Datasets and approaches for the estimation of rainfall erosivity over Italy: A comprehensive comparison study and a new method
| Autor: | Monia Santini, Guido Rianna, Roberta Padulano |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
Combined use 0207 environmental engineering Climate change 02 engineering and technology 01 natural sciences Copernicus climate data store Earth and Planetary Sciences (miscellaneous) 020701 environmental engineering lcsh:Physical geography 0105 earth and related environmental sciences Water Science and Technology Climate reanalysis Estimation Pattern clustering lcsh:QE1-996.5 Empirical modelling Rainfall erosivity Gridded observations dataset lcsh:Geology Data store Italy Climatology Spatial ecology Comparison study Environmental science Empirical R-factor models lcsh:GB3-5030 |
| Zdroj: | Journal of Hydrology: Regional Studies, Vol 34, Iss, Pp 100788-(2021) |
| ISSN: | 2214-5818 |
| Popis: | The paper considers a methodology to assess rainfall erosivity in Italy for the recent decades (1981–2010), building on datasets and materials freely available, such as those included within the Climate Data Store (CDS) of the Copernicus Climate Change Service (C3S). Twenty-one referenced empirical models to assess rainfall erosivity (R-factor) based on coarse rainfall data are tested and compared; then, a custom model is calibrated, with the support of seasonal rainfall pattern clustering by means of the Self-Organizing Map. Moreover, a large database of sub-hourly rainfall observations, covering the period 2002–2011, is collected and used for validation. Model performances are analysed at the point-scale of the rain gauges and at the spatial scale of different relevant gridded rainfall products: the fifth generation of ECMWF ReAnalysis (ERA5, ERA5-Land), the gridded European observational dataset (E-OBS), all included in the CDS, and SCIA-ISPRA (the Italian standard rainfall gridded dataset). New Hydrological Insights from the Region The proposed methodology provides four alternatives of spatially distributed rainfall erosivity datasets covering Italy with diverse levels of reliability. Analysis of results shows that the best performance is achieved by the combined use of the custom model and the SCIA-ISPRA dataset, followed by ERA5-Land, with the main source of error lying in the use of an empirical model instead of the rigorous model for R-factor estimation, and secondly in the use of gridded rainfall data instead of point-scale rainfall observations. |
| Databáze: | OpenAIRE |
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