Process-based crop growth models, as an important analytical tool in agricultural production, face the problem of calibrating many parameters during the application process, and sensitivity analysis (SA) can quantify the effects of the model input parameters on the model output and provide an important basis for parameter calibration. In this study, we combined the good performance of the Agricultural Production Systems sIMulator Next-Generation (APSIM NG) model in simulating crop growth, soil carbon and nitrogen cycles, and soil N₂O emissions with the efficient computational efficiency of the extended Fourier amplitude test (EFAST) method. The sensitivity of the APSIM NG model to the simulation of soil N₂O emissions was systematically investigated using the EFAST method in a dry-crop wheat field in the semi-arid region of the Loess Plateau in Longzhong, China, where 28 crop cultivar parameters, 15 soil parameters, 4 meteorological parameters, and 4 field management parameters were selected. The parameters were selected based on the existing literature and the official documents of the model, and the parameter boundaries were determined based on the initial values of the APSIM NG model and the measured data and adjusted upward and downward by the standard normal distribution. In this study, parameters with a first-order sensitivity index ($S_i$) > 0.05 and a total sensitivity index ($S_{Ti}$) > 0.10 were identified as having a significant influence on the model outputs. The results of this study demonstrated that soil N₂O emission modeling in dry-crop wheat fields showed high sensitivity to the following parameters: (1) Among the crop cultivar parameters, the sensitivity from high to low was the leaf appearance rate, maximum leaf area, maximum nitrogen concentration of the grain, and thermal time from the starting grain-fill stage to end grain-fill stage. (2) Among the soil parameters, the sensitivity from high to low was a lower effective moisture limit, wilting coefficient, and ammonium nitrogen content. (3) Among the meteorological parameters, precipitation and solar radiation showed high sensitivity. (4) Among the field management parameters, the nitrogen application rate exhibited the most significant sensitivity. For this reason, we believe that by prioritizing the calibration of the most sensitive parameters through the results of the sensitivity analysis in this study, the workload of the APSIM NG model in the calibration process can be effectively reduced, which is conducive to the rapid localization and application of the model.

Water and nitrogen are the key factors restricting the productivity improvement of onion in the Hexi Oasis. Unreasonable water and fertilizer management not only increases input costs, but also causes environmental pollution of farmland soil, thereby affecting the sustainable development of agriculture. To explore the effects of the water–nitrogen interaction and optimized combination schemes on onion yield, water–nitrogen use efficiency, and economic benefits under mulched drip irrigation in the Hexi Oasis, a four-year (2020–2023) water–nitrogen coupling regulation experiment was conducted at the Yimin Irrigation Experimental Station in Minle County, Hexi Corridor. The onion was used as the test crop and three irrigation levels were established, based on reference crop evapotranspiration (ET_c): low water (W1, 70% ET_c), medium water (W2, 85% ET_c), and sufficient water (W3, 100% ET_c), as well as high nitrogen N3 (330 kg·ha⁻¹), medium nitrogen N2 (264 kg·ha⁻¹), and low nitrogen N1 (198 kg·ha⁻¹). Meanwhile, no nitrogen application N0 (0 kg·ha⁻¹) was set as the control at three irrigation levels. This study analyzed the effects of different water and nitrogen supply conditions on onion quality, yield, water–nitrogen use efficiency, and economic benefits. A water–nitrogen economic benefit coupling model was established to optimize water–nitrogen combination schemes targeting different economic objectives. The results revealed that medium-to-high water–nitrogen combinations were beneficial for improving onion quality, while excessive irrigation and nitrogen application inhibited bulb quality accumulation. Both yield and economic benefits increased with the increasing amount of irrigation, whereas excessive nitrogen application showed a diminishing yield-increasing effect, simultaneously increasing farm input costs and ultimately reducing the economic benefits. In the four-year experiment, the N3W3 treatment in 2020 achieved the highest yield, economic benefits, and net profit, reaching 136.93 t·ha⁻¹, 20,376.3 USD·ha⁻¹, and 14,320.8 USD·ha⁻¹, respectively, with no significant difference from the N2W3 treatment. From 2021 to 2023, the N2W3 treatment achieved the highest yield, economic benefits, and net profit, averaging 130.87 t·ha⁻¹, 28,449.5 USD·ha⁻¹, and 21,881.5 USD·ha⁻¹, respectively. Lower irrigation and nitrogen application rates mutually restricted the water and nitrogen utilization, resulting in low water use efficiency, irrigation water use efficiency, nitrogen partial factor productivity, and nitrogen agronomic use efficiency. The relationship between the irrigation amount, nitrogen application rate, and the economic benefits of onion fits a bivariate quadratic regression model. This model predicts that onion’s economic benefits are highly correlated with the actual economic benefits, with analysis revealing a parabolic trend in economic benefits as water and nitrogen inputs increase. By optimizing the model, it was determined that when the irrigation amount reached 100%, the ET_c and nitrogen application rate was 264 kg·ha⁻¹, and the economic benefits were close to the target range of 27,000–29,000 USD·ha⁻¹; this can be used as the optimal water and nitrogen management model and technical reference for onion in the Hexi Oasis irrigation area, which can not only ensure high yield and quality but also improve the use efficiency of water and nitrogen.

Nitrous oxide (N₂O), as one of the important greenhouse gases in the atmosphere, has a significant impact on global climate change. Its emissions are significantly regulated by land use changes, especially in ecologically fragile semi-arid areas. However, there is still a lack of systematic analysis on the key biotic and abiotic factors through which different land use patterns affect N₂O emissions. Therefore, this study focuses on four typical land use types in the Loess Plateau of central Gansu: Picea asperata (PA), Medicago sativa (MS), Abandoned land (AL), and Wheat field (WF). Static box gas chromatography was used to monitor soil N₂O flux in situ, and multidimensional analysis was conducted based on soil physicochemical properties, microbial community structure, and nitrogen cycling functional genes. Based on the observational data from the 2024 growing season (April to October), Research findings show that the cumulative emissions of N₂O from wheat fields increased significantly by 26.4%, 19.4%, and 39.8% compared to medicago sativa, abandoned land, and picea asperata, respectively. Mechanism analysis reveals that picea asperata promote nitrogen fixation and absorption in soil through higher soil water content and organic carbon content, as well as enrichment of Proteobacteria and high expression of nrfA and napA genes, thereby inhibiting N₂O production and emissions. The wheat fields, on the other hand, have significantly increased N₂O emissions due to the increased abundance of amoA_B, nxrB, and nirK functional genes and enhanced urease activity, which promote nitrification and denitrification processes. The Partial Least Squares Path Model (PLS-PM) further confirmed that nitrification functional genes are key driving factors for N₂O emissions. This study systematically reveals the microbial and biochemical pathways involved in regulating N₂O emissions through land use in semi-arid regions, providing a theoretical basis for regional nitrogen cycle management and climate mitigation.

This study conducted a systematic evaluation over two years (2023–2024) through field experiments to assess the regulatory effects of biochar on soil properties, carbon and nitrogen cycling, and CO₂ emissions under mulched drip irrigation with varying nitrogen application levels. The core findings indicate that the effects of biochar are strongly dependent on the nitrogen levels. Under reduced nitrogen conditions, biochar demonstrated a synergistic benefit: with a 15% nitrogen reduction (N2-BC), it significantly enhanced soil water retention (increasing moisture by 68.6% at the tasseling stage); with a 30% nitrogen reduction (N1-BC), it improved soil structure (bulk density decreased by 2.1%, porosity increased by 4.3%). Additionally, biochar differentially activates soil carbon and nitrogen pools: under the 30% nitrogen reduction treatment (N1-BC), soil organic carbon increased to 8.34 g kg⁻¹ during the jointing stage, while dissolved organic carbon reached 0.536 g kg⁻¹ at tasseling, and total nitrogen content rose significantly. Notably, the regulatory effect of biochar on CO₂ emissions shifted toward marked suppression as nitrogen input decreased (N1-BC), achieving a net cumulative reduction of 21.4% under deep nitrogen reduction treatment. Correlation analysis further integrated these processes, demonstrating that improvements in the soil physical structure are closely linked to enhanced carbon and nitrogen cycling. This study clarifies that in reduced-N systems, the application of biochar can synergistically achieve “carbon sequestration–nitrogen conservation–emission reduction,” providing a basis for developing green, low-C farmland production models.

Increased atmospheric nitrogen (N) deposition alters the formation and stability of soil organic carbon (SOC) in fragile ecosystems. While biochar (BC) amendment represents a promising strategy for augmenting soil carbon sequestration, its impact on the stability of the SOC pool under high N deposition remains unclear. In this study, we conducted a two-year field trial with three replicates to investigate the effects of combined N (0 and 9 g N·m⁻²·yr⁻¹) and BC (0, 20, and 40 t·ha⁻¹) addition on the stability of the SOC pool in restored grasslands on the Loess Plateau. We assessed SOC pool stability by examining the influence of soil microbial carbon utilization efficiency (CUE), metabolic constraints, and community composition on the content of particulate organic carbon (POC) and mineral-associated organic carbon (MAOC). The results indicate that in comparison to the control treatment (N0BC0), the addition of both high N (N9BC0) and BC (N0BC20 and N0BC40) significantly promoted the accumulation of POC by 15.78%, 9.87%, and 11.05%, respectively. Conversely, the content of MAOC was suppressed under the N9BC0 (−10.64%) and N0BC40 (−8.29%) treatments. However, the combination of high N and BC treatments resulted in increased levels of SOC, POC, and MAOC, while simultaneously reducing the MAOC/POC ratio, with all parameters reaching their peak under the N9BC40 treatment. Meanwhile, high N and BC additions led to differences in bacterial community structure, increased CUE, and enzyme vector angle. Notably, high N shifted the dominant factor of BC on MAOC/POC from physicochemical properties to biological factors. Microbes drive CUE to influence changes in MAOC by adapting to metabolic limitations and stoichiometric imbalances. In contrast, POC is primarily influenced by physicochemical properties. Overall, high additions of N and BC have been shown to reduce the stability of SOC by promoting the accumulation of POC. However, an addition rate of 40 t·ha⁻¹ of BC was found to be more effective in mitigating the negative impacts of high N addition on MAOC. This strategy can serve as an effective management approach for enhancing SOC sequestration in vulnerable regions of the Loess Plateau.