Wang et al. (2026) A synergetic framework for land-atmosphere coupling-based remote sensing inversion of evapotranspiration, surface resistance, and aerodynamic resistance

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-08-20
• Authors: Xiaowei Wang, Yazhen Jiang, Huanyu Zhang, Yitao Li, Menglin Si, Yunsheng Lou, Zhao-Liang Li
• DOI: 10.1016/j.jhydrol.2026.136225

Research Groups

• State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
• School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
• University of Chinese Academy of Sciences, Beijing 100049, China
• Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Short Summary

This study proposes a remote sensing-based ET coupling estimation framework (ETC framework) that simultaneously estimates evapotranspiration (ET), surface resistance (rs), and aerodynamic resistance (rae) with the land-atmosphere coupling coefficient (Ω) clarifying their coupling relationships. The ETC framework demonstrates high accuracy in ET estimation, outperforming conventional products at various spatial scales.

Objective

• Develop a remote sensing-based ET coupling estimation framework that synergistically inverts evapotranspiration (ET), surface resistance (rs), and aerodynamic resistance (rae) with the land-atmosphere coupling coefficient (Ω) explicitly elucidating their intricate interrelationships and feedback.

Study Configuration

• Spatial Scale: Global, with a spatial resolution of 0.05°.
• Temporal Scale: Monthly, with data covering the period from 2001 to 2020.

Methodology and Data

• Models used: The ETC framework uses a nonlinear coupled system linking ET, rs, rae, and Ω, established by deconstructing the fundamental surface energy balance equation and its associated thermodynamic variables.
• Data sources: Remote sensing data from MODIS, GLASS-MODIS, and other relevant datasets; meteorological reanalysis data from ERA5-Land; site-scale measurements from FLUXNET, AmeriFlux, and OzFlux networks.

Main Results

• The inverted rs agrees well with corresponding values derived from the Penman–Monteith (PM) model across 14 land cover types.
• The inverted rae shows strong agreement with observations at the site scale across different land cover types.
• ET simulated by the PM model driven by the inverted rae and rs agrees well with half-hourly measured ET across different land cover types.

Contributions

• This study contributes to an improved understanding of ET-mediated land-atmosphere interactions by providing a physically constrained framework that resolves rs and rae as interdependent components.
• The ETC framework enables the simultaneous retrieval of ET, rs, and rae under physically consistent constraints, driven by remote sensing data together with meteorological reanalysis data.

Funding

• This research was funded by the National Natural Science Foundation of China (Grant No. 42122001) and the Key Research Program of the Chinese Academy of Sciences (Grant No. XDPB09).

Citation

@article{Wang2026synergetic,
  author = {Wang, Xiaowei and Jiang, Yazhen and Zhang, Huanyu and Li, Yitao and Si, Menglin and Lou, Yunsheng and Li, Zhao-Liang},
  title = {A synergetic framework for land-atmosphere coupling-based remote sensing inversion of evapotranspiration, surface resistance, and aerodynamic resistance},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136225},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136225}
}