Satellite-based cover management factor assessment for soil water erosion in the Alps

Gianinetto, Marco; Aiello, Martina; Vezzoli, Renata; Nodari, Francesco Rota; Polinelli, Francesco Niccolò; Frassy, Federico; Rulli, Maria Cristina; Ravazzani, Giovanni; Bocchiola, Daniele; Soncini, Andrea; Chiarelli, Davide Danilo; Passera, Corrado; Corbari, Chiara

doi:10.1117/12.2325536

Cited by 1 publication

(3 citation statements)

References 8 publications

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“…As a result of our simulations, we described the dynamics of the cover management factor through the following land cover maps: Clearly, future projections of the cover management factor cannot exploit the satellite observations for reproducing the seasonal dynamics of vegetation. Thus, the cover management factor was estimated by assigning a fixed value to land cover classes at each simulation period (Table 2) [35,47]. This means that our simulations only considered the trend of the C-factor and were not able to reproduce its seasonal variability.…”

Section: Projections Of Future Cover Management Factormentioning

confidence: 99%

“…The erosion scenarios obtained with static land cover are hereafter referred to as SIM#4.5_D2015 and SIM#8.5_D2015, depending on the climate scenarios used. Figure 12 presents the comparison of observed [35,47] vs. the simulated mean annual soil erosion rates for the period 2003-2017 and using the two climate scenarios SIM#4.5 and SIM#8.5. The simulated maps show spatial patterns that are similar to those observed, but the erosion rates are underestimated of about 29% in SIM#4.5_D2015 and 44% in SIM#8.5_D2015 ( Table 6).…”

Section: Effect Of Climate Projections On the Estimates Of Soil Erosionmentioning

confidence: 99%

“…The erosion scenarios obtained by combining the two climate scenarios with dynamic land cover are hereafter referred to as SIM#4.5_LC and SIM#8.5_LC. Figure 15 shows the comparison of observed [35,47] vs. simulated mean annual soil erosion rates for the period 2003-2017 and extracted from those generated from the erosion scenarios SIM#4.5_LC and SIM#8.5_LC. The simulated maps show spatial patterns that are similar to those observed, but the erosion rates are still underestimated (Table 8) Figure 16 shows the maps of soil erosion rate anomaly for the thirty-year periods 2011-2040, 2041-2070, and 2071-2100 under the hypothesis of changes in both climate and land cover.…”

Section: Combined Effects Of Climate and Land Cover Projections On Thmentioning

confidence: 99%

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

Gianinetto

Aiello

Vezzoli

et al. 2020

Climate

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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.

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Section: Projections Of Future Cover Management Factormentioning

confidence: 99%

Section: Effect Of Climate Projections On the Estimates Of Soil Erosionmentioning

confidence: 99%

Section: Combined Effects Of Climate and Land Cover Projections On Thmentioning

confidence: 99%

See 1 more Smart Citation

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

Gianinetto

Aiello

Vezzoli

et al. 2020

Climate

Self Cite

View full text Add to dashboard Cite

show abstract

Satellite-based cover management factor assessment for soil water erosion in the Alps

Cited by 1 publication

References 8 publications

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

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

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