TY - JOUR
T1 - Estimating spatiotemporal dynamics of evapotranspiration and assessing the cause for its increase in China
AU - Yang, Wenjing
AU - Zhao, Yong
AU - Guan, Huade
AU - Tang, Yingfu
AU - Yang, Mingming
AU - Wang, Qingming
AU - Zhao, Jianshi
PY - 2023/4/15
Y1 - 2023/4/15
N2 - 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.
AB - 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.
KW - CO
KW - P-model
KW - Vegetation restoration
KW - Water-carbon coupling
UR - http://www.scopus.com/inward/record.url?scp=85149398271&partnerID=8YFLogxK
U2 - 10.1016/j.agrformet.2023.109394
DO - 10.1016/j.agrformet.2023.109394
M3 - Article
AN - SCOPUS:85149398271
SN - 0168-1923
VL - 333
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
M1 - 109394
ER -