ALBERT

Description: To date, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, harvesting). The SWAT+ model represents agricultural land by default in a generic way where the start of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and sub-tropical regions such as the sub-Saharan Africa where crop growth dynamics are mainly controlled by rainfall rather than temperature. In this study, we present an approach on how to incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a regional SWAT+ model for Northeast Africa. We evaluate the influence of the crop phenology representation on simulations of Leaf Area Index (LAI) and Evapotranspiration (ET) using LAI remote sensing data from Copernicus Global Land Service (CGLS) and WaPOR ET data respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations especially for regions with a single cropping cycle. However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. In addition, the improvement of the cropping season also helps to improve soil erosion estimates, as the timing of crop cover controls erosion rates in the model. With more realistic growing seasons, soil erosion is largely reduced for most agricultural Hydrologic Response Units (HRUs) which can be considered as a move towards substantial improvements over previous estimates. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in regional to global hydrological models.

Description: The Nile basin is the second largest basin in Africa and one of the regions experiencing high climatic diversity with variability of precipitation and deteriorating water resources. As climate change is affecting most of the hydroclimatic variables across the world, this study assesses whether historical changes in river flow and sediment loads at selected gauges in the Nile basin can be attributed to climate change. An impact attribution approach is employed by constraining a process-based model with a set of factual and counterfactual climate forcing data for 69 years (1951–2019), from the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). To quantify the role of climate change, we use the non-parametric Mann-Kendall test to identify trends and calculate the differences in long-term mean annual river flow and sediment load simulations between a model setup using factual and counterfactual climate forcing data. Results for selected river stations in the Lake Victoria basin show reasonable evidence of a long-term historical increase in river flows (two stations) and sediment load (one station), largely attributed to changes in climate. In contrast, within the Blue Nile and Main Nile basins, there is a slight decrease of river flows at four selected stations under factual climate, which can be attributed to climate change, but no significant changes in sediment load (one station). These findings show spatial differences in the impacts of climate change on river flows and sediment load in the study area for the historical period.

Description: Nutrient pollution derived from anthropogenic activities impacts both inland and coastal waters, altering the aquatic ecosystem. As climate change is affecting most of the hydroclimatic variables, a fundamental concern in river ecology is therefore to understand the degree to which the spatial patterns and variations of nutrient loading in rivers during the last decades can be associated with climate change. This study detects and attributes the impact of historical climate change on long-term changes in the flux of riverine nutrient pollution into the coastal waters of Africa. An impact attribution approach is employed by forcing a continental process-based water quality model (Soil and Water Assessment Tool – SWAT+) for Africa with a set of observational and counterfactual climate data from the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). The nonparametric Mann–Kendall test is used to identify trends while long-term mean annual river nutrient simulation differences between a model setup with observational and counterfactual climate data are calculated to allow for quantification of the climate change attribution. Results show spatial differences with climate change reasonably contributing to both an increase and decrease of both riverine Total Nitrogen and Total Phosphorus to African coastal waters. However, the climate change imprint on the riverine nutrient export is starting to emerge within the 21st century years for most rivers. These findings show spatial differences in the sensitivity of impacts of climate on riverine TP and TN export to coastal waters while highlighting the most impacted rivers in Africa.