Challenges in using hydrology and water quality models for assessing freshwater ecosystem services: A review
Challenges in using hydrology and water quality models for assessing freshwater ecosystem services: A review
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DOI：
10.3390/geosciences8020045
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发表时间：
2018-01
影响因子：
1.8
通讯作者：
T. Hallouin;M. Bruen;M. Christie;C. Bullock;M. Kelly-Quinn
中科院分区：
文献类型：
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作者：
T. Hallouin;M. Bruen;M. Christie;C. Bullock;M. Kelly-Quinn
淡水生态系统有助于许多生态系统服务，其中许多服务正受到人类活动的威胁，例如土地利用变化、河流形态变化和气候变化。许多学科已经研究了淡水生态系统功能的过程，从水文学到生态学，包括水质，并且可以使用多种模型来模拟其行为。这种理解对于生态系统服务的预测很有用，但模型输出必须超越生物物理变量时间序列的产生，并且必须促进对其所描述的生态系统服务所包含的信息的有益利用。本文分析了旨在量化一种或多种淡水生态系统服务的临时方法的文献。它确定了使用特定于学科的模型来预测服务所采用的策略。本综述指出，水文、水质和生态模型构成了预测生态系统条件变化的宝贵知识库，但正确有效地利用这些模型仍然存在挑战。特别是，可以更多地关注时间和空间尺度的考虑，以便为选择特定模型而不是另一个模型提供更好的理由，包括其预测的不确定性。
Freshwater ecosystems contribute to many ecosystem services, many of which are being threatened by human activities such as land use change, river morphological changes, and climate change. Many disciplines have studied the processes underlying freshwater ecosystem functions, ranging from hydrology to ecology, including water quality, and a panoply of models are available to simulate their behaviour. This understanding is useful for the prediction of ecosystem services, but the model outputs must go beyond the production of time-series of biophysical variables, and must facilitate the beneficial use of the information it contains about the ecosystem services it describes. This article analyses the literature of ad hoc approaches that aim at quantifying one or more freshwater ecosystem services. It identifies the strategies adopted to use disciplinary-specific models for the prediction of the services. This review identifies that hydrological, water quality, and ecological models form a valuable knowledge base to predict changes in ecosystem conditions, but challenges remain to make proper and fruitful use of these models. In particular, considerations of temporal and spatial scales could be given more attention in order to provide better justifications for the choice of a particular model over another, including the uncertainty in their predictions.