Clarifying the salt ion composition characteristics and the influence factors of soil salinization of the wasteland in the Kashgar River Basin is of high importance for saline land improvement and utilization in this region. We studied the characteristics and influence factors of soil salinity in the wasteland of the Kashgar River Basin through classical statistics, principal component analysis and grey relational theory. The results showed that the total salt content had a T-shaped distribution pattern in the soil profile. As the most important ions, Cl⁻, Na⁺, and SO₄²⁻ have the characteristics of vertical differentiation from top to bottom in the soil profile. Correlation analysis showed that the total salt content was negatively correlated to the HCO₃⁻ content and positively correlated to other salt ions, The most correlated anions were SO₄²⁻ and Cl⁻. Na⁺, the most important cation, had the closest relationship with Cl⁻, followed successively by SO₄²⁻ and HCO₃⁻. Principal component analysis showed that SO₄²⁻, total salt content, Na⁺, Cl⁻, Mg²⁺, and Ca²⁺ could represent soil salinity status and salt ion composition, while HCO₃⁻ could represent soil alkalization status. The grey relational analysis indicated a differentiation in the intensity of influence of each factor on soil salinization at different depths. Except for groundwater burial depth and elevation, the relational degree between other influence factors and soil salt content decreased with depth. Our research findings offer important clues for understanding the soil salinity characteristics and influence factors of salinization in the wasteland of the Kashgar River Basin.

In regions with arid and semi-arid climates, water consumption for agricultural irrigation is much higher than that used for urban and industrial purposes. Intensive irrigation plays a vital role in influencing the interaction between groundwater and surface water. Understanding the impact of irrigation on the local hydrological cycle is of great significance for maintaining regional food production and -security. In order to study the impact of irrigation on the regional hydrological cycle, the present study employed the SWAT-MODFLOW coupled model to analyze the Weigan River Basin from 2002 to 2016. In the modeling process, detailed agricultural management measures were considered, including the zoning of crop types, amount of irrigation water for different crops, irrigation methods, and different sources of irrigation water. Before coupling, each model was set, calibrated, and validated separately. After coupling, the irrigation pumps and drainage units were mapped with the SWAT automatic irrigation and subbasins. Calibration and validation studies showed that the SWAT-MODFLOW coupled model could simulate the river flow and groundwater levels in the Weigan River Basin well. The model simulation results showed that the sources of water in the soil included groundwater irrigation (1147.5 mm) and surface water irrigation (68.4 mm), as well as precipitation and snowmelt recharge (97.62 mm). The groundwater balance was influenced by the river leakage (75.6 mm), lateral inflow from surrounding areas (3.6 mm), unsaturated zone infiltration (197.7 mm), and irrigation pumping (1275 mm). When compared with the scenario without irrigation, the surface runoff, groundwater infiltration, soil moisture content, and evapotranspiration increased by 7.9%, 3.2%, 4.1%, and 2.3%, respectively. Irrigation activities increased the soil moisture content and permeability, resulting in more groundwater recharge and evaporation, as well as a higher surface runoff. This model provides guidance for evaluating drought irrigation systems in future sustainable water resource management.

The analysis of water-soluble salts in the soil is an important basic work for the development and research of the salinity monitoring and salinization control of saline soils, aiming at the complexity of the development of soil salinization in oases in arid and semi-arid areas. Based on the regionalization theory, GPS positioning technology was adopted in this paper to conduct fixed point sampling of the Weigan River Basin oasis from April to May 2020. Soil sampling levels were between 0 m and 0.25 m, between 1 m and 2 m, and between 2 m and 3 m, respectively, and soil physical and chemical properties were analyzed and tested from May to June 2022. The spatial variability of soil salinity at different depths in the Weigan River Basin oasis was quantitatively studied by GIS and geostatistics, and the results show that: (1) the soil salinity of each layer in the Weigan River Basin oasis was generally high, with an average value of 1.27%, 0.87%, and 0.79%, respectively, and a variation coefficient between 1.023 and 1.265, showing strong variability. (2) A reasonable number of soil sampling should be based on the 95% confidence level and 20% relative error. Therefore, the number of soil samples in the corresponding layers should not be less than 89, 70, and 91. (3) Optimal fitting models of soil salinity at the layers between 0 m and 0.25 m and between 1 m and 2 m were both spherical models, while the optimal fitting model of soil salinity at the layer between 2 m and 3 m was an exponential model. Soil salinity at different depths is affected by random factors and structural factors. Soil salinity at the layer between 0 m and 0.25 m showed moderate spatial correlation, while soil salinity at the layers between 1 m and 2 m and between 2 m and 3 m showed strong spatial correlation. (4) Three layers of soil salinity had obvious anisotropy, and the maximum variation direction was northwest–southeast. The nested model can overcome the influence of directionality on the fitting of soil salinity variation function in the layer between 0 m and 0.25 m and improve the spatial interpolation accuracy. (5) In terms of spatial pattern, the area of high soil salinity was located along the Tarim River and at the edge of oasis (i.e., desert–oasis ecotone). On the whole, the salinity shows a gradual increasing trend from the inner part of the oasis (i.e., cultivation area) to the edge of the oasis, and from the northwest to the southeast. (6) The spatial distribution pattern of soil salinity in the study area was mainly affected by the differences in topography, groundwater level, and water quality, while agricultural activities intensified the formation of the distribution pattern, reflecting the complexity of the development of soil physical and chemical properties in arid and semi-arid areas. This study provided a reference for the improvement, management, and rational utilization of saline soil in the Weigan River Basin oasis.

This study employs the Driving Force–Pressure–State–Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele–Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we analyze the trends in the WRCC and its main hindrance factors in the Cele–Yutian Oasis from 2005 to 2020. Additionally, we employ the Markov model to investigate the dynamic changes in the land use types. The findings reveal that the most unfavorable WRCC status occurred in 2007, with a Grade IV rating (a mild overload). By 2020, the WRCC improved to a Grade III rating (critical), indicating a positive trajectory. However, persistent challenges for water resources remain, with a prolonged critical state. Over the past 15 years, the grassland area has decreased by 15.18%, and the forest area has decreased by 50%. The dynamic degree of grassland, forests, and water bodies is negative, signifying shifts to other land types, with water bodies undergoing the most significant change at −10.16%. Based on the outcomes of these two models, we propose regionally tailored measures to support sustainable development. These research results provide a scientific foundation for optimal water resource allocation and sustainable development in the Cele–Yutian Oasis Economic Belt.

As the largest irrigation area in northwest China, the middle and lower reaches of the Yarkant River basin are limited in economic development by the shortage of surface water resources and the increasing demand for groundwater resources from agriculture and industry, and the phenomenon of over-exploitation is becoming increasingly serious, which is not in line with the concept of sustainable development. Therefore, improving the efficiency of water resource utilization while curbing the trend of declining groundwater levels is an important issue that needs to be addressed in the middle and lower reaches of Yarkant at present, specifically, by establishing a distributed hydrological model MIKE SHE based on a soil texture dataset. The model efficiency coefficient Ens, the water balance coefficient (WB), the correlation coefficient r, and the relative error Re were selected to evaluate the model’s applicability. The results were: Ens = 0.84, WB = 0.80, and r = 0.96 for the annual scale runoff simulation and Ens = 0.85, RE = 0.61, and r = 0.96 for the monthly scale runoff simulation. The relative errors between the simulated and observed values of the typical observation wells were 3.45%, 1.59%, 2.52%, and 0.35%. According to the analysis of the soil parameters on the runoff sensitivity and groundwater table sensitivity, the saturated hydraulic conductivity had the greatest effect on the peak discharge. The results show that the MIKE SHE model has some applicability in the lower and middle reaches of the Yarkant River basin.

Understanding the coupled continuum pipe-flow framework for modeling contaminant transport in karst systems is critical for protecting water resources therein. This study simulated point and non-point source nitrate concentration in a karst spring and investigated the results generated from the flow and transport model with and without discrete conduit flow. CFPv2 and CMT3D models were integrated to address the changes in nitrate concentration at a monthly scale in a karst spring, and the results were compared with that from an equivalent porous media (EPM) model with high-hydraulic conductivity (K) zones set in the main karstified area to represent conduits. The results show that the CFPv2+CMT3D model is able to describe well the recession of nitrate concentration in spring discharge, and the relatively larger deviation (slower nitrate recession) from the observed trend for the EPM model is probably a result of the limitation of utilizing high hydraulic conductivity cells to represent conduit. Moreover, simulated hydraulic heads in poorly karstified areas from the two models both show slight differences from the observations (the head RMSE values of calibration/validation for CFPv2 and MODFLOW models are 0.16 m/0.25 m and 0.26 m/0.17 m, respectively), indicating the inclusion of conduits may not affect the simulation considerably, and the lower the proportion of karstic area, the slight effects brought from the inclusion of conduits in the model. For highly karstified areas, the CFPv2+CMT3D model could provide more accurate results (head RMSE of calibration/validation for CFPv2 and MODFLOW are 0.22 m/0.06 and 0.52 m/0.47 m, respectively), showing the coupled continuum pipe-flow framework may be more appropriate for applying to highly and maturely karstified areas where the variations in the behavior of flow and contaminant transport are more affected by turbulent flow regime.