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1. High-Resolution SMAP Satellite Soil Moisture Product: Exploring the Opportunities

   https://doi.org/10.1175/BAMS-D-21-0016.1  

   Abbaszadeh, Peyman; Moradkhani, Hamid; Gavahi, Keyhan; Kumar, Sujay; Hain, Christopher; Zhan, Xiwu; Duan, Qingyun; Peters-Lidard, Christa; Karimiziarani, Sepehr (April 2021, Bulletin of the American Meteorological Society)
2. Multi-layer high-resolution soil moisture estimation using machine learning over the United States

   https://doi.org/10.1016/j.rse.2021.112706  

   Karthikeyan, L.; Mishra, Ashok K. (December 2021, Remote Sensing of Environment)

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3. DISCERN: Leveraging Knowledge Distillation to Generate High Resolution Soil Moisture Estimation from Coarse Satellite Data

   https://doi.org/10.1109/BigData59044.2023.10386179  

   Matin, Abdul; Khandelwal, Paahuni; Pallickara, Shrideep; Pallickara, Sangmi Lee (December 2023, IEEE)
4. Remotely Sensed High‐Resolution Soil Moisture and Evapotranspiration: Bridging the Gap Between Science and Society

   https://doi.org/10.1029/2024WR037929  

   Huang, Jingyi; Sehgal, Vinit; Alvarez, Laura V; Brocca, Luca; Cai, Shuohao; Cheng, Rui; Cheng, Xinghua; Du, Jinyang; El_Masri, Bassil; Endsley, K Arthur; et al (May 2025, Water Resources Research)

   Abstract This paper reviews the current state of high‐resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high‐resolution remote sensing using visible, near‐infrared, thermal‐infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio‐geo‐physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily). Still, the state‐of‐the‐science products have their challenges and limitations, which we detail across data, retrieval algorithms, and applications. We describe the roles of these data in advancing 10 application areas: drought assessment, food security, precision agriculture, soil salinization, wildfire modeling, dust monitoring, flood forecasting, urban water, energy, and ecosystem management, ecohydrology, and biodiversity conservation. We discuss that future scientific advancement should focus on developing open‐access, high‐resolution (3–30 m), sub‐daily SM and ET products, enabling the evaluation of hydrological processes at finer scales and revolutionizing the societal applications in data‐limited regions of the world, especially the Global South for socio‐economic development. 

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5. Simulating Soil Moisture and Grass Growth in a Eurasian Steppe Grassland by SWAP

   Chereskin, A.D.; Johnson, D.L.; Zhang, A.; Qin, Z.; Dolan, D.; Landis, Z.C.; Potter, N.M.; Gao, R.; Luo, Y.; Yu, R.; et al (January 2018, AGU Fall Meeting 2018)

   The accelerating degradation of native grasslands is becoming a threat to the world’s biome supply and has raised serious environmental concerns such as desertification and dust storm. Given that the steppe grasslands, such as those located in the Inner Mongolia Plateau of north China, have a dry climatic condition, the grass growth closely relies on available soil water, which in turn depends on precipitation prior to the growing season (in particular from May to July). However, our understanding of steppe hydrology and water consumption by grasses is incomplete. In this study, the agro-hydrologic Soil Water Plant Atmosphere (SWAP) model was used to mimic the long-term variations in soil water and vegetation growth in a typical steppe grassland of north China to further understand how alterations of hydrologic processes are related to grassland degradation. A field experiment was conducted to collect the data needed to set up the model. The SWAP model was calibrated using continuous observations of soil moisture and soil temperature at various depths for a simulation period of 2014 to 2017. The results indicated that the SWAP model can be used to simulate the responses of soil moisture and vegetation growth to climates. Moreover, this study examines the water balance and chronological variations of precipitation, evapotranspiration, soil water, and runoff. This study will add new knowledge of steppe hydrologic processes into existing literature. 

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