment
                 LISS-3 (23/70m)                  PAN-(2.5 m) F/A
                           •Structures etc.
                    PAN (5.8 m)
                    WiFS (188m)
                                                   Cartosat2 (80 cm)
ology         COMMAND AREA MAP
                   d
           tho
         Me                      DISTRIBUTORY BOUNDARY MAP

                                   CROP AREA ESTIMATION IN
MET. DATA                              EACH BOUNDARY
temp.,wind speed,RH,sunshinehr




Kc VALUES                        CROP WAT MODEL


    EFFECIENCES
                                        IWR             ETo

      Supply Data
                                     Demand-Supply analysis
CLASSIFIED IMAGE OF KHARIF SEASON
      OF K.PATAN COMMAND
CLASSIFIED IMAGE OF RABI SEASON
     OF K.PATAN COMMAND
CLASSIFIED DIGITAL ELEVATION MODEL
        OF K.PATAN COMMAND
NDVI OF K.PATAN COMMAND OF OCTOBER 1998
VARIATION OF NDVI WITH PLACE & TIME

       0.450
                       0.41
       0.400

       0.350

       0.300                           0.31
NDVI




       0.250

       0.200                                           0.21

       0.150           0.14
                                       0.12
       0.100                                           0.11

       0.050

       0.000
                    PATAN       ANANTPURA         MAKHEEDA
                DISTRIBUTORY    DISRIBUTORY     DISTRIBUTORY

                                                               AVG.OCTOBER NDVI
                               DISTRIBUTORIES
                                                               AVG.JANUARY NDVI
KHARIF SEASON
                                 Head Reach                                                                                                                                                Middle Reach
                                                                                                                                                                         CALCULATED IRRIGATION WATER REQUIREMENT & ACTUAL IRRIGATION WATER
                           CALCULATED IRRIGATION WATER REQUIREMENT & ACTUAL                                                                                                                            SUPPLY
                                        IRRIGATION WATER SUPPLY                                                                                                                       (KHARIF SEASON ,ANANTPURA DISTRIBUTORY)
                                  ( KHARIF SEASON, PATAN DISTRIBUTORY)

                     900
                     800
                                                                                                                                                                   500
                                                                769.54
                                                                                                                                                                                                                          425.29




                                                                                                                                                V O L UM E h a-m
                                                                                                                                                                   400
V O L U M E h a -m




                     700
                     600                           592.33                                                                                                                                                    337.01
                                                                                                                                                                   300                                                                                287.03
                     500                                                                                                                                                                                                                              235.08
                                                                                                                                                                   200                                                                  182.20
                     400                                                                                        401.84
                                                                                             329.07                                                                100                                       102.67                     120.19
                     300
                     200                                                                                                                                            0           11.68
                                                                                                                                                                                0.00          6.63
                                                                                                                                                                                              0.00                        0.00
                     100                                                                                                                                                     MAY           JUNE           JULY        AUGUST       SEPTEMBER     OCTOBER
                             44.80      25.42
                      0
                           MAY       JUNE       JULY        AUGUST           SEPTEMBER                  OCTOBER                                                                                   MONTH
                                                                                                                                                                                                                      CALCULATED IWR             ACTUAL IWS
                                     MONTH                      CALCULATED IWR                          ACTUAL IWS




                                                                                                                           Tail End
                                                                                                 CALCULATED IRRIGATION WATER REQUIREMENT & ACTUAL
                                                                                                              IRRIGATION WATER SUPPLY
                                                                                                       (KHARIF SEASON,MAKHEEDA DISTRIBUTORY)


                                                                                       700
                                                                                                                                                     664.54
                                                                                       600

                                                                                       500                                          487.55
                                                                         VOLUME,ha-m




                                                                                       400

                                                                                       300                                                                                                  314.75
                                                                                                                                                                              283.35
                                                                                       200
                                                                                                                                                                                            151.16
                                                                                       100                                                                                    79.35
                                                                                                        71.13
                                                                                                                        40.36
                                                                                         0              0.00            0.00        0.00         0.00
                                                                                                      MAY            JUNE        JULY        AUGUST                      SEPTEMBER      OCTOBER


                                                                                                                         MONTH                      CALCULATED IWR                      ACTUAL IWS
Rain Water Harvesting
Rain Water Harvesting

RWH: Urban Area
RWH: Rural Area
RWH: Urban Area
Estimation of Rain water harvesting potential
in a City using high resolution Data
A case Study :
  Area: 1115 Sq. m.
  Annual Rainfall: 2000 mm
  Runoff coefficient : 0.9
  Total Runoff to be collected:
1115 x 2000@1000 x 0-9 litre = 20 lakh litre
RWH: Rural area
DECISION RULES BY IMSD & INCOH
  Farm Ponds: Flat topography and low soil permeability
   is required.
  Check Dams: Medium slope, low permeability is required.
  The available area should be more than 25 hectors, preferably
  check dams should be constructed at lower order streams
   (upto third order).
  Ground Water Recharges: Flat to moderate slope and soil
  should be permeable.
  Percolation Tanks: Flat topography and pervious strata are
  required. The available area should be more than 40 hectares.
  Bundhis: Medium permeable soils, adequate area are the
  requisites for bundhis and preferably it should be nearer to
  cultivated land.
FIELD DATA                             SATELLITE DATA          SOI TOPO MAPS

       METEOROLIGICAL DATA
                                     DIGITAL IMAGE PROCESSING       CONTOUR MAP


                             GROUND TRUTH
                                            LANDUSE MAP         DIGITAL ELEVATION MODEL




RUNOFF POTENTIAL MAP                          SOIL MAP               SLOPE MAP
  USING TM MODEL

   HIGH RUNOFF
                                                                    CL.SLOPE MAP
POTENTIAL AREA MAP


 BUFFER MAP FOR                                OVERLAY
   VILLAGES &
AGRICULTURE LAND
                                             ANALYSIS



                                        SITE SUITABILITY MAP
A Case Study of Bisora watershed, Orrissa
SOIL MAP
           LANDUSE MAP




                         CL SLOPE MAP




                                        DRAINAGE
FINAL CROSS MAP
          CROSS MAP OF LULC
          SOIL, CL SLOPE AND
          RUNOFF POTENTIAL
            0           12 km
SITE SUITABILITY
        MAP FOR
        FARMPONDS




      Suitable site
      (total 85.2 H)
0      12 km
SITE SUITABILITY FOR CHECKDAMS




                                             •From these check dams
                                             4.6, 0.4, 5.1 lakh cubic
              3                              meter water can be
                                             collected



                                             • These can irrigate 8.4 lakh
                                             squire meter land during
                  2                          rabi season



         1
                      LEGEND
                   checkdam/
                    Flooded area
0                 12 km   1.VOL - 0.46MCUM
                          2.VOL - .04 MCUM
                          3.VOL- 0.5 Mcum
Interlinking………..



Krishna
Reservoir




                    Velugodu
                    Reservoir
Kindly visit us at   www.iirs-nrsc.gov.in

Related sites:       www.nrsc.gov.in
                     www.isro.gov.in

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Iirs overview -Remote sensing and GIS application in Water Resources Management

  • 1. Remote Sensing and GIS Application in Water Resources Management By Dr. S.P. Aggarwal spa@iirs.gov.in Indian Institute of Remote Sensing (National Remote Sensing Centre) ISRO, Dept. of Space, Govt. of India Dehradun
  • 2. Indian scenario Water Resources of India – A Glance Average Annual Rainfall - 4000 billion cu.m. Natural Runoff - 1953 billion cu.m. ( Surface & Ground Water) Estimated Utilisable Surface Potential - 690 billion cu. m. Ground Water Resource - 432 billion cu. m. Available Groundwater Resource for Irrigation - 361 billion cu. m. Net Utilisable Ground Water Resources for Irrigation - 325 billion cu. m. Groundwater provision for Domestic, Industrial - 71 billion cu. m. and Other About 1700 liter/person/day Source : ICID NEWS, March, 2000
  • 3. Problem! Spatial variation 120 mm to 12000 mm Seasonal Variation Rainy season: 70%-90% Annual variation Some times drought year some times wet year
  • 5. For effective Water Management we need Near real time hydrological information Temporal information : Seasonal variation Spatial information: Point v/s Spatial Synopticity : think globally and act locally Remote Sensing provides Near real time hydrologic information : within few hours to few days Temporal : 30 minutes to few days Spatial information :1 Meter to few km. spatial resolution Synoptic coverage: 25 km to 800 km. or more Geographic Information System is used ….. Develop spatial database Integrate databases ( remote sensing , topographic, Socioeconomic etc . ) and develop water resources management strategies through SDSS
  • 6. Imaging capability of India Imaging ‘Hot spot’ Met/Ocean Observation communication All weather High mapping resolution imaging Laser Terrain Mapper Real Time Mapping
  • 7. 1999 1995/1997 2003 IRS-1C/1D LISS-3 (23/70M, RESOURCESAT-1 STEERABLE PAN (5.8 M); INSAT-2E CCD LISS3 - 23 M; 4 XS WiFS (188M) (1KM RESOLUTION; LISS4 - 5.8 M; 3- 1996 EVERY 30 MNUTESS) XS 2005 1994 AWIFS - 70 M; 4- IRS-P3 XS WiFS MOS 1999 CARTOSAT - 1 IRS-P2 X-Ray PAN - 2.5M, 30 KM, IRS-P4 F/A LISS-2 OCEANSAT OCM, MSMR 2007 1988/91 IRS-1A/1B LISS-1&2 (72/36M, INDIAN CARTOSAT-2 4 BANDS; VIS & NIR) IMAGING PAN – 0.8M 1982 SYSTEMS 2009 RS-D1 IMAGING IMPROVEMENTS MEGHA- 1979 1KM TO 0.8 M RESOLUTION TROPIQUES GLOBAL COVERAGE APPLICATION-SPECIFIC BHASKARA
  • 8. OBSERVATION CAPABILITY INSAT – IRS LISS-3 VHRR/CCD EVERY 30 MIN. IMAGING EACH EVERY 22 DAYS IMAGING IRS – OCM IRS – PAN towards…. EVERY 2 DAYS IMAGING EVERY 5 DAYS IMAGING IRS – WiFS CARTOSAT +AIR- BORNE EVERY 5 DAYS IMAGING SENSORS
  • 9. OPERATIONAL APPLICATIONS • Flood Mapping & Management • Snowmelt Runoff moelling • Hydrological modelling • Irrigation water Management • Drought Monitoring • Rain Water Harvesting
  • 10. Flood Inundation Mapping and Damage Assessment
  • 11. Near Real-Time Flood Inundation Mapping Flood Damage Assessment Flood Risk Zone Mapping Flood forecasting and Spatial Warning System
  • 12. 1998 Brahmaputra Floods -Basinwise monitoring Assam State Water Resources Group,NRSC 08 Sept, 1998 IRS-1C WiFS
  • 13. 1998 Brahmaputra Floods - Inundation extent Marigaon District Marooned village <-- Flood inundation 10 Sept, 1998 IRS-1D WiFS 13 Sept, 1998 IRS-1D WiFS Inundated area 34,240 ha Villages affected 465 Water Resources Group,NRSC
  • 14. 1998 Brahmaputra Floods - Damage to road network Part of Marigaon district Pre-Flood DuringFlood <--Marooned village <-- Flood inundation IRS-1D PAN 03 March, 98 IRS-1C PAN 08 Sept, 98
  • 15. 29 Oct-6gmt 28 Oct-3gmt 30Oct-9gmt Oct-9gmt Oct-6gmt Oct-3gmt SUPER CYCLONE OVER ORISSA COAST INSAT IMAGES SHOWING THE CYCLONE MOVEMENT DURING 28 OCT TO 30 OCT, 1999 …...AND THE AFTERMATH • NEARLY 3.75 LAKH Ha. INUNDATED • ROAD, POWER AND COMMUNICATION NETWORKS SEVERELY AFFECTED IN 10 COASTAL DISTRICTS
  • 17. 3D VIEW OF FLOOD RISK ZONES OF ALLAHABAD CITY 100Year 79.00mt 50 25 Year 10Year 5
  • 18. Snow Melt Runoff Modelling
  • 19. Snow cover depletion 15/05/98 15/06/98 12/10/98 28/11/98 04/12/98 14/02/99 25/05/99 25/06/99 14/07/99 27/09/99 28/10/99 22/11/99
  • 20. September - I August - II July - III July - I zone 10 June - II Snow Cover Depletion Curves May - III zone 9 May - I April - II March - III zone 8 March - I February - II zone 7 January - III January - I zone 6 December - II November - III November - I O ctober - II 100 90 80 70 60 50 40 30 20 10 0 Snow cover [% ]
  • 22. SRM calculation The basic equation of SRM model is Qn+1 = [CSn an (Tn + ΔTn) Sn+ CRn Pn] A·10000 (1-kn+1)+ Qn kn+1 86400 T, S and P are variables to be measured or determined each day. CR, CS, lapse rate to determine T, TCRIT, k are parameters which are characteristic for a given basin. As an Example for a basin of an elevation range of 1500 m. It is sliced in three elevation zones A, B and C of 500 m each, the model equation becomes Qn+1 = {[cSAn · aAn (Tn + ΔTAn) SAn + cRAn · PAn] + AA86400 * 10000 [cSBn · aBn (Tn + ΔTBn ) SBn + cRBn · PBn ] + AB* 10000 86400 [cSCn · aCn (Tn + ΔTCn ) SCn + cRCn · PCn ] +AC* 10000 )} + Qn ·kn+1 (1-kn+1 86400 In this project all the model parameters are derived as 10 daily average values and used to compute the 10 daily average runoff.
  • 23. Dv(%)=1.8 Dec ember II estimated real Nov ember II O c tober II Martinec-Rango SRM (1998-1999) September II Augus t II J uly II J une II May II April II • Snow Cover Area Marc h II • Temperature • Precipitation February II J anuary II Dec ember II Nov ember II O c tober II September II Augus t II J uly II J une II 240 220 200 180 160 140 120 100 80 60 40 20 0 discharge [m /s] 3
  • 24. Martinec-Rango SRM (calibration 2000-2001) September - I measured estimated Dv(%)=15.3 August - II July - III July - I June - II May - III May - I April - II March - III March - I February - II Year: 1998 January - III January - I December - II November - III November - I O ctober - II 180 160 140 120 100 80 60 40 20 0 Discharge [m3 /s]
  • 26. Introduction Hydrological System Input Output System Input: Rainfall System: Watershed/Basin Output: Runoff
  • 28. DRAINAGE MAP OF KULSI BASIN
  • 29. DIGITAL ELEVATION MODEL OF KULSI BASIN
  • 30. ASPECT MAP OF KULSI BASIN
  • 31. Land use/ Land cover Change study (1991 to 2002)
  • 32. Satellite Data (26-11-1991)
  • 33. Satellite Data (17-02-2002)
  • 34. LAND USE/LAND COVER MAP OF KULSI BASIN FOR THE YEAR 1991
  • 35. LAND USE /LAND COVER MAP OF KULSI BASIN FOR THE YEAR 2002
  • 36. Land use/ Land cover statistics for the year 1991 & 2002 LULC 1991 2002 Difference Sq. Km Sq. Km Sq. Km Dense Forest 849.38 823.17 -26.21 (2621 Ha) Open Forest 235.09 249.17 14.08 Agriculture 490.44 502.23 11.79 River/Streams 21.32 21.32 -
  • 38. Daily Simulated and observed Runoff (2002) Date 1 24 47 70 93 116 139 162 185 208 231 254 277 300 323 346 369 392 0 100 90 50 80 70 100 60 Rainfall Rainfall 150 50 Simulate Runoff 40 Observed Runoff 200 30 20 250 10 300 0
  • 39. Impact of LULC Changes on hydrology (1991 to 2002)
  • 40. Impact on Runoff 160 140 120 Runoff(mm) 100 Simulated Runoff (mm ) for 1991 80 Simulated runoff (mm ) for 60 2002 40 20 0 v n l p ar ay Ju No Ja Se M M Month
  • 41. Impact on Sediment Yield 1.4 Sediment Yield (T/Ha) 1.2 1 Monthly Sediment 0.8 Yield for 1991 0.6 Monthly Sediment 0.4 Yield for 2002 0.2 0 v n l p ar ay Ju No Ja Se M M Month
  • 42. Comparison Forest Rain Runoff Sediment Yield 849.38 sq. km 957mm 75 mm 1991 (53 %) (7.8%) 823.17 sq.km 2915 mm 505 mm 2002 (51.5%) (17.3%) Model is run for same rainfall 849.38 sq. km 2915 mm 777.5 million M3 2.41 t/ha 1991 (53 %) Increased Runoff: 27.1 million Cub. M 823.17 sq.km 2915 mm 804.6 million M3 3.88 t/ha 2002 (51.5%)
  • 43. one of the worst natural disasters causes extensive damage to food grain production widespread desert condition in the long run affects social and economic life of millions of people every year Water Resources Group,NRSC
  • 44. NATIONAL AGRICULTURAL DROUGHT ASSESSMENT AND MONITORING SYSTEM (NADAMS) GROUND SYSTEM SATELLITE SYSTEM CROP VI VI RAINFALL ARIDITY LANDUSE CALENDAR STATISTICS MAPS GEOGRAPHIC INFORMATION SYSTEM DROUGHT BULLETIN AND MAP
  • 45. NATIONAL AGRICULTURAL DROUGHT ASSESSMENT & MONITORING SYSTEM ( NADAMS ) NOAA BASED VEGETATION INDEX ANDHRA PRADESH ADILABAD DISTRICT, A.P DISTRICT & MANDAL-WISE ASSESSMENT Water Resources Group,NRSC
  • 46. India NOAA-AVHRR based NDVI - August 1999 Andhra Pradesh IRS-WiFS based NDVI - August 1999 Water Resources Group,NRSC
  • 48. Schematic diagram of an irrigation command D D River Main canal DAM F M D D
  • 49. Part of Upper ganges canal as seen by satellite
  • 52. Bhimgauda barrage thru quickbird (65 cm)
  • 56. Crop type Crop growth stage Canal network Rainfall Soil map
  • 57. Indian Imaging System – Till now 1979/81 1999/2003 BHASKARA –1 /2 Overall INSAT-2E VIDICON, VHRR, CCD (1 km) SAMIR Mapping INSAT-3A VHRR,CCD 1999 1988/91 IRS-1A & 1B •Crop Type IRS-P4 (Oceansat– 1) LISS-1&2 OCM (360m) (72/36m) •Crop Condition MSMR •Crop acreage 2001 1994 Estimation IRS-P5(Cartosat-1) TES IRS-P2 PAN (1m) LISS-2 1996 Canal2003 IRS-P3 Network IRS-P6 (Resourcesat-1) WiFS, LISS 3 (23m) LISS 4 (5.8m) MOS X-Ray AWiFS (55m) 2005&7 1995/1997 •Canal IRS-P5(Cartosat-1) IRS-1C/1DAlignment LISS-3 (23/70m) PAN-(2.5 m) F/A •Structures etc. PAN (5.8 m) WiFS (188m) Cartosat2 (80 cm)
  • 58. ology COMMAND AREA MAP d tho Me DISTRIBUTORY BOUNDARY MAP CROP AREA ESTIMATION IN MET. DATA EACH BOUNDARY temp.,wind speed,RH,sunshinehr Kc VALUES CROP WAT MODEL EFFECIENCES IWR ETo Supply Data Demand-Supply analysis
  • 59. CLASSIFIED IMAGE OF KHARIF SEASON OF K.PATAN COMMAND
  • 60. CLASSIFIED IMAGE OF RABI SEASON OF K.PATAN COMMAND
  • 61. CLASSIFIED DIGITAL ELEVATION MODEL OF K.PATAN COMMAND
  • 62. NDVI OF K.PATAN COMMAND OF OCTOBER 1998
  • 63. VARIATION OF NDVI WITH PLACE & TIME 0.450 0.41 0.400 0.350 0.300 0.31 NDVI 0.250 0.200 0.21 0.150 0.14 0.12 0.100 0.11 0.050 0.000 PATAN ANANTPURA MAKHEEDA DISTRIBUTORY DISRIBUTORY DISTRIBUTORY AVG.OCTOBER NDVI DISTRIBUTORIES AVG.JANUARY NDVI
  • 64. KHARIF SEASON Head Reach Middle Reach CALCULATED IRRIGATION WATER REQUIREMENT & ACTUAL IRRIGATION WATER CALCULATED IRRIGATION WATER REQUIREMENT & ACTUAL SUPPLY IRRIGATION WATER SUPPLY (KHARIF SEASON ,ANANTPURA DISTRIBUTORY) ( KHARIF SEASON, PATAN DISTRIBUTORY) 900 800 500 769.54 425.29 V O L UM E h a-m 400 V O L U M E h a -m 700 600 592.33 337.01 300 287.03 500 235.08 200 182.20 400 401.84 329.07 100 102.67 120.19 300 200 0 11.68 0.00 6.63 0.00 0.00 100 MAY JUNE JULY AUGUST SEPTEMBER OCTOBER 44.80 25.42 0 MAY JUNE JULY AUGUST SEPTEMBER OCTOBER MONTH CALCULATED IWR ACTUAL IWS MONTH CALCULATED IWR ACTUAL IWS Tail End CALCULATED IRRIGATION WATER REQUIREMENT & ACTUAL IRRIGATION WATER SUPPLY (KHARIF SEASON,MAKHEEDA DISTRIBUTORY) 700 664.54 600 500 487.55 VOLUME,ha-m 400 300 314.75 283.35 200 151.16 100 79.35 71.13 40.36 0 0.00 0.00 0.00 0.00 MAY JUNE JULY AUGUST SEPTEMBER OCTOBER MONTH CALCULATED IWR ACTUAL IWS
  • 66. Rain Water Harvesting RWH: Urban Area RWH: Rural Area
  • 68. Estimation of Rain water harvesting potential in a City using high resolution Data
  • 69. A case Study : Area: 1115 Sq. m. Annual Rainfall: 2000 mm Runoff coefficient : 0.9 Total Runoff to be collected: 1115 x 2000@1000 x 0-9 litre = 20 lakh litre
  • 71. DECISION RULES BY IMSD & INCOH Farm Ponds: Flat topography and low soil permeability is required. Check Dams: Medium slope, low permeability is required. The available area should be more than 25 hectors, preferably check dams should be constructed at lower order streams (upto third order). Ground Water Recharges: Flat to moderate slope and soil should be permeable. Percolation Tanks: Flat topography and pervious strata are required. The available area should be more than 40 hectares. Bundhis: Medium permeable soils, adequate area are the requisites for bundhis and preferably it should be nearer to cultivated land.
  • 72. FIELD DATA SATELLITE DATA SOI TOPO MAPS METEOROLIGICAL DATA DIGITAL IMAGE PROCESSING CONTOUR MAP GROUND TRUTH LANDUSE MAP DIGITAL ELEVATION MODEL RUNOFF POTENTIAL MAP SOIL MAP SLOPE MAP USING TM MODEL HIGH RUNOFF CL.SLOPE MAP POTENTIAL AREA MAP BUFFER MAP FOR OVERLAY VILLAGES & AGRICULTURE LAND ANALYSIS SITE SUITABILITY MAP
  • 73. A Case Study of Bisora watershed, Orrissa
  • 74. SOIL MAP LANDUSE MAP CL SLOPE MAP DRAINAGE
  • 75. FINAL CROSS MAP CROSS MAP OF LULC SOIL, CL SLOPE AND RUNOFF POTENTIAL 0 12 km
  • 76. SITE SUITABILITY MAP FOR FARMPONDS Suitable site (total 85.2 H) 0 12 km
  • 77. SITE SUITABILITY FOR CHECKDAMS •From these check dams 4.6, 0.4, 5.1 lakh cubic 3 meter water can be collected • These can irrigate 8.4 lakh squire meter land during 2 rabi season 1 LEGEND checkdam/ Flooded area 0 12 km 1.VOL - 0.46MCUM 2.VOL - .04 MCUM 3.VOL- 0.5 Mcum
  • 79. Kindly visit us at www.iirs-nrsc.gov.in Related sites: www.nrsc.gov.in www.isro.gov.in