To study the effects of water stress on the fluorescence parameters and photosynthetic characteristics of rice under drip irrigation and mulching, so as to determine the response mechanisms to water stress during the tillering stage. A two-year trial was carried out at Shihezi University, China. Three water gradients were investigated. The results showed that the chlorophyll content (a + b), photosynthetic rate (P_n), and leaf area index (LAI) decreased with decreasing soil moisture content at the tillering stage. The chlorophyll content (a + b) and P_n in the flooding irrigation (CK) treatment were significantly higher than those in the stress treatments, and the chlorophyll content (a + b) and P_n in the W1 and W2 treatments were significantly lower than those in the other treatments. The maximum LAI of the CK, W1, and W2 treatments were similar, while the W3 produced lower values; stress treatment improved the ability of tillering in the early and middle stages, while the decrease in soil water content in the tillering stage resulted in a decrease in the final tillering rate; drought stress in the tillering stage resulted in decreased rice yields. The yield of the W1 and W2 treatments were similar, while that of the W3 treatment was seriously reduced. The main reasons for the reduction in yield was the significant decrease in the number of effective panicles, the seed setting rate, and a decrease in the 1000-grains weight. Water consumption in the stress treatments decreased by 51.69%–58.78% compared to the CK treatment; water-use efficiency in the CK treatment was only 0.25 kg·m⁻³, and the water-use efficiency of the stress treatments increased by 40%–72%. We should make full use of the compensation effect of drought stress in the water regulation of drip irrigation in covered rice and adopt the water control measure of the W2 treatment in the tillering stage. These measures are conducive to improving water-use efficiency and achieving the goal of high quality, high yield, and high efficiency.

Xinjiang is a typical continental arid climate zone and ecologically fragile zone. Drought has caused damage to the local social economy, agricultural production, and the ecological environment. However, the study of drought is more difficult due to the complex topography and the lack of monitoring information. In this paper, based on the meteorological data of 94 meteorological stations in Xinjiang from 1961 to 2020, we used the precipitation and potential evapotranspiration (ET₀) to calculate the aridity index (AI); the Mann–Kendall test, Morlet wavelet analysis, and Kriging interpolation were used to identify the trend, period, and spatial distribution. The results showed that (1) the average change rate of the precipitation in Xinjiang was 8.58 mm/10a, the average change rate of the ET₀ was −14.84 mm/10a, and the average change rate of the AI was −1.94/10a; (2) the periods of precipitation, ET₀, and AI in Xinjiang were 39, 29, and 14 years, respectively, and the abrupt changes occurred in 1986, 1971, and 1987, respectively; (3) The Moran index of precipitation and temperature are 0.41 and 0.33, respectively, indicating that precipitation and temperature in Xinjiang are positively correlated in spatial distribution and have spatial clustering characteristics; and the z-values are both greater than 2.58 (p < 0.01), indicating that the spatial autocorrelation of precipitation and temperature in Xinjiang is significant. This study can provide a reference for the diagnosis of the meteorological drought mechanism and the coping with climate change in Xinjiang.

Salinization of irrigation areas is a key environmental challenge faced by arid and semi-arid regions worldwide, and the complexity of natural environment and human activities increases the uncertainty of salinization distribution. This study takes the Xiaohaizi Irrigation Area in Kashgar, Xinjiang as the research location. Soil samples were collected before sowing and after harvesting in 2023 and analyzed. Using geostatistics and digital soil mapping techniques, the spatial distribution and temporal evolution of soil salinization in the region were finely characterized. The results showed that the soil salinization in Xiaohaizi Irrigation District was moderate to high, with mean salt contents of 8.29 g/kg in the 0–30 cm layer, 6.16 g/kg at 30–60 cm, and 4.80 g/kg at 60–100 cm before sowing, all indicating moderate to high salinity levels. The salt content showed a surface aggregation distribution with significant differences between different depths. The main ions that affect salinization are SO₄²⁻, Ca²⁺, Mg²⁺, Cl⁻, K⁺, and Na⁺. The 0–30 cm soil layer is mainly composed of mildly saline soil, and the degree of soil salinization decreases with the depth of the soil layer. After harvesting, the overall degree of salinization in the irrigation area intensified, and the spatial distribution of salinization was uneven. The degree of salinization was higher in the northwest and lower in the south. The impact of human activities on surface soil salinization is greater than that on deep soil. The areas where the degree of salinization in the 0–30, 30–60, and 60–100 cm soil layers undergoes transformation account for 57.18%, 33.15%, and 26.9%, respectively. This study reveals the complex dynamics of soil salinization in the Xiaohaizi irrigation area, providing scientific support for soil management and irrigation strategies in the region, and is of great significance for achieving sustainable development of oasis agriculture.

The cotton-growing region in Southern Xinjiang is plagued by perennial drought and water scarcity, and there is a lack of research on the irrigation mechanism for the “one film, three tubes, four rows” new model of dry sowing and wet emergence of cotton. Therefore, this experiment explores the optimal irrigation regime for cotton under the “one film, three tubes, four rows” planting model in Southern Xinjiang, where a two-year field plot experiment was conducted. Three irrigation levels (W1: 360 mm, W2: 450 mm, W3: 540 mm) were set, with three replications each, to study the effects of different irrigation amounts on cotton growth, soil water content (SWC), irrigation water productivity (IWP), water productivity (WP), and yield (Y). Additionally, the AquaCrop model was used to optimize the irrigation regime. The results showed that irrigation amount significantly affected cotton growth, with plant height, stem diameter, and leaf area index following the order of W3 > W2 > W1. Compared to W1 and W2 treatments, the final biomass (B) and average SWC in the W3 treatment increased by 32.71%, 19.59% and 8.26%, 3.23%, respectively. The seed cotton yield under the W3 treatment was significantly higher than other treatments, being 6575.91 kg/ha in 2023 and 7252.16 kg/ha in 2024. IWP and WP were inversely related to irrigation amount. After two years of data calibration and validation, the model showed good simulation performance for canopy cover (CC), B, WP, and Y (with a concordance index d ≥ 0.904 and a coefficient of determination R² ≥ 0.846). Among the 11 simulated irrigation scenarios (ranging from 360 to 660 mm in 30 mm increments), yield increased with irrigation amount but began to decline slowly beyond 570 mm, peaking at 7.45 t/ha, with IWP and WP being 1.307 kg/m³ and 1.294 kg/m³, respectively. Considering both water conservation and yield increase, an irrigation level or amount of 570 mm under the one-film, three-pipe, four-row planting pattern for dry sowing, wet emergence cotton in Southern Xinjiang can achieve good yields, benefiting the sustainable production of the local cotton industry.

To improve cotton yield and water–nitrogen productivity in arid southern Xinjiang under climate change, field experiments conducted in 2024 (for calibration) and 2025 (for validation) were conducted in Tumushuke City to evaluate planting patterns and water–nitrogen regimes. The local conventional strategy M1T3R6 (600 mm irrigation and 825 kg N ha⁻¹) served as the control. Under the one-film–three-pipes–four-rows pattern (M1T3R4), three irrigation quotas (360, 450, and 540 mm) were combined with three N rates (495, 619, and 743 kg ha⁻¹), and the AquaCrop model was calibrated and validated. Using 40-year (1984–2023) meteorological data and SPEI-6, hydrological years were classified into four categories: wet (Y1), normal (Y2), dry (Y3), and extreme drought (Y4). Simulations assessed cotton yield (Y), water productivity (WP), and partial factor productivity of nitrogen (PFPN) under different managements, and NSGA-II with TOPSIS was used for multi-objective optimization. AquaCrop performed well for canopy cover, soil water, evapotranspiration, and yield (R² > 0.81; d > 0.85). Y, WP, and PFPN declined significantly with increasing drought severity. Compared with M1T3R6, M1T3R4 increased soil water and PFPN while reducing water and N inputs. Optimization for Y1–Y4 identified irrigation intervals of 529.9–599.1 mm and nitrogen intervals of 551.8–584.9 kg/ha, which increased yield by 8.85–21.82% while reducing irrigation by 8.33–14.15% and nitrogen by 58.6–78.1% relative to M1T3R6.