Water resource shortages restrict the economic and societal development of China’s arid northwest. Drawing on groundwater resources for irrigation, field experiments growing seed maize (Zea mays L.) were conducted in 2013 and 2014 in the region’s Shiyang River Basin. The Soil–Water–Atmosphere–Plant (SWAP) model simulated soil water content, salinity, and water–salt transport, along with seed maize yield, in close agreement with measured values after calibration and validation. The model could accordingly serve to simulate different saline water irrigation scenarios for maize production in the study area. Waters with a salinity exceeding 6.0 mg/cm³ were not suitable for irrigation, whereas those between 3.0 and 5.0 mg/cm³ could be acceptable over a short period of time. Brackish water (0.71–2.0 mg/cm³) could be used with few restrictions. Long-term (five years) simulation of irrigation with saline water (3.0–5.0 mg/cm³) showed soil salinity to increase by over 9.5 mg/cm³ compared to initial levels, while seed maize yield declined by 25.0% compared with irrigation with brackish water (0.71 mg/cm³). An irrigation water salinity of 3.0–5.0 mg/cm³ was, therefore, not suitable for long-term irrigation in the study area. This study addressed significance issues related to saline water irrigation and serves as a guide for future agricultural production practices.

The rational development and efficient utilization of saline soils can alleviate the problem of insufficient arable land faced by agricultural production in China. A prominent problem is improving soil salt and water conditions for promoting land resources’ productivity in coastal areas. Biochar is widely used for soil improvement, as it has remarkable properties. A pot experiment was conducted to study the effects of two kinds of biochar (common biochar and acid-modified biochar) with three addition rates (2%, 4%, and 8%) on the growth, yield, photosynthetic characteristics, and quality of spinach. The results revealed that 2% and 4% common biochar increased the plant height, stem diameter, and leaf area index, effectively improving the yield of spinach and water productivity, while 8% common biochar was detrimental to the growth of spinach to some extent. Acid-modified biochar significantly benefited the growth and increased the water productivity of spinach, ensuring high yields, while also improved quality. Similarly, acid-modified biochar was less effective at high additions than at low-to-medium additions. The integrated biological response version 2 (IBRV2) values under acid-modified biochar treatments were all significantly higher than those under common biochar, but there is no significant difference among three treatments in the same biochar group, which suggested a pronounced amelioration in spinach growth within saline-alkali soil upon the incorporation of acid-modified biochar. Overall, applying acid-modified biochar at the rate of 4% exhibited enormous potential for increasing the yield and quality of spinach in saline soils.

In order to investigate the comprehensive effects of straw returning on soil physical and chemical properties, as well as cotton growth in Jiangsu, China, and to determine suitable high-yield and efficient straw returning measures, this study implemented three different straw returning methods: straw mulching (SM), straw incorporation (SI), and straw biochar (BC), with no straw returning served as a control (CT). The study aimed to assess the impact of these straw-returning measures on soil nutrients, soil moisture content, soil water storage, and deficit status, as well as primary indicators of cotton growth. The findings revealed that the total available nutrient storage under SM, SI, and BC showed an increase of 11.93%, 11.15%, and 32.39%, respectively, compared to CT. Among these methods, BC demonstrated a significant enhancement in soil organic carbon content, available phosphorus, and available potassium. Furthermore, SM exhibited a considerable increase in soil moisture content across all layers (0–40 cm), resulting in an average water storage increase of 7.42 mm compared to CT. Consequently, this effectively reduced the soil water deficit during the cotton development period. Moreover, the height of cotton plants was increased by SM, SI, and BC, with SM promoting the greatest growth rate of up to 66.87%. SM resulted in an 11.17 cm increase in cotton plant height compared to CT. Additionally, SM contributed to higher chlorophyll content in leaves at the end of the growth period. Overall, the indicators suggest that straw mulching is particularly effective in enhancing soil moisture and nutrient distribution, especially during dry years, and has a positive impact on promoting cotton development. Based on the results, straw mulching emerges as a recommended straw-returning measure for improving soil quality and maximizing cotton production in the study area.

Soil salinization is the most prevalent form of land degradation in arid, semi-arid, and coastal regions of China, posing significant challenges to local crop yield, economic development, and environmental sustainability. However, limited research exists on estimating soil salinity at different depths under vegetation cover. This study employed field-controlled soil experiments to collect multi-source remote sensing data on soil salt content (SSC) at varying depths beneath barley growth. Three types of feature variables were derived from the images and filtered using the boosting decision tree (BDT) method. In addition, four machine learning algorithms coupled with seven variable combination groups were applied to establish comprehensively soil salinity estimation models. The performances of estimation model for different crop coverage ratios and soil depth were then evaluated. The results showed that the gaussian process regression (GPR) model, based on the whole variable group for depths of 0 ~ 10 cm and 30 ~ 40 cm, outperformed other models, achieving validation R² values of 0.774 and 0.705, with RMSE values are 0.185% and 0.31%, respectively. For depths of 10 ~ 20 cm and 20 ~ 30 cm, the random forest (RF) models, incorporating spectral index and texture data, demonstrated superior accuracy with R² values of 0.666 and 0.714. The study confirms that SSC can be quantitatively estimated at various depths using the machine learning model based on multi-source remote sensing, providing a valuable approach for monitoring soil salinization.

Straw returning is an important measurement to determine the utilization of straw resources. Understanding the decomposition process and nutrient release process of straw is of great significance to the efficient utilization of straw resources and the sustainable development of the agricultural economy. In this study, the literature published in the CNKI and WOS from 2002 to 2022 was used as the data pool, and a keyword co-occurrence network map was drawn with the CiteSpace (6.2.R4) software. Visual analyses were based on the straw returning literature (1998 articles) and straw decomposition agent literature (125 articles), and the decomposition and nutrient release of straw under the action of a decomposition agent were analyzed using a straw decomposition characterization experiment. In general, returning straw can effectively improve soil fertility conditions and provide nutrients for crop growth, and the use of a straw decomposition agent can further improve soil conditions and increase crop yield. The straw decomposition characterization experiment further showed that Pseudomonas could effectively increase the decomposition rate and increase the nutrient release rate of straw. According to the above results, determining how to improve the utilization efficiency of straw resources via decomposable bacteriological agents according to local conditions will become a research hotspot in the future.