Application of multi-criteria decision making and GIS for check dam layout in the Ilanlu basin, northwest of Hamadan Province, Iran. (December 2019)

• Record Type: Journal Article
• Authors: Ildoromi, Ali Reza; Sepehri, Mehdi; Malekinezhad, Hossein; Kiani-Harchegani, Mahboobeh; Ghahramani, Afshin; Hosseini, Seyed Zeynalabedin; Artimani, Mohammad Mehdi
• Is Part Of: Physics and chemistry of the earth. Volume 114(2019)
• Publication Date: 2019-12
• Subjects: Water harvesting -- Flood -- Sediment -- Fuzzy logic -- Soil erosion; Geophysics -- Periodicals; Geochemistry -- Periodicals; Earth sciences -- Periodicals; Geodesy -- Periodicals; Astrophysics -- Periodicals; 550
• DOI: 10.1016/j.pce.2019.10.002
• Languages: English
• ISSNs: 1474-7065

Abstract

Abstract: Monitoring and managing floods and sediments are considered major challenges in the sustainable management of watersheds. Hence, an effective layout of the hydraulic structures across channels is considered as a measure to overcome these two challenges. This study was carried out in the Illanlu catchment in the northwest of Hamadan Province, Iran. A set of effective indices were identified and developed using the Geographic Information System (GIS) and fuzzy logic to model optimal location of sites for construction of the check dams. Based on the ability to construct the check dams e.g. access road and environmental constraints, the map was classified from very high to very low construction ability. In the study area, 26% of the catchment area was located in the very high and high classes, predominantly in the upstream sub-catchments, 13% in the very low class, and 62% in moderate and low ability ranges. Finally, by using superimposing method and the receiver operating characteristic (ROC) curve the accuracy of developed spatial model estimated to be 70% and 73.5%, respectively. Highlights: Check dams layout was optimized by GIS and Multi-Criteria Decision Making (MCDM). Sediment trapping and flood hazard degree were used in Check dams layout. The accuracy of the fuzzy logic model estimated to be 73.5% by receiver operating characteristic (ROC) curve. The accuracy of the fuzzy logic model estimated to be 70% by superimposing method.