ABSTRACT
CONTENTS 7.1 Introduction ............................................................................................... 133
7.1.1 Background.................................................................................... 134 7.1.2 Requirement Study....................................................................... 135 7.1.3 Aims ................................................................................................ 139
7.2 Methods...................................................................................................... 140 7.2.1 Index of Social Vulnerability ...................................................... 140 7.2.2 Index of Flood Probability........................................................... 144 7.2.3 Combined Index of Flood Vulnerability................................... 146
7.3 Results......................................................................................................... 146 7.3.1 Index of Social Vulnerability ...................................................... 146 7.3.2 Index of Flood Probability........................................................... 148 7.3.3 Combined Index of Flood Vulnerability................................... 150
7.4 Discussion .................................................................................................. 151 7.4.1 Evaluation of Results ................................................................... 151 7.4.2 Interface Potential ......................................................................... 153 7.4.3 Modifiable Areal Unit Problem (MAUP).................................. 154
7.5 Conclusions................................................................................................ 155 7.5.1 Answering the Research Questions Posed ............................... 155 7.5.2 Developing the Model for Use within the Flood Industry.... 156
References ........................................................................................................... 156
Around 5 million people in 2 million properties live in flood-risk areas in England and Wales (Environment Agency, 2000). Property worth over
£200 billion and agricultural land worth approximately £7 billion are potentially at risk of flooding (HR Wallingford, 2000). The floods of Easter 1998 and autumn 2000 gave the United Kingdom an important reminder of a hazard that, though ever present, has been neglected by society in recent times. Many organizations are encouraged to deal with the problem, which is predicted to increase in frequency in the future due to climate change and continued urbanization of the floodplain (Price andMcInally, 2001). There is a rise in the philosophical approach of ‘‘living with the hazard’’ (Smith and Ward, 1998) that focuses on flood warning and emergency planning, than flood prevention. Initiatives to help communities to help themselves are therefore high on the agenda but require a clear understanding of the social variability and different needs of communities at risk. It is the high profile of the field of research that motivates this project into
establishing how geographical information systems (GIS) may be used to improve flood warning, and emergency planning and response in the United Kingdom. To determine how the technology could be best put to use with immediate effect, a requirements study has been accomplished from a literature review and interviews with the main organizations involved in flood warning, planning, and research in the United Kingdom. The conclusion of the requirement study identifies that the spatial distribution of vulnerable groups living within the floodplain is a prime target for research, and this group would benefit greatly from GIS investigation. This research attempts to bring together social-vulnerability studies and
flood-probability data with GIS technology to produce a high-resolution index of flood vulnerability (IFV). A number of applications demonstrate how the index and some of the data layers used in its creation may be used to improve the efficiency and quality of flood managers’ decision-making. During a flood emergency, planners can quickly identify different groups of people with different social needs and can thus disseminate resources appropriately. Alternatively, flood-warning education can be adapted for different communities identified by their postcode. The final index produced is a prototype tool, which requires refinement, but demonstrates how existing studies could be improved with the inclusion of GIS technology.
