Measuring urban resilience to flooding under climate change

Author(s):  
Roberta Padulano ◽  
Guido Rianna ◽  
Pierfranco Costabile ◽  
Carmelina Costanzo ◽  
Giuseppe Del Giudice ◽  
...  

<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>

2021 ◽  
Author(s):  
Thomas Noël ◽  
Harilaos Loukos ◽  
Dimitri Defrance

A high-resolution climate projections dataset is obtained by statistically downscaling climate projections from the CMIP6 experiment using the ERA5-Land reanalysis from the Copernicus Climate Change Service. This global dataset has a spatial resolution of 0.1°x 0.1°, comprises 5 climate models and includes two surface daily variables at monthly resolution: air temperature and precipitation. Two greenhouse gas emissions scenarios are available: one with mitigation policy (SSP126) and one without mitigation (SSP585). The downscaling method is a Quantile Mapping method (QM) called the Cumulative Distribution Function transform (CDF-t) method that was first used for wind values and is now referenced in dozens of peer-reviewed publications. The data processing includes quality control of metadata according to the climate modelling community standards and value checking for outlier detection.


10.29007/fbh3 ◽  
2018 ◽  
Author(s):  
Xiaohan Li ◽  
Patrick Willems

Urban flood pre-warning decisions made upon urban flood modeling is crucial for human and property management in urban area. However, urbanization, changing environmental conditions and climate change are challenging urban sewer models for their adaptability. While hydraulic models are capable of making accurate flood predictions, they are less flexible and more computationally expensive compared with conceptual models, which are simpler and more efficient. In the era of exploding data availability and computing techniques, data-driven models are gaining popularity in urban flood modelling, but meanwhile suffer from data sparseness. To overcome this issue, a hybrid urban flood modeling approach is proposed in this study. It incorporates a conceptual model to account for the dominant sewer hydrological processes and a logistic regression model able to predict the probabilities of flooding on a sub-urban scale. This approach is demonstrated for a highly urbanized area in Antwerp, Belgium. After comparison with a 1D/0D hydrodynamic model, its ability is shown with promising results to make probabilistic flood predictions, regardless of rainfall types or seasonal variation. In addition, the model has higher tolerance on data input quality and is fully adaptive for real time applications.


2012 ◽  
Vol 426-427 ◽  
pp. 1-16 ◽  
Author(s):  
Albert S. Chen ◽  
Barry Evans ◽  
Slobodan Djordjević ◽  
Dragan A. Savić

2018 ◽  
Vol 107 ◽  
pp. 85-95 ◽  
Author(s):  
Yuntao Wang ◽  
Albert S. Chen ◽  
Guangtao Fu ◽  
Slobodan Djordjević ◽  
Chi Zhang ◽  
...  

2010 ◽  
Vol 62 (6) ◽  
pp. 1386-1392 ◽  
Author(s):  
N. D. Sto. Domingo ◽  
A. Refsgaard ◽  
O. Mark ◽  
B. Paludan

The potential devastating effects of urban flooding have given high importance to thorough understanding and management of water movement within catchments, and computer modelling tools have found widespread use for this purpose. The state-of-the-art in urban flood modelling is the use of a coupled 1D pipe and 2D overland flow model to simultaneously represent pipe and surface flows. This method has been found to be accurate for highly paved areas, but inappropriate when land hydrology is important. The objectives of this study are to introduce a new urban flood modelling procedure that is able to reflect system interactions with hydrology, verify that the new procedure operates well, and underline the importance of considering the complete water cycle in urban flood analysis. A physically-based and distributed hydrological model was linked to a drainage network model for urban flood analysis, and the essential components and concepts used were described in this study. The procedure was then applied to a catchment previously modelled with the traditional 1D-2D procedure to determine if the new method performs similarly well. Then, results from applying the new method in a mixed-urban area were analyzed to determine how important hydrologic contributions are to flooding in the area.


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