Abstract

Modification of the Earth’s surface i.e. land use change, is the main human activity for survival and is the key player in the management of natural resources, including water. Little attention has, however, been given to understand the role the territorial vegetation changes may play in strategic management of water resources. In the basin of Aswa northern Uganda, the changes in land use due to complex demographic and social economic factors is among the numerous challenges faced in management of the limited water resources in the area. The aim of the current study was to explore the opportunities land use changes in the basin may offer to water resources management, looking mainly at the expansion in future agriculture and afforestation as the critical land use change issues. The study was structured into four broad objectives: The first objective was to generate the reference land use dataset (1986 & 2001). The available techniques (the supervised and the unsupervised image classification) were explored using Landsat multi-spectral images. Through careful evaluation, the supervised image classification with the best classification accuracy of 81.48% was used to generate 1986 and 2001 land use maps. The second objectives of the study was to generate experimental land use scenarios required for testing the effect of spatial land use policies on hydrologic processes in the basin. The Multi-criteria-GIS methodology was developed and six experimental land use scenarios were generated using simple but consistence set of bio-physical and socio-economic parameters. The third objective was to customise the hydrologic process model SWAT that was used to simulate the hydrologic impact of the land use change scenarios. The calibration of the hydrologic model SWAT used monthly historical streamflow records from 1970 to 1974 recorded at the basin outlet. The model was manually calibrated using the Nash-Sutcliffe coefficient as objective function. The efficiency of the model during calibration was 0.46. Validation of the model using an independence monthly streamflow records from 1975 to 1978 was done and the model efficiency was 0.66, much better than in calibration period. The forth and last objective of the study was to simulate the hydrologic processes in the reference years and the hydrologic processes impacted by the land use change scenarios and to evaluate how this impact affects water resources management strategies. An independent validation of the model to identify the validity of extending the optimal parameters set in simulation of 2001 and land use change hydrologic processes was carried out by comparing the simulated actual evapotranspiration fraction with estimated actual evapotranspiration fraction obtained using surface energy balance method and the thermal MODIS images. Validation indicated acceptable model performance in simulating 2001 hydrologic processes, with a spatial correlation coefficient of 0.45. The application of the model in simulations of the hydrologic processes in the reference years noted that 2001 had more water yield than 1986 by 9.2 mm. The analysis of the impact of land use change in the reference years indicated an increase of 2.52 mm of water yield in the year 2001. Simulation of the hydrologic impact of the experimental land use indicated that Land use types, which in this study were restricted to plantation forest and generic agriculture, land use extent and location of the land use with respect to precipitation rate and amount, greatly influence the hydrologic process of the basin and the net water yield. It was noted that the water yield of the basin can be significantly decreased by over 15%, if more than 37% of the plantation forests are introduced in the wet zone. In the dry sub-basins however, afforestation of up to 42% had insignificant effect on water yield, which could therefore be exploited so as to offset the afforestation pressure in the wet sub-basin while at the same time enhancing the basin water yield. The effect of agricultural land use change on water yield was however less sensitive to climatic zones. 53% increase in agricultural land cover responded with an increase in water yield by about 27%.

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