Joris Eekhout

Climate change will most likely cause an increase of extreme precipitation and consequently an increase of soil erosion in many locations worldwide. In most cases, climate model output is used to assess the impact of climate change on soil erosion, however, there is little knowledge of the implications of bias‐correction methods and climate model ensembles on projected soil erosion rates. Using a soil erosion model, we evaluated the implications of three bias‐correction methods (delta change, quantile mapping and scaled distribution mapping) and climate model selection on regional soil erosion projections in two contrasting Mediterranean catchments. Depending on the bias‐correction method, soil erosion is projected to decrease or increase. Scaled distribution mapping best projects the changes in extreme precipitation. While an increase in extreme precipitation not always results in increased soil loss, it is an important soil erosion indicator. We suggest to first establish the deviation of the bias‐corrected climate signal with respect to the raw climate signal, in particular for extreme precipitation. Furthermore, individual climate models may project opposite changes with respect to the ensemble average, hence, climate model ensembles are essential in soil erosion impact assessments to account for climate model uncertainty. We conclude that the impact of climate change on soil erosion can only accurately be assessed with a bias‐correction method that best reproduces the projected climate change signal, in combination with a representative ensemble of climate models.

Climate change will strongly affect essential ecosystem services, like the provision of freshwater, food production, soil erosion and flood control. Sustainable Land Management (SLM) practices are increasingly promoted to contribute to climate change mitigation and adaptation, but there is lack of evidence at scales most relevant for policymaking. We evaluated the effectiveness of SLM in a large Mediterranean catchment where climate change is projected to significantly reduce water security. We show that the on-site and off-site impacts of climate change are almost entirely reversed by the large-scale implementation of SLM under moderate climate change conditions, characterized by limited reductions in annual precipitation but significant increased precipitation intensity. Under more extreme reductions of annual precipitation, SLM implementation reduces the impacts on water security, but cannot prevent significant increased plant water stress and reduced water availability. Under these conditions, additional adaptation measures are required considering their interactions and trade-offs regarding water security.

An increase in extreme precipitation is projected for many areas worldwide in the coming decades. To assess the impact of increased precipitation intensity on water security, we applied a regional-scale hydrological and soil erosion model, forced with regional climate model projections. We specifically considered the impact of climate change on the distribution of water between soil (green water) and surface water (blue water) compartments. We show that an increase in precipitation intensity leads to a redistribution of water within the catchment, where water storage in soil decreases and reservoir inflow increases. This affects plant water stress and the potential of rainfed versus irrigated agriculture, and increases dependency on reservoir storage, which is potentially threatened by increased soil erosion. This study demonstrates the crucial importance of accounting for the fact that increased precipitation intensity leads to water redistribution between green and blue water, increased soil erosion, and reduced water security. Ultimately, this has implications for design of climate change adaptation measures, which should aim to increase the water holding capacity of the soil (green water) and to maintain the storage capacity of reservoirs (blue water), benefiting rainfed and irrigated agriculture.