Joris Eekhout

This research studies the effect of climate change on the hydrological behavior of two semi-arid basins. For this purpose the SWAT model was used, with the simulation of two future climate change scenarios, one 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). Also, 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 = 0.41- 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 RCP4.5 and RCP8.5 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 45.16% and 59.35% and between 45.89% and 63.85%, respectively.

Worldwide, Mediterranean cropping systems face the complex challenge of producing enough high-quality food while preserving the quantity and quality of scarce water for people and agriculture in the context of climate change. While good management of nitrogen (N) is paramount to achieving this objective, the efficient strategies developed for temperate systems are often not adapted to the specificities of Mediterranean systems. In this work we combined original data with a thorough literature review to highlight the most relevant drivers of N dynamics in these semiarid systems. To do so, we provide an analysis at nested scales combining a bottom–up approach from the field scale with a top–down approach considering the agro-food system where cropping systems are inserted. We analyze the structural changes in the agro-food systems affecting total N entering the territory; the contrasting response of yields to N availability under rainfed and irrigated conditions in a precipitation gradient; the interaction between N management and climate change adaptation; the main drivers affecting the release of Nr compounds (NO3-, NH3, NO, N2O) as compared with temperate systems; and finally, the behavior of N once exported to highly regulated river networks. We conclude that a sustainable N management in Mediterranean cropping systems requires the specific adaptation of practices to the particular local agroenvironmental characteristics with special emphasis on water availability for rainfed and irrigated systems. This approach should also include a systemic analysis of N inputs into the territory that are driven by the configuration of the agro-food system.

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 consisted 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 semi-arid 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.