Geospatial soil-water balance approach for estimating potential recharge from an extreme rainfall event: A case of Motloutse Watershed, eastern Botswana

Abstract

ABSTRACT A diagram summarising (from left to right) (1) data sets and their sources (2) the GSWB framework here the soil water balance equation was executed within a GIS environment. Furthermore, the methodology for implementing GSWB framework shown. The results are presented on the right end of the diagram. The map od potential recharge was produced from CHIRPS data. Determining potential recharge from extreme precipitation requires high-resolution monitoring of soil water content at daily time steps. In this study, we applied geospatial-based soil water balance to assess potential recharge from “Dineo” cyclonic event in a semi-arid watershed. This study contributes a novel regional application through the integration of FEWSNet precipitation datasets within a geospatial soil water balance framework to efficiently assess groundwater recharge dynamics in a data-scarce semi-arid environment. The study revealed that 23% of the watershed experienced both rejected infiltration and soil moisture deficit whereas 77% received potential recharge. The minimum recharge value was 0.02 mm and maximum of 171.88 mm with average of 28.5 mm. Areas to the west of 27°20′ longitude received high recharge whereas those to the east received minimum recharge. High recharge potential was recorded in areas of shallow rooted vegetation, soils of high infiltration capacity, and flat to moderate slopes. Furthermore, distribution of potential recharge emulated spatial precipitation amounts. Sensitivity analysis on input parameters proved that potential evapotranspiration and antecedent moisture condition are the most influential parameters on groundwater recharge. Geospatial-based soil water balance approach is a cost-effective and reliable alternative for assessing potential recharge from extreme precipitation events in data scarce regions.