Wang et al. (2026) Canopy resistance-based modeling of maize evapotranspiration in Heilongjiang Province: a multi-site assessment integrating Sentinel-2 data and ground observations

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-04-07
• Authors: Biyu Wang, Haofang Yan, Jianyun Zhang, Guoqing Wang, Desheng Zhang, Chuan Zhang, Xuanxuan Wang, Rongxuan Bao, Youwei Liu, Yujing Han, Yida Zeng, Zhongyu Liu, Rongyang Wang
• DOI: 10.1016/j.jhydrol.2026.135462

Research Groups

• Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, China
• State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, China
• Institute of Agricultural Engineering, Jiangsu University, China

Short Summary

This study developed and evaluated three canopy resistance-based evapotranspiration (λET) models within the Penman-Monteith framework, integrating Sentinel-2 data and ground observations, to improve regional farmland λET estimation for maize in Heilongjiang Province, China. The PMrc-ST model demonstrated the highest accuracy across 19 representative sites, providing valuable insights for precision agricultural water management.

Objective

• To develop and evaluate canopy resistance-based evapotranspiration (λET) models for accurate spatial upscaling from point to regional scale, specifically for maize in Heilongjiang Province, China, to enhance irrigation efficiency and water resource allocation.

Study Configuration

• Spatial Scale: Initial model development at a maize field in Daoli District, Harbin, Heilongjiang Province, China; application and validation across 19 representative sites in Heilongjiang Province, China.
• Temporal Scale: Data collected between 2021 and 2024.

Methodology and Data

• Models used: Penman-Monteith (PM) framework, PMrc-KP (incorporating aerodynamic resistance), PMrc-IS (incorporating canopy-air temperature difference), PMrc-ST (incorporating combined meteorological and crop physiological factors).
• Data sources:
  • Bowen Ratio Energy Balance (BREB) system observations (ground)
  • Field-measured Leaf Area Index (LAI) data (ground)
  • Sentinel-2 high-resolution remote sensing data
  • Ground meteorological observations
  • ERA5-Land reanalysis data (for validation)

Main Results

• The PMrc-ST model consistently outperformed the PMrc-KP and PMrc-IS models at all sites.
• PMrc-ST model estimates achieved R² values above 0.92, with Root Mean Square Error (RMSE) ranging from 36.92 to 96.37 W m⁻² across sites.
• The PMrc-KP model ranked second in performance, while the PMrc-IS model showed relatively lower accuracy.
• Vapor Pressure Deficit (VPD) was identified as the primary factor influencing model performance, showing a significant positive correlation with model residuals.
• Leaf Area Index (LAI) exhibited a significant negative correlation with the residuals of the PMrc-ST model.
• Regional climate differences introduced considerable spatial variability in model performance, with highest accuracy in humid regions (e.g., Baoqing, Jixi) and constrained performance in semi-arid (Anda) and cold, high-latitude (Huma) regions due to water and heat stress.

Contributions

• Developed and assessed three novel canopy resistance-based λET models within the Penman-Monteith framework, integrating multi-source data (Sentinel-2 remote sensing and ground observations).
• Provided valuable insights for regional farmland-scale λET estimation, addressing challenges in spatial upscaling.
• Identified key meteorological and physiological factors (VPD, LAI) influencing model performance and highlighted the impact of regional climate variability.
• Demonstrated the potential application of these models for precision agricultural water management and optimizing water resource allocation.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Wang2026Canopy,
  author = {Wang, Biyu and Yan, Haofang and Zhang, Jianyun and Wang, Guoqing and Zhang, Desheng and Zhang, Chuan and Wang, Xuanxuan and Bao, Rongxuan and Liu, Youwei and Han, Yujing and Zeng, Yida and Liu, Zhongyu and Wang, Rongyang},
  title = {Canopy resistance-based modeling of maize evapotranspiration in Heilongjiang Province: a multi-site assessment integrating Sentinel-2 data and ground observations},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135462},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135462}
}