Francis Matthews (Author), Anže Medved (Author), Pasquale Borrelli (Author), Leonidas Liakos (Author), G. Verstraeten (Author), Panos Panagos (Author), Nejc Bezak (Author)

Abstract

Rainfall erosivity maps for (near) real-time soil erosion predictions require the integration of (combinations of) reanalysis products and satellite-retrievals of rainfall, and the overcoming of potential bias related to their simplified spatial and temporal scale. Across Europe, we evaluate: 1) the European Meteorological Observations (EMO) dataset to simulate the localised characteristics of rainfall erosivity at the event scale (EI30), and 2) different implementations of quantile delta mapping (QDM) bias correction to improve the prediction skill. Between 1990 and 2014, evaluations were made at several spatial (location-specific, climatic zone and panEuropean) and temporal (event, annual and long-term annual average) scales. The uncorrected EMO predictions demonstrated: 1) a slight overprediction of the number of EI30 events, 2) a reduced coefficient of variation in the EI30 (CV EMO = 1.57, CV REDES = 2.5), and 3) a relatively low (R 2 = 0.22, n = 139,306) location-specific predictive skill, with higher discrepancies in all cases in Southern Europe. Following QDM, the EI30 predictions significantly better represented the large-sample variability of EI30 per climate region and improved the monthly correspondence. At specific locations, station-wise bias correction was the only implementation to improve the event (R 2 (R 2 = 0.24, n = 139,306), annual (R 2 = 0.51, n = 14,248) and average annual =0.76, n = 1142) predictions. While bias correction can improve rainfall erosivity predictions, applications should consider possibly large error propagation into subsequent predictions, regional disparities in performance, and the potential to improve the large-sample statistical correspondence but degrade the location-specific time series prediction.

Keywords

erozivnost padavin;odpravljanje pristranskosti;Evropa;baza REDES;klimatske regije;EMO;rainfall erosivity;bias correction;quantile delta mapping;Europe;REDES base;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FGG - Faculty of Civil and Geodetic Engineering
UDC: 502/504:556
COBISS: 106880515 Link will open in a new window
ISSN: 0022-1694
Views: 1213
Downloads: 82
Average score: 0 (0 votes)
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Other data

Secondary language: Slovenian
Secondary keywords: podnebne spremembe;kmetijstvo;tla;spremembe rabe tal;R-faktor;varnost hrane;
Type (COBISS): Article
Pages: str. 1-17
Issue: ǂLetn. ǂ651
Chronology: 2025
DOI: 10.1016/j.jhydrol.2024.132460
ID: 15504052