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

Abstract

Kasungu district in Malawi has mainly been affected by erratic rainfall that are characterised by dry spells. Almost each year the district receives rainfall that is unevenly distributed spatially and temporal hence threatens crop production leading to food insecurity. Soil moisture retention is vital in crop production hence Rainwater harvesting (RWH) technologies have been recommended in literature to mitigate dry spells. In the recent past, the Malawi Government has advocated for the implementation of RWH technologies. Proper planning in identification of suitable sites for various RWH technologies can improve the effectiveness of the technologies. The objective of the study was to develop a GIS-based approach for identifying suitable sites for RWH technologies in Kasungu District of Malawi. Field surveys were conducted in the villages of Chipala Extension Planning Area (EPA), in order to identify and evaluate performance of existing RWH interventions, and establish factors for locating suitable areas for RWH. Soil moisture content was used to test for performance of RWH technologies. A GIS based Soil Conservation Service (SCS) Curve Number method was used to map runoff potential areas for RWH. The results from field study revealed that the most commonly implemented technologies were soil mulching (50%), contour tied ridges (39%), planting pits (7%) and infiltration pits (4%). Performance assessment of the RWH technologies reviewed that there was a statistically significant difference (α=0.05) in the moisture measurements for the various RWH technologies (P< 0.05). A RWH potential map was developed that showed 87% of the land in the study area being suitable for RWH. The model was validated by comparing locations of existing RWH technologies to the suitability map that showed that 79 % of RWH technologies were located in the high suitable area and moderate areas, 17 % in areas of low suitability whilst only 4 % were located in areas of very low suitability. Hence the model can reliably be used to identify suitable areas for RWH technologies.