A GIS-based approach to calculate runoff volume (Qr) and peak runoff rate (Pr)

Abstract

Apart from their use in agricultural water management, runoff volume (Qr) and peak runoff rate (Pr) are essential for estimating sediment yield (Y), sediment delivery ratio (SDR) and non-point source (NPS) pollution. Runoff is a complex, dynamic and nonlinear process, influenced by multiple interconnected physical factors. However, modelling runoff requires extensive spatial information on basins and flood risk areas. Geographic Information Systems (GIS) and Remote Sensing come equipped with tools that facilitate the modelling of complex spatial interactions, including those that interact in a runoff. This study uses the National Resources Conservation Society (NRCS) curve number (CN) method to estimate Qr in a GIS environment, in the Olifants River Basin (Limpopo). The NRCS method is preferred in modelling Qr as it can be applied at any spatial scale. Rainfall data collected for 10 years was used to estimate the mean annual Qr. The CN method results were then compared with those derived from a Water Research Commission (WRC) funded project, which used a locally developed model.

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