ArticleFrontiers in plant science2026
Simulating water-nitrogen transport for winter wheat under drought-rewatering conditions in the North China.
Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: This study integrated field experiments with the HYDRUS-2D model to investigate the effects of water-nitrogen coupling on winter wheat yield and nitrogen transformation. Materials and methods: Field trials incorporated two irrigation regimes-conventional irrigation (75%-100% of field capacity) and drought stress (50%-60% of field capacity)-alongside three nitrogen application rates (100, 200, and 300 kg/ha) applied during the jointing and filling stages. The primary objective was to evaluate the impact of drought and rewatering on the spatiotemporal distribution, transformation, and leaching of soil nitrogen, and to assess the HYDRUS-2D model's applicability in simulating non-steady-state water-nitrogen dynamics. Results: The results indicated that the HYDRUS-2D model demonstrated high accuracy in simulating the spatiotemporal dynamics of ammonium and nitrate nitrogen, with coefficients of determination R2 exceeding 0.78 and both RMSE and MAE values below 5.97. Regarding nitrogen transformation, drought during the jointing stage significantly inhibited nitrification, leading to the accumulation of ammonium nitrogen in the 0-40 cm soil layer. Upon rewatering, the rapid conversion of ammonium to nitrate nitrogen enhanced leaching into deeper soil layers (40-100 cm). Conversely, drought during the filling stage had a minimal impact on nitrogen transformation and posed a comparatively lower risk of nitrate leaching following rewatering. Finally, nitrogen application significantly influenced crop yield; moderate application (200 kg/ha) combined with adequate irrigation maximized winter wheat yield, whereas excessive application resulted in nitrogen loss and yield reduction. Discussion: These findings validate the model's predictive capability and provide theoretical insights for optimizing water and nitrogen management to enhance crop yield and mitigate environmental pollution under water resource constraints.
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