Improving Dryland Depth to Water Table Estimate Using an Integrated Model With Three Submodels
文献类型：期刊论文
| 作者 | Chen, Shaohui |
| 刊名 | WATER RESOURCES RESEARCH
 |
| 出版日期 | 2025-10-24 |
| 卷号 | 61期号:10页码:e2025WR040663 |
| 关键词 | depth to water table integrated model data assimilation phreatic evaporation model optimization |
| ISSN号 | 0043-1397 |
| DOI | 10.1029/2025WR040663 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Investigating dryland phreatic water assets requires an in-deep understanding of depth to water table (DWT). However, current DWT methods suffer from limited accuracy and demand refinement. Therefor, this study suggests one novel integrated model cascaded by twin, assimilation, and DWT submodels. The twin submodel clones land surface model (LSM) with machine learning method (MLM) to capture LSM uncertainties, then the assimilation submodel develops an eigen-uncertainty-weighted four-dimensional variational assimilation framework to optimize LSM outputs using multiple remote sensing (RS) actual evapotranspirations (AETs), thereby, the DWT submodel proposes one physical mechanism based equation with dynamical parameters constrained by optimized LSM outputs and in situ observations. Its effectiveness is evaluated through five pairs of experiments conducted in the Tarim river basin (TRB), China. Results corroborate that the RMSE, MAPE, MAE, R 2 of its estimated DWTs are improved by 21.9%-36.1%, 52.9%-58.3%, 49.5%-59.7%, 2.6%-9.3%, respectively, compared to those from pure-MLMs using original LSM outputs against 84 validation wells across 15 basins. Additionally, the DWT trend obtained well reflects the temporal variability and spatial heterogeneity of the TRB from 2000 to 2020. Owe to its LSM independence and solid physical mechanism, the integrated model ameliorates DWT estimate through a novel insight into the dynamics between phreatic water and heat by maximizing the advantages of multi-source quality RS AETs and LSM outputs without the adjoint models and running of LSMs. |
| URL标识 | 查看原文 |
| WOS关键词 | TARIM RIVER-BASIN ; HIGH-RESOLUTION ; RANDOM FORESTS ; EVAPOTRANSPIRATION ; LAND ; ASSIMILATION ; SIMULATIONS ; CATCHMENT ; STORAGE ; ZONE |
| WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001599439300001 |
| 出版者 | AMER GEOPHYSICAL UNION |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217773]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Chen, Shaohui |
| 作者单位 | Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Shaohui. Improving Dryland Depth to Water Table Estimate Using an Integrated Model With Three Submodels[J]. WATER RESOURCES RESEARCH,2025,61(10):e2025WR040663. |
| APA | Chen, Shaohui.(2025).Improving Dryland Depth to Water Table Estimate Using an Integrated Model With Three Submodels.WATER RESOURCES RESEARCH,61(10),e2025WR040663. |
| MLA | Chen, Shaohui."Improving Dryland Depth to Water Table Estimate Using an Integrated Model With Three Submodels".WATER RESOURCES RESEARCH 61.10(2025):e2025WR040663. |
入库方式： OAI收割
来源：地理科学与资源研究所
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