Porosity Models for Large-Scale Urban Flood Modelling: A Review

In the context of large-scale urban flood modeling, porosity shallow-water models enable a considerable speed-up in computations while preserving information on subgrid topography. Over the last two decades, major improvements have been brought to these models, but a single generally accepted model formulation has not yet been reached. Instead, existing models vary in many respects. Some studies define porosity parameters at the scale of the computational cells or cell interfaces, while others treat the urban area as a continuum and introduce statistically defined porosity parameters. The porosity parameters are considered either isotropic or anisotropic and depth-independent or depth-dependent. The underlying flow models are based either on the full shallow-water equations or approximations thereof, with various flow resistance parameterizations. Here, we provide a review of the spectrum of porosity models developed so far for large-scale urban flood modeling.

Measuring urban resilience to flooding under climate change

<p>Flooding is one of the most challenging weather-induced risks in urban areas, due both to the typically high exposures in terms of people, buildings, and infrastructures, and to the uncertainties lying in the modelling of the involved physical processes. The modelling of urban flooding is usually performed by means of different strategies in accordance with the specific purpose of the analysis, ranging from detailed simulations, requiring large modelling and computational efforts, and typically adopted for design purposes, to simplified evaluations, particularly feasible for scenario analyses, when a large number of simulations is required perturbing one or more input parameters.</p><p>According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, intensity of precipitation events could be greatly impacted by the expected climate change primarily due to the increase in temperature, entailing an increase in the atmospheric moisture retention capability. However, the effect of climate change on the rainfall regime of local areas is not straightforward, but deeply depends on local features such as latitude, topography, distance from the coast. Over Europe, an ensemble of climate simulations coming from the application of different Regional Climate Models (RCMs) (able to perform a dynamical downscaling of General Circulation Models, GCMs, available at the global scale) is freely available within the EURO-CORDEX initiative, which is the current standard for climate change analysis over EU countries. The spatial resolution of EURO-CORDEX simulations (about 12km) is too coarse to be directly used in local impact analyses; in this case, bias corrections are usually performed using local rainfall observations, to adjust climate simulation results to the local rainfall regime. The availability of multiple climate projections coming from different Climate Simulation Chains (in other words, different RCM/GCM couplings) allows to quantify the uncertainty in climate modelling, that should be accounted for in impact analyses.</p><p>In the present work, an approach is proposed that aims to quantify the uncertainty caused by the use of an ensemble of climate projections on urban flood modelling, taking a limited area within the City of Naples (Italy) as test case. The specific purpose is that of understanding the resilience of the area with respect to any variation in rainfall intensity such as those possibly caused by climate change, building on 19 climate projections available within the EURO-CORDEX initiative and bias-corrected to make them suitable to be used for impact analyses at the local scale. The concept of resilience is expressed by a selection of indicators considered useful both in the framework of classical hazard analysis and for transport network, considered a strategic service for the test case. Urban flood modelling is undertaken by using two different numerical codes characterized by two different levels of complexity. In this way, it will be possible to draw conclusions about the computational costs that are actually needed, in terms of input data and resources, when integrating uncertainties due to climate projections in urban flood modelling for multi-purpose analyses.</p>

Building a Multimodal topographic dataset for flood hazard modelling and other geoscience applications

<p>In remote sensing, benchmark and CalVal datasets are routinely provided by learned societies and professional organisations such as the Committee for Earth Observation Satellites (CEOS), European Spatial Data Research (EuroSDR) and International Societies for Photogrammetry and Remote Sensing (ISPRS). Initiatives are often created to serve specific research needs. Many valuable datasets disappear after the conclusion of such projects even though the original data or the results of these investigations might have significant value to other scientific communities that might not have been aware of the projects. Initiatives such as FAIR data (Findable, Accessible, Interoperable, Re-usable) or the European Open Science Cloud (EOSC) aim to overcome this situation and preserve scientific data sets for wider scientific communities.</p><p>Motivated by increased public interest following the emerging effects of climate change on local weather and rainfall patterns, the field of urban flood hazard modelling has developped rapidly in recent years. New sensors and platforms are able to provide high-resolution topographic data from highly agile Earth Observation (EO) satellites to small low-altitude drones or terrestrial mobile mapping systems. The question arises as to which type of topographic information is most suitable for realistic and accurate urban flood modelling and are current methodologies able to exploit the increased level of detail contained in such data? </p><p>In the presented project, we aim to assemble a topographic research data repository to provide multimodal 3D datasets to optimise and benchmark urban flood modelling. The test site chosen is located in the South of Luxembourg in the municipality of Dudelange, which provides a typical European landscape with rolling hills, urban, agricultural but also re naturalised areas over a local stream catchment. The region has been affected by flash flooding following heavy rainfall events in the past.</p><p>The assembled datasets were derived from LiDAR and photogrammetric methodologies and consist of topographic surface representation ranging from medium resolutions DEMs with 10m GSD to highly dense point clouds derived from drone photogrammetry. The data were collected from spaceborne, traditional airborne, low-altitude drone as well as terrestrial platforms. The datasets are well documented with adequate meta information to describe their origin, currency, quality and accuracy. Raw data is provided where intellectual property rights permit the dissemination. Terrain models and point clouds are generally cleaned for blunders using standard methods and manual inspection. However, elaborate cleaning and filtering should be done by the investigators to allow the optimisation towards the requirements of their methodologies. Additional value-added terrain representations e.g. generated through data fusion approaches are also provided.</p><p>It is the intention of the project team to create a ‘living data set’ following the FAIR data principles. The expensive and comprehensive data set collected for flood hazard mapping could also be valuable to other scientific communities. Results of ongoing work should be integrated, and newly collected data layers will keep the research repository relevant and UpToDate. Sharing this well-maintained dataset amongst any interested research community will maximize its value.</p>

High-Resolution Simulation of Hydraulic Structures in a Typhoon Induced Urban Flood Event

<p>Due to climate change and rapid urbanization, urban flooding has become one of the major natural hazards threatening the safety of people and their properties and affecting the overall sustainability of cities across the globe, especially developing countries such as China. Flood modelling has now provided an indispensable tool to support urban flood risk assessment and management, and inform the planning of cities that are more resilient to flooding.</p><p>Hydraulic structures, e.g. regulation gates and pumping stations, play an important role in urban flood risk management. However, direct simulation of these hydraulic structures is not a current practice in 2D urban flood modelling. This work presents and applies a robust numerical approach to directly simulate the effects of hydraulic structures in a 2D high-resolution urban flood model. An additional computational module is developed and fully coupled to a GPU-accelerated finite volume shock-capturing urban flood model to directly simulate the highly transient flood waves through hydraulic structures. The improved flood model is applied to  reproduce a flood event induced by Typhoon “Lekima” in 2019 in Yuhuan, Zhejiang Province, China. At 3m resolution, the model is able to simulate the complete process of the flood event in nearly 3.5 times faster than real time, demonstrating the efficiency and robustness of the new fully coupled model for high-resolution food modelling in cities. Further simulations are performed to systemically investigate the effect of hydraulic structures and different operational regulations on flood dynamics and associated risks, demonstrating the importance of directly considering hydraulic structures and their operations in 2D high-resolution urban flood modelling.</p><p></p>