Downscaling multilayer soil moisture using parameterized depth profiles associated with environmental factors
文献类型：期刊论文
| 作者 | Zhang, Mo1,2; Ge, Yong1,2,3,4; Ma, Yuxin5; Jin, Yan6; Chen, Yingying7; Liu, Shaomin8 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2025-11-01 |
| 卷号 | 661页码:133544 |
| 关键词 | Soil moisture depth functions Pedometrics Machine learning Multi-output regressor Depth curve characteristics |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2025.133544 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | High-resolution multilayer soil moisture is valuable for water resources management, drought monitoring, and crop optimization. However, integrating process-based models into statistical downscaling methods to estimate multilayer soil moisture can increase both prediction uncertainty and computational complexity of parameterization. Here, three parameterized equations (Peak, Trough, and Balance) were proposed to quantify soil moisture profiles associated with environmental factors, and downscale multilayer soil moisture. Global (0-40 cm) and local (0-10, 10-20, and 20-40 cm) fitting strategies represented the vertical extent of environmental influences. Three machine learning models were employed to downscale satellite soil moisture and predict depth parameters, which were then used to generate sub-surface soil moisture. The results indicated that the local fitting strategy consistently outperformed the global strategy across all depths, reducing the mean absolute error (MAE) and root mean square error (RMSE) by 81.8 % and 80.4 %, and increasing the coefficient of determination (R2) by 22.5 %. Furthermore, local fitting revealed distinct nonlinear and linear patterns within the 0-20 cm and 20-40 cm intervals, respectively. The prediction accuracy of sub-surface soil moisture was improved compared to surface results, with MAE and RMSE reduced by 30.2 %-60.7 % and 34.9 %-56.7 %, respectively. The modified local fitting strategy further enhanced prediction performance, with the Peak-Trough-Balance combination recommended as the optimal configuration. Future studies should account for variations in soil and vegetation cover, refine interval division by incorporating soil-forming processes, and adopt advanced uncertainty quantification methods to enhance its adaptability and robustness. This study provides a reference for multilayer soil moisture downscaling in large-scale regions with depth variability and environmental heterogeneity. |
| URL标识 | 查看原文 |
| WOS关键词 | WATER-UPTAKE ; SMAP ; DYNAMICS ; PLATEAU ; WHEAT ; SMOS |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001504614800001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/214569]  |
| 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 | Ge, Yong |
| 作者单位 | 1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100101, Peoples R China; 3.Jiangxi Normal Univ, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Peoples R China; 4.Jiangxi Normal Univ, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Jiangxi, Peoples R China; 5.New South Wales Dept Climate Change Energy Environ, Parramatta, NSW 2150, Australia; 6.Nanjing Univ Posts & Telecommun, Sch Internet Things, Nanjing 210023, Peoples R China; 7.Chinese Acad Sci, Inst Tibetan Plateau Res, State Key Lab Tibetan Plateau Earth Syst Environm, Natl Tibetan Plateau Data Ctr, Beijing 100101, Peoples R China; 8.Beijing Normal Univ, State Key Lab Earth Surface Proc & Hazards Risk Go, Beijing 100875, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Mo,Ge, Yong,Ma, Yuxin,et al. Downscaling multilayer soil moisture using parameterized depth profiles associated with environmental factors[J]. JOURNAL OF HYDROLOGY,2025,661:133544. |
| APA | Zhang, Mo,Ge, Yong,Ma, Yuxin,Jin, Yan,Chen, Yingying,&Liu, Shaomin.(2025).Downscaling multilayer soil moisture using parameterized depth profiles associated with environmental factors.JOURNAL OF HYDROLOGY,661,133544. |
| MLA | Zhang, Mo,et al."Downscaling multilayer soil moisture using parameterized depth profiles associated with environmental factors".JOURNAL OF HYDROLOGY 661(2025):133544. |
入库方式： OAI收割
来源：地理科学与资源研究所
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