Under the influence of climate change, the hydrological processes of glaciers have undergone significant changes, a fact which is seriously affecting agricultural production in the downstream region of the Tianshan Mountains, China. In order to explore the intrinsic relationship between climate change and hydrological elements, we proposed an “evaluation-driving-prediction” system to study it. First, we constructed a glacier-enhanced soil and water assessment tool model (GE-SWAT) and used a two-stage calibration method to optimize the model parameters. Next, a scenario analysis was used to evaluate the driving factors of historical runoff changes. Finally, we projected future runoff changes using bias-corrected regional climate model (RCM) outputs. The results of the case study on the Jinghe River Basin in the Tianshan Mountains show that from 1963 to 2016, total runoff increased by 13.3%, 17.7% of which was due to increasing precipitation and 1.8% of which was negated by rising temperatures. The glacier runoff increased by 14.5%, mainly due to the rising temperatures. A 3.4% reduction in snowmelt was caused by a lower snowfall/precipitation ratio, which significantly reduced the snowfall from June to August. The RCM projection indicated that the warming and humidification phenomenon in the study area will continue at least through to the mid-21st century. A consistent increase in glacier runoff and total runoff is projected, but the contribution rate of the glacier runoff will have little to no change under the RCP4.5 and RCP8.5 emission scenarios. Our research demonstrates the simulation performance of the GE-SWAT model in a basin with moderate glacier cover. This method is shown to be efficient in quantifying the impact of climate change on glacier hydrological processes and predicting future streamflow changes, providing a good research reference for similar regions.

Human activities and climate change have profound impacts on the ecological environment of oases in Xinjiang, and it is of great significance to explore the spatial and temporal evolution patterns of ecological environment quality in this region for the sustainable development of Xinjiang. The remote sensing ecological index (RSEI) was extracted from the Google Earth Engine (GEE) platform from 2000 to 2020, and the coefficient of variation and Hurst index were used to reveal the spatial and temporal characteristics and stability of the ecological environment quality of the artificial oasis and natural oasis in Xinjiang. The key factors affecting the ecological environment quality are explored through correlation analysis and geoprobes. The results show that the distribution of the ecological environment in Xinjiang oases is high in the north and low in the south, and the overall quality shows a fluctuating downward trend from 0.210 to 0.189. Artificial oases have higher RSEI values, stability, and sustainability than natural oases. The RSEI in the study area was mainly influenced by humidity, followed by greenness and heat, and dryness had the least influence on the RSEI model. Based on the geodetector, the top three highest contributors were found to be precipitation (PRE) (0.83) > relative humidity (RHU) (0.82) > evapotranspiration (ET) (0.57). Climate is the main factor affecting the ecological quality of oases, and the RSEI can be improved by increasing the proportion of artificial oases. The study aims to provide a scientific basis for the sustainable development of oases in arid zones.

Water and soil resources are the key elements required to maintain the stability and sustainable development of oases in inland drylands. This study takes oases in Xinjiang as an example, and reveals the spatial and temporal distribution characteristics of oases across Xinjiang, as well as the dynamic migration and transformation process of oases and the mutual influence of human activities on oasis resources, through a combination of land movement and attitude indicators, use of a gravity model, and Geodetector. The results show that: (1) the area containing the oases in the study has expanded, increasing by 24.0% between 1990 and 2020; (2) both artificial oases (AO) and natural oases (NO) were tilted in a northeast–southwest direction, with the center point of AOs moving slightly to the northeast, and the centripetal force and dispersion degree did not change significantly; the center point of NO moved significantly to the northeast, and the dispersion degree weakened, showing spatial convergence; (3) cultivated land and grassland were the main land types of oasis evolution, and their contribution to evolution was over 70%; and (4) the Geodetector results show that the three main factors driving the evolution of oases were vegetation cover, population density, and GDP. The research results have practical implications for land-use management planning and ecological environmental protection in arid zones.