This study examined groundwater dynamics under saline–alkali improvement measures in a 3.66 × 10⁷ m² study area in Wuyuan County, Hetao Irrigation District, where agricultural sustainability is constrained by soil salinization. This work investigated the spatiotemporal evolution patterns and influencing factors of the groundwater environment in the context of soil salinity–alkalinity improvement, as well as the impact of irrigation on the ionic characteristics of groundwater. Furthermore, based on this analysis, a groundwater numerical model and a prediction model for the study area were developed using Visual MODFLOW Flex 6.1 software to forecast the future groundwater levels in the study area and evaluate the effects of varying irrigation scenarios on these levels. The key findings are as follows: (1) The groundwater depth stabilized at 1.63 ± 0.15 m (0.4 m increase) post-improvement measures, maintaining equilibrium under current irrigation but increasing with reductions in water supply. The groundwater salinity increased by 0.59–1.2 g/L across the crop growth period. (2) Spring irrigation raised the groundwater total dissolved solids by 15.6%, as influenced by rock weathering (38.2%), evaporation (31.5%), and cation exchange (30.3%). (3) Maintaining current irrigation systems and planting structures could stabilize groundwater levels at 1.60–1.65 m over the next decade, confirming the sustainable hydrological effects of soil improvement measures. Reducing irrigation to 80% of the current water supply of the Yellow River enables groundwater level stabilization (2.05 ± 0.12 m burial depth) within 5–7 years. This approach decreases river water dependency by 20% while boosting crop water efficiency by 18.7% and reducing root zone salt stress by 32.4%.

Reliable soil moisture projections are critical for optimizing crop productivity and water savings in irrigation in arid and semi-arid regions. However, capturing their spatial and temporal variability is difficult when using individual observations, modeling, or satellite-based methods. Here, we present an integrated framework that combines satellite-derived soil moisture estimates, ground-based observations, the HYDRUS-1D vadose zone model, and the ensemble Kalman filter (EnKF) data assimilation method to improve soil moisture simulations over saline-affected farmland in the Hetao irrigation district. Vegetation effects were first removed using the water cloud model; after correction, a cubic regression using the vertical transmit/vertical receive (VV) signal retrieved surface moisture with an R² value of 0.7964 and a root mean square error (RMSE) of 0.021 cm³·cm⁻³. HYDRUS-1D, calibrated against multi-depth field data (0–80 cm), reproduced soil moisture profiles at 17 sites with RMSEs of 0.017–0.056 cm³·cm⁻³. The EnKF assimilation of satellite and ground observations further reduced the errors to 0.008–0.017 cm³·cm⁻³, with the greatest improvement in the 0–20 cm layer; the accuracy declined slightly with depth but remained superior to either data source alone. Our study improves soil moisture simulation accuracy and closes the knowledge gaps in multi-source data integration. This framework supports sustainable land management and irrigation policy in vulnerable farming regions.

This study explores biochar’s impact on soil fertility, greenhouse gas (GHG) emissions, grain yield, carbon footprint (CF), and net ecosystem carbon budget (NECB) in northwest China’s arid regions. A two-year field experiment tested three biochar rates (15, 30, and 45 t ha⁻¹) against a control. The results showed that biochar significantly reduced overall soil GHG emissions, though the highest rate increased methane emissions. The 30 t ha⁻¹ rate yielded the highest average grain production (13.9 t ha⁻¹), boosted soil organic carbon storage by 76 kg ha⁻¹, and decreased global warming potential (GWP) by 87.8 kg CO₂ ha⁻¹ and GHG emission intensity by 6.74 kg t⁻¹. Biochar also lowered the CF and enhanced the NECB, primarily through increased net primary production and improved soil fertility and crop yields. CO₂ emissions and fertilizer use were major CF contributors, but biochar reduced both the biomass-scaled and yield-scaled CFs. Overall, biochar improved crop yields, NECB, and soil carbon storage while reducing GWP, GHGI, and CF. This study recommends 30 t ha⁻¹ biochar to optimize crop production, enhance carbon balance, and mitigate climate change impacts, highlighting biochar’s potential as a sustainable soil amendment in arid ecosystems.

China is one of the countries most seriously affected by soil salinization, while the impact of salt-controlled irrigation on the relationship between soil dissolved organic matter (DOM) and microbial in farmland affected by salinization remains largely unexplored. We conducted a comprehensive survey of soil DOM and a microbial survey of Ordos’s salinized farmland in China before and after salt-controlled irrigation. Our findings reveal a reduction of 18.4 mg/L in surface soil (0–10 cm) DOC following irrigation, whereas the subsurface soil (20–40 cm) DOC increased by 20.7 mg/L. Moreover, irrigation led to an increase in the aromaticity and humification of the soil, with the salt content of the subsurface soil rising from 2.7 to 3.7 mg/g. Additionally, the total dissolved solids (TDS) in the drained water were 2463 mg/L higher than in the irrigation water (1416.3 mg/L). This suggests that the DOM and salts from the surface soil either leached into deeper layers or were lost via runoff. Furthermore, SEM analysis and a Mantel test revealed that microbial composition significantly influenced soil DOM contents, especially increased levels of Marmoricola and MND1, which are associated with decomposing organic matter and may contribute to the leaching of soil DOM in deep layers following irrigation.