Empirical evidence continues to show that climate change remains a threat to the stability of the hydrologic system. As the climate system interacts with the hydrologic cycle, one significant repercussion of global warming includes changes in water availability at both regional and local scales. Climate change adaptation is intrinsically difficult to attain due to the dynamic earth system and lack of a comprehensive understanding of future climate and its associated uncertainties. Mostly in developing countries, climate adaptation is hampered by scarcity of good quality and adequate hydro-meteorological data. This article provides a synopsis of the modelling chain applied to investigate the response of the hydrologic system under changing climate, which includes choosing the appropriate global climate models, downscaling techniques, emission scenarios, and the approach to be used in hydrologic modelling. The conventional criteria for choosing a suitable hydrological model are discussed. The advancement of emission scenarios including the latest Shared Socioeconomic Pathways and their role in climate modelling, impact assessment, and adaptation, are also highlighted. This paper also discusses the uncertainties associated with modelling the hydrological impacts of climate change and the plausible approaches for reducing such uncertainties. Among the outcomes of this review include highlights of studies on the commonly used hydrological models for assessing the impact of climate change particularly in the sub-Saharan Africa region and some specific reviews in southern Africa. Further, the reviews show that as human systems keep on dominating within the earth system in several ways, effective modelling should involve coupling earth and human systems models as these may truly represent the bidirectional feedback experienced in the modern world. The paper concludes that adequate hydro-meteorological data is key to having a robust model and effective climate adaptation measures, hence in poorly gauged basins use of artificial neural networks and satellite datasets have shown to be successful tools, including for model calibration and validation.

Identifying hydro-meteorological trends is critical for assessing climate change and variability both at a basin and regional level. This study examined the long- and short-term trends from stream discharge, temperature, and rainfall data around the Rietspruit sub-basin in South Africa. The data were subjected to homogeneity testing before performing the trend tests. Inhomogeneity was widely detected in discharge data, hence no further analyses were performed on such data. Temperature and rainfall trends and their magnitudes at yearly, seasonal, and monthly time steps were identified after applying the non-parametric Mann-Kendall and Sen's slope estimator. The possible starting point of a trend was determined by performing the sequential Mann-Kendall test. This study revealed a combination of upward and downward trends in both temperature and rainfall data for the time steps under observation. For rainfall on an annual basis, there were no statistically significant monotonic trends detected, although non-significant downward trends were dominant. However, significant decreasing rainfall trends were observed in dry and low rainfall months, which were April, August, September, and November. In contrast, significant upward temperature trends were detected at the Vereeniging climate station at an annual scale and in October, November, spring, and winter. The findings are critical for climate risk management and reduction decisions for both near- and long-term timescales.

This study integrated climate projections from five global climate models (GCMs) into the soil and water assessment tool to evaluate the potential impact of climate alterations on the Rietspruit River sub-basin under two representative concentration pathways (RCP4.5 and 8.5). The model's performance was evaluated based on the coefficient of determination (R2), percent bias (PBIAS), Nash–Sutcliffe efficiency (NSE), probability (P)-factor and correlation coefficient (R)-factor. Calibration results showed an R2 of 0.62, NSE of 0.60, PBIAS of 20, P-factor of 0.86 and R-factor of 0.91, while validation produced an R2 of 0.64, NSE of 0.61, PBIAS of 40, P-factor of 0.85 and R-factor of 1.22. Precipitation is predicted to increase under both RCPs. Maximum temperature is projected to increase under both RCPs, with a major increase in the winter months. Minimum temperatures are projected to decrease under RCP4.5 in the near (−0.99 °C) and mid (−0.23 °C) futures, while the far future is projected to experience an increase of 0.14 °C. Precipitation and temperature changes correspond to increases in streamflow by an average of 53% (RCP4.5) and 47% (RCP8.5). These results indicate a need for an integrated approach in catchment water resource management amid potential climate and land use variations.

A qualitative system dynamics modelling framework was applied in this study to analyze the main driving forces and their feedback interactions influencing water resources management in the Rietspruit sub-basin, South Africa. The dynamics of the water resource system were analyzed using the Vensim™ PLE modelling platform and its archetypes of causal loop diagram, reinforcing and balancing loops. The model visually displayed the causal links of different processes influencing the water resource system and their feedback loops. Special focus was to ascertain and analyze the reinforcing feedback loops within a typical urbanized watershed, with the aim of depicting constraints that could influence sustainable water resource management and adaptation thereof. The causal loop model synthesized that, based on evidence from scientific literature and policy documents, the main driving forces towards the water resource challenges in the study area are associated with rising temperature, degraded water infrastructure and institutional and socioeconomic processes. The study, through the presented conceptual model, offered leverage points and potential pathways for sustaining both water quantity and quality, including infrastructure investment, sustainable revenue generation, decentralized groundwater use and public awareness and participation. The analysis in this study provided a conceptual framework for understanding of interactions of elements within the different systems influencing water resources in the Rietspruit sub-basin. This could be key for ensuring effective and sustainable management of the resource in the context of changing climate and socioeconomic developments.