High-resolution flood modeling of urban areas using MSN_Flood

• Main Authors: Michael Hartnett, Stephen Nash
• Format: Article
• Language: English
• Published: Elsevier 2017-07-01
• Series: Water Science and Engineering
• Subjects: Multi-scale nesting; Surge-fluvial flooding; Urban flooding; Multi-segmented boundary; Moving boundary
• Online Access: http://www.sciencedirect.com/science/article/pii/S1674237017300819

Although existing hydraulic models have been used to simulate and predict urban flooding, most of these models are inadequate due to the high spatial resolution required to simulate flows in urban floodplains. Nesting high-resolution subdomains within coarser-resolution models is an efficient solution for enabling simultaneous calculation of flooding due to tides, surges, and high river flows. MSN_Flood has been developed to incorporate moving boundaries around nested domains, permitting alternate flooding and drying along the boundary and in the interior of the domain. Ghost cells adjacent to open boundary cells convert open boundaries, in effect, into internal boundaries. The moving boundary may be multi-segmented and non-continuous, with recirculating flow across the boundary. When combined with a bespoke adaptive interpolation scheme, this approach facilitates a dynamic internal boundary. Based on an alternating-direction semi-implicit finite difference scheme, MSN_Flood was used to hindcast a major flood event in Cork City resulting from the combined pressures of fluvial, tidal, and storm surge processes. The results show that the model is computationally efficient, as the 2-m high-resolution nest is used only in the urban flooded region. Elsewhere, lower-resolution nests are used. The results also show that the model is highly accurate when compared with measured data. The model is capable of incorporating nested sub-domains when the nested boundary is multi-segmented and highly complex with lateral gradients of elevation and velocities. This is a major benefit when modelling urban floodplains at very high resolution.