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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/21116
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Deepesh Machiwal | en_US |
dc.contributor.author | Madan K. Jha | en_US |
dc.contributor.author | Bimal C.. Mal | en_US |
dc.date.accessioned | 2019-07-03T09:37:54Z | - |
dc.date.available | 2019-07-03T09:37:54Z | - |
dc.date.issued | 2010-12-03 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/21116 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Remote sensing (RS) and geographic information system (GIS) are promising tools for efficient planning and management of vital groundwater resources, especially in data-scarce developing nations. In this study, a standard methodology is proposed to delineate groundwater potential zones using integrated RS, GIS and multi-criteria decision making (MCDM) techniques. The developed methodology is demonstrated by a case study in Udaipur district of Rajasthan, western India. Initially, ten thematic layers, viz., topographic elevation, land slope, geomorphology, geology, soil, pre- and post-monsoon groundwater depths, annual net recharge, annual rainfall, and proximity to surface water bodies were considered in this study. These thematic layers were scrutinized by principal component analysis technique to select influential layers for groundwater prospecting. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their relative importance in groundwater occurrence. The assigned weights of the thematic layers and their features were then normalized by using AHP (analytic hierarchy process) MCDM technique and eigenvector method. Finally, the selected thematic maps were integrated by weighted linear combination method in a GIS environment to generate a groundwater potential map. Thus, four groundwater potential zones were identified and demarcated in the study area, viz., ‘good’, ‘moderate’, ‘poor’ and ‘very poor’ based on groundwater potential index values. The area falling in the ‘good’ zone is about 2,113 km2 (17% of the total study area), which encompasses major portions of Sarada, Salumber, Girwa, Dhariawad, and Mavli blocks of the study area. The northeast and southwest portions along with some scattered patches fall in the ‘moderate’ zone, which encompasses an area of 3,710 km2 (about 29%). The ‘poor’ zone is dominant in the study area which covers an area of 4,599 km2 (36% of the total area). The western portion and parts of eastern and southeast portions of the study area are characterized as having ‘very poor’ groundwater potential, and this zone covers an area of 2,273 km2 (18%). Moreover, in the ‘good’ zone, the mean annually exploitable groundwater reserve is estimated at 0.026 million cubic metres per km2 (MCM/km2), whereas it is 0.024 MCM/km2 in the ‘moderate’ zone, 0.018 MCM/km2 in the ‘poor’ zone, and 0.013 MCM/km2 in the ‘very poor’ zone. The groundwater potential map was finally verified using the well yield data of 39 pumping wells, and the result was found satisfactory. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Groundwater potential | en_US |
dc.subject | Remote sensing | en_US |
dc.subject | GIS | en_US |
dc.subject | Hard-rock aquifer system | en_US |
dc.subject | Semi-arid region | en_US |
dc.subject | MCDM | en_US |
dc.title | Assessment of groundwater potential in a semi-arid region of India using remote sensing, GIS and MCDM techniques | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Water Resources Management | en_US |
dc.publication.volumeno | 25(5) | en_US |
dc.publication.pagenumber | 1359–1386 | en_US |
dc.publication.divisionUnit | Regional Research Station, Kukma, Bhuj, Gujarat | en_US |
dc.publication.sourceUrl | 10.1007/s11269-010-9749-y | en_US |
dc.publication.authorAffiliation | ICAR::Central Arid Zone Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.naasrating | 8.92 | en_US |
Appears in Collections: | NRM-CAZRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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WARM 2011 Machiwal et al.pdf | 1.74 MB | Adobe PDF | View/Open |
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