« Effective shallow water models for complex flood flow patterns in urban areas. Modèle effectif par une approche de Saint-Venant pour les écoulements complexes lors d’inondations urbaines »

par Shangzhi Chen, ICube équipe MECAFLU.

La soutenance aura lieu le lundi 4 juin 2018 à 10h, amphithéâtre de Dietrich, INSA Strasbourg.

Le jury est composé de :

– H. ROUX, HDR, IMF Toulouse, rapporteur
– V. GUINOT, Professeur, Université de Montpellier, rapporteur
– A. GHENAIM, Professeur, INSA Strasbourg, directeur
– A. TERFOUS, HDR, INSA Strasbourg, directeur
– P-A. GARAMBOIS, MCF, INSA Strasbourg, encadrant
Flooding represents the first natural hazard on each continent, and an unprecedented urbanization of floodplains increases the vulnerability of human societies. Improving the accuracy and robustness of flood inundation forecasts remains a key issue. The state-of-the-art in urban flood modeling suggests that no exisitng model are fully relevant for operationnal flood modeling. The research question is thus « Which modeling complexity and parameterization allows an effective representation of urban flood flows over large domains at a reasonnable computational cost in view of operational forecasts? ».
Based on a rich experimental dataset performed on the 5m × 5m ICUBE urban flood device, this phD explores the hydrodynamics of complex urban flood flows and their effective modeling in the light of various uncertainty sources.
Sensitivities of 1D and 2D shallow water (SW) models of branched urban flood flows are explored thanks to a variance decomposition method for various combinations of uncertainty sources and experimental configurations. General
sensitivity patterns of SW model for fluvial flows show that: simulated water depth variance is explained upstream by inflow discharge and roughness whereas downstream it is fully explained by downstream water depth, influence of lateral inflows propagates in both directions. High sensitivities to roughness can be very localized thus identifying the strongest hydraulic controls for orienting calibration efforts is needed. 2D sensitivities highlight: the filtering effect of branched network topography on inflow, the zone of influence of boundary conditions, the role of large streets as global flow pattern separators, the difference in roughness sensitivity patterns with respect to 1D sensitivities.
A new SW modeling approach adapted to free surface flood flows in urban areas is proposed, it takes advantage of the parcimony of 1D and is coupled to 2D zooms over more complex flow zones including confluences/defluences.
Shallow Water equations are derived and discretized using a finite volume approach: (i) A 2D approach is used at crossroads, (ii) streets are modeled with an effective 1D model accounting for recirculation zones with a porosity like
approach, (iii) a cut-cell approach is implemented to fully couple the effective 1D and 2D models. A calibration method is proposed for roughness and effective porosities based on fine experimental datasets. The modeled flow repartitions are in good agreement with observed ones.
Finally, we show that a SW model parameterized with both porosity and roughness is necessary to model free surface profiles in streets downstream of crossroads that generate 3D flow patterns – recirculation areas contracting the flow veins for instance. This phD paves the way for effective and coupled modeling of complex free surface flow patterns with fair physical meaning and performances, while reducing computational cost. The modeling framework proposed, including an original sensitivity analysis and calibration framework, could be applied to real scale flood scenarios with the ultimate goal to develop integrated flood prediction tools.

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