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Attribution of the 2015-2016 hydrological drought in KwaZulu-Natal to anthropogenic climate change

In 2015-2016 Kwa-Zulu Natal (KZN) and other provinces in South Africa suffered from drought conditions. Drought can have negative impacts on the environment, society and the economy. Climate change is predicted to exacerbate extreme events such as droughts that would adversely affect already vulnera...

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Bibliographic Details
Main Author: Karlie, Makeya
Other Authors: Wolski, Piotr
Format: Thesis
Language:English
Published: University of Cape Town 2021
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Summary:In 2015-2016 Kwa-Zulu Natal (KZN) and other provinces in South Africa suffered from drought conditions. Drought can have negative impacts on the environment, society and the economy. Climate change is predicted to exacerbate extreme events such as droughts that would adversely affect already vulnerable regions such as KZN. The main aim of this study is to implement the attribution procedure, to determine if climate change has contributed to the 2015-2016 hydrological drought in selected KZN catchments. Methodology of the study followed a general framework of implementation of hydrological attribution experiments with climate data obtained from attribution simulations with HadAM3p global climate model. Prior to simulations in attribution mode, QSWAT model was set up for the study area and calibrated using SWAT-CUP and SUFI-2. Calibration results were poor but the model could be applied in the context of this study, under certain constraints. Results of attribution experiments revealed that for all 3 subbasins studied no increase of risk was observed and hence no influence of climate change on the 2015-2016 magnitude of drought for selected catchments was concluded by this study. These results are limited, as they are based on climate attribution experiments with only one climate model, rather than with a multi-model ensemble. Also, QSWAT model, in its implementation with generic climate data is of limited use in attribution (or hydrological) simulations as even after calibration the model performs poorly.