mLDNDCv1.0: a machine learning-based surrogate of LandscapeDNDC for optimising cropping systems in Denmark
<p>Optimising Danish arable management is critical for reducing greenhouse-gas (GHG) emissions and nitrogen (N) losses while maintaining or even improving crop productivity and soil health. Process-based models such as LandscapeDNDC can simulate the effects of management on agroecosystem functioning...
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| 主要な著者: | , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Copernicus Publications
2026-07-01
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| シリーズ: | Geoscientific Model Development |
| オンライン･アクセス: | https://gmd.copernicus.org/articles/19/6335/2026/gmd-19-6335-2026.pdf |
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