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Open AccessArticle

Future Scenarios of Soil Erosion in the Alps under Climate Change and Land Cover Transformations Simulated with Automatic Machine Learning

1
Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, 20133 Milano, Italy
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Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy, 20133 Milano, Italy
3
Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milano, Italy
*
Author to whom correspondence should be addressed.
Climate 2020, 8(2), 28; https://doi.org/10.3390/cli8020028
Received: 4 January 2020 / Revised: 31 January 2020 / Accepted: 3 February 2020 / Published: 7 February 2020
Erosion is one of the major threats listed in the Soil Thematic Strategy of the European Commission and the Alps are one of the most vulnerable ecosystems, with one of the highest erosion rates of the whole European Union. This is the first study investigating the future scenarios of soil erosion in Val Camonica and Lake Iseo, which is one of the largest valleys of the central Italian Alps, considering both climate change and land cover transformations. Simulations were done with the Dynamic Revised Universal Soil Loss Equation (D-RUSLE) model, which is able to account also for snow cover and land cover dynamics simulated with automatic machine learning. Results confirm that land cover projections, usually ignored in these studies, might have a significant impact on the estimates of future soil erosion. Our scenario analysis for 2100 shows that if the mean annual precipitation does not change significantly and temperature increases no more than 1.5–2.0 °C, then the erosion rate will decrease by 67% for about half of the study area. At the other extreme, if the mean annual precipitation increases by more than 8% and the temperature increases by more than 4.0 °C, then about three-quarters of the study area increases the erosion rate by 92%. What clearly emerges from the study is that regions with higher erosion anomalies (positive and negative) are expected to expand in the future, and their patterns will be modulated by future land transformations.
Keywords: machine learning; climate change; land cover changes; soil erosion; Alps machine learning; climate change; land cover changes; soil erosion; Alps
MDPI and ACS Style

Gianinetto, M.; Aiello, M.; Vezzoli, R.; Polinelli, F.N.; Rulli, M.C.; Chiarelli, D.D.; Bocchiola, D.; Ravazzani, G.; Soncini, A. Future Scenarios of Soil Erosion in the Alps under Climate Change and Land Cover Transformations Simulated with Automatic Machine Learning. Climate 2020, 8, 28.

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