On the impacts of climate change on water resources, lessons from the River Nith Catchment and Shire River Basin

One of the most complex and challenging problems faced by the world today is that of water scarcity which has been recognized as a global risk. According to experts, freshwater scarcity affects close to two-thirds of the world's population at least one month of the year while half a billion people are estimated to be living under water scarcity throughout the year. Climate change, population growth, increased reliance on irrigated agriculture and changes in land-use threaten to exacerbate water scarcity risk. In recent decades, solutions to these challenges and threats have been proposed through various interventions such as the Millennium Development and Sustainable Development Goals (MDGs and SDGs respectively).;Responsible management of water systems and resources entails having a thorough understanding of the quantity and quality of these resources. Researchers have used simplistic 1-dimensional models to complex semi-distributed models to understand how water systems such as lakes, rivers and entire basins are replenished. However, most studies have focussed on only one aspect of the hydrologic cycle when quantifying freshwater resources. In the past decade or so, the issue of integrated hydrologic modelling (IHM) where surface and groundwater is modelled as an integrated unit has gained traction in the research community.;More recently, it has become fashionable to couple integrated hydrologic models coupled with atmospheric models to account for climate change. Notwithstanding this development, there is still no unified and systematic methodology and/or framework that has been adopted by the water research community for integrated hydrologic modelling. This, coupled with the challenge of filtering through the many spatial climate data products offered by the climate research centres, makes the task all the more challenging. This has led to a slow adoption of these models by the water resources community.;This thesis applies integrated hydrologic models (SWAT-MODFLOW) coupled with atmospheric models to two watersheds (River Nith Catchment and Shire RiverBasin) from different climatic settings to determine the quantity and availability of future water resources. The River Nith Catchment (RNC) is located in South-West Scotland, UK while the Shire River Basin (SRB) is located in Southern Malawi. Downscaling of Global Circulation Models (GCMs) that were used to force the integrated hydrologic models was done using the quantile mapping method. Six GCMs and a total of thirty-six climate scenarios and hydrological models under RCP4.5 and RCP8.5 were developed for the SRB while five GCMs and a total of thirty climate and hydrological models under RCP4.5 and RCP8.5 were developed for the RNC. In total, sixty-six models were developed for the two study are as encompassing climate change and variability analyses, surface-water modelling and groundwater recharge modelling. The methodology was found to be applicable in both temperate and semi-arid climates.;This thesis documents methods that can be used to model climate change impacts on groundwater resources using a multi-GCM and integrated hydrologic modelling approach using freely available data and tools within an Integrated Water Resources Management (IWRM) framework. It is the hope of the authorthat these tools and methodologies will be adopted by the wider IWRM community in an effort to meet Sustainable Development Goal number 6 (SDG 6) by 2030. The contribution to research of this thesis can be viewed from four perspectives. Firstly, a novel method for GCM subset selection incorporating Symmetrical Uncertainty (SU), Probability Density Function (PDF) ranking and the Random Forest Algorithm was developed.;Secondly, this is the first time such a model has been applied for future water resources quantification in both the RNC and SRB. Thirdly, this work has demonstrated that it is possible to do high quality predictive hydrological modelling that can be incorporated into climate adaptability planning using freely available remotely-sensed climate data. Fourthly, the methodology developed in this thesis provides a basis for a unified framework (i.e. software tools adopted in this work including related software) and methodology for integrated hydrologic modelling that can be applied in different climatic settings using freely available hydro-climatic data products.One of the most complex and challenging problems faced by the world today is that of water scarcity which has been recognized as a global risk. According to experts, freshwater scarcity affects close to two-thirds of the world's population at least one month of the year while half a billion people are estimated to be living under water scarcity throughout the year. Climate change, population growth, increased reliance on irrigated agriculture and changes in land-use threaten to exacerbate water scarcity risk. In recent decades, solutions to these challenges and threats have been proposed through various interventions such as the Millennium Development and Sustainable Development Goals (MDGs and SDGs respectively).;Responsible management of water systems and resources entails having a thorough understanding of the quantity and quality of these resources. Researchers have used simplistic 1-dimensional models to complex semi-distributed models to understand how water systems such as lakes, rivers and entire basins are replenished. However, most studies have focussed on only one aspect of the hydrologic cycle when quantifying freshwater resources. In the past decade or so, the issue of integrated hydrologic modelling (IHM) where surface and groundwater is modelled as an integrated unit has gained traction in the research community.;More recently, it has become fashionable to couple integrated hydrologic models coupled with atmospheric models to account for climate change. Notwithstanding this development, there is still no unified and systematic methodology and/or framework that has been adopted by the water research community for integrated hydrologic modelling. This, coupled with the challenge of filtering through the many spatial climate data products offered by the climate research centres, makes the task all the more challenging. This has led to a slow adoption of these models by the water resources community.;This thesis applies integrated hydrologic models (SWAT-MODFLOW) coupled with atmospheric models to two watersheds (River Nith Catchment and Shire RiverBasin) from different climatic settings to determine the quantity and availability of future water resources. The River Nith Catchment (RNC) is located in South-West Scotland, UK while the Shire River Basin (SRB) is located in Southern Malawi. Downscaling of Global Circulation Models (GCMs) that were used to force the integrated hydrologic models was done using the quantile mapping method. Six GCMs and a total of thirty-six climate scenarios and hydrological models under RCP4.5 and RCP8.5 were developed for the SRB while five GCMs and a total of thirty climate and hydrological models under RCP4.5 and RCP8.5 were developed for the RNC. In total, sixty-six models were developed for the two study are as encompassing climate change and variability analyses, surface-water modelling and groundwater recharge modelling. The methodology was found to be applicable in both temperate and semi-arid climates.;This thesis documents methods that can be used to model climate change impacts on groundwater resources using a multi-GCM and integrated hydrologic modelling approach using freely available data and tools within an Integrated Water Resources Management (IWRM) framework. It is the hope of the authorthat these tools and methodologies will be adopted by the wider IWRM community in an effort to meet Sustainable Development Goal number 6 (SDG 6) by 2030. The contribution to research of this thesis can be viewed from four perspectives. Firstly, a novel method for GCM subset selection incorporating Symmetrical Uncertainty (SU), Probability Density Function (PDF) ranking and the Random Forest Algorithm was developed.;Secondly, this is the first time such a model has been applied for future water resources quantification in both the RNC and SRB. Thirdly, this work has demonstrated that it is possible to do high quality predictive hydrological modelling that can be incorporated into climate adaptability planning using freely available remotely-sensed climate data. Fourthly, the methodology developed in this thesis provides a basis for a unified framework (i.e. software tools adopted in this work including related software) and methodology for integrated hydrologic modelling that can be applied in different climatic settings using freely available hydro-climatic data products