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The use of dynamic global vegetation models for simulating hydrology and the potential integration of satellite observations

机译:利用动态全球植被模型模拟水文学和卫星观测资料的潜在整合

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Dynamic global vegetation models (DGVMs) offer explicit representations of the land surface through time and have been used to research large-scale hydrological responses to climate change. These applications are discussed and comparisons of model inputs and formulations are made among and between DGVMs and global hydrological models. It is shown that the configuration of process representations and data inputs are what makes a given DGVM unique within the family of vegetation models. The variety of available climatic forcing datasets introduces uncertainty into simulations of hydrological variables. It is proposed that satellite-derived data, validated thoroughly, could be used to improve the quality of model evaluations and augment ground-based observations, particularly where spatial and temporal gaps are present. This would aid the reduction of model uncertainties and thus potentially enhance our understanding of global hydrological change.
机译:动态全球植被模型(DGVM)可以显示时间上的陆地表面,并已用于研究对气候变化的大规模水文响应。讨论了这些应用,并在DGVM和全球水文模型之间进行了模型输入和公式的比较。结果表明,过程表示和数据输入的配置是使给定的DGVM在植被模型族中唯一的原因。各种可用的气候强迫数据集将不确定性引入了水文变量的模拟中。建议将经过充分验证的卫星数据用于提高模型评估的质量并增强地面观测,特别是在存在时空差距的地方。这将有助于减少模型的不确定性,从而有可能增进我们对全球水文变化的了解。

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