IMPACTS OF CLIMATE CHANGE ON STREAMFLOW AND HYDROLOGICAL EXTREMES IN THE SOUTH PHUTHIATSANA CATCHMENT, LESOTHO

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dc.contributor.authorMaphutseng, M
dc.date.accessioned2026-04-28T13:39:48Z
dc.date.available2026-04-28T13:39:48Z
dc.date.issued2025-10-01
dc.description.abstractGlobal climate change is predicted to significantly modify hydrological processes, which will have a big impact on ecosystem sustainability, flood risk, and water availability. Knowing how future climate changes may impact river systems is especially important in southern Africa, where population increase and fluctuating rainfall are already placing a strain on water resources. One such critical system is the South Phuthiatsana catchment, which serves as a vital supply of water for Maseru and the other metropolitan areas. This study explores how projected climatic shifts may influence streamflow behavior and the occurrence of hydrological extremes within the South Phuthiatsana watershed, an essential source of water for Maseru and surrounding urban communities. Bias-adjusted data from the MPI-ESM1-2-LR global climate model, along with two sample emissions trajectories for the mid-21st century (2041–2080), were used to project climate inputs. Suboptimal performance indicators showed that the process-based model (SWAT+), which was used to simulate streamflow, was not very reliable in capturing historical daily flow patterns. SWAT+ was therefore thought to be insufficient for predicting future hydrological reactions in this context. A machine learning approach using the XGBoost algorithm was adopted to address this challenge. This data-driven model was trained on bias-corrected climate variables and observed streamflow, providing a more reliable tool for future streamflow prediction. The results from XGBoost revealed substantial and complex hydrological shifts. A consistent warming trend combined with highly variable seasonal precipitation patterns was evident across both emission scenarios. Extreme high flows, represented by the 98th percentile (Q98), are projected to decline by more than 52% compared to historical values, suggesting a reduced risk of flooding. In contrast, low flows are expected to increase dramatically; the 1st percentile (Q1) flow is projected to rise from near-zero values historically to approximately 9.0 m³/s, indicating a significant shift toward more perennial flow conditions. Mid-range flows (Q25, Q50, and Q75) are also expected to increase substantially, depending on the flow percentile and scenario. While the absolute magnitude of low flows improves, the number v of days with historically low flow conditions may still increase during certain months, highlighting a shift in the intra-annual flow variability. These findings point to a future with altered hydrological regimes in the South Phuthiatsana catchment characterised by diminished flood peaks, elevated baseflows, and more frequent low-flow conditions during critical periods. Despite initial limitations with the process-based model, the machine learning approach provided robust insights that form a valuable foundation for developing adaptive, forward-looking water resource management strategies. These results underscore the need for resilient planning to ensure long-term water security under evolving climate conditions.
dc.identifier.urihttps://hdl.handle.net/20.500.14155/2238
dc.titleIMPACTS OF CLIMATE CHANGE ON STREAMFLOW AND HYDROLOGICAL EXTREMES IN THE SOUTH PHUTHIATSANA CATCHMENT, LESOTHO
dc.typeThesis
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