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Adjusting for Conditional Bias in Process Model Simulations of Hydrological Extremes: An Experiment Using the North Wyke Farm Platform.

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第一作者： Stelian,Curceac

第一单位： Rothamsted Research, Department of Sustainable Agriculture Sciences, Devon, United Kingdom.

作者： Stelian,Curceac ^[1] ; Peter M,Atkinson ^[2] ; Alice,Milne ^[3] ; Lianhai,Wu ^[1] ; Paul,Harris ^[1]

作者单位： Rothamsted Research, Department of Sustainable Agriculture Sciences, Devon, United Kingdom. ^[1] Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster, United Kingdom.;Geography and Environment, University of Southampton, Highfield, Southampton, United Kingdom.;State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. ^[2] Rothamsted Research, Department of Sustainable Agriculture Sciences, Harpenden, United Kingdom. ^[3]

关键词 conditional extreme model extreme learning machine grassland agriculture hybrid peak flow process-based model

DOI 10.3389/frai.2020.565859

PMID 33733212

发布时间 2025-05-30

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Frontiers in artificial intelligence

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Adjusting for Conditional Bias in Process Model Simulations of Hydrological Extremes: An Experiment Using the North Wyke Farm Platform.

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Adjusting for Conditional Bias in Process Model Simulations of Hydrological Extremes: An Experiment Using the North Wyke Farm Platform.

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