Novel approaches for large-scale two-dimensional hydrodynamic modelling of rivers

被引:1
|
作者
Yossef, Mohamed F. M. [1 ]
de Jong, J. S. [1 ]
Spruyt, A. [1 ]
Scholten, M. [2 ]
机构
[1] Deltares, Delft, Netherlands
[2] Rijkswaterstaat, Lelystad, Netherlands
关键词
D O I
10.1051/e3sconf/20184005040
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
For decades, the decision-making process for water management in the Netherlands makes full utilisation of state of the art models. For rivers, two-dimensional hydrodynamic models are considered essential for a wide range of questions. Every five years, there is a major model revision that includes software updates, improved physical processes, new modelling strategy, and a new calibration. 2017 marked the setup and calibration of the first river model in the sixth generation of these models. In this paper, we discuss the most recent developments in two-dimensional hydrodynamic modelling of rivers. We give an overview of the process followed to agree on the functional design of the model and address the use of the recently developed Delft3D Flexible Mesh suite. We address, in some details: i) a mesh independent approach for model setup; ii) the utilisation of a new calibration technique, which is automated using data assimilation and includes spatial and discharge dependencies; and iii) the use of a novel operational module to control hydraulic structures. The first river model within the 6th generation of models is that of the Meuse River, where the new approaches are being successfully applied. In conclusion: the mesh independent modelling approach offers great flexibility and facilitates that the same data set can be used for multiple versions of the model (e.g. different grid resolution; or different model extent). The automated calibration approach makes it possible to utilise a comprehensive calibration data set for a large-scale model in a reproducible way. The increased complexity of modelling has become possible over the last decade due to the availability of large datasets and increased computational power. This paper is particularly relevant for modellers and decision makers alike.
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页数:8
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