## 3 Results
### Comparison of Nonstationary and Stationary Drought Characteristics in China
The results showed that stationary approaches under-estimated the drought duration in the spring-summer season for the past 42 years. The CRB requires further attention, as most of the grid points with changes in the distribution parameters are concentrated here. Figure 6: Probability density of duration estimated by SPEI and NSPEI in the nine river basins of China under different classifications of (\(\mu\), \(\sigma\)) changes in the spring–summer season. Figure 7: Probability density of severity estimated by SPEI and NSPEI in the nine river basins of China under different classifications of (\(\mu\), \(\sigma\)) changes in the spring–summer season. The drought severity evaluated by the NSPEI and SPEI shows some variation not only in the distribution of the severity but also probability density (as shown in Figure 7). For the CRB, where there are the main hotspots of nonstationary response areas and the most grid points showing changes in the distribution parameters (\(\mu\), \(\sigma\)), the stationary SPEI not only quantitatively under-estimated drought severity, but also identified some of the more severe droughts as less severe. In other river basins in China, the (0, 0) class has shown consistent drought evaluation results for the past 42 years in the spring-summer season. Numerically, the SPEI and NSPEI assessed the severity similarly, but for some grid points, the stationary SPEI over-estimated the severity of ones with smaller severity while under-estimating that of ones with larger severity. As with the spring-summer season in Figure 8, the drought duration also shows only quantitative differences in the fall-winter seasons; there is no probabilistic bias, and the differences are small. The stationary SPEI seemed to over-estimate the drought duration in river basins, such as CRB, YRB1, YRB2, and SRB, which had more grid point variations in the location parameters (\(1,0\)); while under-estimating the drought severity in the river basin SRB2 because there was little evapotranspiration in Northwest China during the fall-winter season. Therefore, drought conditions considered nonstationary seemed to ease while significant precipitation decreased, and evapotranspiration increased in Southwestern China during this season (shown in Supplementary Figures S1 and S2). The nonstationary and stationary results of the (0, 1) class exhibited only minor differences. The grid points of the (1, 1) class accounted for a small number and indicated an under-estimation of drought severity, as in the spring-summer season. The same results for severity are shown in Figure 9. For river basins, such as CRB, YRB1, SRB2, and HRB1, that had more variable grid points for the distribution parameters, there was under-estimation under the stationary SPEI for droughts of greater severity. Figure 8: Probability density of duration estimated by SPEI and NSPEI in the nine river basins of China under different classifications of (\(\mu\), \(\sigma\)) changes in the fall–winter season. Generally, in the cases wherein there were no changes in either parameter (0, 0) or only a change in the scale parameter (0, 1), the nonstationary or stationary model evaluated the same drought event, whereas there was under-estimation under the stationary SPEI in the case wherein there were both location and scale parameter changes (1, 1). Under the combined effect of precipitation and evapotranspiration changes, the traditional stationary SPEI under-estimated the drought in Northwest China during the spring-summer season; and then, under-estimated it in Southwest China in the fall-winter season. Meanwhile, the stationary SPEI under-estimated the occurrence of drought events with longer durations and greater severity in China, possibly resulting in the inadequate identification of severe or even extreme droughts under conditions of climate change.