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Stellenbosch University (2021)

Modelling the future impacts of climate change on sediment yield for a semi-arid catchment in South Africa using SHETRAN

Barnardt, Georg Frederik

Titre : Modelling the future impacts of climate change on sediment yield for a semi-arid catchment in South Africa using SHETRAN

Auteur : Barnardt, Georg Frederik

Université de soutenance : Stellenbosch University

Grade : Master Degree (Civil Engineering) 2021

Résumé partiel
Sedimentation (caused by soil erosion and high sediment yields) has become a major problem in South Africa, especially in semi-arid regions like the Karoo, where water scarcity and reduction of reservoir storage capacity can cause social and environmental concerns. The uncertainties regarding the impact climate change may have on the hydrological cycle, and the effect on catchment response increase these concerns. This thesis’s main objective was to evaluate the possible future impacts of climate change on sediment yield by incorporating predicted future climate data and a physically-based hydrological and sediment yield model, SHETRAN. From a literature study, background information regarding soil and vegetation properties, soil erosion, sediment yield, physically-based models (focussing on the SHETRAN model), climate change, and climate models were obtained. The Nqweba Dam catchment (3651 km2), located in the semi-arid region of the Eastern Cape of South Africa, was identified for the analysis. All the information and data required to execute a SHETRAN simulation were obtained, which include : Topography ; soil distribution and -characteristics ; land cover distribution and vegetation properties ; streamflow data ; and reservoir survey data. The reservoir survey data was used to determine the historical bed sediment densities and average sediment yield for numerous historical periods in the catchment. The SHETRAN model was calibrated against observed streamflow and sediment data for current catchment and climate conditions. The calibration parameters were verified, and high sediment yield areas were identified. Future climate data projected by eleven climate models for two possible future emission scenarios were used to determine climate change signals for numerous future periods.

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