The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN) and focus on the basin-scale water–energy–food–ecology (WEFE) nexus. We applied it to the Syr Darya River basin (SDB) and the Amu Darya River basin (ADB), of which poor water management caused the Aral Sea disaster. The causality of the nexus was effectively compared and universality of this framework was discussed. In terms of changes in the nexus, the sensitive factor for the water supplied to the Aral Sea changed from the agricultural development during the Soviet Union period to the disputes in the WEFE nexus after the disintegration. The water–energy contradiction of the SDB is more severe than that of the ADB, partly due to the higher upstream reservoir interception capacity. It further made management of the winter surplus water downstream of the SDB more controversial. Due to this, the water–food–ecology conflict between downstream countries may escalate and turn into a long-term chronic problem. Reducing water inflow to depressions and improving the planting structure prove beneficial to the Aral Sea ecology, and this effect of the SDB is more significant. The construction of reservoirs on the Panj River of the upstream ADB should be cautious to avoid an intense water–energy conflict such as the SDB's. It is also necessary to promote the water-saving drip irrigation and to strengthen the cooperation.

Precipitation has been considered to be a critical water source for both human livelihoods and ecosystems in Central Asia. Using observational data and gridded datasets, we studied the regional and seasonal differences of precipitation climate characteristics and variations in precipitation over Central Asia. Using observational data obtained from the China Meteorological Administration, Global Historical Climatology Network (V3.02), we divided Central Asia into four subregions (North, Center, Southwest, and Southeast) based on the differences in seasonal cycles of precipitation. ‘Single peaks’ were detected as types of seasonal cycles over the North and the Southeast, while ‘two peaks’ was the type that occurred in the Southwest. For the Center, the zone of transition between the North and the Southwest, each monthly precipitation value was higher than the Southwest’s and less than the North’s. GPCC (R² of 0.89, RMSE of 64.5 mm/year) was proven to be the most suitable dataset of the four datasets (CRU, GPCC, MERRA, and TRMM) to describe precipitation in Central Asia, based on validation against observational data, and used to detect the spatial and temporal trend of precipitation in Central Asia and four subregions during 1960–2013. No significant trends were observed for annual precipitation in Central Asia, while precipitation in winter displayed a significant increase (0.11 mm/year). Additionally, significantly increasing trends (0.16, 0.27, 0.13, and 0.13 mm/year) were detected in spring, summer, autumn, and winter over the Southeast during 1960–2013.