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<p>Potential Evapotranspiration (PET) is a core parameter for assessing the water and heat balance of alpine grassland ecosystems. Its accurate estimation is crucial for water resource evaluation, carbon flux simulation, and vegetation productivity prediction. Considering the strong climatic heterogeneity and limited applicability of single-source PET data in Northwest Sichuan, this study integrates three types of PET data—MODIS, ERA5-Land, and Hargreaves—using the Bayesian Triangle Cap (BTCH) method to construct a high-accuracy fusion product. The fusion product’s accuracy is validated against data from the FLUXNET Hongyuan site and pan evaporation observations from regional meteorological stations, and the applicability of the BTCH method in alpine grassland regions is systematically assessed. The results demonstrate that BTCH-PET outperforms single-source datasets in terms of Nash-Sutcliffe Efficiency and Root Mean Square Error, exhibiting greater stability and regional representativeness. Additionally, spatial distribution analysis and wavelet analysis are employed to reveal the seasonal patterns and dominant periodic variations of PET, providing valuable data support and methodological references for evapotranspiration monitoring and water resource management in alpine grassland ecosystems.</p>

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Validation and spatiotemporal analysis of multi-source potential evapotranspiration in Northwest Sichuan alpine grasslands

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Rui Zhang,
  • Yuanjun Zhang,
  • Hweesan Lim,
  • Huaiyong Shao,
  • Chengyu Hu

摘要

Potential Evapotranspiration (PET) is a core parameter for assessing the water and heat balance of alpine grassland ecosystems. Its accurate estimation is crucial for water resource evaluation, carbon flux simulation, and vegetation productivity prediction. Considering the strong climatic heterogeneity and limited applicability of single-source PET data in Northwest Sichuan, this study integrates three types of PET data—MODIS, ERA5-Land, and Hargreaves—using the Bayesian Triangle Cap (BTCH) method to construct a high-accuracy fusion product. The fusion product’s accuracy is validated against data from the FLUXNET Hongyuan site and pan evaporation observations from regional meteorological stations, and the applicability of the BTCH method in alpine grassland regions is systematically assessed. The results demonstrate that BTCH-PET outperforms single-source datasets in terms of Nash-Sutcliffe Efficiency and Root Mean Square Error, exhibiting greater stability and regional representativeness. Additionally, spatial distribution analysis and wavelet analysis are employed to reveal the seasonal patterns and dominant periodic variations of PET, providing valuable data support and methodological references for evapotranspiration monitoring and water resource management in alpine grassland ecosystems.