The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha−1 h−1 yr−1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

Land surface cover affects runoff generation and soil loss processes. Splash erosion occurs by the impact of raindrops on the soil surface. As a result of this process, raindrops detach soil particles, destroy soil structure, and finally, increase runoff and erosion. Amendments improve and reinforce soil aggregates and some physical barriers against raindrop impacts and runoff. The present research was an attempt to determine the efficiency of straw mulch applied at a rate of 0.5 g m−2 in changing the runoff commencement time, runoff amount, splash erosion, and sediment yield from eroded mid‐sized plots at different rainfall intensities under laboratory conditions. The research was conducted on a sandy loam soil taken from summer rangeland in the Alborz Mountains, northern Iran, with simulated rainfall intensities of 30, 50, 70, and 90 mm h−1 and a slope of 30% in three replicates. The collected data from 36 splash cups showed that the straw mulch played an effective role in reducing the splash erosion in both up and down directions, with the maximum reduction occurring at a rainfall intensity of 70 mm h−1. The results of the research also showed that the straw mulch had a significant effect in changing runoff and soil erosion characteristics at a confidence level of 99%. The maximum increase in runoff commencement time (110.10%) was observed for the rainfall intensity of 90 mm h−1. The runoff coefficient had a maximum reduction at rainfall intensities of 30 and 90 mm h−1. The maximum decrease in sediment yield (63.24%) also occurred at the rainfall intensity of 90 mm h−1.

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Abstract. In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type (∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.

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