Application of SAW and TOPSIS in Prioritizing Watersheds

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Meshram S. G., Alvandi E., Meshram C., Kahya E., Al-Quraishi A. M. F.

WATER RESOURCES MANAGEMENT, vol.34, pp.715-732, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 34
  • Publication Date: 2020
  • Doi Number: 10.1007/s11269-019-02470-x
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Page Numbers: pp.715-732
  • Istanbul Technical University Affiliated: Yes


Prioritization of watersheds for conservation measures is essential for a variety of functions, such as flood control projects in which the determination of top priority areas is an important management decision. The purpose of this study is to examine watershed morphological characteristics and identify critical sub-watersheds, which are prone to be damaged, using Remote Sensing/Geographical Information Systems (GIS) and SAW/TOPSIS (Simple Additive Weighting/ Technique for Order of Preference by Similarity to Ideal Solution). Fourteen morphometric parameters were chosen to organize sub-watersheds using SAW/TOPSIS, which examines sub-watersheds (as susceptible zones) from the perspective of classification in four priority levels (namely, low, moderate, high and very high levels). The SAW/TOPSIS approach is a useful strategy to find out potential zones provided that the ultimate goal is to achieve successful management strategies, particularly in particular zones where information accessibility is limited and soil assorted variety is high. Without facing with high cost and exercises in futility, sub-watersheds could be organized through morphometric parameters in executing conservational measures to save soil and the earth at the same time. In short, our results showed that morphometric parameters are highly efficient in identifying erosion-prone areas.