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.

The development of an accurate root water-uptake model is pivotal for evaluating crop evapotranspiration; understanding the combined effect of drought and waterlogging stresses; and optimizing water use efficiency, namely, crop yield [kg/ha] per unit of ET [mm]. Existing models often lack quantitative approaches to depicting crop root water uptake in scenarios of concurrent drought and waterlogging moisture stresses. Addressing this as our objective; we modified the Feddes root water-uptake model by revising the soil water potential response threshold and by introducing a novel method to calculate root water-uptake rates under simultaneous drought and waterlogging stresses. Then, we incorporated a water stress lag effect coefficient, $\phi \left(W_s\right)$, that investigated the combined effect of historical drought and waterlogging stress events based on the assumption that the normalized influence weight of each past stress event decreases with an increase in the time interval before simulation as an exponential function of the decay rate. Further, we tested the model parameters and validated the results obtained with the modified model using data from three years (2016–2018) of rice (Oryza sativa, L) trails with pots in Bengbu, China. The modified Feddes model significantly improved precision by 9.6% on average when calculating relative transpiration rates, particularly post-stress recovery, and by 5.8% on average when simulating soil moisture fluctuations during drought periods. The root mean square error of relative transpiration was reduced by 60.8%, and soil water was reduced by 55.1%. By accounting for both the accumulated impact of past moisture stress and current moisture conditions in rice fields, the modified model will be useful in quantifying rice transpiration and rice water use efficiency in drought–waterlogging-prone areas in southern China.

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.

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.

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.