Predicting soil erosion risk using the revised universal soil loss equation (RUSLE) model and geo-spatial methods

IF 3.2 3区 地球科学 Q1 Environmental Science Hydrological Processes Pub Date : 2024-08-07 DOI:10.1002/hyp.15248
Syed Ali Asad Naqvi, Aqil Tariq, Mudsar Shahzad, Shoaib Khalid, Zara Tariq, Ume Salma, Muhammad Haseeb, Walid Soufan
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Abstract

Anthropogenic activities like overgrazing, deforestation and mismanaged land use accelerate soil erosion (SE), causing nutritional and organic matter loss. In this study, we predicted the annual rate of soil loss in the Salt Range, extending south from the Potohar plateau, Pakistan, using the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model parameters and erosion probability zones were estimated using remote sensing and Geo-Spatial methods. The annual average soil loss rates were calculated by considering five geo-environmental factors, that is, slope length and steepness (LS), rainfall erosivity (R), cover management (C), soil erodibility (K), and conservation practice (P) range from 0–559 527, 1404–4431, 0–1, −0.14 to 1.64, and 0.2–122 t . ha 1 . year 1 $$ \left(t.{ha}^{-1}.{year}^{-1}\right) $$ respectively. This research determined that the yearly average rate of SE in the Salt Range varies from over 50 to above 350 t . ha 1 . year 1 $$ \mathrm{t}.{\mathrm{ha}}^{-1}.{\mathrm{year}}^{-1} $$ . The distribution of land area across different SE probability zones reveals that a small portion (2.11%) is classified as High, a moderate portion (7.13%) falls under the category of Moderate, while the majority (90.7%) is classified as Low in terms of proneness towards erosion. The land devoid of vegetation and characterized by steep slopes is especially prone to SE. The Salt Range is highly vulnerable to SE risk due to climatic variations and improper land use practices. The result provides a spatial distribution of SE across the salt range, utilized for management planning processes and conservation at the policy level among decision-makers and land-use planners.

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利用修订的通用土壤流失方程 (RUSLE) 模型和地理空间方法预测土壤侵蚀风险
过度放牧、森林砍伐和土地使用不当等人为活动会加速土壤侵蚀(SE),造成营养和有机物质流失。在这项研究中,我们使用修订的通用土壤流失方程 (RUSLE) 预测了从巴基斯坦波托哈尔高原向南延伸的盐岭地区每年的土壤流失率。RUSLE 模型参数和侵蚀概率区是利用遥感和地理空间方法估算的。考虑到五个地质环境因素,即坡度长度和陡度 (LS)、降雨侵蚀率 (R)、覆盖管理 (C)、土壤可侵蚀性 (K) 和保护措施 (P),计算出的年平均土壤流失率范围分别为 0-559 527、1404-4431、0-1、-0.14 至 1.64 和 0.2-122。这项研究确定,盐岭的年平均 SE 率从 50 以上到 350 以上不等。不同 SE 概率区的土地面积分布显示,一小部分(2.11%)被归类为高侵蚀区,中等部分(7.13%)被归类为中侵蚀区,而大部分(90.7%)被归类为低侵蚀区。没有植被且山坡陡峭的土地特别容易受到东南侵蚀。由于气候多变和土地使用不当,盐岭极易受到 SE 风险的影响。该结果提供了整个盐岭的 SE 空间分布情况,可用于决策者和土地使用规划者的管理规划过程和政策层面的保护。
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来源期刊
Hydrological Processes
Hydrological Processes 环境科学-水资源
CiteScore
6.00
自引率
12.50%
发文量
313
审稿时长
2-4 weeks
期刊介绍: Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.
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