The spatiotemporal variations of global rainfall erosivity and erosive rainfall event based on half-hourly satellite rainfall data

Abstract

At present, station observation data are widely utilized for rainfall erosivity estimation while the spatiotemporal coverage of the data is limited. High-resolution satellite precipitation data offer the possibility of estimating rainfall erosivity with global coverage in a real time manner. A few studies have attempted to use satellite precipitation to derive rainfall erosivity and found that satellite data systematically underestimate rainfall erosivity compared to station observations. Thus, a Global Erosive Rainfall Database (GERD) was constructed using half-hourly satellite rainfall data from 2001 to 2020. Rainfall erosivity was calculated using the rainfall erosivity estimation method in RUSLE2 and bias corrected by a station-based annual average rainfall erosivity map. Then, the spatiotemporal variations of global rainfall erosivity and erosive rainfall event are revealed. The results showed that: (Ⅰ) The 20-year average rainfall erosivity was 2,538.6 MJ mm ha^-1 h⁻¹ yr⁻¹. The 20-year average number of erosive rainfall events was 67 events per annum. (Ⅱ) There has been a discernible downward trend in the global rainfall erosivity anomaly from 2001 to 2020, with an average change rate of –22.09 MJ mm ha^-1 h⁻¹ yr⁻², particularly pronounced in the Southern Hemisphere, where the decline rate reached −68.21 MJ mm ha^-1 h⁻¹ yr⁻². In contrast, the number of erosive rainfall events has exhibited an upward trend during the same period. (III) Seasonal rainfall erosivity and number of erosive rainfall events during the period of June to August were obviously different from other seasons. On 34.1 % and 24.6 % of the global area, rainfall erosivity and number of erosive rainfall events in this period constituted more than half of the whole year.