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首页> 外文期刊>Journal of Hydrology >Identifiability of distributed floodplain roughness values in flood extent estimation
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Identifiability of distributed floodplain roughness values in flood extent estimation

机译:洪泛区估计中分布式洪泛区粗糙度值的可识别性

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In this paper we explore the potential for identifying roughness values for distributed land use types using a comprehensive calibration data set of the 1995 flood event in the River Meuse, including gauged levels, flood extent maps and distributed flood plain level observations. The reach studied is modelled using an integrated 1D-2D hydrodynamic model, with floodplain flow modelled in the 2D domain. Detailed information on floodplain land use types is aggregated to form one, two or five classes of floodplain roughness. Sensitivity analysis of model performance against the calibration data shows that as the number of floodplain classes increases, sensitivity to these roughness values decreases, given allocation of prior roughness values on the basis of constituent land use types and associated roughness values found from literature. Evaluating the identifiability of the roughness in these classes using the Generalised Likelihood Uncertainty Estimation (GLUE) method confirms this insensitivity. As a consequence, application of complex formulae to establish roughness values for changed floodplain land use would seem inappropriate, and evaluation of such changes within a probabilistic framework is suggested. (c) 2005 Elsevier B.V. All rights reserved.
机译:在本文中,我们探索了使用1995年默兹河洪水事件的全面校准数据集(包括测量水位,洪水范围图和分布式洪水平原水位观测值)来确定分布式土地利用类型的粗糙度值的潜力。使用集成的1D-2D水动力模型对研究范围进行建模,并在2D域中建模洪泛区流量。汇总了漫滩土地利用类型的详细信息,以形成一,二或五类漫滩平原粗糙度。对模型数据对标定数据的敏感性分析表明,随着洪泛平原类别数量的增加,在根据组成性土地利用类型和文献中发现的相关粗糙度值分配先前粗糙度值的情况下,对这些粗糙度值的敏感性降低。使用广义似然不确定度估计(GLUE)方法评估这些类别中粗糙度的可识别性,确认了这种不敏感性。结果,应用复杂公式来确定洪泛区土地利用变化的粗糙度值似乎是不合适的,并建议在概率框架内评估这种变化。 (c)2005 Elsevier B.V.保留所有权利。

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