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

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Remote sensing and GIS application in Water Resources Management- By S.P. Aggarval spa@iirs.gov.in Indian Institute of Remote sensing ISRO, Department of space, Dehradun

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

  1. 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. 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. 3. Problem!Spatial variation 120 mm to 12000 mmSeasonal Variation Rainy season: 70%-90%Annual variation Some times drought year some times wet year
  4. 4. Solution!Water Resources Management
  5. 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 locallyRemote 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 moreGeographic Information System is used ….. Develop spatial database Integrate databases ( remote sensing , topographic, Socioeconomic etc . ) and develop water resources management strategies through SDSS
  6. 6. Imaging capability of India Imaging ‘Hot spot’ Met/Ocean Observation communication All weather High mappingresolution imaging Laser Terrain Mapper Real Time Mapping
  7. 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 1988/91IRS-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. 8. OBSERVATION CAPABILITY INSAT – IRS LISS-3 VHRR/CCDEVERY 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- BORNEEVERY 5 DAYS IMAGING SENSORS
  9. 9. OPERATIONAL APPLICATIONS• Flood Mapping & Management• Snowmelt Runoff moelling• Hydrological modelling• Irrigation water Management• Drought Monitoring• Rain Water Harvesting
  10. 10. Flood Inundation Mappingand Damage Assessment
  11. 11. Near Real-Time FloodInundation MappingFlood DamageAssessmentFlood Risk ZoneMappingFlood forecasting andSpatial WarningSystem
  12. 12. 1998 Brahmaputra Floods -Basinwise monitoring Assam State Water Resources Group,NRSC 08 Sept, 1998 IRS-1C WiFS
  13. 13. 1998 Brahmaputra Floods - Inundation extentMarigaon District Marooned village <-- Flood inundation10 Sept, 1998 IRS-1D WiFS 13 Sept, 1998 IRS-1D WiFS Inundated area 34,240 ha Villages affected 465 Water Resources Group,NRSC
  14. 14. 1998 Brahmaputra Floods - Damage to road network Part of Marigaon districtPre-Flood DuringFlood <--Marooned village <-- Flood inundation IRS-1D PAN 03 March, 98 IRS-1C PAN 08 Sept, 98
  15. 15. 29 Oct-6gmt28 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
  16. 16. 3D VIEW OF FLOOD RISK ZONES OF ALLAHABAD CITY 100Year 79.00mt 50 25 Year 10Year 5
  17. 17. Snow Melt Runoff Modelling
  18. 18. Snow cover depletion15/05/98 15/06/98 12/10/98 28/11/98 04/12/98 14/02/9925/05/99 25/06/99 14/07/99 27/09/99 28/10/99 22/11/99
  19. 19. September - I August - II July - III July - I zone 10 June - IISnow 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 [% ]
  20. 20. 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 becomesQn+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 86400In this project all the model parameters are derived as 10 daily average values and used to compute the 10 daily average runoff.
  21. 21. Dv(%)=1.8 Dec ember II estimated real Nov ember II O c tober IIMartinec-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
  22. 22. 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]
  23. 23. Hydrological Modelling
  24. 24. IntroductionHydrological System Input Output System Input: Rainfall System: Watershed/Basin Output: Runoff
  25. 25. LOCATION OF KULSI BASIN
  26. 26. DRAINAGE MAP OF KULSI BASIN
  27. 27. DIGITAL ELEVATION MODEL OF KULSI BASIN
  28. 28. ASPECT MAP OF KULSI BASIN
  29. 29. Land use/ Land cover Change study (1991 to 2002)
  30. 30. Satellite Data (26-11-1991)
  31. 31. Satellite Data (17-02-2002)
  32. 32. LAND USE/LAND COVER MAP OF KULSI BASIN FOR THE YEAR 1991
  33. 33. LAND USE /LAND COVER MAP OF KULSI BASIN FOR THE YEAR 2002
  34. 34. Land use/ Land cover statistics for the year 1991 & 2002LULC 1991 2002 Difference Sq. Km Sq. Km Sq. KmDense Forest 849.38 823.17 -26.21 (2621 Ha)Open Forest 235.09 249.17 14.08Agriculture 490.44 502.23 11.79River/Streams 21.32 21.32 -
  35. 35. Hydrologic Simulation
  36. 36. 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 60Rainfall Rainfall 150 50 Simulate Runoff 40 Observed Runoff 200 30 20 250 10 300 0
  37. 37. Impact of LULC Changes on hydrology (1991 to 2002)
  38. 38. Impact on Runoff 160 140 120Runoff(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
  39. 39. 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
  40. 40. Comparison Forest Rain Runoff Sediment Yield 849.38 sq. km 957mm 75 mm1991 (53 %) (7.8%) 823.17 sq.km 2915 mm 505 mm2002 (51.5%) (17.3%) Model is run for same rainfall 849.38 sq. km 2915 mm 777.5 million M3 2.41 t/ha1991 (53 %) Increased Runoff: 27.1 million Cub. M 823.17 sq.km 2915 mm 804.6 million M3 3.88 t/ha2002 (51.5%)
  41. 41. one of the worst natural disasterscauses extensive damage to foodgrain productionwidespread desert condition in thelong runaffects social and economic life ofmillions of people every year Water Resources Group,NRSC
  42. 42. NATIONAL AGRICULTURAL DROUGHT ASSESSMENT AND MONITORING SYSTEM (NADAMS) GROUND SYSTEM SATELLITE SYSTEM CROP VI VIRAINFALL ARIDITY LANDUSE CALENDAR STATISTICS MAPS GEOGRAPHIC INFORMATION SYSTEM DROUGHT BULLETIN AND MAP
  43. 43. 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
  44. 44. IndiaNOAA-AVHRR based NDVI - August 1999 Andhra Pradesh IRS-WiFS based NDVI - August 1999 Water Resources Group,NRSC
  45. 45. IRRIGATION WATERMANAGEMENT: RS GIS Approach
  46. 46. Schematic diagram of an irrigation command D D River Main canal DAM F M D D
  47. 47. Part of Upper ganges canal as seen by satellite
  48. 48. IRS 1D Pan(5.8)
  49. 49. Cartosat 1(2.5 m)
  50. 50. Bhimgauda barrage thru quickbird (65 cm)
  51. 51. Branching of canals
  52. 52. Superpassage
  53. 53. Complex…..why?
  54. 54. Crop typeCrop growth stageCanal networkRainfallSoil map
  55. 55. 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)
  56. 56. ology COMMAND AREA MAP d tho Me DISTRIBUTORY BOUNDARY MAP CROP AREA ESTIMATION INMET. DATA EACH BOUNDARYtemp.,wind speed,RH,sunshinehrKc VALUES CROP WAT MODEL EFFECIENCES IWR ETo Supply Data Demand-Supply analysis
  57. 57. CLASSIFIED IMAGE OF KHARIF SEASON OF K.PATAN COMMAND
  58. 58. CLASSIFIED IMAGE OF RABI SEASON OF K.PATAN COMMAND
  59. 59. CLASSIFIED DIGITAL ELEVATION MODEL OF K.PATAN COMMAND
  60. 60. NDVI OF K.PATAN COMMAND OF OCTOBER 1998
  61. 61. VARIATION OF NDVI WITH PLACE & TIME 0.450 0.41 0.400 0.350 0.300 0.31NDVI 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
  62. 62. 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 400V 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
  63. 63. Rain Water Harvesting
  64. 64. Rain Water HarvestingRWH: Urban AreaRWH: Rural Area
  65. 65. RWH: Urban Area
  66. 66. Estimation of Rain water harvesting potentialin a City using high resolution Data
  67. 67. 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
  68. 68. RWH: Rural area
  69. 69. 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.
  70. 70. FIELD DATA SATELLITE DATA SOI TOPO MAPS METEOROLIGICAL DATA DIGITAL IMAGE PROCESSING CONTOUR MAP GROUND TRUTH LANDUSE MAP DIGITAL ELEVATION MODELRUNOFF POTENTIAL MAP SOIL MAP SLOPE MAP USING TM MODEL HIGH RUNOFF CL.SLOPE MAPPOTENTIAL AREA MAP BUFFER MAP FOR OVERLAY VILLAGES &AGRICULTURE LAND ANALYSIS SITE SUITABILITY MAP
  71. 71. A Case Study of Bisora watershed, Orrissa
  72. 72. SOIL MAP LANDUSE MAP CL SLOPE MAP DRAINAGE
  73. 73. FINAL CROSS MAP CROSS MAP OF LULC SOIL, CL SLOPE AND RUNOFF POTENTIAL 0 12 km
  74. 74. SITE SUITABILITY MAP FOR FARMPONDS Suitable site (total 85.2 H)0 12 km
  75. 75. 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 area0 12 km 1.VOL - 0.46MCUM 2.VOL - .04 MCUM 3.VOL- 0.5 Mcum
  76. 76. Interlinking………..KrishnaReservoir Velugodu Reservoir
  77. 77. Kindly visit us at www.iirs-nrsc.gov.inRelated sites: www.nrsc.gov.in www.isro.gov.in

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