Biochar’s benign effects on agricultural production have been demonstrated. Still, no consistent conclusions have been drawn on the impact of biochar-amended paddy fields on carbon sequestration, gas emission reduction, and efficiency enhancement in typical cropping areas in the middle Yangtze River. A field experiment using five dosages of biochar (CK, BC1.5, BC3, BC4.5, and BC6) at 0, 1.5, 3, 4.5, and 6 kg·m⁻² was conducted at the Hubei Irrigation Experiment Center Station, Jingmen City, Hubei Province, China, to investigate the effects of biochar on carbon sequestration, greenhouse gas emissions, and agricultural efficiency in paddy in the middle Yangtze River Region. This study showed that the optimal biochar dosage was 4.5 kg·m⁻² (BC4.5). Biochar significantly improved soil properties, increased rice yield by 26.4–61.4%, and enhanced water use efficiency (WUE) and economic profit (EP) by 32.0–83.7% and −8.0–48.6%, respectively. Biochar increased soil carbon sequestration (SCS) and carbon pool management index (CPMI) by 23.0–198.3% and 22.9–71.5%, respectively. Biochar also reduced greenhouse gas emission intensity (GHGI), global warming potential (GWP), and emissions of CO₂, CH₄, and N₂O. Furthermore, structural equation modeling (SEM) indicated that soil organic carbon (SOC), in addition to the “biochar” influence factor, was a key positive influence factor for SCS, CPMI, and EP. Another major positive factor for GWP was silt, and for WUE it was saturated hydraulic conductivity, while TN and SOC were the major negative variables for GHGI. In summary, biochar demonstrated outstanding carbon sequestration and emission reduction impacts while ensuring crop production growth and efficiency improvement. The results provide a research basis for safeguarding food security and mitigating climate warming in the middle Yangtze River region.

Groundwater depth is a key control on soil salinization in arid irrigation districts, but seasonal groundwater depth thresholds for different salinization risks remain poorly constrained. Here, we examined the Yichang irrigation area of the Hetao Irrigation District using groundwater depth observations and 0–60 cm soil salinity samples collected before spring irrigation and during the crop-growing season. Indicator Kriging was used to map threshold-based probability zones for groundwater depth and soil salinity in the 0–60 cm root zone; soil salinity thresholds of 2 and 3 g kg⁻¹ represented light-or-higher and moderate-or-higher salinization, respectively, and high-probability matching rates were used to identify the corresponding critical groundwater depths. Groundwater depth showed moderate spatial variability in both seasons, whereas soil salt content showed strong spatial variability. The critical groundwater depths for light and moderate salinization were 2.6 and 2.2 m before spring irrigation and 2.2 and 1.8 m during the growing season, respectively. Soil salt content in the 0–20, 20–40, 40–60 and 0–60 cm layers decreased with increasing groundwater depth, with the 0–60 cm layer well described by an exponential response function. These findings provide a spatially explicit basis for seasonal groundwater regulation, salinization risk zoning and field-scale water–salt management in arid irrigation districts.

Flooded rice paddies emit large quantities of greenhouse gases, and biochar amendment serves as a promising strategy to conserve water, sequester carbon, mitigate emissions and stabilize crop yields. Nevertheless, the DNDC (DeNitrification-DeComposition) model has no specific biochar module and fails to precisely quantify coupled water–carbon–nitrogen cycles in biochar-amended paddies. Using two-season field observations from the Jianghan Plain, this study constructs the Biochar-DNDC model by introducing biochar pH and substrate adsorption parameters into the original organic fertilizer module and coupling a double-tank exponential decay model. Five biochar application rates (0, 1.5, 3, 4.5, and 6 kg∙m⁻²; CK, BC1.5, BC3, BC4.5, BC6) were set. Combined with the 40-year historical precipitation series of the study area, five hydrological year types were classified to carry out multi-scenario simulations. The results indicated that, compared with DNDC, Biochar-DNDC improved the simulation accuracy by an average of 28.4%. In terms of RRMSE, Biochar-DNDC improved the simulation accuracy of yield, SOC, CH₄, and N₂O by 37.0%, 28.7%, 28.6%, and 42.1%, respectively. Environmental temperature, precipitation, soil bulk density, optimal rice yield, and the proportion of straw returned to the field were key sensitive factors regulating water–carbon–nitrogen fluxes. Biochar reduced irrigation water use by 6.3~28.5% while promoting the accumulation of soil carbon stocks, optimizing nitrogen-use efficiency, and suppressing greenhouse gas emissions. There was a significant interaction between rainfall regime and biochar: DOC and NH₄⁺-N were higher in wet years, while NO₃⁻-N tended to accumulate in arid conditions. Biochar weakened the positive driving effect of precipitation on net primary productivity (NPP). Rice yield, NPP, and net ecosystem exchange (NEE) first increased and then decreased with increasing biochar dosage. Overall, the optimal dosage of biochar for water conservation, carbon sequestration, yield increases, and emission reductions in paddy fields on the Jianghan Plain was 4.5 kg∙m⁻². This study develops a modeling tool for the carbon and nitrogen cycles in biochar-amended paddy fields, which can provide quantitative support for low-carbon water and fertilizer management in the rice-growing regions of the middle Yangtze River Basin.

Groundwater depth is a key control on soil salinization in arid irrigation districts, but seasonal groundwater-depth thresholds for different salinization risks remain poorly constrained. Here, we examined the Yichang irrigation area of the Hetao Irrigation District using groundwater-depth observations and 0-60 cm soil-salinity samples collected before spring irrigation and during the crop-growing season. Indicator Kriging was used to map threshold-based probability zones for groundwater depth and soil salinity, and high-probability matching rates were used to identify critical groundwater depths for light and moderate salinization. Groundwater depth showed moderate spatial variability in both seasons, whereas soil salt content showed strong spatial variability. The critical groundwater depths for light and moderate salinization were 2.6 and 2.2 m before spring irrigation, and 2.2 and 1.8 m during the growing season, respectively. Soil salt content in the 0-20, 20-40, 40-60 and 0-60 cm layers decreased with increasing groundwater depth, with the 0-60 cm layer well described by an exponential response function. These findings provide a spatially explicit basis for seasonal groundwater regulation, salinization-risk zoning and field-scale water-salt management in arid irrigation districts.

Background/Objectives: The controlled attenuation parameter (CAP) is widely used for non-invasive assessment of hepatic steatosis, but its discrimination for moderate-to-severe steatosis may be limited in patients with obesity. We developed and internally validated a model combining CAP, alanine aminotransferase (ALT), and glycated haemoglobin (HbA1c) to identify biopsy-confirmed S ≥ 2 steatosis in bariatric surgery candidates. Methods: This retrospective single-centre study included 320 bariatric surgery candidates with preoperative CAP and laboratory data and intraoperative wedge liver biopsy as the reference standard. Candidate predictors were evaluated using univariable logistic regression, least absolute shrinkage and selection operator (LASSO) screening, and multivariable logistic regression. Model performance was assessed using receiver operating characteristic analysis, paired DeLong testing, bootstrap internal validation, calibration, Brier score, and decision curve analysis. Results: S ≥ 2 steatosis was present in 182 patients (56.9%). The combined model showed higher discrimination than CAP alone (area under the curve [AUC] 0.768, 95% CI 0.717–0.819 vs. 0.671, 95% CI 0.612–0.731), with an AUC difference of 0.096 (95% CI 0.049–0.144; paired DeLong p < 0.001). At the internally derived Youden threshold, sensitivity was 53.8% and specificity was 86.2%. The combined model also showed a lower Brier score than CAP alone (0.1941 vs. 0.2234). Bootstrap internal validation yielded an optimism-corrected AUC of 0.760 and a mean absolute calibration error of 0.017. Decision curve analysis suggested modest incremental net benefit over CAP alone. Conclusions: The CAP–ALT–HbA1c model showed higher discrimination and lower overall prediction error than CAP alone. It may complement CAP as an adjunctive tool for preoperative risk stratification, but external validation and assessment of clinically appropriate decision thresholds are required before routine clinical implementation.

Biochar has recently been widely used as a soil amendment. However, the interaction effects of biochar with irrigation management on soil water leakage and water use efficiency of paddy black soil remain unclear, which seriously restricts the production potential of black soil. Therefore, the purpose of this paper was to explore the response rule of water loss and water use efficiency of black soil under the coupling effects of biochar, irrigation amounts, and irrigation methods through column experiment, field experiment, and HYDRUS-AquaCrop coupling simulation. Biochar application rates, irrigation amounts, and irrigation methods were set at five levels (B = 0, 1.5, 3, 4.5, 6 kg·m⁻²), seven levels (I = 0, 60, 120, 180, 240, 300, 360 mm), and two levels (M, conventional irrigation and drip irrigation), respectively. The results showed that B and M had a significant coupling effect on water leakage loss (p < 0.05). Single factor B promoted water loss, but B and M inhibited water loss, which helps reduce water waste and environmental pollution. Compared with a single effect, the synergistic effect of B, I, and M on water consumption (ET), yield (Y), and water use efficiency (WUE) was better, increasing Y by 18.2%–57.9% and WUE by 17.1%–34.9%. Additionally, ET, Y, and WUE were also correlated with hydrological years, and this correlation works best in dry years. The maximum of Y and WUE in wet and normal years occurred in the ‘BDI6, 0 mm’ treatment (saving water and high yield), while that in dry years occurred in the ‘BDI6, 360 mm’ treatment (a stable yield). Therefore, the interaction effects of biochar and irrigation management should be comprehensively considered in black soil agricultural production to improve the agricultural potential of black soil and ensure food security.