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利用 GIS 和遥感技术的 RUSLE 模型估算土壤侵蚀:孟加拉国第三纪丘陵地区 2017 年至 2021 年的案例研究。

Soil erosion estimation by RUSLE model using GIS and remote sensing techniques: A case study of the tertiary hilly regions in Bangladesh from 2017 to 2021.

机构信息

Soil, Water and Environment Discipline, Khulna University, Khulna-9208, Bangladesh.

French National Research Institute for Agriculture, Food and Environment (INRAE), Poitou-Charentes, URP3F, 86600, Lusignan, France.

出版信息

Environ Monit Assess. 2023 Aug 26;195(9):1096. doi: 10.1007/s10661-023-11699-4.

Abstract

Soil erosion is one of the major environmental threats in Bangladesh, especially in the tertiary hilly regions located in the northeastern and southeastern parts of the country. The revised universal soil loss equation (RUSLE), combined with Geographic Information System, is a reliable methodology to estimate the potential soil loss in an area. This research aimed to use the RUSLE model to estimate the soil erosion in the tertiary hill tracts of Bangladesh from 2017 to 2021. The erosivity factor was determined from the annual average precipitation, and erodibility factor was estimated from FAO soil database. The elevation model was used to analyze slope length steepness factors, while land use land cover was used to compute cover management factor. Lastly, land use and elevation were integrated to estimate the support practice factor. Results revealed that the potential mean annual soil loss in 2017, 2019, and 2021 was 68.77, 69.84, and 83.7 ton ha year from northeastern and 101.72, 107.83, and 114.04 ton ha year from southeastern region, respectively. Although total annual rainfall was high in 2017, soil loss was found higher in 2021 which indicates the impact of land use change on erosion. This investigation will help the policymakers to identify the erosion-vulnerable areas in the hill tracts that require immediate soil conservation practices. Additionally, there is no latest field-based data available for the country for the validation, and hence, it is recommended to conduct field-based studies for validating the model-derived results and creating a reliable soil erosion database for the country.

摘要

土壤侵蚀是孟加拉国面临的主要环境威胁之一,尤其是在该国东北部和东南部的第三纪丘陵地区。修正后的通用土壤流失方程(RUSLE)结合地理信息系统是估算一个地区潜在土壤流失的可靠方法。本研究旨在利用 RUSLE 模型估算 2017 年至 2021 年期间孟加拉国第三纪丘陵地区的土壤侵蚀。侵蚀性因子由年平均降水量确定,可蚀性因子由粮农组织土壤数据库估计。利用高程模型分析坡度长度陡峭因子,利用土地利用/土地覆被计算覆盖管理因子。最后,综合土地利用和高程来估算支撑实践因子。结果表明,2017 年、2019 年和 2021 年东北部地区的潜在平均年土壤流失量分别为 68.77、69.84 和 83.7 吨公顷年,东南部地区分别为 101.72、107.83 和 114.04 吨公顷年。尽管 2017 年的总年降雨量较高,但 2021 年的土壤流失量较高,这表明土地利用变化对侵蚀的影响。这项研究将帮助决策者识别丘陵地区需要立即采取土壤保持措施的侵蚀易损区。此外,由于该国没有最新的实地数据进行验证,因此建议进行实地研究,以验证模型得出的结果,并为该国创建可靠的土壤侵蚀数据库。

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