Estimating spatiotemporal dynamics of evapotranspiration and assessing the cause for its increase in China

Wenjing Yang, Yong Zhao, Huade Guan, Yingfu Tang, Mingming Yang, Qingming Wang, Jianshi Zhao

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Evapotranspiration (E) is a key flux on terrestrial surfaces connecting water–carbon cycle changes to environmental variabilities. Due to forcing data uncertainties, model structure complexities, and attribution method biases, the responses of E to environmental changes are poorly understood. In this study, we used a combined model based on the optimality principle to estimate 0.1° monthly E values and the components of E in China from 1982 to 2018. This model was independently tested with flux tower and basin-scale water balance, showing a predictive performance comparable to other models. The modeling result indicates that, in China, the average weighted mean annual E was 397.90 mm yr−1, of which 46.60% came from transpiration (Ec), 43.04% came from soil evaporation (Es) and 9.53% came from canopy interception evaporation (Ei). The growth in E (1.33 mm yr−2) was mainly caused by the increased Ec (78.95%), followed by the increased Es (21.05%). We further found that precipitation was the largest contributor to E, which primarily controlled the northwest E trends. The air temperature and net radiation mainly regulated the southern E trends. The leaf area index (LAI) dictated the E variations over central China. Although the LAI-induced increase in E (17%) could be offset by the CO2-induced decrease in E (13%), these contributing factors had different trends along an aridity index gradient. We highlight the divergent driving pattern of water, energy and vegetation in shaping E, which can support water resource planning and management.

Original languageEnglish
Article number109394
Number of pages12
JournalAgricultural and Forest Meteorology
Volume333
Early online date3 Mar 2023
DOIs
Publication statusPublished - 15 Apr 2023

Keywords

  • CO
  • P-model
  • Vegetation restoration
  • Water-carbon coupling

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