INVESTIGATING GIS APPROACH IN SITE SELECTION FOR RAINWATER HARVESTING A CASE OF T/A TENGANI, NSANJE
Abstract
The main obstacle to development in arid areas is the scarce and intermittent rainfall. Rainfall is a key source to diminish the problem of water scarcity in the arid and semi-arid regions. Rainwater harvesting is considered an imperious tool for rainwater conservation. Locating the appropriate location for rainwater harvesting structure plays an important role to increase water availability and improve water resources planning. The main goal of the paper is to recognize appropriate site for the allocation of rainwater harvesting structures using GIS and remote sensing which was generated using ArcGIS PRO and ArcGIS 10.8.Many thematic maps were extracted such as soil map, slope map, drainage map, rainfall map, temperature map, land use map and sedimentation map. The result shows that 3% represent the suitable sites for rainwater harvesting of the total study area, 97% represents the medium suitable area and 0% represents not suitable areas to implement rainwater harvesting structure. The proposed method is relatively supportive in analyzing geospatial data to determine and select the optimal site for rainwater harvesting for mitigation dry spells and floods.
Research summary
Locating the appropriate location for rainwater harvesting structure plays an important role to increase water availability and improve water resources planning. The main goal of the paper is to recognize appropriate site for the allocation of rainwater harvesting structures using GIS and remote sensing which was generated using ArcGIS PRO and ArcGIS 10.8.Many thematic maps were extracted such as soil map, slope map, drainage map, rainfall map, temperature map, land use map and sedimentation map. The result shows that 3% represent the suitable sites for rainwater harvesting of the total study area, 97% represents the medium suitable area and 0% represents not suitable areas to implement rainwater harvesting structure. The proposed method is relatively supportive in analyzing geospatial data to determine and select the optimal site for rainwater harvesting for mitigation dry spells and floods.