Simulating event-scale rainfall erosivity across European climatic regions

Soil erosion is time compressed into a number of episodic erosive rainfall events with an associated potential to detach and transport soil particles (rainfall erosivity), each possessing unique spatial temporal characteristics. Rainfall erosivity in Europe follow extreme value distributions which limited rainstorms dominate the long-term budget available energy. To combat targeted manor, timely mitigation measures should derive from dynamic model simulations that incorporate spatially temporally distributed estimations erosivity. Rain gauge measurements singular points are typically used quantify erosivity, however uniqueness presents key limitation dynamically across broad scales point measurements. Discretised gridded precipitation datasets widespread (e.g. continental) coverage potentially offer opportunity adequately replicate dynamics events, their performance remains poorly tested pan-European context. This study builds upon comprehensive Erosivity Database at European Scale (REDES) archive over 300,000 1181 stations develop two-step modelling process: 1) firstly, optimal monthly models were fitted evaluated between gauge-recorded depth (EI30) climatic regions European-scale parameter surface, 2) secondly, three (EMO-5 (6-hr), E-OBS (24-hr), UERRA MESCAN-SURFEX (24hr)) directly via grid-to-point analysis based on ability simulate station-specific event timeseries random selection 32 locations. EMO-5 (Nash-Sutcliffe efficiency mean = 0.24) outperformed other datasets, showing capability number, timing, average magnitude. A higher Northern compared Southern regions, characteristically spatially-complex magnitudes found, was symptomatic poor grid-based outer extents frequency-magnitude spectrum. The absence clear global systematic predictive bias amongst simulated locations suggests need for future upscaling this entire REDES dataset fully understand correct method-derived climate region-specific way.