Variation characteristics of rainfall erosivity in Guizhou Province and the correlation with the El Niño Southern Oscillation.

Rainfall erosivity is an important indicator that can be used to measure the ability of rain to cause erosion and is connected with the El Niño Southern Oscillation (ENSO) through the transmission of rainfall. This work aimed to explore the characteristics of rainfall erosivity in Guizhou Province and determine its correlation with ENSO. Rainfall erosivity was calculated from daily rainfall data from January 1960 to December 2017. The analyses were conducted using a daily rainfall erosivity model, inverse distance weighted (IDW) interpolation, linear regression analysis, Mann-Kendall test and correlation analysis. The long-term (1960-2017) average rainfall erosivity was 5825.60 MJ·mm·ha-1·h-1 in the study area and showed a high temporal variability with the estimates from the linear trend line ranging from -449.5 MJ·mm·ha-1·h-1/10a to 496.8 MJ·mm·ha-1·h-1/10a. According to rainfall and erosive rainfall, an uneven spatial distribution of rainfall erosivity was observed with an increasing trend from south to north. Temporal distribution of monthly rainfall erosivity was consistent with that of seasonal rainfall erosivity, and concentrated in the summer months (June to August). As the representation indices of ENSO phenomena, the Oceanic Niño Index (ONI), Southern Oscillation Index (SOI) and multivariate ENSO Index (MEI) were selected for correlation analysis with rainfall erosivity. During El Niño events, the ONI, SOI and MEI showed significant correlations (>95% confidence level) with rainfall erosivity, while during La Niña events, only the ONI and MEI were significantly correlated with rainfall erosivity, but no significant correlation was detected during the neutral period or for the entire study period. The degree of rainfall erosion is proportional to the ENSO duration; the longer the ENSO duration, the greater the rainfall erosivity. These findings could help predict soil erosion and be used to develop further adaptation measures to prevent water and soil loss.