A GIS-based approach for identifying suitable sites for rainwater harvesting technologies in Kasungu District, Malawi

Abstract

A GIS-based approach for identifying suitable sites for rainwater harvesting (RWH) technologies was developed and applied in Kasungu District, Malawi. Data were obtained from reports, socio-economic survey documents of the area and maps. Field surveys were conducted in the villages of Chipala Extension Planning Area (EPA), in order to identify and evaluate the performance of existing RWH interventions, and determine factors for   locating suitable areas for RWH. Observed soil moisture content was used to assess the water retention    performance of the prevalent RWH technologies: contour tied ridging and soil mulching. A GIS-based Soil  Conservation Service Curve Number (SCS-CN) method was used to map runoff potential for areas with RWH  technologies, using physical factors of rainfall, land use, soil type and slope to estimate runoff potential. This  was then integrated in a GIS database, with social-economic factors in the form of household income level and environmental factors, including impacts of implementing RWH, to determine the suitability of land areas for  RWH in Kasungu District. One way analysis of variance (ANOVA) was used to test the impact of identified  technologies by comparing the moisture content measurements for each of the identified technologies at 5% level of significance. The ANOVA results showed a statistically significant difference in the moisture    measurements for the three technologies identified (P < 0.05). The RWH suitability map for the study area  showed that 0.2% of the area considered had very high potential, 33.5% high, 55.9% moderate, 10.1% marginal and 0.3% not suitable for in-field RWH. The model was verified by locating the existing RWH on the suitability map obtained from GIS: 81% of RWH were located in the highly and moderately suitable areas whilst only 13% were located in areas of low suitability. Hence the developed model can reliably be used to predict potential areas for RWH.