Hydrological drought has posed serious threats to water security in the arid and semi-arid regions. Particularly, the surface water resources are already scarce in the typical oasis areas in the Hotan River Basin of the southern Xinjiang Uygur Autonomous Region in China. However, the water demands have expanded to cause a non-consistent pattern in the hydrological regime of the basin under climate change. The conventional consistency assumption on the hydrological drought is also limited in the large-scale production of sustainable agriculture. Previous research has also focused on the non-consistent drought indices and drought features under changing conditions. It is often required to accurately assess the dynamic drought risk for agricultural planning and water resources. In this study, a dynamic risk assessment framework was developed for the non-consistent hydrological drought in the Hotan River Basin. The runoff series was selected to examine the non-consistent features using statistical testing. Empirical evidence was then provided for the impacts of environmental changes on the hydrological process. The Generalized Additive Models for Location, Scale, and Shape (GAMLSS) framework was employed to construct a non-consistent standardized runoff index (NSRI). Distribution parameters were explicitly incorporated with the time-varying influences of the climatic factors and anthropogenic activities. Consistent drought indices were avoided to validate the superiority of the framework. The NSRI was systematically compared against SRI using drought characteristic analysis and historical drought events. Better performance was achieved in capturing the drought severity, in agreement with actual disaster occurrences. Multiple drought features were integrated with the occurrence probabilities under non-consistent conditions using the Vine Copula method. The high-dimensional joint distributions were decomposed into a series of conditional bivariate copulas, effectively reducing the complex parameter estimation and the complex dependencies among different drought attributes. The drought risk was quantified as more actionable information using continuous, time-varying metrics rather than a static value. The performance was validated using well-documented historical drought events, indicating reliable early warnings. Some insights were obtained. Firstly, there was a significant variation in the hydrological regime, where the non-consistent features of the runoff series were attributable to both climatic shifts and human interventions. Secondly, the superior performance of the NSRI was achieved in capturing the drought events, compared with the SRI. More accurate characterization of drought severity resulted in better agreement with the documented drought occurrences. Thirdly, the risk assessment indicates that the basin is currently subjected to moderate drought risk levels, where both major tributaries share similar risk profiles. The effectiveness of the model was validated to identify the high-risk periods, according to the typical drought events in 1991-1992. Timely warnings were provided for both scientific and practical applications. Non-consistent hydrological drought analysis was integrated with the GAMLSS index with Vine Copula-based dynamic risk assessment in a unified framework. The model can be readily adapted to similar regions under hydrological conditions. The finding can provide valuable support for drought monitoring, agricultural irrigation, and risk management in the oasis agricultural regions. Non-consistent hydrological drought can also offer a robust framework to enhance the drought resilience in the water-stressed regions under environmental conditions in sustainable agriculture.

In order to sort out the thermal dynamic characteristics and driving factors of rivers in the inland arid region, based on the systematic investigation of the water temperature of Yili River, a numerical model of river hydrodynamic-water temperature based on HEC-RAS was constructed. Remote sensing meteorological spatio-temporal data was used to analyze the variation law of the water temperature of the 210 km section downstream of the reservoir at the outlet of the Yili River. The impacts of the development and utilization of water resources and future climate change on the water temperature of the river were quantified and discussed. The results show that the constructed HEC-RAS model can identify the impacts of the development and utilization of water resources and climate change. In April, the low-temperature water discharged from large reservoirs is limited by the small temperature difference between water and air, and the downstream river warms up slowly along the way, and measures such as stratified water intake have limited effects. The changes in river flow caused by water intake and other behaviors have changed the heat capacity of the river, resulting in differences in the variation law of water temperature. When the river flow decreases in April, the rise in water temperature is not significant, but when the flow increases, the water temperature decreases significantly, with a maximum decrease of - 0. 60℃. When the flow decreases in July, the rise in water temperature changes significantly, with a maximum increase of 0. 65℃, and when the water volume increases, the water temperature changes little. Under different climate models of low, medium and high carbon emission scenarios in the future, the water temperature of the Yili River will show an upward trend on the long time scale from 2020 to 2080. The increase range and fluctuation range of the water temperature are both lower than the air temperature. The average 10-year temperature increase rate at section 2 is 0. 09, 0. 21, and 0. 56℃ respectively. It is predicted that by 2080, the increase in water temperature caused by the decrease of river water volume will account for 6% and 21% in April and July, respectively.