MODELLING THE SPATIO-TEMPORAL VARIATION OF SURFACE AND GROUNDWATER RESOURCES IN THE ETHIOPIAN RIVER BASIN

Abstract

Assessment of spatial-temporal variation of surface water and groundwater resources and their responses to hydrological processes in hydrological systems under high data scarcity of catchment characteristics such as hydro-climate, hydrogeology, and physiological conditions are highly challenging. This thesis aimed at investigating the above-highlighted virtual conditions in the large-scale river basin, and the abstracts of the works addressed are detailed as follows. Surface water resources assessment: Investigation of spatio-temporal variation of long-term mean monthly, seasonal, and annual surface water balance components (SWBCs) for catchments with limited observed data and complex topography is challenging. The WetSpass-M model was used in this study for the calculation of the spatiotemporal variation SWBCs in data scare catchments such as Omo River, Ethiopia. Further, the spatial variation of the mean monthly crop water deficit was calculated from the model output. The WetSpass-M model's global and local parameters were used for the analysis of model parameters' sensitivity relative to SWBCs variation. The finding reveals that the model global parameter such as average rainfall intensity is insensitive to actual evapotranspiration (AET), and interception and is highly sensitive to surface runoff (SRO). The spatio-temporal distribution of SWBCs at different combinations of land-use/land cover (LULC) and soil type depicts that SWBCs such as SRO, AET, and interception are highly influenced by LULC compared to soil type. Groundwater recharge assessment: Assessment of spatial and temporal distribution groundwater recharge (GWR) at large-scale river basins is crucial for sustainable water resources management. Further, it helps in the identification of critical zones where GWR highly varies and leads to stress conditions. Investigation of GWR using models seeking catchment-related data such as hydro-climate, hydrogeology, and physiological details for data scarcity regions is challenging. This demands alternative modelling techniques that suites limited data and provide sound information on spatio–temporal variation of water balance components (WBCs). This study investigated the spatial variation of GWR's at monthly, seasonal, and annual scales using WetSpass-M model. The model was chosen as it needs limited data on the catchment for analysis of GWR. Further, the sensitivity of model parameters to variation of GWR was assessed in this study. The finding reveals that in the Omo River basin, the mean monthly maximum GWR of 13.4 mm occurs in ii the month of July. It is also found that GWR in the summer and winter seasons is 32.5 mm/yr and 47.6 mm/yr, respectively. Furthermore, the finding reveals that GWR is highly sensitive to the model parameter such as mean rainfall intensity. Assessment of groundwater develop and response to soil erosion Sustainable water resource management benefits the country's economy, particularly agriculture. The several countries around the world have constrained surface water resources and thus reliant on groundwater for crop irrigation. Moreover, soil erosion is a major issue, resulting in decreased soil fertility, land-use disturbances, and sedimentation, particularly in large-scale watersheds with complex terrain. As a result, assessing the spatial-temporal variation of groundwater development, such as GWR and GWSY, as well as their response to topsoil erosion and SRO in large-scaled river basins, is crucial for long-term groundwater development. The purpose of this research is to determine the spatio-temporal variation of groundwater development in response to topsoil loss. The proposed modelling techniques were demonstrated using a large-scale East African basin, such as the Omo River basin. The estimated spatial variation of GWR using the WetSpass-M model was used to analyse GWSY. Furthermore, the spatial variation of yearly topsoil erosion was estimated using a combination of methods including the Revised Universal Soil Loss Equation (RUSLE) model, the ArcGIS tool, and remote sensing data. The finding reveals that the Omo River basin has moderate to high productive aquifers (2–28 l/s), with maximum GWSY capacity ranging from 0.4 to 4 m3/day/ha in cultivation LULC. The estimated long-term mean annual soil loss is 12.35 t ha−1yr−1 and is comparable with the measured sediment yield of 13.24 t ha−1yr−1. The condition of occurrence of maximum GWR and moderate to severe topsoil erosion in cultivation (disturbed soil) regions indicates that GWR topsoil erosion has a direct relationship.