scholarly journals How normative interpretations of climate risk assessment affect local decision-making: an exploratory study at the city scale in Cork, Ireland

Author(s):  
T. K. J. McDermott ◽  
S. Surminski

Urban areas already suffer substantial losses in both economic and human terms from climate-related disasters. These losses are anticipated to grow substantially, in part as a result of the impacts of climate change. In this paper, we investigate the process of translating climate risk data into action for the city level. We apply a commonly used decision-framework as our backdrop and explore where in this process climate risk assessment and normative political judgements intersect. We use the case of flood risk management in Cork city in Ireland to investigate what is needed for translating risk assessment into action at the local city level. Evidence presented is based on focus group discussions at two stakeholder workshops, and a series of individual meetings and phone-discussions with stakeholders involved in local decision-making related to flood risk management and adaptation to climate change, in Ireland. Respondents were chosen on the basis of their expertise or involvement in the decision-making processes locally and nationally. Representatives of groups affected by flood risk and flood risk management and climate adaptation efforts were also included. The Cork example highlights that, despite ever more accurate data and an increasing range of theoretical approaches available to local decision-makers, it is the normative interpretation of this information that determines what action is taken. The use of risk assessments for decision-making is a process that requires normative decisions, such as setting ‘acceptable risk levels' and identifying ‘adequate’ protection levels, which will not succeed without broader buy-in and stakeholder participation. Identifying and embracing those normative views up-front could strengthen the urban adaptation process—this may, in fact, turn out to be the biggest advantage of climate risk assessment: it offers an opportunity to create a shared understanding of the problem and enables an informed evaluation and discussion of remedial action. This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’.

2018 ◽  
Vol 94 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Haixing Liu ◽  
Yuntao Wang ◽  
Chi Zhang ◽  
Albert S. Chen ◽  
Guangtao Fu

2012 ◽  
Vol 22 (3) ◽  
pp. 518-536 ◽  
Author(s):  
P. J. Ward ◽  
W. P. Pauw ◽  
M. W. van Buuren ◽  
M. A. Marfai

2020 ◽  
Author(s):  
B. Thanga Gurusamy ◽  
Avinash D Vasudeo ◽  
Aniruddha Dattatraya Ghare

<p><strong>Abstract: </strong>Because of the uncertainty and high cost involved, the Absolute Flood Protection has not been considered as a rational decision. Hence the trend is to replace Absolute Flood Protection strategy by Flood Risk Management Strategy. This Paper focus on the development of Multiple Criteria Decision Making (MCDM) model towards Flood Risk Management (FRM) across Godavari Lower Sub-Basin of India using GIS based methodologies for Flood Hazard Zonation in order to achieve global minimum of the Flood predicted Risk level.  Flood Hazard Zone Map for the historical flood events obtained with the use of GIS based Digital Elevation Models across the study area have been presented and used for the estimation of Hazard Risk. Uncertainty (or Control) Risk levels of each Flood estimated using various Flood Forecasting methodologies have been compared for the selected locations of the study area. Effectiveness of Passive Flood Protection Measures in the form of Flood Levees has been quantitatively analyzed for the increase in the Opportunity Risk and corresponding reduction in the Flood Hazard Risk. Various types of Multi-Objective Evolutionary Algorithms (MOEAs) have been used  to determine a Compromise solution with conflicting criteria between Hazard Risk and Opportunity (or Investment) Risk and the results were compared for each of the selected levels of Flood estimated with corresponding uncertainty. Traditional optimization method in the form of Pareto-Optimal Front have also been graphically depicted for the minimization of both Hazard Risk Objective function and Opportunity Risk Objective Function and compared with those obtained using MOEAs. Watershed wise distribution of optimized Flood Risk variation across the Sub-basin has been presented graphically for both the cases of with and without active Flood Routing Measures. <strong>Keywords:  </strong>Flood Risk Management; GIS based Flood Hazard Zonation; Multi-Criteria Decision Making; Multi-Objective Evolutionary Algorithms; Godavari Lower Sub-Basin of India;</p>


2020 ◽  
Author(s):  
Jeroen Aerts

<p>Despite billions of dollars of investments in disaster risk reduction (DRR), data over the period 1994- 2013 show natural disasters caused 1.35 million lives. Science respond with more timely and accurate information on the dynamics of risk and vulnerability of natural hazards, such as floods. This information is essential for designing and implementing effective climate change adaptation and DRR policies. However, how much do we really know about how the main agents in DRR (individuals, businesses, government, NGO) use this data? How do agents behave before, during, and after a disaster, since this can dramatically affect the impact and recovery time. Since existing risk assessment methods rarely include this critical ‘behavioral adaptation’ factor, significant progress has been made in the scientific community to address human adaptation activities (development of flood protection, reservoir operations, land management practices) in physically based risk models.</p><p>This presentation gives an historic overview of the most important developments in DRR science for flood risk. Traditional risk methods integrate vulnerability and adaptation using a ‘top- down’ scenario approach, where climate change, socio economic trends and adaptation are treated as external forcing to a physically based risk model (e.g. hydrological or storm surge model). Vulnerability research has made significant steps in identifying the relevant vulnerability indicators, but has not yet provided the necessary tools to dynamically integrate vulnerability in flood risk models.</p><p>However, recent research show novel methods to integrate human adaptive behavior with flood risk models. By integrating behavioral adaptation dynamics in Agent Based Risk Models, may lead to a more realistic characterization of the risks and improved assessment of the effectiveness of risk management strategies and investments. With these improved methods, it is also shown that in the coming decades, human behavior is an important driver to flood risk projections as compared to other drivers, such as climate change. This presentation shows how these recent innovations for flood risk assessment provides novel insight for flood risk management policies.</p>


2011 ◽  
Vol 4 (4) ◽  
pp. 339-349 ◽  
Author(s):  
M. Woodward ◽  
B. Gouldby ◽  
Z. Kapelan ◽  
S.-T. Khu ◽  
I. Townend

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