A Future Scenario Prediction for the Arid Inland River Basins in China Under Climate Change: A Case Study of the Manas River Basin

Global warming poses significant threats to agriculture, ecosystems, and human survival. This study focuses on the arid inland Manas River Basin in northwestern China, utilizing nine CMIP6 climate models and five multi-model ensemble methods (including machine learning algorithms such as random forest and support vector machines) to evaluate historical temperature and precipitation simulations (1979–2014) after bias correction via Quantile Mapping (QM). Future climate trends (2015–2100) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) are projected and analyzed for spatiotemporal evolution. The results indicate that the weighted set method (WSM) significantly improves simulation accuracy after excluding poorly performing models. Under SSP1-2.6, the long-term average increases in maximum temperature, minimum temperature, and precipitation are 1.654 °C, 1.657 °C, and 34.137 mm, respectively, with minimal climate variability. In contrast, SSP5-8.5 exhibits the most pronounced warming, with increases reaching 4.485 °C, 4.728 °C, and 60.035 mm, respectively. Notably, the minimum temperature rise gradually surpasses the maximum temperature, indicating a shift toward warmer and more humid conditions in the basin. Spatially, high warming rates are concentrated in low-altitude desert areas, while the precipitation increases correlate with elevation. These findings provide critical insights for climate adaptation strategies, sustainable water resource management, and ecological conservation in China’s arid inland river basins under future climate change.