Against the backdrop of global warming, climate extremes and drought events have become more severe, especially in arid and semi-arid areas. This study forecasted the characteristics of climate extremes in the Xilin River Basin (a semi-arid inland river basin) of China for the period of 2021–2100 by employing a multi-model ensemble approach based on three climate Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from the latest Coupled Model Intercomparison Project Phase 6 (CMIP6). Furthermore, a linear regression, a wavelet analysis, and the correlation analysis were conducted to explore the response of climate extremes to the Standardized Precipitation Evapotranspiration Index (SPEI) and Streamflow Drought Index (SDI), as well as their respective trends during the historical period from 1970 to 2020 and during the future period from 2021 to 2070. The results indicated that extreme high temperatures and extreme precipitation will further intensify under the higher forcing scenarios (SSP5-8.5>SSP2-4.5>SSP1-2.6) in the future. The SPEI trends under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios were estimated as −0.003/a, −0.004/a, and −0.008/a, respectively, indicating a drier future climate. During the historical period (1970–2020), the SPEI and SDI trends were −0.003/a and −0.016/a, respectively, with significant cycles of 15 and 22 a, and abrupt changes occurring in 1995 and 1996, respectively. The next abrupt change in the SPEI was projected to occur in the 2040s. The SPEI had a significant positive correlation with both summer days (SU) and heavy precipitation days (R10mm), while the SDI was only significantly positively correlated with R10mm. Additionally, the SPEI and SDI exhibited a strong and consistent positive correlation at a cycle of 4–6 a, indicating a robust interdependence between the two indices. These findings have important implications for policy makers, enabling them to improve water resource management of inland river basins in arid and semi-arid areas under future climate uncertainty.
