Hydroinformatics support to flood forecasting and flood management

被引:0
|
作者
Verwey, Adri [1 ]
机构
[1] WL Delft Hydraul, Delft, Netherlands
关键词
data mining; flood forecasting; flood management; flow resistance; flood simulation modelling; hydroinformatics; Open MI; open source; proprietary software; unsteady flow modelling;
D O I
暂无
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
This keynote paper describes state-of-the-art hydroinformatics support to the water sector. A few examples are worked out in some detail, whereas for other examples the reader is guided to recent literature. The focus is on flood forecasting and flood management, with a brief description of the potential of changing technologies that support studies and facilities in this area. Examples are: new data collection methods; data mining from these extensive new sources of information, e.g. the use of genetic programming; data driven modelling techniques, e.g. artificial neural networks; decision support systems; and the provision of a hydroinformatics platform for flood forecasting. Particular attention is given to advances in numerical flood modelling. Over recent years the robustness of numerical models has increased substantially, solving for example, the flooding and drying problem of flood plains and the computation of supercritical flows. In addition, the emergence of hybrid 1D2D models is discussed with their different options for linking model components of flood prone areas.
引用
收藏
页码:23 / 36
页数:14
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