A stepwise approach for flood risk and vulnerability assessment for urban flood critical infrastructures

2012 ◽  
Author(s):  
Serge Lhomme ◽  
Damien Serre ◽  
Linmei Nie ◽  
Elise Balmand ◽  
Kristina Heilemann ◽  
...  
Keyword(s):  
Vulnerability Assessment ◽  
Flood Risk ◽  
Critical Infrastructures ◽  
Urban Flood ◽  
Stepwise Approach

Vulnerability assessment and interdependency analysis of critical infrastructures for climate adaptation and flood mitigation

2015 ◽  
Vol 6 (3) ◽  
pp. 313-346 ◽  
Author(s):  
Rodolfo Jr. Espada ◽  
Armando Apan ◽  
Kevin McDougall
Keyword(s):  
Vulnerability Assessment ◽  
Flood Risk ◽  
Climate Adaptation ◽  
Critical Infrastructure ◽  
Integrated Approach ◽  
System Of Systems ◽  
Flood Mitigation ◽  
Mitigation Measures ◽  
Critical Infrastructures ◽  
Content Type

Purpose – The purpose of this paper is to present a novel approach that examines the vulnerability and interdependency of critical infrastructures using the network theory in geographic information system (GIS) setting in combination with literature and government reports. Specifically, the objectives of this study were to generate the network models of critical infrastructure systems (CISs), particularly electricity, roads and sewerage networks; to characterize the CISs’ interdependencies; and to outline the climate adaptation (CA) and flood mitigation measures of CIS. Design/methodology/approach – An integrated approach was undertaken in assessing the vulnerability and interdependency of critical infrastructures. A single system model and system-of-systems model were operationalized to examine the vulnerability and interdependency of the identified critical infrastructures in GIS environment. Existing CA and flood mitigation measures from government reports were integrated in the above-mentioned findings to better understand and gain focus in the implementation of natural disaster risk reduction (DRR) policies, particularly during the 2010/2011 floods in Queensland, Australia. Findings – Using the results from the above-mentioned approach, the spatially explicit framework was developed with four key operational dimensions: conceiving the climate risk environment; understanding the critical infrastructures’ common cause and cascade failures; modeling individual infrastructure system and system-of-systems level within GIS setting; and integrating the above-mentioned results with the government reports to increase CA and resilience measures of flood-affected critical infrastructures. Research limitations/implications – While natural DRR measures include preparation, response and recovery, this study focused on flood mitigation. Temporal analysis and application to other natural disasters were also not considered in the analysis. Practical implications – By providing this information, government-owned corporations, CISs managers and other concerned stakeholders will allow to identify infrastructure assets that are highly critical, identify vulnerable infrastructures within areas of very high flood risk, examine the interdependency of critical infrastructures and the effects of cascaded failures, identify ways of reducing flood risk and extreme climate events and prioritize DRR measures and CA strategies. Originality/value – The individualist or “pigeon-hole” approach has been the common method of analyzing infrastructures’ exposure to flood hazards and tends to separately examine the risk for different types of infrastructure (e.g. electricity, water, sewerage, roads and rails and stormwater). This study introduced an integrated approach of analyzing infrastructure risk to damage and cascade failure due to flooding. Aside from introducing the integrated approach, this study operationalized GIS-based vulnerability assessment and interdependency of critical infrastructures which had been unsubstantially considered in the past analytical frameworks. The authors considered this study of high significance, considering that floodplain planning schemes often lack the consideration of critical infrastructure interdependency.

RIMurban – A generalized GPU-based model for urban pluvial flood risk modelling and forecasting

2021 ◽  
Author(s):  
Heiko Apel ◽  
Sergiy Vorogushyn ◽  
Mostafa Farrag ◽  
Nguyen Viet Dung ◽  
Melanie Karremann ◽  
...  
Keyword(s):  
Risk Management ◽  
Extreme Events ◽  
Flood Risk ◽  
Convective Precipitation ◽  
Sewer System ◽  
Urban Flood ◽  
The Core ◽  
Model Based ◽  
Management Plans ◽  
Model Setup

<p>Urban flash floods caused by heavy convective precipitation pose an increasing threat to communes world-wide due to the increasing intensity and frequency of convective precipitation caused by a warming atmosphere. Thus, flood risk management plans adapted to the current flood risk but also capable of managing future risks are of high importance. These plans necessarily need model based pluvial flood risk simulations. In an urban environment these simulations have to have a high spatial and temporal resolution in order to site-specific management solutions. Moreover, the effect of the sewer systems needs to be included to achieve realistic inundation simulations, but also to assess the effectiveness of the sewer system and its fitness to future changes in the pluvial hazard. The setup of these models, however, typically requires a large amount of input data, a high degree of modelling expertise, a long time for setting up the model setup and to finally run the simulations. Therefor most communes cannot perform this task.</p><p> In order to provide model-based pluvial urban flood hazard and finally risk assessments for a large number of communes, the model system RIM<em>urban</em> was developed. The core of the system consists of a simplified raster-based 2D hydraulic model simulating the urban surface inundation in high spatial resolution. The model is implemented on GPUs for massive parallelization. The specific urban hydrology is considered by a capacity-based simulation of the sewer system and infiltration on non-sealed surfaces, and flow routing around buildings. The model thus considers the specific urban hydrological features, but with simplified approaches. Due to these simplifications the model setup can be performed with comparatively low data requirements, which can be covered with open data in most cases. The core data required are a high-resolution DEM, a layer of showing the buildings, and a land use map.</p><p>The spatially distributed rainfall input can be derived local precipitation records, or from an analysis of weather radar records of heavy precipitation events. A catalogue of heavy rain storms all over Germany is derived based on radar observations of the past 19 years. This catalogue serves as input for pluvial risk simulations for individual communes in Germany, as well as a catalogue of possible extreme events for the current climate. Future changes in these extreme events will be estimated based on regional climate simulations of a ΔT (1.5°C, 2°C) warmer world.</p><p>RIM<em>urban</em> simulates the urban inundation caused by these events, as well as the stress on the sewer system. Based on the inundation maps the damage to residential buildings will be estimated and further developed to a pluvial urban flood risk assessment. Because of the comparatively simple model structure and low data demand, the model setup can be easily automatized and transferred to most small to medium sized communes in Europe and even beyond, if the damage estimation is modified. RIM<em>urban</em> is thus seen as a generally appölicable screening tool for urban pluvial flood risk and a starting point for adapted risk management plans.</p>

scholarly journals Estimating urban flood risk – uncertainty in design criteria

2015 ◽  
Vol 370 ◽  
pp. 3-7 ◽  
Author(s):  
M. Newby ◽  
S. W. Franks ◽  
C. J. White
Keyword(s):  
Data Analysis ◽  
Flood Risk ◽  
Rainfall Intensity ◽  
Design Criteria ◽  
Climate Change Scenarios ◽  
Urban Flood ◽  
Frequency Distributions ◽  
Rainfall Variation ◽  
Design Rainfall ◽  
Australian Rainfall

Abstract. The design of urban stormwater infrastructure is generally performed assuming that climate is static. For engineering practitioners, stormwater infrastructure is designed using a peak flow method, such as the Rational Method as outlined in the Australian Rainfall and Runoff (AR&R) guidelines and estimates of design rainfall intensities. Changes to Australian rainfall intensity design criteria have been made through updated releases of the AR&R77, AR&R87 and the recent 2013 AR&R Intensity Frequency Distributions (IFDs). The primary focus of this study is to compare the three IFD sets from 51 locations Australia wide. Since the release of the AR&R77 IFDs, the duration and number of locations for rainfall data has increased and techniques for data analysis have changed. Updated terminology coinciding with the 2013 IFD release has also resulted in a practical change to the design rainfall. For example, infrastructure that is designed for a 1 : 5 year ARI correlates with an 18.13% AEP, however for practical purposes, hydraulic guidelines have been updated with the more intuitive 20% AEP. The evaluation of design rainfall variation across Australia has indicated that the changes are dependent upon location, recurrence interval and rainfall duration. The changes to design rainfall IFDs are due to the application of differing data analysis techniques, the length and number of data sets and the change in terminology from ARI to AEP. Such changes mean that developed infrastructure has been designed to a range of different design criteria indicating the likely inadequacy of earlier developments to the current estimates of flood risk. In many cases, the under-design of infrastructure is greater than the expected impact of increased rainfall intensity under climate change scenarios.

scholarly journals Evaluating urban flood risk using hybrid method of TOPSIS and machine learning

2021 ◽  
pp. 102614
Author(s):  
Elham Rafiei Sardooi ◽  
Ali Azareh ◽  
Bahram Choubin ◽  
Amir Mosavi ◽  
John J. Clague
Keyword(s):  
Machine Learning ◽  
Hybrid Method ◽  
Flood Risk ◽  
Urban Flood ◽  
Urban Flood Risk

Conceptualization of a Critical Infrastructure Network – Model for Flood Risk Assessments

2021 ◽  
Author(s):  
Roman Schotten ◽  
Daniel Bachmann
Keyword(s):  
Risk Analysis ◽  
Flood Risk ◽  
Critical Infrastructure ◽  
Risk Mitigation ◽  
Mitigation Measures ◽  
Critical Infrastructures ◽  
Flood Exposure ◽  
Infrastructure Network ◽  
Flood Risk Analysis ◽  
De Bruijn

<p><span>In flood risk analysis it is a key principle to predetermine consequences of flooding to assets, people and infrastructures. Damages to critical infrastructures are not restricted to the flooded area. The effects of directly affected objects cascades to other infrastructures, which are not directly affected by a flood. Modelling critical infrastructure networks is one possible answer to the question ‘how to include indirect and direct impacts to critical infrastructures?’.</span></p><p>Critical infrastructures are connected in very complex networks. The modelling of those networks has been a basis for different purposes (Ouyang, 2014). Thus, it is a challenge to determine the right method to model a critical infrastructure network. For this example, a network-based and topology-based method will be applied (Pant et al., 2018). The basic model elements are points, connectors and polygons which are utilized to resemble the critical infrastructure network characteristics.</p><p>The objective of this model is to complement the state-of-the-art flood risk analysis with a quantitative analysis of critical infrastructure damages and disruptions for people and infrastructures. These results deliver an extended basis to differentiate the flood risk assessment and to derive measures for flood risk mitigation strategies. From a technical point of view, a critical infrastructure damage analysis will be integrated into the tool ProMaIDes (Bachmann, 2020), a free software for a risk-based evaluation of flood risk mitigation measures.</p><p>The data on critical infrastructure cascades and their potential linkages is scars but necessary for an actionable modelling. The CIrcle method from Deltares delivers a method for a workshop that has proven to deliver applicable datasets for identifying and connecting infrastructures on basis of cascading effects (de Bruijn et al., 2019). The data gained from CIrcle workshops will be one compound for the critical infrastructure network model.</p><p>Acknowledgment: This work is part of the BMBF-IKARIM funded project PARADes (Participatory assessment of flood related disaster prevention and development of an adapted coping system in Ghana).</p><p>Bachmann, D. (2020). ProMaIDeS - Knowledge Base. https://promaides.myjetbrains.com</p><p>de Bruijn, K. M., Maran, C., Zygnerski, M., Jurado, J., Burzel, A., Jeuken, C., & Obeysekera, J. (2019). Flood resilience of critical infrastructure: Approach and method applied to Fort Lauderdale, Florida. Water (Switzerland), 11(3). https://doi.org/10.3390/w11030517</p><p>Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering and System Safety, 121, 43–60. https://doi.org/10.1016/j.ress.2013.06.040</p><p>Pant, R., Thacker, S., Hall, J. W., Alderson, D., & Barr, S. (2018). Critical infrastructure impact assessment due to flood exposure. Journal of Flood Risk Management, 11(1), 22–33. https://doi.org/10.1111/jfr3.12288</p>

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