Comparative Analysis of Multi-Source Evapotranspiration Products in Xinjiang, China
Evapotranspiration (ET) is essential to the terrestrial water and energy cycle. Accurate evapotranspiration estimates are crucial for understanding global and regional climate change and effective water management. This research uses meteorological observations to provide insights into the spatial and temporal trend patterns of potential evapotranspiration (PET) and evapotranspiration in Xinjiang. A comparative analysis was conducted on six remote sensing-based, land surface model-based, and reanalysis-based products across multiple temporal scales (yearly, seasonally, and monthly) and point-to-point spatial dimensions and impacts of different land cover types was explored. The results show that: (1) The annual PET in Xinjiang showed a significant increasing trend, but showed a significant decreasing trend in summer and autumn. The actual evapotranspiration increased significantly in autumn. (2) The simulation of ET products in Xinjiang exhibits pronounced spatial heterogeneity and seasonal dependency. The datasets demonstrated a superior ability to simulate evapotranspiration in the northern part of Xinjiang compared to the southern part. Product performance varied extremely widely in desert areas but was stable in oasis areas. (3) Significant discrepancies exist across the multiple datasets, with the reanalysis-based products demonstrating superior comprehensive performance. This study offers critical insights for the suitable selection of evapotranspiration products and model optimization in the hydro-meteorological research of Xinjiang.
Authors
- Jian Peng (ORCID: https://orcid.org/0000-0002-4071-0512)
- Weiyi Mao (ORCID: https://orcid.org/0000-0003-1448-3026)
- Gangyong Li
- Junqiang Yao
- Jing Chen
- Chenzhi Ma
Institutions
- Tongji University (CN)
- China Meteorological Administration (CN)
- Xinjiang Institute of Ecology and Geography (CN)
- State Forestry and Grassland Administration (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-09-25
- DOI
- https://doi.org/10.3390/rs17193297
- Citations
- 1
- Primary Topic
- Plant Water Relations and Carbon Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 1.11