Open AccessA GIS-based approach for identifying suitable sites for rainwater harvesting technologies in Kasungu District, Malawi
Author(s) -
F Nyirenda,
Alexander Mhizha,
Webster Gumindoga,
Armwell Shumba
Publication year - 2021
Publication title -
water s.a./water sa
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.389
H-Index - 59
eISSN - 1816-7950
pISSN - 0378-4738
DOI - 10.17159/wsa/2021.v47.i3.11863
Subject(s) - rainwater harvesting , surface runoff , environmental science , water content , soil map , geographic information system , hydrology (agriculture) , runoff curve number , land cover , drainage , water resource management , land use , soil water , environmental engineering , geography , remote sensing , cartography , drainage basin , engineering , civil engineering , soil science , ecology , geotechnical engineering , biology
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.