In order to safeguard the health of river ecosystems and maintain ecological balance, it is essential to rationally allocate water resources. This study utilized continuous runoff data from 1967 to 2020 at the Zhouqu Hydrological Station on the Bailong River. Five hydrological methods, tailored to the hydrological characteristics of the Zhouqu hydrological cross-section, were employed. These methods included the improved dynamic calculation method, the NGPRP method, the improved monthly frequency computation method, the improved RVA method, and the Tennant method. Ecological flow calculations were conducted to determine the ecological flow, with analysis carried out through the degree of satisfaction, economic benefits, and the nonlinear fitting of the GCAS model. We established an ecological flow threshold and early warning program for this specific hydrological cross-section. Ecological flow values calculated using different methods for each month of the year were compared. The improved RVA method and Tennant method resulted in small values ranging from 4.05 to 36.40 m³/s and 7.65 to 22.94 m³/s, respectively, with high satisfaction levels and economic benefits, but not conducive to ecologically sound development. In contrast, the dynamic calculation method, NGPRP method, and improved monthly frequency calculation method yielded larger ecological flow values in the ranges of 21.79–97.02 m³/s, 23.90–137.00 m³/s, and 28.50–126.00 m³/s, respectively, with poor fulfillment and economic benefits. Ecological flow thresholds were determined using the GCAS model, with values ranging from 16.72 to 114.58 m³/s during the abundant water period and from 5.03 to 63.63 m³/s during the dry water period. A three-level ecological warning system was proposed based on these thresholds, with the orange warning level indicating optimal sustainable development capacity for the Zhouqu Hydrological Station. This study provides valuable insights into the scientific management of water resources in the Bailong River Basin to ensure ecological security and promote sustainable development.

Groundwater research on climate change is one of the significant topics in the field of natural sciences that is receiving increasing attention. However, no bibliometric research papers have been published that have analyzed the field for relevant knowledge graphs and relational networks. R-Bibliometrix and VOSviewer software are used to quantitatively analyze and visually represent the literature on the research of groundwater under climate change from 2010 to 2024 based on the Web of Science Core Collection. The findings demonstrated that a total of 4748 articles have been published on this topic, with publications increasing yearly. The most influential journal was the Journal of Hydrology, and the ten most influential papers were published from 2013 to 2017. The United States and China published significantly more research than any other country and had the closest cooperation, while Europe is the continent with the most publications. The Chinese Academy of Sciences was the leading institution in terms of the number of publications, and the Delft University of Technology was the institution with the highest average number of citations. British scholar Chris Soulsby was the author with the highest number of articles. The top three keywords were ‘climate change’, ‘groundwater’, and ‘model’. Machine-learning methods and remote-sensing techniques were emerging research hotspots that guided future research directions.

Inefficient irrigation and fertilizer practices in spring maize production in a Chinese semi-arid region have led to suboptimal fertilizer utilization and yield limitations. Few studies in this region have adequately incorporated long-term meteorological data to optimize irrigation and fertilizer strategies. In this study, we employed the Root Zone Water Quality Model 2 (RZWQM2) to evaluate and optimize irrigation and fertilizer management practices. The model was calibrated and validated using field experimental data during 2022–2023, including two irrigation levels [75%–95% (I1) and 55%–75% field capacity (I2)] and three fertilizer treatments [234.27 (F1), 157.5 (F2), and 157.5 kg hm⁻² nitrogen fertilizer (F3), and F3 plus 63 kg hm⁻² organic fertilizer). The validated model demonstrated excellent performance in simulating key parameters, including soil water content (SWC) [mean relative error (MRE) and normalized root mean squared error (NRMSE) < 15%, consistency index (d) > 0.80], biomass (d > 0.85), grain yield (MRE < 15%), and NH₄⁺-N and NO₃⁻-N contents (RMSE < 10 mg kg⁻¹, MRE and NRMSE < 15%, d > 0.60), of spring maize in 2022 and 2023. Under simulated climate scenarios, optimal yields of 21.54, 20.78, and 17.57 t hm⁻² were achieved using a combined application of 60% nitrogen and 40% organic fertilizer across three irrigation quotas. The irrigation quota of 250 m³ hm⁻² demonstrated superior water use efficiency (WUE), irrigation water use efficiency (IWUE), and partial factor productivity (PFP) compared to quotas of 300 and 200 m³ hm⁻². These findings provide valuable insights for developing sustainable irrigation and fertilizer strategies for spring maize production in a semi-arid region of China.

Different fertilization measures affect the soil’s physical and chemical properties and bacterial community structure, which in turn affects the growth environment and yield of maize seed production. Therefore, rational fertilization measures are important in maintaining and improving soil fertility and promoting maize crop growth. Research on fertilization practices in maize fields for seed production can help to increase agricultural productivity while protecting and enhancing soil health and achieving sustainable agricultural development. To clarify the effects of different fertilization measures on soil bacterial communities in seed corn fields, 16S rRNA high-throughput sequencing technology and PICRUSt method were used to explore the soil under different fertilization measures (CK as control, effects of single application of liquid organic fertilizer (M), single application of bacterial agents (BF), and combined application of liquid organic fertilizer and bacterial agents (M + BF)) on soil bacterial community structure characteristics and ecological functions. Proteobacteria (20.14–25.30%), Actinobacteriota (18.21–20.47%), Actinobacteriota (13.55–22.00%), and Chloroflexi (14.24–17.59%) were the dominant phyla. Bacillus, RB41, Arthrobacter, and Sphingomonas were the dominant genera. M + BF treatment significantly increased the relative abundance of Planctomycetota. The relative abundance of Bacillus and PaeniBacillus in M treatment decreased considerably, while the relative abundance of Turicibacter increased significantly. The relative abundance of Sphingomonas was reduced considerably in M and M + BF treatments. The relative abundance of Subgroup 10 decreased significantly after BF and M + BF treatments. BF treatment significantly increased the relative abundance of Skermanella. Redundancy analysis showed that alkali-hydrolyzed nitrogen (p = 0.044) was the main environmental factor affecting soil bacterial communities under different fertilizer treatments. PICRUSt function prediction results showed that metabolism was the main functional component of bacteria, accounting for 78.45–78.94%. The abundance of functional genes for terpenoid and polyketone metabolism, the endocrine system, the excretory system, and the immune system of the soil bacterial community was significantly increased under M treatment, while the abundance of functional genes for the digestive system was decreased considerably. Different fertilizer cultivation measures changed soil bacterial community composition and ecological function in maize fields. These results can provide a theoretical reference for the study of bacterial community succession characteristics in maize fields and the determination of appropriate fertilizer cultivation measures.

Pingliang City has a complex topography and diverse soil types. To realize the improvement of soil according to local conditions and the reasonable and sustainable use of soil resources, an evaluation of soil quality in Pingliang City was carried out, based on the soil distribution situation in Pingliang City, adopting a method combining fuzzy mathematics and cluster analysis of the main evaluation factors, such as soil organic matter, topsoil depth, soil erosion intensity, soil moisture regime, effective soil thickness, soil texture, soil profile structure, soil nutrient status and topographical parts, to carry out a comprehensive evaluation. A comprehensive evaluation of soil quality was conducted in seven counties under the jurisdiction of Pingliang City, and the evaluation results were compared and analyzed against the national standard, “Cultivated land quality grade”, to provide a basis for the selection of scientific soil improvement methods. The results of the arable land quality grades indicate that the quality of farmland in Pingliang City is divided into three to ten grades, and the average quality grade of farmland is 6.83, which is in the middle–lower level, and the overall grade distribution shows the characteristics of low in the middle and high in the east and west. The results of fuzzy mathematics combined with cluster analysis indicated the following trends in soil quality for the 12 soil genera: Chuan black gunny soil > yellow moist soil > sandy soil > silt soil > mulching helilu soil> loessal soil> loamy soil > slope loessal soil > arenosol > tillage leaching gray cinnamon soil > calcareous gray cinnamon soil > red clay soil. The results of the combination of fuzzy mathematics and clustering were significantly correlated with the results of the evaluation of the soil quality of arable land; the correlation coefficient was 0.884. This indicates that the method can accurately and objectively review the advantages and disadvantages of arable land soil and can be effectively applied to the evaluation of the soil quality of agricultural soils in other regions. It is a complement to the existing evaluation of the soil quality of arable land and at the same time provides a reference for the improvement of soil quality in agricultural regions.

Bacterial fertilizers, which contain beneficial soil microorganisms, are becoming more widely used as they can mitigate the problems of crop yields reduction and soil environment degradation caused by the overuse of chemical fertilizer. However, the impact of bacterial fertilizer on greenhouse grape yields and the rhizosphere soil environment has not been assessed in arid and semi-arid region of Northwest China. Thus, a 2-year field trial was conducted with five treatments: adequate water supply without bacterial fertilizer (CK); mild (W1), moderate (W2) water stress and small (F1), maximize (F2) fertilizer cross-combination, respectively. The results indicated that water stress had a negative impact on the accumulation of dissolved organic carbon (DOC), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) in the rhizosphere soil. The addition of pseudomonas fluorescent bacterial fertilizer significantly increased the content of available phosphorus (AP), DOC, MBC and MBN content. The W1F2 treatment significantly increased the activities of urease, catalase and sucrase (p < 0.05). The W1F1 and W1F2 treatments increased fungal and bacterial diversity. Bacterial community composition was closely related to soil total organic carbon (TOC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), MBC, and sucrase, while fungi community composition was significantly related to Nitrate-N (NO₃⁻-N), TN, and sucrase. Additionally, compared with CK treatment the yield and economic benefit of the W1F2 treatment increased by 35.44 and 44.04%, respectively. Therefore, W1F2 is recommended as the optimal water and fertilizer management scheme for efficient greenhouse grape production in the arid and semi-arid region of Northwest China.