Hydrological modelling

This chapter deals primarily with hydrological flood modelling. Its history began in the mid-nineteenth century with the ‘Rational Method’ for peak flows attributed to Thomas Mulvany. Many different models have been developed, varying greatly in scope and level of detail, and are used for different purposes including science-driven testing of ideas to problem-oriented applied studies. But all represent greatly simplified analogies or visions of the real world. The chapter is concerned with non real-time flow forecasting. It follows a broad classification of models of increasing complexity into metric-, conceptual- and physics-based. The simplest are black-box, data-driven or metric models, which rely solely on observed relationships and have limited or no representation of physical processes. A generation of topographically oriented models has evolved, starting from TOPMODEL to more recent models such as TOPKAPI and Grid-to-Grid which achieve a parsimonious representation of the dominant component processes

Modeling of floods: state of the art and research challenges

International audienceThis chapter presents a state of the art review and research challenges in modeling flood propagation and floodplain inundation. The challenges for flood inundation models are directly linked to the representation of flow processes, to the formulation of theoretical physical laws and to practical considerations. First, we review the various structures of coupled spatially distributed hydrological-hydraulic models and the corresponding spatial representation of flow processes. Second, we present the theoretical basis of 1-D and 2-D Saint-Venant "shallow water" equations with overbank flow, the approximation of Saint-Venant models such as the Diffusive Wave and the Kinematic Wave models and then discuss the domains and limits of applications of each type of models. Practical considerations linked to numerical solution schemes, boundary conditions and model parameterization, calibration, validation and uncertainty analysis were also considered. Finally, the discussion addresses the research challenges for guiding the modeler, according to the principle of parsimony, in seeking the simplest modeling strategy capable of (i) a realistic representation of the physical processes, (ii) matching the performances of more complex models and (iii) providing the right answers for the right reasons