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Spatiotemporal Changes in Grassland Yield and Driving Factors in the Kherlen River Basin (2000-2024): Insights from CASA Modeling and Geodetector Analysis

文献类型：期刊论文

作者Yang, Meihuan4; Yang, Haowei4; Wang, Tao4; Li, Pengfei4; Wang, Juanle3; Shao, Yating3; Li, Ting4; Zhang, Jingru1,2; Wang, Bo1,2
刊名WATER
出版日期2025-11-28
卷号17期号:23页码:3397
关键词grassland yield MODIS NDVI Carnegie-Ames-Stanford approach (CASA) model Geodetector Kherlen River Basin transboundary ecosystem
DOI10.3390/w17233397
产权排序2
文献子类Article
英文摘要The Kherlen River Basin is a typical basin in the eastern Mongolian Plateau and is dominated by grassland. This study estimated the grassland yield in the Kherlen River Basin using the Carnegie-Ames-Stanford approach (CASA) model, combined with Theil-Sen median trend analysis and the Geodetector, to explore its spatiotemporal changes and driving factors. This integrated framework links temporal trend detection with spatial interaction analysis to better reveal ecological responses to climatic and anthropogenic influences. The results showed the following: (1) The root mean square error (RMSE) between the estimated grassland yield and the laboratory measurements was 37.88 g/m(2), with an estimation accuracy (EA) of 73.52%. (2) From 2000 to 2024, the grassland yield increased significantly at a rate of 1.98 g/(m(2)a) (p < 0.05), with the fastest growth in the middle reaches. (3) Spatially, 79.78% of the basin exhibited significant increases, mainly in the central and western regions. The proportion of significant increase was highest in the upper reaches (40.36%), followed by the middle (32.89%) and lower reaches (6.53%). (4) Due to limited temporal resolution of socioeconomic data, the driving factor analysis covered the period 2000-2020, during which the overall grassland yield was primarily influenced by the interaction between precipitation and elevation (q = 0.6371). Specifically, the upper, middle, and lower reaches were mainly influenced by the interactions between temperature and precipitation (q = 0.6772), precipitation and elevation (q = 0.6377), and temperature and elevation (q = 0.4255), respectively. The study indicates that grassland yield in the Kherlen River Basin exhibited an overall increasing trend during 2000-2024, with climatic factors (precipitation and temperature) and the geographic factor (elevation) identified as the dominant drivers. The influence of human activities was not significant, although this result may be affected by uncertainties associated with data resolution limitations. Future work should incorporate higher-resolution remote sensing and socioeconomic datasets to better assess the impacts of human activities.
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WOS关键词BIOMASS
WOS研究方向Environmental Sciences & Ecology ; Water Resources
语种英语
WOS记录号WOS:001635276500001
出版者MDPI
源URL[http://ir.igsnrr.ac.cn/handle/311030/219395]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Wang, Tao
作者单位1.China Geol Survey, Xian Mineral Resources Invest Ctr, Xian 710100, Peoples R China;
2.Qinling Loess Plateau Transit Zone Observat & Res, Weinan 714300, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China;
4.Xian Univ Sci & Technol, Coll Geomat, Xian 710054, Peoples R China;
推荐引用方式
GB/T 7714		 Yang, Meihuan,Yang, Haowei,Wang, Tao,et al. Spatiotemporal Changes in Grassland Yield and Driving Factors in the Kherlen River Basin (2000-2024): Insights from CASA Modeling and Geodetector Analysis[J]. WATER,2025,17(23):3397.
APA Yang, Meihuan.,Yang, Haowei.,Wang, Tao.,Li, Pengfei.,Wang, Juanle.,...&Wang, Bo.(2025).Spatiotemporal Changes in Grassland Yield and Driving Factors in the Kherlen River Basin (2000-2024): Insights from CASA Modeling and Geodetector Analysis.WATER,17(23),3397.
MLA Yang, Meihuan,et al."Spatiotemporal Changes in Grassland Yield and Driving Factors in the Kherlen River Basin (2000-2024): Insights from CASA Modeling and Geodetector Analysis".WATER 17.23(2025):3397.

入库方式： OAI收割

来源：地理科学与资源研究所

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