Climate variability impacts on runoff projection in the 21st century based on the applicability assessment of multiple GCMs: A case study of the Lushi Basin, China

In this study, we initiatively employed the improved Secure Hash Algorithm (SHA) to evaluate and compare the competencies of multiple Coupled Model Intercomparison Project Phase Six (CMIP6) General Circulation Models (GCMs). The selected GCM outputs were bias-corrected by the non-parametric quantile mapping (QM) method. The calibrated and validated data were then used to run the XAJ (Xin’anjiang) model to assess long-term climate variation impacts on runoff under four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), where the results were compared with the baseline period (1976–2000). Overall, the CNRM-CM6-1-HR, FIO-ESM-2–0, INM-CM5-0 and NorESM2-MM models reconstructed better spatio-temporal evolutionary trends related to historical precipitation and evaporation, and were applied as selected GCMs for reliable runoff projection applications. The intensification amplitudes of precipitation and evaporation produced by selected GCMs gradually spread from SSP1-2.6 to SSP5-8.5 throughout the 21st century. Compared to the baseline period (257 m3/s), the extreme streamflow during the wet periods is likely to increase for SSP5-8.5 (288 ∼ 298 m3/s), SSP3-7.0 (276 ∼ 294 m3/s), and SSP2-4.5 (222 ∼ 280 m3/s), whereas SSP1-2.6 decreases to varying degrees (178 ∼ 255 m3/s). Meanwhile, during the dry periods, the extreme streamflow is projected to decrease by 28 ∼ 73 m3/s (SSP5-8.5), 32 ∼ 38 m3/s (SSP3-7.0), 8 ∼ 31 m3/s (SSP2-4.5), and 5 ∼ 33 m3/s (SSP1-2.6) from historical levels (62 m3/s). The overwhelming majority of increasing trends in the wet periods and vastly decreasing trends in the dry seasons indicate that the basin will face some floods and water shortage risks in the mid to late 21st century. The findings broaden the efficacious applications of SHA in the performance selection of GCMs and QM method in bias correction. The conclusions provide a reference for flood and drought mitigation planning and water resources policymaking in the Yellow River Basin.