, Odisha, India.
Hydrology and Engineering Division, ICAR-Indian Institute of Soil and Water Conservation, Dehradun, 248195, India.
Environ Monit Assess. 2020 Oct 29;192(11):733. doi: 10.1007/s10661-020-08688-2.
Human-induced agricultural and developmental activities cause substantial alteration to the natural geography of a landscape; thereby accelerates the geologic soil erosion process. This necessitates quantification of catchment-scale soil erosion under both retrospective and future scenarios for efficient conservation of soil resources. Here, we present a revised universal soil loss equation (RUSLE) based soil erosion estimation framework at an unprecedentedly high spatial resolution (30 × 30 m) to quantify the average annual soil loss and sediment yield from an agriculture-dominated river basin. The input parameters were derived by using the observed rainfall data, soil characteristics (soil texture, hydraulic conductivity, organic matter content), and topographic characteristics (slope length and percent slope) derived from digital elevation model (DEM) and satellite imageries. The developed approach was evaluated in the Brahmani River basin (BRB) of eastern India, wherein the different RUSLE inputs, viz., rainfall erosivity (R factor), soil erodibility (K factor), topographic (LS factor), crop cover (C factor), and management practice (P factor) factors have the magnitude of 1937 to 4867 MJ mm ha h year, 0.023 to 0.039 t h ha MJ ha mm, 0.03 to 74, 0.16 to 1, and 0 to 1, respectively. The estimated average annual soil loss over the BRB ranged from 0 to 319.55 t ha year, and subsequent erosion categorization revealed that 54.2% of basin area comes under extreme soil erosion zones in the baseline period. Similarly, the sediment yield estimates varied in the range of 0.96 to 133.31 t ha year, and 35.81% area were identified as high soil erosion potential zones. The extent of erosion under climate change scenario was assessed using the outputs of HadGEM2-ES climate model for the future time scales of 2030, 2050, 2070, and 2080 under the four representative concentration pathways (RCPs) 2.6, 4.5, 6.0, and 8.5. The severity of soil erosion under climate change is expected to have a mixed impact in the range of -25 to 25% than the baseline scenario. The outcomes of this study will serve as a valuable tool for decision-makers while implementing management policies over the BRB, and can be well extended to any global catchment-scale applications.
人为的农业和发展活动极大地改变了景观的自然地理；从而加速了地质土壤侵蚀过程。这就需要在回顾性和未来情景下对流域尺度的土壤侵蚀进行量化，以有效地保护土壤资源。在这里，我们提出了一个基于修正的普遍土壤流失方程（RUSLE）的土壤侵蚀估算框架，该框架具有前所未有的高空间分辨率（30×30 m），用于量化以农业为主的河流流域的年平均土壤流失和泥沙产量。输入参数是通过利用观测到的降雨数据、土壤特性（土壤质地、水力传导率、有机质含量）和地形特征（坡度长度和坡度百分比）从数字高程模型（DEM）和卫星图像中得出的。所开发的方法在印度东部的布拉马普特拉河流域（BRB）进行了评估，其中不同的 RUSLE 输入，即降雨侵蚀力（R 因子）、土壤可蚀性（K 因子）、地形（LS 因子）、作物覆盖（C 因子）和管理实践（P 因子）的大小分别为 1937 至 4867 MJ mm ha h year、0.023 至 0.039 t h ha MJ ha mm、0.03 至 74、0.16 至 1 和 0 至 1。BRB 的年平均土壤流失量估计值在 0 至 319.55 t ha year 之间，随后的侵蚀分类表明，在基准期内，流域面积的 54.2%属于极端土壤侵蚀区。同样，泥沙产量估计值在 0.96 至 133.31 t ha year 之间变化，35.81%的区域被确定为高土壤侵蚀潜力区。使用 HadGEM2-ES 气候模型的输出，在未来的 2030 年、2050 年、2070 年和 2080 年的四个代表性浓度途径（RCPs）2.6、4.5、6.0 和 8.5 下，评估了气候变化情景下的侵蚀程度。与基准情景相比，气候变化下的土壤侵蚀严重程度预计将在-25%至 25%之间产生混合影响。本研究的结果将为决策者在 BRB 实施管理政策时提供有价值的工具，并可以很好地扩展到任何全球流域尺度的应用。
