To evaluate changes in the occurrence of water scarcity, this study used the SPEI (58). The SPEI is a multiscalar drought index that quantifies drought intensity on various time scales. The SPEI can be computed on the basis of 1, 3, 6, 9, or 12 months of accumulated surface water deficits and surpluses (i.e., precipitation minus PET). The calculation then uses statistical probability distributions to quantify the drought intensity, termed the 1-, 3-, 6-, 9-, or 12-month SPEI, respectively. The 1-month SPEI is closely related to the shallow layer soil moisture and can be used to evaluate short-term drought variability. The 12-month SPEI is closely related to the deep layer soil moisture and long-term drought variability.

In this study, the PET was estimated using the physically based Penman-Monteith method [PET_PM; (65)], which accounts for the impacts of temperature, relative humidity, wind speed, and solar radiation. We applied an approach that derives PET_PM from the surface energy budget (i.e., Rn-G = SH + LH), where Rn, G, SH, and LH are the net radiation, ground heat flux, and sensible and latent heat flux, respectively (66). The CO2 increase, vegetation growth and feedback, and CO2 effect on plant transpiration can all influence the surface energy budget in the future. Because the PET_PM is based on the surface energy budget, the CO2 effects on plant transpiration, vegetation growth, and feed feedback were implicitly considered by the PET_PM. In addition to consistent warming (67), the models were also consistent in showing regional changes in relative air humidity (68). The roles of wind speed and solar radiations in PET are secondary (69) in the future. Because of the strong impacts of temperature and relative humidity, the climate models project consistently increasing PET. This finding is understandable because the future climate is expected to be dominated by the radiative effects of increasing GHGs.

The 1-, 3-, 6-, 9-, and 12-month SPEI values were calculated on the basis of the monthly precipitation and PET. The snow-melting module developed by Van der Schrier et al. (70) was also tested to quantify the impact of snow on water supplies. However, the differences between SWS/EWS with and without considering snow melt were not significant over the wheat-growing areas. A simplified scheme that did not account for snow melting was therefore implemented. For a given climate model output, the statistical probability distribution parameters (58) used to calculate the SPEI were determined on the basis of the modeled monthly data from 1901 to 2000. These parameters were subsequently used to calculate the SPEI values for this grid cell from 1860 to 2005 and under different future scenarios. The same procedures were applied to calculate the SPEI from 1901 to 2016 based on the CRU dataset.

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