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Erosivity and seasonal rainfall for Pelotas-RS, Brazil with the RainfallErosivityFactor package and Modified Fournier Index

环境科学 降水 气候学 数据系列 相关系数 水文学(农业) 索引(排版) 腐蚀 系列(地层学) 气象学 地质学 统计 地理 数学 古生物学 岩土工程 万维网 计算机科学 计量经济学
作者
Maria Cãndida Moitinho Nunes,Dione Pereira Cardoso,Tainara Vaz de Melo,Viviane Rodrigues Dorneles,Ana Paula Knapp,Samanta Tolentino Cecconello
出处
期刊:Journal of South American Earth Sciences [Elsevier BV]
卷期号:132: 104649-104649 被引量:1
标识
DOI:10.1016/j.jsames.2023.104649
摘要

One of the main factors affecting water erosion is rainfall erosivity. Knowledge of this factor can contribute to the prediction of soil losses and to the identification of the most suitable periods for agricultural cultivation operations. The use of software, based on current calculation tools, can contribute to the quick and accurate analysis of long series of rainfall data. The objective of this work is to determine the rainfall volume and rainfall erosivity (R), in different seasons of the year, through the correlation between the EI30 index, the rainfall coefficient (Rc) and the Fournier Index modified (MFI), for rainfall data from Pelotas-RS-Brazil. Rainfall data was used with an interval of 10 min, from 1993 to 2015, evaluated with the RainfallErosivityFactor package of the R-Project software. In the package, the R-factor is obtained by averaging the monthly EI30 values from the data series. Data was evaluated on a monthly, annual and seasonal scale. It was found that the average annual rainfall is 1369.46 mm, with February being the month with the highest rainfall. The series of annual precipitation data did not show a significant trend according to the Mann-Kendall test and the average annual erosivity is 8166.8 MJ mm h−1 ha−1 yr−1. Erosivity in summer is significantly higher than in winter, with the summer-autumn period accounting for 64.4% and winter represented only 17% of annual erosivity. There is a strong positive correlation between the erosivity and the rainfall coefficient, for monthly average data. Erosivity and MFI showed a very strong significant correlation for summer and autumn. The rainfall coefficient tended to show lower values in March and higher values in February. The results obtained are important to identify the periods of most critical erosivity, in which management systems must prioritize surface coverage and minimum soil disturbance.

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