The characteristics of the growing environment (arid and semi-arid regions with abundant light), wastage of water, types of fertilizers used, quality of the plants, and the decline in yield due to the need for large quantities of water and fertilizers are the most significant obstacles to wolfberry cultivation. To cope with the scarcity of water caused by the increase in the area of wolfberry cultivation and to improve the efficiency of the utilization of water and fertilizers, a two-year field experiment was conducted in a typical area of the central dry zone of Ningxia in 2021 and 2022. The effects of different water and nitrogen coupling on the physiology, growth, quality, and yield of wolfberry were investigated, and a water and nitrogen management model with better indicators was constructed based on the TOPSIS model and a comprehensive scoring method. In the experiment, three irrigation quotas of 2,160, 2,565, and 2,970 m³ ha^–1 (I₁, I₂, and I₃) and three N applications of 165, 225, and 285 kg ha^–1 (N₁, N₂, and N₃) were established; the local conventional management served as the control (CK). The results showed that the growth index of wolfberry was most significantly affected by irrigation, followed by the water and nitrogen interaction effect, and the nitrogen application had the least effect. The growth and development of wolfberry plants mainly takes place during the fruit ripening and flowering periods, and growth almost stops after entering the fruit ripening period. The chlorophyll (SPAD) values were affected by irrigation and nitrogen application to a significant level, except for during the spring tip period, but the effect of water and nitrogen interaction was not significant. The SPAD values of N2 treatment were better under different irrigation. The daily photosynthetic activity of wolfberry leaves peaked between 10:00 am and noon. The daily photosynthetic dynamics of wolfberry were affected by irrigation and nitrogen application to a significant level during the fruit ripening period, and the transpiration rate and leaf water use efficiency were affected by water and nitrogen interaction to a significant level during 8:00 am and noon, while the effect was not significant during the spring tip period. The yield, dry-to-fresh ratio, and 100 grain weight of wolfberry were significantly affected by the irrigation, nitrogen application, and their interaction effects. Specifically, the two-year yield with I₂N₂ treatment increased by 7.48% and 3.73%, respectively, compared to CK. The quality indices were significantly affected by irrigation and nitrogen application, except for the total sugars; other indexes were also significantly affected by water and nitrogen interaction effects. The evaluation of the TOPSIS model showed that the I₃N₁ treatment yielded the best quality of wolfberry, and the results of the integrated scoring method based on the growth, physiology, yield, and quality indicators and water-saving objectives showed that the I₂N₂ (2,565 m3 ha^-1, 225 kg ha^-1) treatment was the optimal water and nitrogen management mode for drip-irrigated wolfberry. Our findings provide a scientific basis for the optimal irrigation and management of fertilization of wolfberry in arid regions.

Potatoes require water and fertilizer management systems to optimize economic outcomes and fertilizer use, especially in arid areas such as Ningxia, China. In this study, three irrigation quotas (1200 (W1), 1650 (W2), and 2100 (W3) m³/hm²) and three nitrogen application treatments (110 (N1), 190 (N2), and 270 (N3) kg/hm²) were evaluated. Potato growth, final yield, and quality indices were assessed in relation to fertility periods, irrigation utilization efficiency, nitrogen and fertilizer bias productivity, and economic efficiency, using the TOPSIS model. Stem thickness and plant height varied significantly with irrigation and nitrogen treatments; total yield and vitamin C, reducing sugar, and starch contents were the highest under the W3N1, W3N1, W1N2, and W2N3 treatments, increasing by 54.56, 17.00, 69.00, and 45.00%, respectively, compared with those in the control. The regression relationships between water and nitrogen regulation and yield, irrigation water use efficiency, nitrogen fertilizer bias productivity, and economic efficiency agreed with the binary quadratic regression model, and the coefficients of determination (R²) were >0.85. W3N1 was optimal for model yield, nitrogen fertilizer bias productivity, and economic efficiency, and W1N3 was optimal for irrigation water use efficiency. Our findings will help optimize potato management in central Ningxia.

Potato is one of the key food crops and China is the largest potato producer in the world. However water scarcity is the major constraint to increase the productivity of potato in the arid regions such as Ningxia in northwest China where this crop is extensively cultivated. The overall objective of this study was to optimize the irrigation for potato cultivated under the drip irrigation. To do this, the AquaCrop model was calibrated and validated using the data obtained from two years of field experiment. Then, the calibrated crop model was used to simulate growth and tuber yield of potato in response to 30 different irrigation schemes under two different irrigation scenarios. The crop model evaluation parameters namely, the root mean square error (RMSE), the index of agreement (d), the normalized root mean square error (NRMSE) and the coefficient of determination (R²) showed that the AquaCrop model could simulate the growth and yield of potato under the drip irrigation with different irrigation treatments with reasonable accuracy. Furthermore, yield of potato has increased with increasing amount of total irrigation under drip irrigation; however, yield begins to decline when the amount of total irrigation exceeds 2500 m³ ha^-1. The study also found that the optimum irrigation schedule for potato was 20 mm of irrigation quota at 7 days of irrigation cycle (i.e., 1800 m³ ha^-1 or 180 mm of total irrigation). The above irrigation scheduling has achieved 46.77 t ha^-1 of tuber yield with 15.74 kg m^-3 of water use efficiency. These findings may be evaluated in potato cultivation across different climate and soil conditions for wide applicability at different arid regions of the world.

To understand the characteristics of the water’s environmental carrying capacity in the Aiyi River in Yinchuan, Ninxia, China, a BP artificial neural network analysis based on water environmental factors and aquatic biodiversity metrics were conducted. Twelve indicators were used to construct an evaluation index system to examine the water environment carrying capacity of the river, namely ratio of water supply and water requirements; ratios of water environmental capacity to pollutant emissions of COD_Mn, BOD₅, TN, NH_3-N, and TP; self-purification rate; biodiversity indices of phytoplankton, zooplankton zoobenthos, and aquatic macrophytes; and a comprehensive nutrition state index. A model of water environmental carrying capacity was constructed according to the BP artificial neural network. The model, which quantitatively analyzed the water environmental carrying capacity of the Aiyi River, found it to be in the basic carrying state.

Potato, a globally important food crop, plays a key role in ensuring food security and poverty alleviation. Addressing the prominent contradiction between water scarcity and low nitrogen use efficiency in potato production in the arid regions of northwest China, this study conducted a water-nitrogen regulation experiment to explore the synergistic effects of water-nitrogen management on potato yield and physiological ecology. Irrigation treatments included the full irrigation quota (2250 m ³ ha ^-1 , W3), 20% water-saving (1800 m ³ ha ^-1 , W2), and 40% water-saving (1350 m ³ ha ^-1 , W1), while nitrogen application treatments consisted of the full nitrogen rate (195 kg ha ^-1 , N3), 20% nitrogen reduction (156 kg ha ^-1 , N2), 40% nitrogen reduction (117 kg ha ^-1 , N1), with the local conventional practice as the control (CK). The results showed that the W2N2 treatment had the highest chlorophyll content, which was significantly higher than other treatments and 2.87% higher than CK on average. Under water-nitrogen interaction, potato leaf gas exchange parameters first increased and then decreased with growth stages, peaking at the tuber formation stage, and the W2N2 treatment was significantly superior to other combinations. For nutrient contents in various plant organs, the W2N2 treatment also achieved the highest total nitrogen and total phosphorus contents, which were significantly higher than other treatments. The distribution ratios of nutrient contents in different organs varied with water-nitrogen treatments across years. Based on quadratic regression analysis and the TOPSIS model, the optimal water-nitrogen coupling pattern for potato cultivation in the arid zone of central Ningxia was determined as W2N2, providing theoretical and technical references for efficient potato cultivation with water-saving and nitrogen-reducing practices in arid regions.

This study investigated bacterial community structure in surface water, sediment, and riparian soil habitats within the Qingshui River Basin in Ningxia, China, across normal, wet, and dry periods using 16S rDNA sequencing. Our findings revealed habitat-specific microbial dynamics, with surface water exhibiting significantly lower α-diversity compared to sediments and riparian soils (e.g., wet period Chao1: 1255.69 vs. 2319.93 and 2377.64, respectively; P < 0.001). Despite this difference, core taxa such as Pseudomonas (average relative abundance: 2.85 % in surface water, 2.05 % in sediments, and 3.53 % in riparian soils) were shared across habitats, suggesting cross-habitat connectivityand thereby reconciling high β-diversity with broad-scale functional stability. Distinct environmental drivers were identified: fluoride (including water-soluble fluoride in sediments and F⁻ in interstitial water) was a key driver of phylum-level community structure in sediments (Mantel test r = 0.189 or 0.116, P < 0.01), enriching fluoride-tolerant Campilobacterota, while ASV/genus-level structure was modulated by pH/EC; TN/TP primarily influenced riparian soils (P < 0.05); and surface water communities were shaped by ionic stress (e.g., Na⁺ up to 1266.68 mg·L⁻¹) and hydrological variability. Hydrological-period-dependent interactions revealed that dry-period surface water formed low-modularity (0.315), high-connectivity networks (1569 edges), favoring functional redundancy. In contrast, sediments maintained stability through high modularity (0.761), while riparian soils exhibited 70.62 % node reduction but increased modularity (0.801) under drought, indicating niche conservatism. These results demonstrate how geochemical gradients (e.g., F⁻, TN/TP) and hydrological variability collectively structure microbial communities in arid watersheds. Our findings provide a framework for managing fluoride and nutrient impacts in the Yellow River Basin and similar ecosystems globally, emphasizing the need for habitat-specific conservation strategies.