Increasing Evapotranspiration in China: Quantifying the Roles of CO2 Fertilization, Climate and Vegetation Changes
Year: 2025
Type: article
Abstract: Contradictory views are still existing on the dominating drivers and the underlying mechanisms for the overall increasing evapotranspiration (ET) in China, a region has undergone substantial vegetation and climate changes. Particularly, some studies conclude that climate change is the dominating factor, while other researchers believe that it is the vegetation change. To fill this knowledge gap, here we developed a physical‐based ET model by combining the modified Penman–Monteith model and a newly developed canopy resistance model, which effectively links ET and its potential drivers, with the mean correlation and relative RMSE between the observed and modeled canopy resistance being 0.83 ± 0.09 and 3.4 ± 1.6%, respectively. The reliability of the model was also demonstrated by comparing the derived sensitivity of canopy resistance to air CO2 concentration (mean of 0.14 ± 0.03% ppm−1) and the observations (∼0.15% ppm−1). Based on this model and a scenario analysis approach, we demonstrated that vegetation change, air temperature, air CO2 concentration and soil moisture were the dominating factors of ET variabilities during 1982–2014, which dominated ET changes at 36.0 ± 16.3%, 16.5 ± 4.5%, 20.2 ± 11.6 and 18.2 ± 10.9% of the land grids, and averagely contributed 0.72 ± 0.32, 0.28 ± 0.15, −0.51 ± 0.15 and 0.13 ± 0.78 mm yr−2, respectively. These indicated that vegetation change was the most important factor for the increasing ET over China during the past several decades. These findings and the model are helpful for assessing the ecohydrological cycles in a changing environment.
Source: Water Resources Research
DOI: 10.1029/2024wr038148
Authors: Meixian Liu, Kairong Lin, Xinjun Tu
Institution: Sun Yat-sen University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,000
OpenAlex ID: W4407980775
