Harutyun Shahumyan

Exploring a spatial statistical approach to quantify flood risk perception using cognitive maps

Modern flood risk management strategies have evolved from flood resistance to a holistic approach incorporating prevention, protection and preparedness with the aim of reducing the likelihood and/or impact of flooding. This evolution has been driven by a trend of increasingly damaging and frequent flood events due to climate change. Populations at risk are required to be an active participant within modern flood risk management plans, resulting in management plan effectiveness being partially dependent on the relevant population’s flood risk perception. Thus, understanding how at-risk populations perceive their own flood risk, and how this compares to the reality of the situation, is a significant component of flood risk management. This paper compares subjective risk perception to an objective measure of risk within a specific case study area, where 305 residents were surveyed on their perception of flood risk. As part of the survey, respondents were asked to delineate the areas of the study area that they perceived would be at risk of inundation during a severe flood event. Using spatial statistical indicators, including Fuzzy Kappa comparison, it was possible to quantify the divergence between subjective and objective measures of risk extent, enabling an assessment of the ‘correctness’ of subjective perceived risk. This novel approach identified significant deviations between risk perception and objective risk measures at an individual level. The paper concludes by considering potential policy implications.

The Impact of Perceived Flood Exposure on Flood-Risk Perception: The Role of Distance

Natural hazards, such as major flood events, are occurring with increasing frequency and inflicting increasing levels of financial damages upon affected communities. The experience of such major flood events has brought about a significant change in attitudes to flood-risk management, with a shift away from built engineering solutions alone towards a more multifaceted approach. Europes experience with damaging flood episodes provided the impetus for the introduction of the European Floods Directive, requiring the establishment of flood-risk management plans at the river-basin scale. The effectiveness of such plans, focusing on prevention, protection, and preparedness, is dependent on adequate flood awareness and preparedness, and this is related to perception of flood risk. This is an important factor in the design and assessment of flood-risk management. Whilst there is a modern body of literature exploring flood perception issues, there have been few examples that explore its spatial manifestations. Previous literature has examined perceived and real distance to a hazard source (such as a river, nuclear facility, landfill, or incinerator, etc.), whereas this article advances the literature by including an objectively assessed measure of distance to a perceived flood zone, using a cognitive mapping methodology. The article finds that distance to the perceived flood zone (perceived flood exposure) is a crucial factor in determining flood-risk perception, both the cognitive and affective components. Furthermore, we find an interesting phenomenon of misperception among respondents. The article concludes by discussing the implications for flood-risk management.

Urban development scenarios and probability mapping for greater Dublin region: the MOLAND model applications

The MOLAND land use model was used in several studies to simulate possible scenarios of future settlement patterns in the Greater Dublin Region (GDR). This paper compares the results of three different research outputs with ten possible scenarios for GDR urban development. Brief descriptions of the scenarios and probability maps combining these scenarios are presented. The suggested approach of scenario analysis can be used by planners and decision makers to get an idea of the most likely development areas in the region if several scenarios are under consideration. In addition, probability maps help to find areas where the decisions could have the most influence on development patterns with minimal efforts.

Exploring the spatial dimension of community-level flood risk perception: a cognitive mapping approach

ABSTRACT Environmental perceptions are central to individuals’ behavioural interactions with the environment. Cognitive maps, portraying a spatial representation of an individual’s environmental perception, can be aggregated to gain insight into the collective environmental perception of groups and populations. This paper uses cognitive mapping techniques to examine one aspect of environmental perception, flood risk perception, within a residential population (n = 305). Flood risk perception was examined for the whole sample and six subgroup pairs. Using subgroups allowed examination of how factors previously shown to influence flood risk perception influence the cognitive map production in this population. We use a novel technique (slope analysis) to examine how the population’s perception of flood risk compares with expert assessments of flood risk, and compare the results of this novel technique with a commonly used cognitive map analysis technique (majority threshold method). Both methods identify areas where there is consensus within the population as to which areas are at risk of flooding. However, slope analysis usefully identifies areas where the population’s perception of flood risk lacks consensus, and is at odds with expert assessments of flood risk, without the loss of information inherent in the majority threshold method. Thus, this technique provides a novel approach to studies of environmental perception that can be widely applied within many fields.

Simulating the effects of climate change, economic and urban planning scenarios on urban runoff patterns of a metropolitan region

Urban development and climate change are expected to have significant effects on urban stormwater runoff. In this study, the Dynamic Urban Water Simulation Model (DUWSiM) is applied to Dublin, Ireland, to explore urban runoff patterns under varying urban growth and climate scenarios. Results show that annual urban runoff could decrease by 3.0% from climate change and monthly runoff could increase by 30% in winter and decrease by 28% in summer. Results also indicate that urban growth could increase annual runoff by up to 15%. The combined effect of climatic and land-use change generated runoff may potentially increase annual totals from between 2.9% to 21%. Monthly changes in runoff totals could increase by up to 57%. Accommodating these variations in runoff between the scenarios, flexible decentralised systems such as green roofs and pervious pavements, have a vital role in increasing the adaptability and long term sustainability of water infrastructure.

RESEARCH ARTICLE: Applying Spatial Indicators to Support a Sustainable Urban Future

Indicators can contribute to land use management, particularly in the context of sustainable urban development. Together with scenario analysis, they are key instruments in producing information for stakeholders and policy makers and aid their understanding of urban development processes. Based on such information, stakeholders and policy makers can understand better the driving forces, the current state of urban development, how their decision can influence the future trends, and what impacts their decisions can have on the urban landscape. This article presents an application of scenario modeling and indicator evaluation for sustainable land use management in the Greater Dublin Region, based on discussions with scientists, policy makers, and stakeholders in order to guarantee its relevance to practice. This research was a core contribution to the Strategic Environmental Assessment and the Habitats Directive Appropriate Assessment procedures (areas for conservation and protection) for the 2010 Regional Planning Guidelines for Dublin.

Utilizing an Urban-Regional Model (MOLAND) for Testing the Planning and Provision of Wastewater Treatment Capacity in the Dublin Region 2006–2026

Abstract Ensuring adequate provision of waste water treatment facilities in a rapidly growing urban area is a complex task. This article analyses the key legislation and planning frameworks which underpin the provision of new treatment facilities in Ireland and the extension of existing facilities as well as the mechanisms for mobilizing investment therein. Using the MOLAND model, the spatial distribution of three population projections for the Greater Dublin Region are examined and how this will impact on planned future capacity and defined catchment areas in two specific cases is discussed.

Identifying and Using Key Indicators to Determine Neighborhood Types in Different Regions

Identification of a key indicators capturing essential patterns in a region can be a cost-effective solution for neighborhood classification and targeted policy making. Yet, such a “core” set of indicators can vary from region to region. Here, we define set of indicators measuring education, housing, accessibility, and employment which can be used to classify neighborhoods. We test these indicators in two study regions: the Baltimore Metropolitan Area and the Greater Dublin Region. We apply factor analysis to distill indicators to smaller sets that capture differences in neighborhood types in terms of social, economic, and environmental dimensions. We use factors loadings in cluster analyzes to identify unique neighborhood types spatially. Comparison of the core set of indicators and clustering patterns for case study regions sheds new lights on the important factors for both regions. The proposed approach will help compare variations in neighborhood types between and within different regions internationally.

Quantitative assessments of the spatial distribution of business clusters in Ireland

This research aims to provide a robust evidence base contributing to improving the quality of policy formation from local to national level in Ireland. The distributions of businesses within key economic sectors in Ireland are explored aiming to find clustering effects occurring across the country. The density mapping and hot spot analysis approaches were applied to find statistically significant clusters of companies for specific business sectors. The research was implemented in collaboration with Dublin Regional Authority and Dublin City Council to inform key policy makers in Ireland. It assists in the assessments of the nationwide spatial distribution of economic activities adding to the overall body of evidence on business intensive regions. The results show the continued statistically proven significance of the main urban growth centres or gateways as key centres for the main business sectors in Ireland, while public policy has prioritised rebalancing economic development to other regions.

Integration of land use, land cover, transportation, and environmental impact models: Expanding scenario analysis with multiple modules

It is an expensive and time-consuming task to develop a new model. Furthermore, a single model often cannot provide answers required for complex decision making based on multiple criteria. Coupling models are often applied to make use of existing models and analyze complex policy questions. This paper provides an overview of possible model integration approaches, briefly explains the modules that were integrated in a particular application, and focuses on the integration methods applied in this research. While the initial attempt was to integrate all models as tightly as possible, the authors developed a much more agile integration approach that allows adding and replacing individual modules easily. Python wrappers were developed to loosely couple land use, land cover, transportation, and emission models developed in different environments. ArcGIS Model Builder was used to provide a graphical user interface and to present the models’ workflow. The suggested approach is especially efficient when the models are developed in different programming languages, their source codes are not available, or the licensing restrictions make other coupling approaches impractical.