The ecological water diversion project (EWDP) in the Tarim River Basin, China, aims to allocate more surface water to downstream reaches to restore the degraded ecosystems. However, seasonal changes in ecological water diversion; the factors (natural and anthropogenic) controlling the ecological water diversion, whether the seasonal delivery of water temporally corresponded to the vegetation’s seasonal water demands; and the benefits of the ecological water diversion through overflowing surface water irrigation are unclear. To address the above issues, this study examines the intra-annual changes and its influencing factors in ecological water diversion (inundation) in the Daliyaboyi Oasis in the lower Keriya River valley within the Tarim Basin, discusses whether the seasonal delivery of water temporally corresponded to the vegetation’s seasonal water demands, and assesses the ecological benefits of overflowing surface water irrigation. Inundation was quantified by digitizing monthly changes in the inundated area from 2000 to 2018 in the oasis using 184 Landsat images. The results demonstrate that seasonal changes in the inundated area varied significantly, with maximum peaks occurring in February and August; a period of minimal inundation occurred in May. Differences in the July/August peak (i.e., July or August) in inundation dominated the inter-annual variations in the inundated area over the 19-year study period. The two peaks in the inundation area were temporally consistent with the vegetation’s seasonal water demand. Local residents have used ecological water to irrigate vegetation in different parts of the oasis during different seasons, an approach that expanded the inundated area. The February peak in the inundated area is closely linked to elevated downstream groundwater levels and the melting of ice along the river. The August peak is related to a peak in runoff from headwater areas. The minimum May value is correlated to a relatively low value in upstream runoff and an increase in agricultural water demand. Thus, natural factors control the intra-annual and inter-annual variations in the inundated area. Humans changed the spatial distribution of the inundated area and enhanced the water’s ecological benefits, but did not alter the correlation between peak periods of inundation and vegetation water demand. The results from this study improve our understanding of the benefits of the EWDP in the Tarim River Basin.

Vegetation and groundwater are important components of the ecological environment of oases in desert hinterlands and their relationship is crucial to ecosystem stability. In this study, Sentinel-2 data for 2016–2022 and measured groundwater burial depths were analysed for the Dariyabui Oasis in the hinterland of the Taklamakan Desert. The spatial and temporal changes in vegetation and groundwater burial depth from 2019 to 2022 were analysed based on the image–element dichotomous model of the normalised difference vegetation index, utilising the inverse distance weight interpolation method, cubic curve regression, image–element difference, slope trend analysis, and the Markov transfer matrix for determining the temporal and spatial response law between the two. Finally, the threshold value of groundwater burial depth for different vegetation cover types was clarified. The fractional vegetation cover of the Dariyabui Oasis showed a slight increase from 2016 to 2022. Vegetation in the northwest and southeast of the oasis increased, whereas vegetation decreased in the mid-north and northeast regions; 5.14% of the total area experienced increased coverage, whereas 3.35% experienced decreased coverage. The depth of groundwater in the oasis showed a pattern of gradual increase from the entrance to the end of the oasis, that is, south to north. The depth of groundwater in the oasis from 2019 to 2022 was stable, with a 4-year average depth of 4.1069 m and a maximum fluctuation of 0.4560 m. The interannual changes in the groundwater level showed an increasing trend in January–April, while groundwater levels showed a decreasing trend in May–July and August–October and remained constant in June–July and October–December. Oasis vegetation cover showed a negative correlation with groundwater depth, with a depth interval for the highest low-cover vegetation distribution of 3–6 m, and an ultimate depth threshold of 7 m. The depth interval with the highest medium-cover vegetation distribution was 3–4 m, that with the highest high-cover distribution was 2–4 m, and the ultimate depth threshold was 6 m. The depth of the oasis ranged from 3 to 6 m and the ultimate depth threshold was 7 m.

Arid regions are considered to be among the most ecologically fragile and highly sensitive to environmental change globally, and land use and land cover conditions in the region directly influence large-scale ecosystem processes. Currently, thanks to diverse remote sensing platforms, geographers have developed an array of land cover products. However, there are differences between these products due to variations in spatio-temporal resolutions. In this context, assessing the accuracy and consistency of different land cover products is crucial for rationalizing the selection of land cover products to study global or regional environmental changes. In this study, Xinjiang Uygur Autonomous Region (XUAR) is taken as the study area, and the consistency and performance (type area deviation, spatial consistency, accuracy assessment, and other indexes) of the five land cover products (GlobeLand30, FROM_GLC30, CLCD, GLC_FCS30, and ESRI) were compared and analyzed. The results of the study show that (1) the GlobeLand30 product has the highest overall accuracy in the study area, with an overall accuracy of 84.06%, followed by ESA with 75.57%, while CLCD has the lowest overall accuracy of 70.05%. (2) The consistency between GlobeLand30 and CLCD (area correlation coefficient of 0.99) was higher than that among the other products. (3) Among the five products, the highest consistency was found for water bodies and permanent snow and ice, followed by bare land. In contrast, the consistency of these five products for grassland and forest was relatively low. (4) The full-consistency area accounts for 49.01% of the total study area. They were mainly distributed in areas with relatively homogeneous land cover types, such as the north and south of the Tianshan Mountains, which are dominated by bare land and cropland. In contrast, areas of inconsistency make up only 0.03% and are mostly found in heterogeneous areas, like the transitional zones with mixed land cover types in the Altai Mountains and Tianshan Mountains, or in areas with complex terrain. In terms of meeting practical user needs, GlobeLand30 offers the best comprehensive performance. GLC_FCS30 is more suitable for studies related to forests, while FROM_GLC30 and ESRI demonstrate greater advantages in identifying permanent ice and snow, whereas the performance of CLCD is generally average.

Runoff is closely related to human production, the regional environment, and hydrological characteristics. It is also an important basis for water cycle research and regional water resource development and management. However, obtaining hydrological information for uninformed river sections is complicated by harsh environments, limited transportation, sparse populations, and a low density of hydrological observation stations in the inland arid zone. Here, low-altitude remote sensing technology was introduced to combine riverbed characteristics through unmanned aerial vehicle (UAV) inversion with classical hydraulic equations for ungauged basins in the middle and lower reaches of the Keriya River, northwest China, and investigate the applicability of this method on wide and shallow riverbeds of inland rivers. The results indicated that the estimated average error of the low-altitude remote sensing flow was 8.49% (ranging 3.26–17.00%), with a root mean square error (RMSE) of 0.59 m³·s⁻¹ across the six selected river sections, suggesting that this method has some applicability in the study area. Simultaneously, a method for estimating river flow based on the water surface width– and water depth–flow relationship curves for each section was proposed whereas the precise relationships were selected based on actual section attributes to provide a new method for obtaining runoff data in small- and medium-scale river areas where information is lacking.