Erosivity Estimation and Spatialization in Climatic Mesoregions in the State of Alagoas

Abstract The lack of rainfall data in Alagoas, similar in many regions of the country, makes them use regression equations obtained in other regions of Brazil to calculate the R factor of the Universal Soil Loss Equation. The study aims to: i) define an equation to estimate rainfall erosivity based on the EI30 index and the rain coefficient Rc, ii) validate the data imputation method for rain and erosivity and iii) spatially estimate erosivity in rainy, dry and transition periods to Alagoas. Monthly rainfall data from 54 stations in the period (1960-2016) were used. The equation used showed a significant correlation between the observed and estimated data, according to the coefficients r (93%), R2 (87%) and RMSE (775.2 MJ.mm.ha−1.h−1). The Ordinary Kriging was the best spatial interpolator. The monthly isoerosivity showed that the highest EI30 rates occurred between April and July, a period coinciding with the rainy season in the state. In annual erosivity, the largest records are located in eastern Alagoas, close to the coast. Highlight for the stations Satuba, Maceió, São Luiz do Quitunde and Flexeiras, categorized between moderate and strong. These results will assist in planning conservation practices, especially in areas of vulnerability.摘要 巴西诸多地区与阿拉戈斯州（Alagoas）一样缺乏降雨观测数据，因此常借助巴西其他地区推导得到的回归方程，计算通用土壤流失方程（Universal Soil Loss Equation）中的R因子。本研究旨在实现三项核心目标：一是基于EI30指数与降雨系数Rc，构建降雨侵蚀力估算方程；二是验证降雨与侵蚀力的数据插补方法的有效性；三是针对阿拉戈斯州的雨季、旱季及过渡季，开展侵蚀力的空间估算。本研究采用了1960—2016年间54个气象站点的月尺度降雨数据。所采用的回归方程展现出观测值与估算值间的显著相关性，相关系数r达93%、决定系数R²为87%、均方根误差（RMSE）为775.2 MJ·mm·ha⁻¹·h⁻¹。普通克里金（Ordinary Kriging）为最优空间插值方法。月尺度等侵蚀力分布图显示，最高EI30值出现在4月至7月，该时段与该州的雨季完全吻合。年侵蚀力的高值区集中于阿拉戈斯州东部近海区域。萨图巴（Satuba）、马塞约（Maceió）、圣路易杜基滕德（São Luiz do Quitunde）及弗莱谢拉斯（Flexeiras）等站点的侵蚀力等级被划分为中等至强侵蚀级别，表现尤为突出。本研究结果可为水土保持规划提供科学支撑，尤其适用于生态脆弱区域。