This paper presents a methodology based on a decision support system (DSS) that employs remote sensing and field survey data and geographic information system (GIS) to identify potential rainwater harvesting areas (RWH). This DSS was implemented to obtain suitability maps and to evaluate the existing RWH structures in the study area. The DSS inputs comprised maps of rainfall surplus, slope, potential runoff coefficient, land cover/use, and soil texture. On the basis of an analytical hierarchy process analysis taking into account five layers, the spatial extents of RWH suitability areas were identified by multi-factor evaluation. The spatial distribution of the classes in the suitability map showed that the excellent and good areas are mainly located in the southern and western parts of the study area. On average, 12.2% and 22.2% of the study area are classified as excellent and good for RWH, respectively, while 34.7% and 30.9% of the area are classified as moderately suitable and poorly suited and unsuitable, respectively. Most of the existing RWH structures that are categorized as successful were within the good (72% of the structures) areas followed by moderately suitable (24% of the structures) and excellent areas (4% of the structures).
"A Knowledge-based decision support system for planning reforestation projects in developing countries; a geographic information system".
