Soil erosion is a growing challenge for agricultural production in Northern China. To explore the effect of variation in stubble height and mulching biomass on soil erosion caused by wind, we conducted a field experiment using a quadratic rotation combination design. Results showed that the quantity of straw mulch was the dominant factor affecting soil erosion and stubble height was of secondary importance. The soil water content in stubble and straw mulching treatments was higher than in a control treatment at 0–20 cm soil and the tendency in the amount of soil water content was opposite to the amount of wind erosion (r = −0.882, n = 10, p < 0.01). The change in soil water content observed in the stubble and mulch treatments at the 15–20 cm depth was higher than the change from 0–5 cm to 5–10 cm. Combined, the influence of a stubble height of 34 cm and mulch quantity of 4260 kg·ha⁻¹lowered the amount of erosion to 0.42 t·ha⁻¹and increased the corn yield to 11900 kg·ha⁻¹. We determined that those were the most appropriate levels of stubble height and straw mulch for crop fields in the semi-arid regions of Northern China.

Accurate estimation of crop evapotranspiration (ET_c) is crucial for effective irrigation and water management. To achieve this, support vector regression (SVR) was applied to estimate the daily ET_c of spring maize. Random forest (RF) as a data pre-processing technique was utilized to determine the optimal input variables for the SVR model. Particle swarm optimization (PSO) was employed to optimize the SVR model. This study used data obtained from field experiments conducted between 2017 and 2019, including crop coefficient and daily meteorological data. The performance of the innovative hybrid RF–SVR–PSO model was evaluated against a standalone SVR model, a back-propagation neural network (BPNN) model and a RF model, using different input meteorological variables. The ET_c values were calculated using the Penman–Monteith equation, which is recommended by the FAO, and used as a reference for the models’ estimated values. The results showed that the hybrid RF–SVR–PSO model performed better than all three standalone models for ET_c estimation of spring maize. The Nash–Sutcliffe efficiency coefficient (NSE), root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R²) ranges were 0.956–0.958, 0.275–0.282 mm d⁻¹, 0.221–0.231 mm d⁻¹ and 0.957–0.961, respectively. It is proved that the hybrid RF–SVR–PSO model is appropriate for estimation of daily spring maize ET_c in semi-arid regions.

Water and nitrogen are crucial for producing spring maize. Currently, irrigation and fertilization systems often rely on a single indicator, resulting in inefficient practices. This study aims to determine an optimal nitrogen application rate for shallow buried drip irrigation (SBDI) to balance growth characteristics, yield (Y), water use efficiency (WUE), and soil nitrogen levels. In a typical semi-arid region of Northeast China, we conducted controlled experiments from 2022 to 2023, adopting a two-factor quadratic saturation D-optimal design method to study the effects of different irrigation amounts (145.40, 271.70, 348.20, and 436.20 mm) and nitrogen fertilizer application amounts (34.80, 185.90, 277.40, and 382.80 kg·hm⁻²) on spring maize. The results indicate that increasing both irrigation and nitrogen application rates can enhance dry matter accumulation (DMA) from 15.17% to 32.70%. The impact of irrigation and fertilization on the net photosynthetic rate (Pn) of spring maize was greater for the irrigation applications than the nitrogen applications, particularly at 9:00 a.m. and 13:00 p.m. and slightly less so at 11:00 a.m. and 15:00 p.m. Concurrently, there were significant increases in total nitrogen (TN1 by 20.85% in the 0–20 cm soil layer; TN2 by 33.33% in the 20–40 cm soil layer) and alkali-hydrolyzed nitrogen (AHN1 by 14.65% at 0–20 cm; AHN2 by 28.86% at 20–40 cm). Y improved from 12.02% to 44.09%, and WUE increased from 20.08% to 140.07%. The optimal water and fertilizer management mode for spring maize SBDI in semi-arid areas was determined through comprehensive analysis using the TOPSIS entropy weight method. When the irrigation amount is 436.20 mm, and the nitrogen fertilizer application amount is 277.40 kg·hm⁻², it can significantly promote the DMA, Y, WUE, photosynthetic characteristics, and soil nitrogen content of spring maize. This study provides a theoretical basis for the practical application of SBDI water–fertilizer coupling for spring maize.

Global agricultural intensification has exacerbated soil compaction and nitrogen (N) inefficiency, thereby threatening sustainable crop production. Sub-soiling, a tillage technique that fractures subsurface layers while preserving surface structure, offers potential solutions by modifying soil physical properties and enhancing microbial-mediated N cycling. This study investigated the effects of subsoiling depth (0, 20, and 40 cm) on soil microbial communities and N transformations in a semi-arid maize system in China. The results demonstrated that subsoiling to a depth of 40 cm (D2) significantly enhanced the retention of nitrate-N and ammonium-N, which correlated with improved soil porosity and microbial activity. High-throughput 16S rDNA sequencing revealed subsoiling depth-driven reorganization of microbial communities, with D2 increasing the abundance of Proteobacteria (+11%) and ammonia-oxidizing archaea (Nitrososphaeraceae, +19.9%) while suppressing denitrifiers (nosZ gene: −41.4%). Co-occurrence networks indicated greater complexity in microbial interactions under subsoiling, driven by altered aeration and carbon redistribution. Functional gene analysis highlighted a shift from denitrification to nitrification-mineralization coupling, with D2 boosting maize yield by 9.8%. These findings elucidate how subsoiling depth modulates microbiome assembly to enhance N retention, providing a mechanistic basis for optimizing tillage practices in semi-arid agroecosystems.

Hydromulching is a new mulch product which has positive effects on soil moisture conservation and the inhibition of evaporation. However, current research on its soil moisture conservation effect mainly adopted field fixed-point observation method, rather than revealing the soil moisture conservation mechanism from the microstructure of the hydromulching. This paper applied spectrum analysis technology to observe structure and micromorphological features of hydromulching, which will be able to reveal the mechanism of soil moisture conservation. Three types of hydromulching, based on laboratory preparation, were used to analyze the mechanism of soil moisture, using the infrared spectrometer (FTIR) and environmental scanning electron microscope (ESEM). The results showed that −OH generates intermolecular hydrogen bonds between carboxymethylcellulose sodium (CMC) and polyvinyl alcohol (PVA); the hydrogen bonds were formatted between the molecules of the two components strengthening their compatibility, which increased the hydromulching's effectiveness and shaping a dense mesh structure. ESEM observation results showed that preparation 1's hydromulching coverage had good effects, while preparations 2 and 3 performed poorly. Therefore, we can conclude that hydromulching effectively cemented soil particles. Then it can generate the soil membrane structure to reduce evaporation and improve soil moisture conservation function.

The current design of irrigation and fertilization systems often depends on a single index, leading to irrational systems due to the lack of a comprehensive multi-index evaluation. The aim of this study is to optimize the irrigation and nitrogen fertilizer application levels of spring maize using the TOPSIS method, in order to achieve a balance between growth characteristics, yield, water use efficiency, and soil nitrogen content. In the typical semi-arid region of Northeast China, through precise control experiments from 2022 to 2023, we adopted a two factor quadratic saturation D-optimal design method to study the effects of different irrigation amounts (145.40, 271.70, 348.20, 436.20 mm) and nitrogen fertilizer application amounts (34.80, 185.90, 277.40, 382.80 kg·hm-2) on spring maize. Results indicate that increasing both irrigation and nitrogen application rates can enhance dry matter accumulation by 15.17% to 32.70%. The impact of irrigation and fertilization on the net photosynthetic rate (Pn) of spring maize was found to be greater for irrigation amount than nitrogen application, particularly at 9:00 am and 13:00 pm, and slightly less so at 11:00 am and 15:00 pm. Concurrently, there was a significant increase in total nitrogen (TN1 by 20.85% for 0-20 cm soil layer, TN2 by 33.33% for 20-40 cm soil layer) and alkali-hydrolyzed nitrogen (AHN1 by 14.65% for 0-20 cm, AHN2 by 28.86% for 20-40 cm). Yields improved by 12.02% to 44.09%, and water use efficiency (WUE) saw an increase ranging from 20.08% to 140.07%. The optimal water and fertilizer management mode for spring maize SBDI (shallow buried drip irrigation) in semi-arid areas was determined through comprehensive analysis using TOPSIS entropy weight method. When the irrigation amount is 436.20 mm and the nitrogen fertilizer application amount is 277.40 kg·hm-2, it can significantly promote the accumulation of dry matter, yield, water use efficiency, photosynthetic characteristics, and soil nitrogen content of spring maize. This study provides a theoretical basis for the practical application of SBDI water fertilizer coupling technology for spring maize.