The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are suggested to be an important source of uncertainty. Here, we present a novel soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments. The model ensemble consists of five continuous process‐based soil erosion models that run at a daily time step (i.e., DHSVM, HSPF, INCA, MMF, SHETRAN). The models were implemented in the SPHY hydrological model and simulate detachment by raindrop impact, detachment by runoff, and immediate deposition. The soil erosion model ensemble was applied in a semiarid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3°C). Data from two contrasting regional climate models were used to assess how an increase and a decrease in projected extreme precipitation affect model uncertainty. Soil loss is projected to increase (up to 95%) and decrease (up to −30%) under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent of the projected change in annual precipitation and extreme precipitation. This stresses the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate‐change impact assessments.
This research studies the effect of climate change on the hydrological behavior of two semi-arid basins. For this purpose, the Soil and Water Assessment Tool (SWAT) model was used with the simulation of two future climate change scenarios, one Representative Concentration Pathway moderate (RCP 4.5) and the other extreme (RCP 8.5). Three future periods were considered: close (2019–2040), medium (2041–2070), and distant (2071–2100). In addition, several climatic projections of the EURO-CORDEX model were selected, to which different bias correction methods were applied before incorporation into the SWAT model. The statistical indices for the monthly flow simulations showed a very good fit in the calibration and validation phases in the Upper Mula stream (NS = 0.79–0.87; PBIAS = −4.00–0.70%; RSR = 0.44–0.46) and the ephemeral Algeciras stream (NS = 0.78–0.82; PBIAS = −8.10–−8.20%; RSR = 0.4–0.42). Subsequently, the impact of climate change in both basins was evaluated by comparing future flows with those of the historical period. In the RCP 4.5 and RCP 8.5 scenarios, by the end of the 2071–2100 period, the flows of the Upper Mula stream and the ephemeral Algeciras stream will have decreased by between 46.3% and 52.4% and between 46.6% and 55.8%, respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.