Experimental and Numerical Study of the Effect of Model Geometric Distortion on Laboratory Modeling of Urban Flooding. Issue 10 (30th September 2021) - Li, Xuefang; Kitsikoudis, Vasileios; Mignot, Emmanuel; Archambeau, Pierre; Pirotton, Michel; Dewals, Benjamin; Erpicum, Sébastien
Abstract: Laboratory studies of urban flooding often use geometrically distorted scale models due to the multi‐scale nature of these specific flows. The possible bias induced by geometric distortion has never been thoroughly investigated with dedicated laboratory experiments. In this study, we combine experimental and computational modeling to systematically assess the influence of the distortion ratio, that is, the ratio of horizontal to vertical scale factors, on upscaled flow depths and discharge partition between streets. Three flow configurations were considered: a street junction, a street bifurcation, and a small synthetic urban district. When the distortion ratio is varied up to a value of about 5, the upscaled flow depths at the model inlets decrease monotonously and the flow discharge in the branch that conveys the largest portion of the flow is greatly enhanced. For equal flow depths at the model outlets and depending on the configuration, the distortion effect induces a variation of the upstream flow depth approximately from ∼4% to ∼17% and a change in outlet discharge partition up to 24 percentage points. For a distortion ratio above 5, both upscaled upstream flow depths and outlet discharge partition tend to stabilize asymptotically. Our study indicates the direction and magnitude of the bias induced by geometric distortion for a broad range of flow cases, which is valuable for offsetting these effects in practical laboratory studies of urban flooding. Plain Language Summary: Experimental data from laboratory scale models are a valuable complement to field data for validating computational models used for flood risk management. Geometrically distorted models (i.e., different horizontal and vertical scale factors) are widely used to downscale urban flooding in a network of streets. The possible biases induced by this geometric distortion have not been investigated extensively for this type of flows. This study combines experimental and computational modeling to systematically quantify the bias induced by geometric distortion in laboratory experiments simulating urban flooding. Key Points: We evaluated the possible bias induced by geometric distortion in the case of laboratory‐scale modeling of urban flooding In all the tests, this bias reached up to 17% for the upscaled flow depths and 24 percentage points for the outlet discharge partition For distortion ratios up to 5, this bias varies greatly, but it stabilizes asymptotically for larger distortion ratios