Review of APSIM's soil nitrogen modelling capability for agricultural systems analyses

作者：Kirsten Verburg, Heather Pasley, J. S. Biggs, Iris Vogeler, Enli Wang, Henrike Mielenz, Val Snow, Chris Smith, Chiara Pasut, Andrea Basche, Di He, Sotirios V. Archontoulis, Donald S. Gaydon, Neil Huth, Dean Holzworth, Joanna Sharp, Rogerio Cichota, Edith N. Khaembah, Edmar Teixeira, Hamish Brown, Mark Farrell, Chelsea K. Janke, V. V. S. R. Gupta, Peter J. Thorburn · 发表于：Agricultural Systems · 年份：2024 · DOI：10.1016/j.agsy.2024.104213 · 被引用次数：22 · 研究领域：Soil Carbon and Nitrogen Dynamics、Wastewater Treatment and Nitrogen Removal、Crop Yield and Soil Fertility

CONTEXT Over the last 26 years, researchers globally have successfully applied the soil nitrogen (N) model in the Agricultural Production Systems sIMulator (APSIM) to simulate N cycling and its effects on crop production across a range of agricultural systems and environments. As the modelling community further expands its focus to include environmental impacts of farming, it needs the model to be fit for this broader purpose. OBJECTIVE Accurately modelling N loss via different pathways demands more of the model and so, to inform and prioritise future development needs, we embarked on a detailed review of APSIM's soil N modelling capability. METHODS We conducted a comprehensive search of APSIM Soil N model verification studies and found 131 relevant publications across a wide range of systems, applications, and processes. We examined their approaches and findings, and distilled out the lessons learnt. RESULTS AND CONCLUSIONS The model-data comparisons showed strong performance across all modelled processes, despite limited changes to the core of the soil N model since its inception. The model's relatively simple conceptual pool approach to modelling carbon (C) dynamics with N cycling linked via C:N ratios, has proven remarkably versatile. However, these conceptual pools have posed challenges relating to initialisation methods and the resulting sensitivity of predictions at different time scales, e.g. long-term C trajectories vs. short-term seasonal N dynamics. Correctly predi...