Effect of erosive efficient rains specification on rainfall erosivity factor

0584242 - ÚVGZ 2024 RIV SK eng J - Journal Article
Středová, H. - Štěpánek, Petr - Středa, T. - Nejedlík, P.
Effect of erosive efficient rains specification on rainfall erosivity factor.
Contributions to geophysics and geodesy. Roč. 53, č. 3 (2023), s. 301-318. ISSN 1338-0540
Research Infrastructure: CzeCOS IV - 90248
Institutional support: RVO:86652079
Keywords : period * storms * kinetic energy * climate change * water erosion
OECD category: Climatic research
Impact factor: 0.7, year: 2022
Method of publishing: Open access
https://journal.geo.sav.sk/cgg/article/view/472/427

The water erosion represents one of the most dangerous degradation processes on agricultural land. Its estimation is thus necessary for setting rules and defining appropriate strategies for soil protection. An estimation of a long-term average annual soil loss by water erosion is frequently based on the Universal Soil Loss Equation (USLE) defined as a product of six factors, where rainfall erosivity factor (R factor) is a leading one. R factor is a multi-annual average index that measures rainfall kinetic energy and intensity describing the effect of erosive efficient rains (EER) on sheet and rill erosion. EER were defined by total higher than 12.7 mm and intensity higher than 6.4 mm in 15 minutes. As those ERR criteria are being used differently by various studies, we decided to compare R factor derived by two variants of ERR criteria: i) EER must fulfil both minimal total and minimal intensity (VAR_AND), ERR must fulfil either minimal total or minimal intensity (VAR_OR). Based on 1-minute precipitation totals database of Czech hydrometeorological institute for 111 stations for 1991-2021 we conclude that mean of Ra VAR_AND across altitude is about 30% lower than Ra VAR OR while there is high statistical significant correlation between those two variants. In addition, annual values of R factor derived by both variants show a statistically significant increase in a long run which calls for updating the R-factor values to reflect increasing climate change impacts.
Permanent Link: https://hdl.handle.net/11104/0352202