Temporal analysis on quantitative attribution of karst soil erosion: A case study of a peak-cluster depression basin in Southwest China
文献类型：期刊论文
| 作者 | Gao, Jiangbo1 ; Wang, Huan1,2
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| 刊名 | CATENA
 |
| 出版日期 | 2019 |
| 卷号 | 172页码:369-377 |
| 关键词 | Karst soil erosion Quantitative attribution Modified RUSLE Geographical detector Temporal dynamics China |
| ISSN号 | 0341-8162 |
| DOI | 10.1016/j.catena.2018.08.035 |
| 通讯作者 | Gao, Jiangbo(gaojiangbo@igsnrr.ac.cn) |
| 英文摘要 | In karst areas, soil erosion is a significant problem, seriously impeding sustainable socioeconomic development. A thorough understanding and quantitative identification of the influencing factors are essential for soil erosion protection and rocky desertification management. This study identifies the dominant factors (and interactions) influencing soil erosion and its spatiotemporal variability in a karst basin, the Sancha River Basin, China. The geographical detector method was used to conduct the quantitative attribution analysis, based on the modified universal soil loss equation model for karst environments. The results revealed that karst soil erosion exhibited a notable decreasing trend over the past 36 years (p < 0.01), decreasing from 16.70 t ha(-1) a(-1) in 1980 to 12.22 t ha(-1) a(-1) in 2015. The geographical detector results indicated significant differences in the strength of the association between influencing factors (or factor combinations) and karst soil erosion. Land use type was the dominant factor, followed by slope; a combination of land use type and slope was the dominant interaction factor, explaining at least 74% of the karst soil erosion distribution. Land use change dominated karst soil erosion dynamics in the 1980s and 1990s, and rainfall variability dominated in the 2000s. In addition, karst soil erosion showed high spatial heterogeneity, and the strength of the association differed substantially among diverse geomorphological types due to differences in the inner characteristics of each. These findings suggest that the characteristics of different geomorphological types should be considered for effective management and prevention of soil erosion at a regional level, and that steep croplands, especially with slopes higher than 15, should be prohibited in karst areas. The methodology and framework can be used to better understand the relationships between soil erosion and its influencing factors in karst areas. |
| WOS关键词 | LAND-USE ; ROCKY DESERTIFICATION ; WATER EROSION ; LOSS EQUATION ; RUSLE ; GIS ; RUNOFF ; MODEL ; GEOMORPHOLOGY ; PRECIPITATION |
| 资助项目 | National Natural Science Foundation of China[41671098] ; National Basic Research Program of China[2015CB452702] ; 'Strategic Priority Research Program' of the Chinese Academy of Sciences[XDA20020202] ; 'Strategic Priority Research Program' of the Chinese Academy of Sciences[XDA19040304] |
| WOS研究方向 | Geology ; Agriculture ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000449136800035 |
| 出版者 | ELSEVIER SCIENCE BV |
| 资助机构 | National Natural Science Foundation of China ; National Basic Research Program of China ; 'Strategic Priority Research Program' of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/52626]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Gao, Jiangbo |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Jiangbo,Wang, Huan. Temporal analysis on quantitative attribution of karst soil erosion: A case study of a peak-cluster depression basin in Southwest China[J]. CATENA,2019,172:369-377. |
| APA | Gao, Jiangbo,&Wang, Huan.(2019).Temporal analysis on quantitative attribution of karst soil erosion: A case study of a peak-cluster depression basin in Southwest China.CATENA,172,369-377. |
| MLA | Gao, Jiangbo,et al."Temporal analysis on quantitative attribution of karst soil erosion: A case study of a peak-cluster depression basin in Southwest China".CATENA 172(2019):369-377. |
入库方式： OAI收割
来源：地理科学与资源研究所
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