Temporal variability of global potential water erosion based on an improved USLE model
文献类型：期刊论文
| 作者 | Li, Jialei1,2; Xiong, Muqi3; Sun, Ranhao1,2; Chen, Liding1,2 |
| 刊名 | INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH
 |
| 出版日期 | 2024-03-01 |
| 卷号 | 12期号:1页码:1-12 |
| ISSN号 | 2095-6339 |
| 关键词 | Soil erosion Distributed USLE model Rainfall erosivity Soil conservation Global change |
| DOI | 10.1016/j.iswcr.2023.03.005 |
| 通讯作者 | Sun, Ranhao(rhsun@rcees.ac.cn) |
| 英文摘要 | Assessing spatiotemporal variation in global soil erosion is essential for identifying areas that require greater attention and management under the effects of anthropogenic activities and climate change. Soil erosion can be modelled using the universal soil loss equation (USLE), which includes rainfall erosivity (R-factor), vegetation cover (C-factor), topography (LS-factor), soil erodibility (K-factor), and management practices (P-factor). However, global soil erosion modeling faces numerous challenges, including data acquisition, calculation processes, and parameter calibration under different climatic and topographic backgrounds. Thus, we presented an improved USLE-based model using highly distributed parameters. The R-, C-, and P-factors were modified by the climate zone, country, and topography. This distributed model was applied to estimate the intensity and variations in global soil erosion from 1992 to 2015. We validated the accuracy of this model by comparing simulations with measurements from 11,439 plot years of erosion data. The results showed that i) the average global erosion rate was 5.78 t ha-1 year-1, with an increase rate of 4.26 x 10-3 t ha-1 year-1; ii) areas with significantly increasing erosion accounted for 16% of the land with water erosion, whereas those with significantly decreasing erosion accounted for 7%; and iii) areas with severe erosion included the western Ghats, Abyssinian Plateau, Brazilian Plateau, south and east of the Himalayas, and western coast of South America. Intensified erosion occurred mainly on the Amazon Plain and the northern coast of the Mediterranean. This study provides an improved water erosion prediction model and accurate information for researchers and policymakers to identify the drivers underlying changes in water erosion in different regions.(c) 2023 International Research and Training Center on Erosion and Sedimentation, China Water and Power Press, and China Institute of Water Resources and Hydropower Research. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| WOS关键词 | SOIL-EROSION ; RAINFALL EROSIVITY ; LAND-USE ; SUPPORT PRACTICES ; SEDIMENT YIELD ; CLIMATE ; SCALE ; IMPACTS ; CHINA ; RATES |
| 资助项目 | National Natural Science Foun-dation of China[U2102209] |
| WOS研究方向 | Environmental Sciences & Ecology ; Agriculture ; Water Resources |
| 语种 | 英语 |
| 出版者 | KEAI PUBLISHING LTD |
| WOS记录号 | WOS:001150341700001 |
| 资助机构 | National Natural Science Foun-dation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202607]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Sun, Ranhao |
| 作者单位 | 1.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Jialei,Xiong, Muqi,Sun, Ranhao,et al. Temporal variability of global potential water erosion based on an improved USLE model[J]. INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH,2024,12(1):1-12. |
| APA | Li, Jialei,Xiong, Muqi,Sun, Ranhao,&Chen, Liding.(2024).Temporal variability of global potential water erosion based on an improved USLE model.INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH,12(1),1-12. |
| MLA | Li, Jialei,et al."Temporal variability of global potential water erosion based on an improved USLE model".INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH 12.1(2024):1-12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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