Sustainability · 2019 · 100 citations · 71 references
Natural ResourcesHydrologyWatershed ManagementGeographic Information SystemsWater Resources EngineeringWatershed PlanningHydrologic AnalysisHydrologic Data AnalysisWatershed AssessmentWatershed ModelingGeo-spatial Analysis For WatershedsGeographic Information Systems (Gis) Based Flood MappingGeospatial Watershed AnalysisGis-based Site AnalysisStream PowerTopographic Wetness IndexTopographic Wetness Index MappingWatershed Management Planning
Check dams are widely used watershed management measures for reducing flood peak discharge and sediment transport, and increasing lag time and groundwater recharge throughout the world. However, identifying the best suitable sites for check dams within the stream networks of various watersheds remains challenging. This study aimed to develop an open-source software with user-friendly interface for screening the stream network possibilities and identifying and guiding the selection of suitable sites for check dams within watersheds. In this developed site selection software (SSS), multi-criteria decision analysis (MCDA) was integrated into geographic information systems (GIS), which allowed for numerous spatial data of the multiple criteria to be relatively simply and visually processed. Different geomorphometric and topo-hydrological factors were considered and accounted for to enhance the SSS identification of the best locations for check dams. The factors included topographic wetness index (TWI), terrain ruggedness index (TRI), topographic position index (TPI), sediment transport index (STI), stream power index (SPI), slope, drainage density (DD), and stream order (SO). The site identification performance of the SSS was assessed using the receiver operating characteristic (ROC) curve method, with results for the case study example of the Poldokhtar watershed in Iran showing excellent performance and identifying 327 potential sites for efficient check dam construction in this watershed. The SSS tool is not site-specific but is rather general, adaptive, and comprehensive, such that it can and should be further applied and tested across different watersheds and parts of the world.
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System for Automated Geoscientific Analyses (SAGA) v. 2.1.4
Olaf Conrad, Benjamin Bechtel, M. Bock et al. · Geoscientific model development · 2015 · 2.4K citations · Full text
GLM versus CCA spatial modeling of plant species distribution
Antoine Guisan, S. B. Weiss, Andrew D. Weiss · Plant Ecology · 1999 · 853 citations