Why the Effect of CO2 on Potential Evapotranspiration Estimation Should Be Considered in Future Climate

Abstract

Potential evapotranspiration (PET) is an important factor that needs to be considered in regional water management and allocation; thus, the reasonable estimation of PET is an important topic in hydrometeorology and other related fields. There is evidence that increased CO2 concentration alters the physiological properties of vegetation and thus affects PET. In this study, changes in PET with and without the CO2 effect over China is investigated using seven CMIP6-GCMs outputs under seven shared socioeconomic pathways (SSPs) based scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5), as well as the contribution rate of CO2 on PET in different climatic regions. Changes in estimated PET based on modified Penman–Monteith (PM) method that considers the CO2 effect is compared with the traditional PM method to examine how PET quantity varies (differences) between these two approaches. The results show that the PET values estimated by the two methods explored opposite trends in 1961–2014 over entire China; it decreases with consideration of CO2 but increases without consideration of CO2. In the future, overall PET is projected to increase under all scenarios during 2015–2100 for China and its three sub-regions. PET generally tends to grow slower when CO2 is taken into account (modified PM approach), than when it is not (traditional PM method). In terms of differences in the estimated PET by the two methods, the difference between the two adopted methods increased in China and its sub-regions for the 1961–2014 period. In the future, the difference in estimated PET is anticipated to continuously increase under SSP3-7.0 and SSP5-8.5. Spatially, a much greater extent of difference is found in the arid region. Across the arid region, the PET difference is projected to be the highest at 138% in the mid-term (2041–2060) with respect to the 1995–2014 period, whereas it tends to increase slower in the long-term period (2081–2100). Importantly, CO2 is found to be the most dominant factor (−154.2% contribution) to have a great effect on PET changes across the arid region. Our findings suggest that ignorance of CO2 concentration in PET estimation will result in significant overestimation of PET in the arid region. However, consideration of CO2 in PET estimation will be beneficial for formulating strategies on future water resource management and sustainable development at the local scale.