• Energy Research

Understanding the impacts of climate change requires the development of hydrological modelling tools. However, data scarcity hinders model application, performance, process simulation and uncertainty, especially for Sub-Saharan Africa. In this study, a multi-catchment approach was used to assess hydrological process variability in the Western Cape (WC) of South Africa using the JAMS/J2000 rainfall–runoff model and a Monte Carlo analysis (MCA). Due to much steeper slopes and lower evapotranspiration, the models suggest that WC is dominated by surface runoff from mountainous regions and regional groundwater flow. The results highlight the impact of the catchment size, availability and position of hydroclimatic and anthropogenic factors and the frequency of the signal-to-noise ratio (water balance). For large catchments (>5000 km2), the calibration was able to achieve a Nash–Sutcliffe efficiency (NSE) of 0.61 to 0.88. For small catchments (<2000 km2), NSE was between 0.23 to 0.39. The large catchments had an overall surface runoff, interflow and baseflow contribution of 44, 19 and 37%, respectively, and lower overall uncertainty. The simulated flow components for the small catchments were variable and these results are less certain. The use of a multi-catchment approach allows for identifying the specific factors impacting parameter sensitivities and in turn provides a means to improve hydrological process simulation.

Understanding the impacts of climate change requires the development of hydrological modelling tools. However, data scarcity hinders model application, performance, process simulation and uncertainty, especially for Sub-Saharan Africa. In this study, a multi-catchment approach was used to assess hydrological process variability in the Western Cape (WC) of South Africa using the JAMS/J2000 rainfall–runoff model and a Monte Carlo analysis (MCA). Due to much steeper slopes and lower evapotranspiration, the models suggest that WC is dominated by surface runoff from mountainous regions and regional groundwater flow. The results highlight the impact of the catchment size, availability and position of hydroclimatic and anthropogenic factors and the frequency of the signal-to-noise ratio (water balance). For large catchments (>5000 km2), the calibration was able to achieve a Nash–Sutcliffe efficiency (NSE) of 0.61 to 0.88. For small catchments (<2000 km2), NSE was between 0.23 to 0.39. The large catchments had an overall surface runoff, interflow and baseflow contribution of 44, 19 and 37%, respectively, and lower overall uncertainty. The simulated flow components for the small catchments were variable and these results are less certain. The use of a multi-catchment approach allows for identifying the specific factors impacting parameter sensitivities and in turn provides a means to improve hydrological process simulation.

In the case of the African continent, the estimates of most climate forcing components are associated with large uncertainties, above all the greenhouse gas budget. The EU-funded SEACRIFOG project is designing an observation network which aims at reducing these uncertainties. In this practice paper, we present the various steps towards the design of this network and discuss the data-related implications. This includes the formulation of appropriate observational requirements for each variable considered essential to quantify Africa-wide climate forcing as well as an assessment of corresponding available observational infrastructures and data in order to determine data gaps, needs and priorities. The results are intended to inform the design of an interoperable African data infrastructure for environmental observations.

In the case of the African continent, the estimates of most climate forcing components are associated with large uncertainties, above all the greenhouse gas budget. The EU-funded SEACRIFOG project is designing an observation network which aims at reducing these uncertainties. In this practice paper, we present the various steps towards the design of this network and discuss the data-related implications. This includes the formulation of appropriate observational requirements for each variable considered essential to quantify Africa-wide climate forcing as well as an assessment of corresponding available observational infrastructures and data in order to determine data gaps, needs and priorities. The results are intended to inform the design of an interoperable African data infrastructure for environmental observations.

AbstractGlobal population projections foresee the biggest increase to occur in Africa with most of the available uncultivated land to ensure food security remaining on the continent. Simultaneously, greenhouse gas emissions are expected to rise due to ongoing land use change, industrialisation, and transport amongst other reasons with Africa becoming a major emitter of greenhouse gases globally. However, distinct knowledge on greenhouse gas emissions sources and sinks as well as their variability remains largely unknown caused by its vast size and diversity and an according lack of observations across the continent. Thus, an environmental research infrastructure—as being setup in other regions—is more needed than ever. Here, we present the results of a design study that developed a blueprint for establishing such an environmental research infrastructure in Africa. The blueprint comprises an inventory of already existing observations, the spatial disaggregation of locations that will enable to reduce the uncertainty in climate forcing’s in Africa and globally as well as an overall estimated cost for such an endeavour of about 550 M€ over the next 30 years. We further highlight the importance of the development of an e-infrastructure, the necessity for capacity development and the inclusion of all stakeholders to ensure African ownership.

AbstractGlobal population projections foresee the biggest increase to occur in Africa with most of the available uncultivated land to ensure food security remaining on the continent. Simultaneously, greenhouse gas emissions are expected to rise due to ongoing land use change, industrialisation, and transport amongst other reasons with Africa becoming a major emitter of greenhouse gases globally. However, distinct knowledge on greenhouse gas emissions sources and sinks as well as their variability remains largely unknown caused by its vast size and diversity and an according lack of observations across the continent. Thus, an environmental research infrastructure—as being setup in other regions—is more needed than ever. Here, we present the results of a design study that developed a blueprint for establishing such an environmental research infrastructure in Africa. The blueprint comprises an inventory of already existing observations, the spatial disaggregation of locations that will enable to reduce the uncertainty in climate forcing’s in Africa and globally as well as an overall estimated cost for such an endeavour of about 550 M€ over the next 30 years. We further highlight the importance of the development of an e-infrastructure, the necessity for capacity development and the inclusion of all stakeholders to ensure African ownership.