Fadong Li

Water erosion is an important pathway of soil organic carbon redistribution, particularly in semiarid environments. However, the extent to which erosion-mobilized carbon is effectively transferred through drainage networks remains poorly constrained, especially when sediment delivery, landscape connectivity, depositional sinks, and post-depositional carbon fate are considered separately. This study examined how these processes influence erosion-driven carbon redistribution in the Seridó River watershed, northeastern Brazil. Soil organic carbon was determined from field sampling and laboratory analysis, while gross erosion was estimated using the Universal Soil Loss Equation. Mobilized carbon was calculated by combining erosion rates with soil organic carbon concentrations, and potentially exported carbon was estimated using the sediment delivery ratio. Landscape connectivity was independently evaluated using the Borselli Connectivity Index, while potentially exported carbon within the contributing areas of eight monitored reservoirs was compared with observed specific sediment accumulation. Soil organic carbon contents ranged from 0.722% to 2.153%, soil erosion from 0.50 to 165.15 Mg ha−1 yr−1, and mobilized carbon reached 2.99 Mg C ha−1 yr−1. Sediment delivery ratios ranged from 0.083 to 0.541, reducing potentially exported carbon to a maximum of 0.847 Mg C ha−1 yr−1. Under complete mineralization, the maximum potential CO2 equivalent was 3.11 Mg CO2 ha−1 yr−1, whereas regional literature-informed mineralization scenario of 70% reduced this estimate to 2.17 Mg CO2 ha−1 yr−1. Connectivity showed moderate associations with mobilized carbon (ρ = 0.391) and potentially exported carbon (ρ = 0.428), but only a weak relationship with sediment delivery (ρ = 0.120). Across the eight monitored reservoirs, mean potentially exported carbon was positively associated with specific sediment accumulation (ρ = 0.762), while sediment-retention efficiencies ranged from 96% to 98%. These results show that integrating carbon mobilization, sediment delivery, landscape connectivity, depositional response, and post-depositional mineralization provides a more process-based interpretation of erosion-driven carbon redistribution in regulated semiarid watersheds.

1. Soil erosion is now an escalating and serious problem, which damages land, reduces crop yields, and deteriorates ecosystems by washing away fertile topsoil. Annually, 28 to 75 billion tons of to...

Organic amendments (OAs) are recognized as a promising strategy for enhancing soil organic carbon (SOC) stocks in agroecosystems. However, the effects of different OAs combined with chemical fertilizers (CF) on carbon (C) mineralization and how microorganisms mediate this process remain poorly understood. Here, to examine the effects of different fertilization management practices on SOC mineralization, an 85‐day incubation experiment was conducted using farmland soil from the Lhasa Valley, Tibetan Plateau. Six treatments were established: no‐fertilizer control (CK), pure urea treatment (U), and four OAs replacing 40% of urea, namely compost (CP), yak dung (YD), Qingke straw (QS), and Tibetan sheep dung (SD). We further explored relationships between SOC mineralization and soil physicochemical properties, enzyme stoichiometry, C‐cycling functional genes, and microbial community composition. Results indicated that cumulative CO ₂ emissions were significantly higher under all fertilization treatments than in the CK. Among the fertilization treatments, the highest cumulative CO ₂ emissions were observed in the QS treatment at 763.77 mg/kg, while the lowest were in the CP and U treatments at 192.36 and 166.46 mg/kg, respectively. Moreover, significant positive correlations were observed between CO ₂ emissions and soil labile organic C (LOC), extracted organic C (EOC), dissolved organic C (DOC), and microbial biomass C (MBC). Fertilization alleviated soil microbial C limitation but exacerbated phosphorus (P) limitation while increasing C‐cycling gene abundance, particularly for cbhI in the QS treatment. OAs significantly altered microbial community structure, promoting high C–preferring taxa such as Proteobacteria. Bacterial networks were more complex, stable, and sensitive to nutrient availability than fungal networks in driving SOC mineralization. Key predictors of cumulative CO ₂ emissions included C source availability (e.g., MBC, DOC, and LOC), C‐cycling functional genes (e.g., cbhI ), total P, and alkaline phosphatase activities. Under equivalent N input, CP most effectively mitigated soil CO ₂ emissions and maintained relative soil C stability, whereas QS showed greater potential to promote the turnover of labile C. Accordingly, we recommend prioritizing compost application in farmlands of the Lhasa Valley, supplementing OAs with P to alleviate nutrient limitations, and avoiding excessive application of untreated straw to minimize short‐term carbon loss. These locally tailored, microbe‐ and soil‐aligned strategies support sustainable SOC enhancement and high‐altitude agricultural.

Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth in mulched drip-irrigated cotton fields under different irrigation gradients. The SWAP crop growth model effectively simulates crop growth. However, the original SWAP model lacks a dedicated module to consider the impact of mulching on cotton field evapotranspiration and cotton dry matter mass. Therefore, in this study, the source codes of the soil moisture, evapotranspiration, and crop growth modules of the SWAP model were improved. The evapotranspiration and cotton growth data of the mulched drip-irrigated cotton fields under three irrigation treatments (W1 = 3360 m³·hm⁻², W2 = 4200 m³·hm⁻², and W3 = 5040 m³·hm⁻²) in 2023 and 2024 at the Xinjiang Modern Water-saving Irrigation Key Experimental Station of the Corps were used to verify the simulation accuracy of the improved SWAP model. Research shows the following: (1) The average relative errors of the simulated evapotranspiration, leaf area index, and dry matter weight of cotton in the improved SWAP crop growth model are all −2, and 55.01 to 69 kg·hm⁻², respectively. The accuracy of the improved model in simulating evapotranspiration and cotton growth in the mulched cotton field increased by 37.49% and 68.25%, respectively. (2) The evapotranspiration rate of cotton fields is positively correlated with the irrigation water volume and is most influenced by meteorological factors such as temperature and solar radiation. During the flowering stage, evapotranspiration accounted for 62.83%, 62.09%, 61.21%, 26.46%, 40.01%, and 38.8% of the total evapotranspiration. Therefore, the improved SWAP model can effectively simulate the evaporation and transpiration of the mulched drip-irrigated cotton fields in the Manas River Basin. This study provides a scientific basis for the digital simulation of mulched farmland in the arid regions of Northwest China.