Hydroinformatics and its applications at Delft Hydraulics

Abstract

Hydroinformatics concerns applications of advanced information technologies in the fields of hydro-sciences and engineering. The rapid advancement and indeed the very success of hydroinformatics is directly associated with these applications. The aim of this paper is to provide an overview of some recent advances and to illustrate the practical implications of hydroinformatics technologies. A selection of characteristic examples on various topics is presented here, demonstrating the practical use at Delft Hydraulics. Most surely they will be elaborated upon in a more detailed way in forthcoming issues of this Journal. First, a very brief historical background is outlined to characterise the emergence and evolution of hydroinformatics in hydraulic and environmental engineering practice. Recent advances in computational hydraulics are discussed next. Numerical methods are outlined whose main advantages lie in their efficiency and applicability to a very wide range of practical problems. The numerical scheme has to adhere only to the velocity Courant number and is based upon a staggered grid arrangement. Therefore the method is efficient for most free surface flows, including complex networks of rivers and canals, as well as overland flows. Examples are presented for dam break problems and inundation of polders. The latter results are presented within the setting of a Geographical Information System. In general, computational modelling can be viewed as a class of techniques very much based on, and indeed quite well described by, mathematical equations. These equations often symbolically represent underlying physical phenomena, like conservation of mass, momentum and energy. Diversification to application areas where no clear mathematical formulation may (yet) be present but where adequate data sets are available is illustrated by several practical examples. Again, using computer based technologies, various applications of so-called sub-symbolic techniques like Artificial Neural Networks (ANNs) are discussed and presented. Finally, some reflections on forthcoming developments and likely implications for engineering practice as well as education are outlined.