| Autor: |
Luyao Zhu, Junyu Qi, Hongquan Wang, Mengmeng Zhou, Yang Ye, Yongjun Li, Cheng Tong, Xiaodong Deng, Shan He, Ke Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8319-8333 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2151-1535 |
| DOI: |
10.1109/JSTARS.2023.3310197 |
| Popis: |
Integrating satellite observations into hydrologic models has the potential to enhance soil moisture (SM) retrievals at high spatial and temporal resolutions. The hydrological model Soil and Water Assessment Tool (SWAT) can produce spatiotemporally continuous SM product with high resolution. This article proposed to physically couple the SWAT and Tau-omega radiative transfer model to retrieve SM with a spatial resolution of 30 m. First, the SWAT model integrated a physically based SM module used to simulate hourly SM, from which the brightness temperature (TB) at 30 m was obtained by forwardly simulating the Tau-omega model. Then, the simulated TB at fine resolution and Soil Moisture Active and Passive (SMAP) TB at coarse resolution were merged by Kalman filter into a disaggregated TB. Finally, SM at 30 m resolution was retrieved from the disaggregated TB. The proposed methods were evaluated over the Lanjiang River Basin. The results show that the retrieved SM is highly correlated with two official SMAP SM products and that it has a better accuracy than five SMAP SM products. Particularly, due to the high resolution, the retrieved product captured the heterogeneity of SM within and among fields, compared to the individual use of the hydrological model or satellite observation. Our proposed approach can aid the decision-making in agricultural management at the field scale. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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