60 research outputs found
Flood risk in urban areas: modelling, management and adaptation to climate change. A review
[Abstract:] The modelling and management of flood risk in urban areas are increasingly recognized as global challenges. The complexity of these issues is a consequence of the existence of several distinct sources of risk, including not only fluvial, tidal and coastal flooding, but also exposure to urban runoff and local drainage failure, and the various management strategies that can be proposed. The high degree of vulnerability that characterizes such areas is expected to increase in the future due to the effects of climate change, the growth of the population living in cities, and urban densification. An increasing awareness of the socio-economic losses and environmental impact of urban flooding is clearly reflected in the recent expansion of the number of studies related to the modelling and management of urban flooding, sometimes within the framework of adaptation to climate change. The goal of the current paper is to provide a general review of the recent advances in flood-risk modelling and management, while also exploring future perspectives in these fields of research
Modelling urban floods using a finite element staggered scheme with an anisotropic dual porosity model
In porosity models for urban flooding, artificial porosity is used as a statistical descriptor of the urban medium. Buildings are treated as subgrid-scale features and, even with the use of relatively coarse grids, their effects on the flow are accounted for. Porosity models are attractive for large-scale applications due to limited computational demand with respect to solving the classical Shallow Water Equations on high-resolution grids. In the last decade, effective schemes have been developed that allowed accounting for a wealth of sub-grid processes; unfortunately, they are known to suffer from over-sensitivity to mesh design in the case of anisotropic porosity fields, which are typical of urban layouts. In the present study, a dual porosity approach is implemented into a two-dimensional Finite Element numerical scheme that uses a staggered unstructured mesh. The presence of buildings is modelled using an isotropic porosity in the continuity equation, to account for the reduced water storage, and a tensor formulation for conveyance porosity in the momentum equations, to account for anisotropy and effective flow velocity. The element-by-element definition of porosities, and the use of a staggered grid in which triangular cells convey fluxes and continuity is balanced at grid nodes, allow avoiding undesired mesh-dependency. Tested against refined numerical solutions and data from a laboratory experiment, the model provided satisfactory results. Model limitations are discussed in view of applications to more complex, real urban layouts
Modelling of Floods in Urban Areas
This Special Issue publishes the latest advances and developments concerning the modelling of flooding in urban areas and contributes to our scientific understanding of the flooding processes and the appropriate evaluation of flood impacts. This issue contains contributions of novel methodologies including flood forecasting methods, data acquisition techniques, experimental research in urban drainage systems and/or sustainable drainage systems, and new numerical and simulation approaches in nine papers with contributions from over forty authors
Leveraging Crowdsourced Navigation Data In Roadway Pluvial Flash Flood Prediction
This dissertation develops and tests a new data-driven framework for short-term roadway pluvial flash flood (PFF) risk estimation at the scale of road segments using crowdsourced navigation data and a simplified physics-based PFF model. Pluvial flash flooding (PFF) is defined as localized floods caused by an overwhelmed natural or engineered drainage system. This study develops a data curation and computational framework for data collection, preprocessing, and modeling to estimate the risk of PFF at road-segment scales. A hybrid approach is also developed that couples a statistical model and a simplified physics-based simulation model in a machine learning (ML) model to rapidly predict the risk of roadway PFF using Waze alerts in real-time
City-scale hydrodynamic modelling of urban flash floods: the issues of scale and resolution
Hydrodynamic models have been widely used in urban flood modelling. Due to the prohibitive computational cost, most of urban flood simulations have been currently carried out at low spatial resolution or in small localised domains, leading to unreliable predictions. With the recent advance in high-performance computing technologies, GPU-accelerated hydrodynamic models are now capable of performing high-resolution simulations at a city scale. This paper presents a multi-GPU hydrodynamic model applied to reproduce a flood event in a 267.4Â km2 urbanised domain in Fuzhou, Fujian Province, China. At 2Â m resolution, the simulation is completed in nearly real time, demonstrating the efficiency and robustness of the model for high-resolution flood modelling. The model is used to further investigate the effects of varying spatial resolution and using localised domains on the simulation results. It is recommended that urban flood simulations should be performed at resolutions higher than 5Â m and localised simulations may introduce unacceptable numerical errors
A novel 1D-2D coupled model for hydrodynamic simulation of flows in drainage networks
Drainage network modelling is often an essential component in urban flood prediction and risk assessment. Drainage network models most commonly use different numerical procedures to handle flows in pipes and junctions. Numerous numerical schemes and models of different levels of complexity have been developed and reported to predict flows in pipes. However, calculation of the flow conditions in junctions has received much less attention and has been traditionally achieved by solving only the continuity equation. This method is easy to implement but it neglects the momentum exchange in the junctions and cannot provide sufficient boundary conditions for the pipe calculation. In this work, a novel numerical scheme based on the finite volume solution to the two-dimensional (2D) shallow water equations (SWEs) is proposed to calculate flow dynamics in junctions, which directly takes into account both mass and momentum conservation and removes the necessity of implementing complicated boundary settings for pipe calculations. This new junction simulation method is then coupled with the widely used two-component pressure approach (TPA) for the pipe flow calculation, leading to a new integrated drainage network model. The new 1D-2D coupled drainage network model is validated against an experimental and several idealised test cases to demonstrate its potential for efficient and stable simulation of flow dynamics in drainage networks.<br
Predictive Modeling of Envelope Flood Extents Using Geomorphic and Climatic-Hydrologic Catchment Characteristics
A topographic index (flood descriptor) that combines the scaling of bankfull depth with morphology was shown to describe the tendency of an area to be flooded. However, this approach depends on the quality and availability of flood maps and assumes that outcomes can be directly extrapolated and downscaled. This work attempts to relax these problems and answer two questions: (1) Can functional relationships be established between a flood descriptor and geomorphic and climatic-hydrologic catchment characteristics? (2) If so, can they be used for low-complexity predictive modeling of envelope flood extents? Linear stepwise and random forest regressions are developed based on classification outcomes of a flood descriptor, using high-resolution flood modeling results as training benchmarks, and on catchment characteristics. Elementary catchments of four river basins in Europe (Thames, Weser, Rhine, and Danube) serve as training data set, while those of the Rh\uf4ne river basin in Europe serve as testing data set. Two return periods are considered, the 10- and 10,000-year. Prediction of envelope flood extents and flood-prone areas show that both models achieve high hit rates with respect to testing benchmarks. Average values were found to be above 60% and 80% for the 10- and the 10,000-year return periods, respectively. In spite of a moderate to high false discovery rate, the critical success index value was also found to be moderate to high. It is shown that by relating classification outcomes to catchment characteristics, the prediction of envelope flood extents may be achieved for a given region, including ungauged basins
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