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A Dual-Source Energy Balance Model Coupled with Jarvis Canopy Resistance for Estimating Surface Evapotranspiration in Arid and Semi-Arid Regions

Author

Listed:
  • Qiutong Zhang

    (College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)

  • Jinling Kong

    (College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)

  • Lizheng Wang

    (College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)

  • Xixuan Wang

    (College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)

  • Zaiyong Zhang

    (College of Water and Environment, Chang’an University, Xi’an 710054, China)

  • Yizhu Jiang

    (College of Earth Sciences and Resources, Chang’an University, Xi’an 710054, China)

  • Yanling Zhong

    (College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China)

Abstract

Soil moisture is one of the main factors influencing evapotranspiration (ET) under soil water stress conditions. The TSEB SM model used soil moisture to constrain soil evaporation. However, the transpiration schemes constrained by soil moisture require greater physical realism and the soil evaporation schemes parameters usually need calibration. In this study, the TSEB SM model was enhanced by incorporating Jarvis’s canopy resistance which considered the influence of soil moisture on transpiration schemes. We assessed the new model (TSEB SM+ ) in the Heihe and Haihe basins of China. The TSEB SM+ model displayed a consistency to the TSEB in the ET estimation at the A’rou site, but approximately 30% and 35% reductions in RMSEs at the Huazhaizi and Huailai sites. It produced approximately 20% and 10% of the reductions in the ET RMSEs at the Huailai and A’rou sites compared to the TSEB SM model, but had a similar performance at the Huazhaizi site. Moreover, the TSEB SM+ model estimated ET in the Heihe River Basin with an RMSE of 0.58 mm·day −1 , and it was sensitive to the soil moisture, particularly when the soil moisture was below 30%. In conjunction to soil moisture, the TSEB SM+ model could potentially be a more effective tool for monitoring the ET.

Suggested Citation

  • Qiutong Zhang & Jinling Kong & Lizheng Wang & Xixuan Wang & Zaiyong Zhang & Yizhu Jiang & Yanling Zhong, 2024. "A Dual-Source Energy Balance Model Coupled with Jarvis Canopy Resistance for Estimating Surface Evapotranspiration in Arid and Semi-Arid Regions," Agriculture, MDPI, vol. 14(12), pages 1-20, December.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:12:p:2362-:d:1550011
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    References listed on IDEAS

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    2. Shih-Lun Fang & Yi-Shan Lin & Sheng-Chih Chang & Yi-Lung Chang & Bing-Yun Tsai & Bo-Jein Kuo, 2024. "Using Artificial Intelligence Algorithms to Estimate and Short-Term Forecast the Daily Reference Evapotranspiration with Limited Meteorological Variables," Agriculture, MDPI, vol. 14(4), pages 1-20, March.
    3. Xu, Junzeng & Liu, Xiaoyin & Yang, Shihong & Qi, Zhiming & Wang, Yijiang, 2017. "Modeling rice evapotranspiration under water-saving irrigation by calibrating canopy resistance model parameters in the Penman-Monteith equation," Agricultural Water Management, Elsevier, vol. 182(C), pages 55-66.
    4. Yuei-An Liou & Sanjib Kumar Kar, 2014. "Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review," Energies, MDPI, vol. 7(5), pages 1-29, April.
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