Wang et al. (2025) Applicability of the Surface Energy Balance System (SEBS) Model for Evapotranspiration in Tropical Rubber Plantation and Its Response to Influencing Factors

Identification

• Journal: Forests
• Year: 2025
• Date: 2025-12-05
• Authors: Jingjing Wang, Wenbin Lin, Qiwen Cheng, Huichun Ye, Jinlong Zhu, Zhixiang Wu, Chuan Yang, Bingsun Wu
• DOI: 10.3390/f16121820

Research Groups

• School of Tropical Agriculture and Forestry, Hainan University, China
• Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, China
• Key Laboratory of Earth Observation of Hainan, Hainan Aerospace Information Research Institute, China
• Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, China

Short Summary

This study evaluated the applicability of the Surface Energy Balance System (SEBS) model for estimating evapotranspiration (ET) in a tropical rubber plantation using Landsat-8 imagery and flux tower data, demonstrating high accuracy and identifying key meteorological and physiological drivers of ET.

Objective

• To estimate the daily evapotranspiration (ET) of a tropical rubber plantation using the Surface Energy Balance System (SEBS) model by combining Landsat-8 image data and meteorological data.
• To validate the accuracy and applicability of the SEBS model for ET estimation in different source areas of rubber plantations using the eddy covariance method.
• To explore the key meteorological factors and physiological growth indicators influencing ET in rubber plantations at daily and monthly scales.

Study Configuration

• Spatial Scale: Tropical rubber plantation in Danzhou City, Hainan Province, China (19°32′47″ N, 109°28′30″ E). Validation areas were selected at 1 km (2.08 km²), 1.5 km (4.62 km²), and 3 km (19.57 km²) radii from a flux tower.
• Temporal Scale: From 2022 to 2024 (3 years).

Methodology and Data

• Models used:
  • Surface Energy Balance System (SEBS) model for ET estimation.
  • Eddy Covariance method for validation of SEBS model accuracy.
• Data sources:
  • Satellite data: 30 periods of Landsat-8 image data (USGS, strip/line 124/047) from 2022 to 2024.
  • Flux tower data: Meteorological and flux data (daily average air temperature, daily average air pressure, latent heat flux, relative humidity, wind speed, precipitation, net radiation) from a forest gradient flux tower (Campbell Scientific, Inc., Li-COR Biosciences) from 1 January 2022 to 31 December 2024.
  • Digital Elevation Model (DEM): ASTER GDEM V2 (30 m spatial resolution) from Geospatial Data Cloud.
  • Field measurements (2024):
    • Soil Water Content (SWC): 0-5 cm depth, monthly (January-December).
    • Soil and Plant Analyzer Development (SPAD): LYS-B plant chlorophyll meter, monthly (April-December).
    • Leaf Area Index (LAI): LAI-2200C canopy analyzer, monthly (April-December).

Main Results

• The SEBS model demonstrated high accuracy for estimating ET in tropical rubber plantations, with a coefficient of determination (R²) ranging from 0.89 to 0.91 across different source areas.
• The highest estimation accuracy was observed for the rubber plantation ET in the region 1.5 km away from the flux tower (R² = 0.90, RMSE = 0.43 mm, RE = 15.23%).
• Daily average and monthly cumulative ET exhibited a unimodal distribution from 2022 to 2024, with peak values in July (summer) and lowest values in winter.
• The average monthly accumulated ET during the wet season (May-October) was significantly greater (102.75 mm) than during the dry season (November-April) (50.61 mm).
• On both daily and monthly scales, atmospheric pressure (Pre) and air temperature (Ta) were the most significant factors influencing ET. Pre showed a highly significant negative correlation with ET (daily r = -0.77, monthly r = -0.96), while Ta showed a highly significant positive correlation (daily r = 0.69, monthly r = 0.95).
• Other factors significantly correlated with ET included precipitation (Prc), wind speed (WS), net radiative flux (Rn), soil water content (SWC), SPAD, and LAI.

Contributions

• Provided a systematic evaluation of the SEBS model's applicability for estimating evapotranspiration in tropical artificial forest ecosystems (rubber plantations) using remote sensing technology.
• Enhanced the understanding of water use patterns in rubber plantations and their response mechanisms to environmental changes.
• Identified the main driving factors of ET in tropical rubber plantations, highlighting the different feedback and key factors on climate change.
• Established a scientific foundation for water resource management and sustainable development strategies for rubber plantation ecosystems in response to climate change.

Funding

• National Natural Science Foundation of China (No. 42167011)
• Hainan Provincial Science and Technology Special Fund (No. ZDYF2025XDNY112, No. ZDYF2024XDNY196)
• Fundamental Research Funds for Rubber Research Institute, CATAS (1630022024020)
• Natural Science Foundation of Hainan Province (No. 323MS076)

Citation

@article{Wang2025Applicability,
  author = {Wang, Jingjing and Lin, Wenbin and Cheng, Qiwen and Ye, Huichun and Zhu, Jinlong and Wu, Zhixiang and Yang, Chuan and Wu, Bingsun},
  title = {Applicability of the Surface Energy Balance System (SEBS) Model for Evapotranspiration in Tropical Rubber Plantation and Its Response to Influencing Factors},
  journal = {Forests},
  year = {2025},
  doi = {10.3390/f16121820},
  url = {https://doi.org/10.3390/f16121820}
}

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