关于河口一维水文动力学模型的全球参数化,以埃姆斯河口为例

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-06-27 DOI:10.1016/j.envsoft.2024.106125
Keivan Kaveh, Andreas Malcherek
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引用次数: 0

摘要

水文地貌动力学模型中的每个子模型都有自己的局部校准参数,导致其应用的高度不确定性。本文提出了水文流态动力学模型的全局参数化框架,包括开发和实施共享某些共同校准参数的子模型。建议的模型减少了可调整参数的总数,同时有助于更好地理解问题的物理原理。作为案例研究,我们建立了埃姆斯河口的整体一维垂直数值模拟。该模拟能够很好地定性再现观测到的垂直速度、浓度和速度切变剖面。利用所提出的全局参数化方法,该模型仅使用埃姆斯河口的流变学测量数据进行校准,这些参数普遍适用于所有子模型,无需对其他子模型进行单独校准。模拟结果表明,模型与测量数据的一致性值得称赞,同时还减少了校准参数的数量。
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On the global parameterization of a 1DV hydromorphodynamic model of estuaries, the case of the Ems estuary

Each submodel in a hydro-morphodynamic model has its own local calibration parameters, leading to a high degree of uncertainty in their application. This paper proposes a global parameterization framework of hydro-morphodynamic models, which involves the development and implementation of submodels that share some common calibration parameters. The proposed model reduces the total number of adjustable parameters while helping to better understand the physics of the problem. As a case study, a holistic 1D vertical numerical simulation of the Ems estuary has been established. This simulation is proficient in qualitatively reproducing observed profiles of vertical velocity, concentration, and velocity shear. Using the proposed global parameterization, the model is calibrated using only measured rheological data from the Ems estuary, with these parameters universally applied to all submodels, eliminating the need for separate calibration for other submodels. The simulation demonstrates a commendable agreement with measurements while concurrently reducing the number of calibration parameters.

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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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