Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia View Full Text


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Article Info

DATE

2015-02

AUTHORS

Ayele Almaw Fenta, Addis Kifle, Tesfamichael Gebreyohannes, Gebrerufael Hailu

ABSTRACT

Sustainable development and management of groundwater resources require application of scientific principles and modern techniques. An integrated approach is implemented using remote sensing and geographic information system (GIS)-based multi-criteria evaluation to identify promising areas for groundwater exploration in Raya Valley, northern Ethiopia. The thematic layers considered are lithology, lineament density, geomorphology, slope, drainage density, rainfall and land use/cover. The corresponding normalized rates for the classes in a layer and weights for thematic layers are computed using Saaty’s analytical hierarchy process. Based on the computed rates and weights, aggregating the thematic maps is done using a weighted linear combination method to obtain a groundwater potential (GP) map. The GP map is verified by overlay analysis with observed borehole yield data. Map-removal and single-parameter sensitivity analyses are used to examine the effects of removing any of the thematic layers on the GP map and to compute effective weights, respectively. About 770 km2 (28 % of the study area) is designated as ‘very good’ GP. ‘Good’, ‘moderate’ and ‘poor’ GP areas cover 630 km2 (23 %), 600 km2 (22 %) and 690 km2 (25 %), respectively; the area with ‘very poor’ GP covers 55 km2 (2 %). Verification of the GP map against observed borehole yield data shows 74 % agreement, which is fairly satisfactory. The sensitivity analyses reveal the GP map is most sensitive to lithology with a mean variation index of 6.5 %, and lithology is the most effective thematic layer in GP mapping with mean effective weight of 52 %. More... »

PAGES

195-206

References to SciGraph publications

  • 2004-06. Planning and Design of Cost-effective Water Harvesting Structures for Efficient Utilization of Scarce Water Resources in Semi-arid Regions of Rajasthan, India in WATER RESOURCES MANAGEMENT
  • 2005-10. An integration of GIS and remote sensing in groundwater investigations: A case study in Burdur, Turkey in HYDROGEOLOGY JOURNAL
  • 2011-02. Hydrogeochemical analysis and evaluation of groundwater quality in the Gadilam river basin, Tamil Nadu, India in JOURNAL OF EARTH SYSTEM SCIENCE
  • 2011-03. Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques in WATER RESOURCES MANAGEMENT
  • 1994-06. Optimal allocation of surface water in regional water management in WATER RESOURCES MANAGEMENT
  • 2007-02. Remote sensing and GIS for mapping groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia in HYDROGEOLOGY JOURNAL
  • 2005-03. The future of satellite remote sensing in hydrogeology in HYDROGEOLOGY JOURNAL
  • 2005-10. Identification of groundwater prospective zones by using remote sensing and geoelectrical methods in Jharia and Raniganj coalfields, Dhanbad district, Jharkhand state in JOURNAL OF EARTH SYSTEM SCIENCE
  • 2009-12. Spatial analysis of groundwater potential using remote sensing and GIS in the Kanyakumari and Nambiyar basins, India in JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
  • 2014-03. Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach in APPLIED WATER SCIENCE
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    38 schema:description Sustainable development and management of groundwater resources require application of scientific principles and modern techniques. An integrated approach is implemented using remote sensing and geographic information system (GIS)-based multi-criteria evaluation to identify promising areas for groundwater exploration in Raya Valley, northern Ethiopia. The thematic layers considered are lithology, lineament density, geomorphology, slope, drainage density, rainfall and land use/cover. The corresponding normalized rates for the classes in a layer and weights for thematic layers are computed using Saaty’s analytical hierarchy process. Based on the computed rates and weights, aggregating the thematic maps is done using a weighted linear combination method to obtain a groundwater potential (GP) map. The GP map is verified by overlay analysis with observed borehole yield data. Map-removal and single-parameter sensitivity analyses are used to examine the effects of removing any of the thematic layers on the GP map and to compute effective weights, respectively. About 770 km2 (28 % of the study area) is designated as ‘very good’ GP. ‘Good’, ‘moderate’ and ‘poor’ GP areas cover 630 km2 (23 %), 600 km2 (22 %) and 690 km2 (25 %), respectively; the area with ‘very poor’ GP covers 55 km2 (2 %). Verification of the GP map against observed borehole yield data shows 74 % agreement, which is fairly satisfactory. The sensitivity analyses reveal the GP map is most sensitive to lithology with a mean variation index of 6.5 %, and lithology is the most effective thematic layer in GP mapping with mean effective weight of 52 %.
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