The calculation of the R-factor (Rainfall erosivity) for implementation in soil erosion models such as USLE (Universal Soil Loss Equation) and RUSLE (Revised Universal Soil Loss Equation) encounters substantial difficulties due to the scarcity of spatial databases in adequate resolution for actions of territorial planning at the local level. Otherwise, there is a spatial database available with a coarse resolution of themes that can be used to calculate the R-factor. We apply the spatial downscaling, based on regression models: linear (LN), general additive model (GAM), random forest (RF), cubist (CU), on erosivity data (target variable) prepared for the State of São Paulo, Brazil, with a spatial resolution of 2,500 m. We used DEM and slope data with 30 m fine-resolution from the Atibaia watershed, located between the metropolitan regions of São Paulo (RMSP) and Campinas (RMC) to apply the downscaling. This framework improved the spatial resolution of the R-factor, necessary to calculate soil loss in the USLE and RUSLE equations in a territory where the scarcity of data with the fine resolution is still limited to the development of territorial planning projects at the local level. The RF model was better with R2 0.93.
The proceding considered an validated R factor database. The paper proposed a resample based on regression models tested in spatial analysis. The methodology can improve with research advanced, for example, apply other fine resolution datasets.
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To downscale the REF resolution, several approaches can be employed. One common method involves using high-resolution rainfall data obtained from weather stations or remote sensing technologies. These data sources provide more detailed information on precipitation patterns, allowing for a more accurate representation of erosivity within the watershed. Additionally, incorporating local topographic factors, such as slope gradient, minecraftle game, and aspect, into the erosion calculations can help refine the downscaled REF estimations. These factors influence the redistribution of rainfall and runoff, further affecting erosive forces in the Atlantic Forest biome.
