考虑模型和参数不确定性的两种全球灵敏度方法的比较评估

Heng Dai, Yujiao Liu, A. Guadagnini, Songhu Yuan, Jing Yang, Ming Ye
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摘要

全局敏感性分析(GSA)是通过考虑多种不确定性来源的模型诊断来协助评估水文系统行为的关键。不确定性来源通常包括以下方面的不完整知识:(a) 模型的概念和数学表述;(b) 模型中的参数。在这种情况下,有必要进行详细调查,以便在严格的多模型背景下对模型和参数不确定性的重要性进行可靠的量化。本研究旨在评估和比较两种现代多模型 GSA 方法。这是第一种同时嵌入模型和参数不确定性来源的 GSA 方法,包括基于 Sobol 指数的方差框架(由 Dai 和 Ye 推导,2015 年,https://doi.org/10.1016/j.jhydrol.2015.06.034)和基于矩的方法(由 Dell'Oca 等人推导,2020 年,https://doi.org/10.1029/2019wr025754),多模型 AMA 指数的制定就是基于矩的方法。我们考虑在多模型背景下对这两种方法进行联合分析,对敏感性的各个方面进行评估。我们的工作以成熟的方案为基础,这些方案包括:(a)与地下水系统中的反应性迁移有关的合成环境;(b)基于实验的研究,考虑土壤中的重金属吸附。我们的研究表明,联合使用这些 GSA 方法可以提供不同但互补的信息,以评估各种方法的相互一致性,并丰富 GSA 在模型和参数不确定的情况下提供的信息内容。我们的研究结果虽然与地下水环境有关,但也可作为未来应对模型和参数不确定性的 GSA 研究的参考。
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Comparative Assessment of Two Global Sensitivity Approaches Considering Model and Parameter Uncertainty
Global Sensitivity Analysis (GSA) is key to assisting appraisal of the behavior of hydrological systems through model diagnosis considering multiple sources of uncertainty. Uncertainty sources typically comprise incomplete knowledge in (a) conceptual and mathematical formulation of models and (b) parameters embedded in the models. In this context, there is the need for detailed investigations aimed at a robust quantification of the importance of model and parameter uncertainties in a rigorous multi‐model context. This study aims at evaluating and comparing two modern multi‐model GSA methodologies. These are the first GSA approaches embedding both model and parameter uncertainty sources and encompass the variance‐based framework based on Sobol indices (as derived by Dai & Ye, 2015, https://doi.org/10.1016/j.jhydrol.2015.06.034) and the moment‐based approach upon which the formulation of the multi‐model AMA indices (as derived by Dell'Oca et al., 2020, https://doi.org/10.1029/2019wr025754) is based. We provide an assessment of various aspects of sensitivity upon considering a joint analysis of these two approaches in a multi‐model context. Our work relies on well‐established scenarios that comprise (a) a synthetic setting related to reactive transport across a groundwater system and (b) an experimentally‐based study considering heavy metal sorption onto a soil. Our study documents that the joint use of these GSA approaches can provide different while complementary information to assess mutual consistency of approaches and to enrich the information content provided by GSA under model and parameter uncertainty. While being related to groundwater settings, our results can be considered as reference for future GSA studies coping with model and parameter uncertainty.
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