Estimation of rainfall erosivity in Piedmont (Northwestern Italy) by using 10-minute fixed-interval rainfall data

Abstract

⎯ Rainfall erosivity index (EI 30) is widely used in soil erosion models for predicting soil loss. This index consists in the product between the maximum intensity of 30-min rainfall and the total kinetic energy of a precipitation event. The main goal of this study was to characterize the soil erosion in Piedmont (Northwestern Italy), studying the magnitude, frequency, and trends of rainfall erosivity. Rainfall erosivity for twelve stations well distributed over the whole region were firstly computed on the basis of 10-min timeresolution rainfall data using a continuous 17-year series of daily rainfall events. For each station the equation to predict EI 30 from daily rainfall data was calculated, and, using the Nash and Sutcliffe (1970) model-efficiency, the relationships between real EI 30 and modeled EI 30 was validated. The rainfall erosivity model was applied to the long term daily rainfall series of the selected stations, to create annual and seasonal erosivity time series for the climate normal period 1986-2015. Afterwards, the Mann-Kendall non-parametric test statistic to detect time trends in the rainfall erosivity time series was applied. The results have led to the conclusion that the annual rainfall erosivity should have experienced mixed trends in most of the study area, although more than half of the stations did not show a statistical trend.

Reconstruction of erosivity density in northwest Italy since 1701

“…the ratio of rainfall erosivity to precipitation, as a proxy of the rainfall erosive hazard (Renard et al 2011). A precipitation dataset was recently released for this region, and data were published for 12 stations over 30 years at a 10minute time resolution (Acquaotta et al 2019). Based on this novel set of data, we developed and assessed a parsimonious rainfall erosivity model for estimating the related ED.…”

“…Although Acquaotta et al (2019) quantified rainfall erosivity in Piedmont for the period 1989-2015, there is a particular interest in investigating long-term variability and trends of erosive precipitation in the region. This is because in northwest Italy, geomorphology is an important factor shaping the water height and flooded areas (Giordan et al 2018).…”

Historical predictability of rainfall erosivity: a reconstruction for monitoring extremes over Northern Italy (1500–2019)

“…Annual (R)USLE-based rainfall erosivity data (1981-2015) were extracted from a high-resolution database with precipitation measurements taken at 23 locations across the PRL (over 7°-11°E and 44°-46°N), of which 11 are from the upper west side of the Po River Basin (Susa, Luserna, Boves, Mondovì, Bra, Turin, Lanzo, Oropa, Varallo Sesia, Vercelli, and Casale Monferrato, in the Piedmont Region) 100 , and 12 from the central and lower east-side (Carpeneto, Milano, Zanzarina, Montanaso Lombardo, Colico, Parma, Bedonia, Levanto, Albareto, Piacenza, Brescia and Padua). For the period 1993-2015, (R)USLE-based data were available for the 23 meteorological stations (with updating until 2015) 101,102 because the digital National Agrometeorological Network (https://tinyurl.com/h4juzuv) came into operation in 1993. For this period, an annual series of erosivity data for the PRL was obtained by averaging the annual erosivity values determined in each station located in the basin, and this dataset was used to determine model parameters (calibration dataset).…”

Fingerprint of climate change in precipitation aggressiveness across the central Mediterranean (Italian) area

“…(R)USLE-based actual rainfall erosivity data. Annual (R)USLE-based R-factor data (1981-2015) were derived from Diodato 89 and Acquaotta et al 90 , with updating from the network of SCIA (http://www.scia.ispra mbien te.it/wwwro otsci a/scia.html)-National System for the Collection and Elaboration of Climatological Data 91 , for a total of 37 stations (Fig. 6).…”