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Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical...

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Detalles Bibliográficos
Autores principales: Panagos, Panos, Ballabio, Cristiano, Meusburger, Katrin, Spinoni, Jonathan, Alewell, Christine, Borrelli, Pasquale
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier, etc 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473165/
https://www.ncbi.nlm.nih.gov/pubmed/28649140
http://dx.doi.org/10.1016/j.jhydrol.2017.03.006
Descripción
Sumario:The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha(−1) h(−1) yr(−1) till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April–September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.