Application of GIS and Remote Sensing Techniques in Identification, Assessment and Development of Groundwater Resources

  • Fares M. Howari
  • Mohsen M. Sherif
  • Vijay P. Singh
  • Mohamed S. Al Asam


Geographical Information Systems (GIS) and Remote Sensing (RS) techniques have emerged as efficient and powerful tools in different fields of science over the last two decades. The GIS has the ability to store, arrange, retrieve, classify, manipulate, analyze and present huge spatial data and information in a simple manner. The RS technique is used to collect detailed information in space and time even from inaccessible areas. Nowadays, both GIS and RS are regarded as essential tools for groundwater studies especially for extended and complex systems.


Geographic Information System Hydrological Modeling Land Surface Temperature Advance Very High Resolution Radiometer Advance Very High Resolution Radiometer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Albertson, J.D., Kustas, W.P. and Scanlon, T.M. (2001). Large eddy simulation over heterogeneous terrain with remotely sensed land surface conditions. Water Resour. Res. 377: 1939–1953.CrossRefGoogle Scholar
  2. Allord, G.J. and Scarpace, F.L. (1979). Improving Streamflow Estimates through Use of Landsat. In: Satellite Hydrology, 5th Annual William T. Pecora Memorial Symposium on Remote Sensing: Sioux Falls, SD. pp. 284–291.Google Scholar
  3. Argus Interware (1997). Argus Numerical Environment and MeshMaker User’s Guide, 510 p.Google Scholar
  4. Barrett, E.C. and Kidd, C. (1987). The use of SMMR data in support of a VIR/IR satellite rainfall monitoring technique in highly-contrasting climatic environments. In: Passive Microwave Observing from Environmental Satellites, a Status Report (ed. J.C. Fischer), NOAA Tech. Rep. NESDIS 35, Washington DC, pp. 109–123.Google Scholar
  5. Barrett, E.C. and Curtis, L.F. (1982). Introduction to Environmental Remote Sensing. Chapman and Hall, London.Google Scholar
  6. Barrett, E.C. and Martin, D.W. (1981). The Use of Satellite Data in Rainfall Monitoring. Academic Press, London, 340 pp.Google Scholar
  7. Barrett, E.C. (1970). The estimation of monthly rainfall from satellite data. Mon. Weather. Rev., 98: 322–327.CrossRefGoogle Scholar
  8. Barton, I.J. (1978). A case study comparison of microwave radiometer measurements over bare and vegetated surfaces. J. Geophy. Res., 83: 3513–3517.Google Scholar
  9. Beven, K.J. and Moore, I.D. (Eds.) (1992). Terrain analysis and distributed modelling in hydrology. Chichester, UK: Wiley & Sons.Google Scholar
  10. Bhaskar, N.R., Wesley, P.J. and Devulapalli, R.S. (1992). Hydrologic parameter estimation using geographic information systems. Journal of Water Resources Planning and Management, 118: 492–512.Google Scholar
  11. Blyth, K. (1993). The use of microwave remote sensing to improve spatial parameterization of hydrological models. J. of Hydrology, 152: 103–129.CrossRefGoogle Scholar
  12. Brimicombe, A.J. and Bartlett, J.M. (1996). Linking GIS with hydraulic modeling for flood risk assessment: The Hong Kong approach. In: M.F. Goodchild, L.T. Steyaert and B.O. Parks (Eds.), GIS and environmental modeling: Progress and research issues (pp. 165–168). Fort Collins Co: GIS World Books.Google Scholar
  13. Camillo, P.J., Gurney, R.J. and Schmugge, T.J. (1983). A soil and atmospheric boundary layer model for evapotranspiration and soil moisture studies. Water Resources Research, 19: 371–380.CrossRefGoogle Scholar
  14. Carlson, T.N. and Buffum, M.J. (1989). On estimating total daily evapotranspiration from remote surface measurements. Remote Sens. Environ., 29: 197–207.CrossRefGoogle Scholar
  15. Carroll, S.S. and Carroll, T.R. (1989). Effect of forest biomass on airborne snow water equivalent estimates obtained by measuring terrestrial gamma radiation. Remote Sensing Environment, 7: 313–320.CrossRefGoogle Scholar
  16. Carroll, T.R. and Vadnais, K.G. (1980). Operational airborne measurement of snow water equivalent using natural terrestrial gamma radiation. In: Proc. 48th Annual Western Snow Conf., Laramie, WY: 97–106.Google Scholar
  17. Chow, V.T., Maidment, D.R. and Mays, L.W. (1988). Applied hydrology. New York: McGraw-Hill.Google Scholar
  18. Clark, M.J. (1996). Professional integrity and the social role of hydro-GIS. In: K. Kovar and H.P. Nachtnebel (Eds.), HydroGIS: Applications of geographic information systems in hydrology and water resources management (IAHS Publication, 235: 279–287). Wallingford, CT: International Association of Hydrological Sciences.Google Scholar
  19. Clark, M.J. (1998). Putting water in its place: A perspective on GIS in hydrology and water management. Hydrological Processes, 126: 823–834.CrossRefGoogle Scholar
  20. Das, D. (1990). Satellite remote sensing in subsurface water targeting. Proceeding ACSM-ASPRS annual convention, 99–103.Google Scholar
  21. Das, D. (1996). Environmental appraisal for water resource development proceedings. International conference on Disaster Management (ICODIM) 499–507 Guwahati: India, Organised by Tejpur University.Google Scholar
  22. DeVantier, B.A. and Feldman, A.D. (1993). Review of GIS applications in hydrologic modeling. Journal of Water Resources Planning and Management, 119: 246–261.CrossRefGoogle Scholar
  23. DeVries, J.J. and Hromadka, T.V. (1993). Computer models for surface water. In: D.R. Maidment (Ed.), Handbook of hydrology (pp. 23.1–24). New York: McGraw.Google Scholar
  24. Dewey, K.F. and Heim, R. Jr. (1981). Satellite observations of variations in northern hemisphere seasonal snow cover. NOAA Technical Report NESS 87, Washington DC, 83 pp.Google Scholar
  25. Dillard, J.P. and Orwig, C.E. (1979). Use of satellite data in runoff forecasting in the heavily forested, cloud covered Pacific northwest. Proc. Final Workshop on Operational Applications of Satellite Snow Cover Observations. NASA CP-2116, pp. 127–150.Google Scholar
  26. Djokic, D., Coates, A. and Ball, J.E. (1995). GIS as integration tool for hydrologic modeling: A need for generic hydrologic data exchange format. Paper presented in the 1995 ESRI User Conference. Redlords, CA, 22–26 May. Available: p245.htmlGoogle Scholar
  27. Dozier, J. (1984). Snow reflectance from Landsat-4 thematic mapper. IEEE Trans. Geosci. and Rem. Sens. GE-22(3): 323–328.CrossRefGoogle Scholar
  28. Engman, E.T. and Gurney, R.J. (1991). Remote Sensing in Hydrology. Chapman and Hall, London, 225 pp.Google Scholar
  29. Engman, E.T., Angus, G. and Kustas, W.P. (1989). Relationship between the hydrologic balance of a small watershed and remotely sensed soil moisture. Proc. IAHS Third Intl. Assembly, Baltimore, IAHS Publ., 186: 75–84.Google Scholar
  30. Gossel, W., Ebraheem, A.M. and Wycisk, P. (2004). A very large scale GIS-based groundwater flow model for the Nubian sandstone aquifer in Eastern Sahara (Egypt, northen Sudan and Eastern Libya). Report—Hydrogeology Journal.Google Scholar
  31. Howari, F.M., Goodell, P.C. and Miyamoto, S. (2002). Spectral properties of salt crusts formed on saline soils. J. Environ. Qual., 31: 1453–1461.CrossRefGoogle Scholar
  32. Howari, F.M. (2003). The use of remote sensing data to extract information from agricultural land with emphasis on soil salinity. Australian Journal of Soil Research, 41(7): 1243–1253.CrossRefGoogle Scholar
  33. Lanza, L.G., Schultz, G.A. and Barrett, E.C. (1997). Remote sensing in hydrology: Some downscaling and uncertainty issues. Physics and Chemistry of The Earth, 22(3–4): 215–219.CrossRefGoogle Scholar
  34. Schmugge, T.J., William, P. Kustas, Jerry, C. Ritchie, Thomas J. Jackson and Al Rango (2002). Remote sensing in hydrology. Advances in Water Resources, 25(8–12): 1367–1385.CrossRefGoogle Scholar
  35. Sherif, M.M. and others (2004). Assessment of the Effectiveness of Al Bih, Al Tawiyean and Ham Dams in Groundwater Recharge using Numerical Models. Progress Report, Ministry of Agriculture and Fisheries, Dubai, UAE.Google Scholar
  36. Su, Z.B. Troch P.A. (2003). Applications of quantitative remote sensing to hydrology. Physics and Chemistry of the Earth, 28(1–3): 1–2.Google Scholar
  37. Sui, D.Z. and Maggio, R.C. (1999). Integrating GIS with hydrological modeling: practices, problems, and prospects. Computers, Environment and Urban Systems, 23(1): 33–51.CrossRefGoogle Scholar
  38. Voss, C.I. and Provost, A.M. (2002). SUTRA: a model for saturated-unsaturated variable-density ground-water flow with solute or energy transport. US. Geological Survey Water Resources Investigation Report WRIR 02-4231, 250 pp.Google Scholar
  39. Voss, C.I. (1984). SUTRA—Saturated-Unsaturated Transport: A Finite Element Simulation Model for Saturated-Unsaturated, Fluid-Density-Dependent Groundwater Flow with Energy Transport or Chemically-Reactive Single Solute Transport: US. Geological Survey Water Resources Investigation Report WRIR 84-4369 (revised 1990, 1997), 409 pp.Google Scholar
  40. Winston, R.B. and Voss, C.I. (2003). SutraGUI, a graphical-user interface for SUTRA, a model for saturated-unsaturated variable-density ground-water flow with solute or energy transport. US. Geological Survey Open-File report 03-285, 114 pp.Google Scholar

Copyright information

© Capital Publishing Company 2007

Authors and Affiliations

  • Fares M. Howari
    • 1
  • Mohsen M. Sherif
    • 2
  • Vijay P. Singh
    • 3
  • Mohamed S. Al Asam
    • 4
  1. 1.Geology Dept., College of ScienceUAE UniversityAl AinUAE
  2. 2.Civil and Environmental Engineering Dept., College of EngineeringUAE UniversityAl AinUAE
  3. 3.Department of Civil and Environmental EngineeringLouisiana State UniversityBaton RougeUSA
  4. 4.Ministry of Agriculture and FisheriesDubaiUAE

Personalised recommendations