MO Dengting, GAO Ya, ZHU Changxin, et al. Simulation of water and nitrogen dynamics and crop growth and parameter calibration for winter wheat in North China based on AHC modelJ. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2026, 42(14): 167-177. DOI: 10.11975/j.issn.1002-6819.202511023
Citation: MO Dengting, GAO Ya, ZHU Changxin, et al. Simulation of water and nitrogen dynamics and crop growth and parameter calibration for winter wheat in North China based on AHC modelJ. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2026, 42(14): 167-177. DOI: 10.11975/j.issn.1002-6819.202511023

Simulation of water and nitrogen dynamics and crop growth and parameter calibration for winter wheat in North China based on AHC model

  • Winter wheat production in North China was characterized by low water and nitrogen use efficiency and substantial environmental losses. This study aimed to quantify coupled water and nitrogen transport and transformation within the soil–crop wheat system using an agro-hydrological model. Such insights are critical for formulating efficient irrigation and nutrient management strategies, improving resource use efficiency, and ensuring sustainable crop production. To quantify coupled water-nitrogen cycling in winter wheat fields across the North China Plain, two field experiments were carried out over the 2021—2022 and 2023—2024 winter wheat growing seasons, data from 2023—2024 was used for model calibration, and independent validation was performed using 2021—2022 observations. Field measurements included soil water content, ammonium nitrogen (NH4-N), nitrate nitrogen (NO3-N), leaf area index (LAI), aboveground dry biomass, plant height, and grain yield. These datasets were used to calibrate and validate the Agricultural Hydrological, Chemical and Crop Systems Simulator (AHC), a tool designed to simulate soil water movement, nitrogen transformation cycles, and crop growth dynamics. Site-specific parameters describing soil properties, crop traits and field management practices were incorporated into the model to accurately replicate actual field conditions accurately. Model performance was assessed using multiple statistical indicators, including mean relative error (MRE), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and coefficient of determination (R2). These metrics jointly quantified the simulation accuracy of soil water dynamics, nitrogen cycling, and crop growth. Results demonstrated that the AHC model performed well in simulating the coupled soil–plant system across both growing seasons. For simulations of soil water content and nitrogen concentrations, MRE values ranged from -8.87% to -14.22% and -1.35 to -63.39%, while RMSE values ranged from 0.03 to 0.04 cm3/cm3 and 0.45 mg/kg to 2.47 mg/kg, respectively. NSE values ranged from 0.52 to 0.72 for soil water content and from 0.82 to 0.97 for nitrogen concentration, while R2 values were 0.83 to 0.88 and 0.93 to 0.99, respectively, revealing consistency between simulated and measured data. For crop growth variables (LAI, aboveground biomass, and plant height), MRE fell within 2.33% to 12.79%, NSE ranged from 0.71 to 0.99, and R2 consistently exceeded 0.90, which verified the model’s reliable capacity to capture crop growth dynamics. Nitrogen balance analysis further identified clear seasonal variations in nitrogen transformation and loss pathways. Estimated nitrate leaching losses reached 37.67 kg/hm2 and 28.14 kg/hm2 for the two seasons, which were mainly induced by deep soil water percolation. The results showed that ammonia volatilization dominated the nitrogen losses, contributing 51.8% and 52.3% of total N losses, whereas nitrous oxide (N2O) emissions accounted for 2.5% and 6.2%. By comparation, crop nitrogen uptake accounted for 74.1% and 78.2% of total applied N, showing that plant assimilation constituted the main pathway of nitrogen recovery in the cropping system. Soil water regimes and irrigation-nitrogen fertilization schedules significantly regulated nitrogen cycling and its overall balance in farmland ecosystems. Changes in soil water content altered nitrogen dynamic, which further influence nitrogen leaching and gaseous nitrogen losses in agricultural soils. In conclusion, the AHC model exhibited satisfactory performance in simulating soil water and nitrogen dynamics and crop growth processes in winter wheat fields across the North China Plain. Furthermore, the AHC model serves as a reliable tool to support optimized irrigation and nitrogen fertilization management decisions, as it can accurately quantify water and nitrogen cycling characteristics within winter wheat farmlands of the North China Plain.
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