Estimativa do índice de erosividade da chuva no Brasil com dados de precipitação sub-horários

Abstract

Rain erosivity is one of the parameters of the universal soil loss equation (USLE) and quantifies the erosive potential of a rainfall event. To calculate this variable, precipitation data with sub- hourly resolution is necessary, since it is defined according to the occurrence of the intensity peak in relation to its duration. Furthermore, there is a need for temporal coverage of at least 10 years to guarantee the representativeness of the results. Many studies have been carried out with the aim of calculating and spatializing this quantity, however, the difficulties in obtaining rainfall data with these characteristics pose an impasse for this type of study, and many authors end up opting for the use of synthetic series or empirical equations that relate daily or monthly precipitation and erosivity. This research proposed, in an unprecedented way, to use sub-hourly data from 2 different databases (CEMADEN and ANA) combined with 4,560 rain gauge stations over the last 11 years (2014 to 2024) to estimate the erosivity of rain in the National territory. The methodology adopted for the calculation follows the guidelines established by Wischmeier and Smith (1978). Using the Minimum Time Intervals (MIT) method to identify rainy events. For data analysis, statistical and geostatistical techniques were applied, including Ordinary Kriging, which allows the spatial interpolation of erosivity values based on the spatial correlation between the sampled points. Cross-validation was applied to evaluate the accuracy of the erosivity map generated by interpolation. The model presented a coefficient of determination (R²) of 0.64, indicating a good correlation between the estimated and observed values. Furthermore, the mean absolute percentage error (EMA%) was less than 10%, demonstrating the reliability of the map produced. As a result of the study, three sets of products were generated: (1) A database with highly reliable rainfall erosivity values with sub-hourly resolution; (2) Interpolated rain erosivity map for Brazil highlighting the areas with the greatest erosive potential; (3) And a main script validated with RIST software (USDA) for calculations plus other scripts for reading, processing and presenting results. The results of this study allow the identification of areas of greater erosivity and provide a detailed spatial view, assisting in planning soil conservation and water resources management.