Abstract

A study was carried out during 2022 to assess the potential of rainwater harvesting for sustaining small-scale irrigated coffee farming in the Bigasha watershed of Isingiro District, south-western Uganda. In this study, remote sensing, Geographical Information System (GIS), the Quantum GIS Soil and Water Assessment Tool (QSWAT+) and Crop Water and Irrigation Requirements Program (CROPWAT) models were utilised to assess the potential of rainwater harvesting (RWH) that can be used for irrigation. The criteria used to identify suitable RWH sites were based on four factors namely; topography, soils, land use land cover and rainfall. It was found out that seventy per cent of the watershed is hilly with slopes greater than 10 per cent and half of the area is covered by Leptosols. Three temporal land use land cover (LULC) maps (of 1999, 2010 and 2022), were derived using the K-nearest neighbor (KNN) algorithm. These LULC databases were used to assess the impacts of land use land cover changes on the runoff hence potential for RWH. The annual average rainfall received in the study area over the 21-year period studied (2000 – 2020) was 954 mm which is adequate for irrigation if harvested. The QSWAT+ model simulated runoff depths from 62, 125 and 114 Hydrologic Response Units (HRUs) of the 1999, 2010 and 2022 LULC maps respectively, were used to estimate potential RWH sites. The 114 HRUs from the 2022 LULC map could generate an annual average surface runoff volume of 1.39 million cubic meters (MCM) which could potentially irrigate 101.8 per cent of the current coffee production areas in the Bigasha watershed. The prediction accuracy of the Kagera river basin model was very good with NSE (R2) of 0.81(0.82) for calibration and 0.87(0.88) for validation. The Kagera watershed model fitted parameters were further used to calibrate the Bigasha watershed model. This was done because the Bigasha is a sub-basin of Kagera and it does not have its own gauged outlet.

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