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Iirs Role of Remote sensing and GIS in Ground water studies

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Role of Remote sensing and GIS in Ground water studies –Potentials. Constaints and case studies – By Dr S K Srivastav. Isro Dehradun

Role of Remote sensing and GIS in Ground water studies –Potentials. Constaints and case studies – By Dr S K Srivastav. Isro Dehradun

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  • 1. Role of Remote Sensing & GIS in Ground Water StudiesPotentials, Constraints and Case Studies Dr. S.K. Srivastav Indian Institute of Remote Sensing (National Remote Sensing Centre) ISRO, Dept. of Space, Govt. of India Dehra Dun e-mail: sksrivastav@iirs.gov.in
  • 2. Background RS data provide only the surface or near-surface information; therefore, a link must be established between the surface observation and the subsurface (groundwater) phenomena (Jackson, 2002). Of all the hydrological applications of remote sensing, the hydrogeological analysis is one of the most difficult tasks (Farnsworth et al., 1984). However, the spatially complete and temporal nature of the RS data provide excellent opportunities to hydrogeologists for improving the understanding of the hydro- geological system, especially in remote and unexplored areas (Hoffmann and Sander, 2007). Since RS data have limitations with regard to depth penetration, the best approach is to integrate the airborne, space-borne and ground-based remote sensing techniques with field measurements (Meijerink et al., 2007). The RS data are most useful when they are combined with GIS and numerical modelling (Becker, 2006). iirs/nrsc/nrsc/isro
  • 3. Potentials and constraintsVIS-NIR-SWIR Region Mapping of surface features of hydrogeological relevance (or g.w. indicators) for understanding the controls of ground water occurrence and movement . These include – lithologies, structures, geomorphology, drainage patterns, land use / land cover and soil moisture. The amount of information which can be extracted from RS data depends on many factors – type of data including spatial and spectral resolutions, scale of image, date of acquisition of the image, type and knowledge of terrain, experience/ skill of the interpreter, etc. Mapping and monitoring the spatial distribution of ground water exfiltration (effluent streams) and infiltration (influent streams) zones. However, quantifying the magnitude of flux from space is still a major challenge Moist soils, swampy/waterlogged zones and vegetation (in dry climate) indicate ground water occurrence at shallow depth. However, quantification of soil moisture not possible. Further, in humid areas, the relation between g.w. and vegetation is complex and does not readily indicate g.w. occurrence. iirs/nrsc/nrsc/isro
  • 4. DEMs generated using stereo images can be used to map the topographic attributesof the terrain.Spatial distribution and quantification of the magnitude of actual evapotranspiration rates(i.e. g.w. discharge by natural process and net draft for irrigation in g.w. irrigated areas)along with TIR and meteorological data. Absolute values estimated using SEBAL technique are often overestimated, however, the strength of RS data lies in providing the spatial patterns of g.w. use.Salt crusts provide an indication of high water table and also throw light ong.w. quality. iirs/nrsc/nrsc/isro
  • 5. Thermal Region Mapping moist soils and shallow water table areas. However, quantitative and temporal measurements of soil moisture are difficult. Mapping discharge of ground water into rivers, lakes and sea. Possibility of detection of such ground water discharges depends on temperature contrast and quantum of g.w. discharge. Quantification of g.w. discharge also not possible. Quantifying the spatial distribution of actual evapotranspiration rates in conjunction with VIS-NIR-SWIR and meteorological data. High resolution thermal images useful for mapping geothermal vents, hot springs, finding relation between distribution of hot springs and lineaments. iirs/nrsc/nrsc/isro
  • 6. Microwave Region Most suitable for mapping spatial distribution and temporal dynamics of soil moisture. Present configuration of microwave sensors provides soil moisture information restricted to 0–2 cm, and to areas free of dense vegetation cover. Coarse spatial resolution of the order of few kilometers is another major constraint. Detection of buried channels and palaeo-drainage up to certain depth (~ 2 m). Limited to only in hyper-arid conditions and in absence of surface cover. Generation of high-resolution digital elevation models (DEMs) using SAR data with a technique called radar or SAR interferometry (InSAR). Provides digital surface model (DSM) rather than digital terrain model (DTM). Height accuracy is of the order of few meters, therefore, elevations can not be directly used in quantitative g.w. flow modelling studies. iirs/nrsc/nrsc/isro
  • 7. Subtle changes in land surface elevation due to ground water withdrawalor recharge from/to the aquifers in unconsolidated sediments can bedetected using a technique called differential radar interferometry (D-InSAR). The limitations include – (1) low availability of suitable InSAR images; and (2) Temporal decorrelation of radar signal due to change in land cover and atmospheric conditions.Measuring surface water elevation using Radar altimetry at sub-meteraccuracy. However, the coarse spatial resolution limits its applicability only to large lakes and wetland systems. iirs/nrsc/nrsc/isro
  • 8. GRACE – A special satellite mission for quantifying seasonal andinter-annual variations in terrestrial water storage GRACE – Gravity Recovery and Climate Experiment (launched by NASA & DLR in 2002) Principle - Spatio-temporal changes in mass distribution causes perturbations in the orbits of twin satellites, separated by about 220 km, inducing change in the relative distance between two satellites, which is used to map the gravity field. Accuracy estimates for interannual and seasonal water storage variations are of the order of 9 mm (at 1300 km resolution) and 10–15 mm (for area >2 million km2) water equivalent, respectively (Guntner et al., 2007). For estimating ground water recharge, storage changes due to other components of terrestrial water storage such as snow, surface water (rivers, lakes and wetlands), soil moisture, and biomass are separated using auxiliary observations and numerical models . Coarse resolution limits its applicability to study ground water dynamics at basin/ continental/ global scale (>900,000 km2 ) iirs/nrsc/nrsc/isro
  • 9. RS & GIS applications in ground water Mapping of prospective ground water zones, Ground water quality zonation including finding zones vulnerable to pollution, Site selection for artificial ground water recharge structures, Inputs in ground water budgeting, Upscaling of aquifer related parameters/ recharge rate, Ground water information management, etc. iirs/nrsc/nrsc/isro
  • 10. Infiltration Vs. Exfiltration Zones(Examples: Doon Valley & Indo-Gangetic Plain iirs/nrsc/nrsc/isro
  • 11. A few conspicuous landforms(Example: part of Spiti Valley) Ground photo IRS LISS-3 Image Ground photoiirs/nrsc/nrsc/isro
  • 12. G.W. carriers and barriers(Examples: S. India) iirs/nrsc/nrsc/isro
  • 13. Surface manifestation of faults on satellite imageryvis- a-vis hydrogeological section(Example: Doon Valley) R. na 45 0 mu ± 47 5 Ya F 500 42 5 55 77 5 0 500 60 0 550 57 5 60 0 Legend 5 57 Nagsidh 55 F Piezometric Head (m amsl) Hill 475 50 0 0 500 (contour interval = 25 m) Surface/Ground Water Divide 475 450 450 Direction of Ground Water 400 . Movement aR Hills 0 ng 0 5 10 20 35 Ga River / Stream Kilometers 1 F 2 50 m Dehradun Southern F 3 4 Fan Piedmont 5 7 6 1 2 Dehradun Southern 3 Fan Piedmont 4 5 7 6 25 m Tube Well 2 km 100 m Topographic Surface 2 km Piezometric Surface High-permeability facies Low-permeability facies Intermediate-permeability facies Tube Well Aquifer Tapped Piezometric Surface/SWL (Source: Srivastav, 2008) iirs/nrsc/nrsc/isro
  • 14. Case Studies
  • 15. Ground Water Potential Zoning Segmentation or Hydrogeomorphic Approach using Satellite Imagery (Example – RGNDWM Project) GIS-based Integration of relevant data layers (Example – Doon Valley) iirs/nrsc/nrsc/isro
  • 16. RGNDWM Project Methodology IRS- LISS-III Data WGS 84 - UTM SOI toposheets SOI toposheets On screen Existing Existing WGS 84 -- UTM WGS 84 UTM interpretation maps maps Base map Lithological Structural Geomorphic Hydrological overlay map overlay Map overlay Map overlay Map overlay Integration Hydrogeomorphic units Evaluation of Identification of Observation Observation ground water locations for Well data Well data prospects recharge structures Map composition using GIS Ground water prospects map on 1: 50,000 Scale Geodatabase of ground water National Remote Sensing Agency iirs/nrsc/nrsc/isro
  • 17. iirs/nrsc/nrsc/isro
  • 18. RGNDWM Project Details of Map Legend: Lithological, Geomorphological, structural, Hydrological & base information along with .. 1. DEPTH TO WATER TABLE 2. RECHARGE CONDITIONS 3. NATURE OF AQUIFER MATERIAL 4. TYPE OF WELLS SUITABLE 5. DEPTH RANGE OF WELLS 6. YIELD RANGE OF WELLS 7. SUCCESS RATE OF WELLS 8. QUALITY OF WATER 9. STATUS OF GROUND WATER EXPLOITATION 10. TYPE OF RECHARGE STRUCTURES SUITABLE 11. PRIORITIZATION OF AREAS FOR RECHARGE STRUCTURES 12. REMARKS / PROBLEMS / LIMITATIONS iirs/nrsc/nrsc/isro
  • 19. RGNDWM Project States covered Phase-I Andhra Pradesh (part) 247 Karnataka 267 Kerala 67 Madhya Pradesh 458 Chhattisgarh 202 Rajasthan 413 Phase-II Jharkhand 129 Himachal Pradesh 91 Gujarat 210 Orissa 220Total Sheets Covered = 2304 iirs/nrsc/nrsc/isro
  • 20. RGNDWM Project Work in progress (Phase-III) Phase Coverage No. of Schedule / Maps Status I 6 States 1654 Completed II 4 States 650 Completed III A 6 States 1290 In progress (Sept 07- Sept 09) B 4 States 339 Recently Launched (June 08 – June 10)Phase-III A Phase-III B Sl. No. State No. of Maps Sl. No. State No. of Maps 1 AP (part) 204 1 Arunachal Pradesh 120 2 Assam 103 3 Jammu & Kashmir 360 2 Haryana 73 4 Maharashtra 455 3 Uttar Pradesh (part) 88 5 Punjab 82 4 West Bengal (part) 58 6 Uttarakhand 86 Total 339 Total 1290 iirs/nrsc/nrsc/isro
  • 21. RGNDWM Project A sample map (53J/4) of Uttarakhand (Phase-III) iirs/nrsc/nrsc/isro
  • 22. RGNDWM Project iirs/nrsc/nrsc/isro
  • 23. RGNDWM ProjectFeedback on the use of Ground Water Prospects Maps by State Govts. upto October 2008 State No. of Success No. of Recharge wells rate Structures Drilled Planned Constructed Andhra- Pradesh 43827 93% 478 478 Chhattisgarh 33413 92.5% 1155 327 Karnataka 47951 95% 2641 2589 Kerala 7730 92% 65 8 Madhya Pradesh 22006 90% 5190 3361 Rajasthan 98994 85 – 95% 320 320 Gujarat 12014 94.3 % 470 29 Orissa 292 92% Nil Nil Total 266227 10319 7112 iirs/nrsc/nrsc/isro
  • 24. GIS-based Integration(Example: Doon Valley, Uttarakhand) R. 4 Intermontane Valley Part na ± Ya mu Vikasnagar As 2a Mussoorie ± an R. Sahaspur y lle Va 2b on Do Dehra Dun Legend 1 Sw GW MB Prospects T MBT 0.10 - 0.39 Poor Litho/Geom boundary 0.39 - 0.58 Poor to Moderate ey Water Divide Doiwala all 0.58 - 0.68 Moderate to Good V Road on Rail 0.68 - 0.81 Good to V. Good Do District boundary So Rishikesh 0.81 - 1.0 V. Good to Excellent River/stream ng R. Settlement R. Hill/Scarp zone 0 5 10 a ng 3 Lineament (Thrust/Fault/Fracture) Kilometers Ga (d) (b) Ya mu na R. ± Hilly/Mountainous Part ± Dehra Dun Legend GW Sw Pros- pects 0.1 - 0.2 V. Low 0.2 - 0.32 Low (Source: Srivastav, 2008) 0.32 - 0.45 Low to Moderate 0.45 - 0.61 Moderate to Good 0.61 - 0.95 Good to V. Good R. 0 10 20 0 5 10 a ng Ga Kilometers Kilometers iirs/nrsc/nrsc/isro
  • 25. Data Layers (hill / mountainous part) (a) lithology; (b) lineament density; (c) dip-direction and slope-aspect relation; (d) relief; (e) curvature; (f) plan curvature; (g) profile curvature; (h) slope; (i) log of specific catchment area; (j) topographic wetness index.(Source: Srivastav, 2008) iirs/nrsc/nrsc/isro
  • 26. Data Layers (valley part) (a) geomorphology; (b) lithology; (c) depth to potentiometric surface; (d) distance to aquifer boundary; (e) distance to perennial stream; (f) distance to valley axis; (g) slope; (h) drainage density; and (i) recharge source.(Source: Srivastav, 2008) iirs/nrsc/nrsc/isro
  • 27. D-InSAR technique for detecting land subsidence due toground water withdrawal(Example: Kolkata city) GW2 GW2 3 0.0 3 1.0 0.0 2.5 L1 5.0 3.0 GW2 L1 GW2 4.0 4 4 L3 L3 L2 L2 Average subsidence Average subsidence rate = ~5mm/year rate = ~6.5mm/year (Max.) (Max.) L1 : Machhua Bazar . . GW23 and GW24: Piezometric pressure observation L2 : Calcutta University 1.0 points L3 : Rajabazar Science College Subsidence contour with figures in mm/year Estimated rate of subsidence during 1992–98 = 5 – 6.5 mm/yIHS colour composition of the interferograms showing subsidence fringes in Kolkata City during the1990s due to ground water withdrawal(Source: Chatterjee et al., 2007) iirs/nrsc/nrsc/isro
  • 28. 1. Rat-hole type coal mines and AMD Study under M.Sc. Geohazards Research (Blahwar, 2010)• Coal is extracted by an artisanal method of mining called as “rat-hole” mining.• Carried out by individuals and highly unorganized.• From literature: Water bodies polluted with acid mine drainage (AMD).
  • 29. “To identify and map the rat-hole type coal mines (Visual Interpret.)” CARTOSAT-1 PAN and RESOURCESAT-1 LISS-4 merged FCC depicting rat-hole type coal mines and other landscape features.
  • 30. “To determine the presence & hydro-chemical characteristics of AMD” Sampling locationsMonsoon14 – water samples; 4 additional – pH, EC, T; 8 – stream sedimentsNon-monsoon30 – water samples; 12 additional – pH, EC, T; 22 – stream sediments
  • 31. Mines as source of AMD? X-axis stream provenance S = Sedimentary rock M = Metamorphic rock S+M = Mixed sedimentary and metamorphic
  • 32. Geospatial analysis of fluoride incidence in ground water(Example: part of Raigarh Dist., Chhattisgarh) N Konpara W E #% % Kathrapalli Salehapara % % # Raikera #% S Nundaraha % # # # Auraimura kerakhol % % # Charbhanta # % # Banai Chirmura Bajarmura # % % % Gharghoda Dholnara % Bhalumuda# #% ## ##% Karuwahi % Kolam # Jhankhadarha Barkaspalli #%# # % Rodopalli ## # # # % % Muragaon Bhendra Jhariapalli Patrapalli# Chitwahi % #% # Saraitola # #% Baihamura ## % # # % #% ## # # % # #Dolesara # %# # # # % Pata # Mahuapalli # # #% Gare % # # % # Ukrapalli ## Devgarh Pata Bandhap# # LEGEND # % % # # % Kunjhemura Regaon # Jerekela % # % Village location Bhalumara #% % # Murhinar % Manjhapara # # % # Pre-monsoon sampling wells Amlidih Chhaiadoria Kachkoba % % # % Paved road # # # Basanpalli #% Unpaved road ## Tamnar % Parkipahri # Jhindolpara Amaghat % #% Gorhi # ## % # %(Source: Beg, 2009) iirs/nrsc/nrsc/isro
  • 33. Health Risk and Population at RiskPre-monsoonPost-monsoon Pre- and post-monsoon combined (Source: Beg, 2009) iirs/nrsc/nrsc/isro
  • 34. Ground water quality zonation using GIS(Example: part of Nalgonda Dist., A.P.) (Source: Kumar and Anjaneyulu, 2003) iirs/nrsc/nrsc/isro
  • 35. (Source: Kumar and Anjaneyulu, 2003) iirs/nrsc/nrsc/isro
  • 36. Ground water pollution potential zoning(Example: Solani watershed, Uttarakhand & U.P.)Method: DRASTIC Model (Aller et al., 1987) DI = DwDr + RwRr + AwAr + SwSr + TwTr + IwIr + CwCr (1) where DI is the Drastic Index, and w and r represent weights and ratings, respectively. D - Depth to ground water R - Recharge rate A - Aquifer media S - Soil Media T - Topography I - Impact of Vadose Zone C - Hydraulic conductivity of aquifer Higher the DRASTIC index, greater the relative pollution potential. iirs/nrsc/nrsc/isro
  • 37. 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E DEPTH TO WATER TABLE MAP Rainfall Recharge Map ± ± 30°150"N 30°150"N 30°150"N 30°150"N 30°100"N 30°100"N 30°100"N 30°100"N ( ! ( ! 30°50"N 30°50"N (( !! (( !! 30°50"N 30°50"N (( !!! ( (( !! ( ! ( ! ( ! ( ! !! (( ( ! ( ! ( ! 30°00"N ( ! 30°00"N 30°00"N 30°00"N ( ! ( ! ( ! ! ( LEGEND ( ! ( ! ( ! 29°550"N ( ! ( ! 29°550"N ( ! Dug well 29°550"N ( ! 29°550"N ( ! ( ! ( ! ( ! Tube Well ( ! ! ( LEGEND ( ! Depth to water table ( ! <107 mm/yr <5 m ( ! 107 - 161mm/yr (( !! ( ! 5-10 m 161 - 202 mm/yr 29°500"N 29°500"N ( ! 29°500"N 10-15 m ! ( 202 - 239 mm/yr 29°500"N ( ! 15-20 m 239 - 361 mm/yr Hilly Area Kilometers >20 m Kilometers 0 2 4 8 12 16 Hilly Area 0 2 4 8 12 16 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro
  • 38. 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E Aquifer Media Map Soil Media Map Slope Map ± ± 30°150"N ± 30°150"N 30°150"N 30°150"N 30°150"N 30°150"N 30°100"N 30°100"N 30°100"N 30°100"N 30°100"N 30°100"N 30°50"N 30°50"N 30°50"N 30°50"N 30°50"N 30°50"N 30°00"N 30°00"N 30°00"N 30°00"N 30°00"N 30°00"N 29°550"N 29°550"N 29°550"N 29°550"N 29°550"N 29°550"N percent slope 0-2 2-6 Legend (rating value) 6-12 29°500"N 29°500"N 29°500"N 4 Legend 29°500"N 29°500"N 29°500"N 12-18 6 sand and gravel >18 9 Hilly Area Kilometers Kilometers Kilometers Hilly area 0 2 4 8 12 16 Hilly Area 0 2 4 8 12 16 0 2 4 8 12 16 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro
  • 39. 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E Vadose Zone Media Map Hydraulic Conductivity Map ± ± 30°150"N 30°150"N 30°150"N 30°150"N 30°100"N 30°100"N 30°100"N 30°100"N 30°50"N 30°50"N 30°50"N 30°50"N 30°00"N 30°00"N 30°00"N 30°00"N 29°550"N 29°550"N 29°550"N 29°550"N Legend Legend in rating value 29°500"N 29°500"N sand and gravel with 2 29°500"N 29°500"N significant amount of silts and clay 4 sand and gravel 6 Kilometers Kilometers Hilly Area 0 2 4 8 12 16 Hilly Area 0 2 4 8 12 16 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro
  • 40. 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E DRASTIC INDEX MAP ± 30°150"N 30°150"N 30°100"N 30°100"N 30°50"N 30°50"N 30°00"N 30°00"N 29°550"N 29°550"N DRASTIC INDEX 115 - 132 132 - 142 142. - 152 29°500"N 29°500"N 152 - 163 163 - 181 Kilometers Hilly Area 0 2 4 8 12 16 77°450"E 77°500"E 77°550"E 78°00"E 78°50"E(Source: Than Zaw, 2008) iirs/nrsc/nrsc/isro