A Spatial Multi-Criteria Analysis Approach for Locating Suitable Sites for Construction of Subsurface Dams in Northern Pakistan

Imran Jamali (), Ulla Mörtberg, Bo Olofsson and Muhammad Shafique

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2014, vol. 28, issue 14, 5157-5174

Abstract: Pakistan is an agricultural country with an increasing interest for hydropower. Water management problems such as sedimentation and evaporation have been of high concern for surface water reservoirs for many years. Therefore, groundwater storage through subsurface dams could be promising, especially considering the monsoon rainfall and seasonal river flows in Pakistan. The paper aims to develop and test a methodology to locate suitable sites for construction of subsurface dams using spatial multi-criteria analysis (SMCA) in the northern parts of Pakistan. For the study, spatial data on geology, slope, land cover, soil depth and topographic wetness index (TWI) was used. Two weighting techniques, i.e. the analytic hierarchy process (AHP) and the factor interaction method (FIM), were employed and compared. The sensitivity of the two methods as well as of the model parameters was analysed. The suitability map derived from AHP yielded about 3 % (16 km 2 ) of the total area as most suitable, about 4 % (22 km 2 ) as moderately suitable and about 0.8 % (5 km 2 ) as least suitable. The suitability map derived from FIM identified about 2.7 % (14 km 2 ) of the total area as most suitable, about 4 % (22 km 2 ) as moderately suitable and about 1 % (7 km 2 ) as least suitable. The sensitivity analyses suggested that AHP was a more robust weighting technique than FIM and that land cover was the most sensitive factor. The methodology presented here shows promising results and could be used in early planning to locate suitable sites for construction of subsurface dams. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Subsurface dams; Pakistan; Groundwater; Spatial multi-criteria analysis; AHP; GIS (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11269-014-0800-2

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