Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil.
Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil; Water Resources Department, Federal University of Lavras, Campus Universitário, CP 3037, 37200-900, Lavras, MG, Brazil.
J Environ Manage. 2022 Nov 1;321:115933. doi: 10.1016/j.jenvman.2022.115933. Epub 2022 Aug 13.
One of the greatest threats to maintaining sustainable agro-ecosystems is mitigating the episodic soil loss from farm operations, further exacerbated by meteorological extremes. The Revised Universal Soil Loss Equation (RUSLE) is a model that combines the effects of rain, soil erodibility, topography, land cover, and conservation practices for estimating the annual average soil losses. This study aims to quantify soil water erosion to continental South America (S.A.) through RUSLE using available datasets and characterizing the average sediment delivery rate (SDR) to the major S.A. basins. Soil erodibility was estimated from the Global Gridded Soil Information soil database. LS-factor's topographical parameter was derived from Digital Elevation Models using the "Shuttle Radar Topography Mission" dataset. The R-factor was estimated from a previous study developed for S.A. and the C-factor from the Global Land Cover (Copernicus Global Land Services) database. We used a modeling study for SDR that simulated the annual average sediment transport in 27 basins in S.A. RUSLE set up presented a satisfactory performance compared to other applications on a continental scale with an estimated averaged soil loss for S.A. of 3.8 t ha year. Chile (>20.0 t ha year) and Colombia (8.1 t ha year) showed the highest soil loss. Regarding SDR, Suriname, French Guyana, and Guyana presented the lowest values (<1.0 t ha year). The highest soil losses were found in the Andes Cordillera of Colombia and the Center-South Region of Chile. In the former, the combination of "high" K-factor, "very high" C-factor, and "very high" LS-factor were the leading causes. In the latter, agriculture, livestock, deforestation, and aggressive R-factor explained the high soil loss. Basins with the highest SDR were located in the North Argentina - South Atlantic basin (27.73%), Mar Chiquitita (2.66%), Amazon River basin (2.32%), Magdalena (2.14%) (in Andes Cordillera), and Orinoco (1.83%).
维持可持续农业生态系统的最大威胁之一是减轻农业作业引起的间歇性土壤流失，而气象极端事件则进一步加剧了这一问题。修正后的通用土壤流失方程（RUSLE）是一种模型，它结合了降雨、土壤可蚀性、地形、土地覆盖和保护措施的影响，用于估算年平均土壤流失量。本研究旨在通过使用现有数据集的 RUSLE 量化南美洲大陆（S.A.）的土壤水蚀，并对主要 S.A.流域的平均泥沙输送率（SDR）进行特征描述。土壤可蚀性是根据全球网格化土壤信息土壤数据库估算的。LS 因子的地形参数是从数字高程模型中利用“Shuttle Radar Topography Mission”数据集推导出的。R 因子是根据之前为 S.A.开发的研究估算的，C 因子是从全球土地覆盖（哥白尼全球土地服务）数据库中获得的。我们使用了一项针对 SDR 的建模研究，模拟了 S.A. 27 个流域的年平均泥沙输送。与其他大陆尺度的应用相比，RUSLE 设定表现出了令人满意的性能，估计 S.A.的平均土壤流失为 3.8 t ha year。智利（>20.0 t ha year）和哥伦比亚（8.1 t ha year）的土壤流失最高。关于 SDR，苏里南、法属圭亚那和圭亚那的数值最低（<1.0 t ha year）。在安第斯山脉的哥伦比亚和智利中南部地区发现了最高的土壤流失。在前一个地区，“高”K 因子、“非常高”C 因子和“非常高”LS 因子的组合是主要原因。在后一个地区，农业、畜牧业、森林砍伐和激进的 R 因子解释了高土壤流失的原因。SDR 最高的流域位于北阿根廷-南大西洋流域（27.73%）、马奇基塔（2.66%）、亚马逊河流域（2.32%）、马格达莱纳（2.14%）（在安第斯山脉）和奥里诺科（1.83%）。
