Investigating Dimensions and Classification of Urban Neighbourhoods' Flood Resilience Indicators (Case study of Ahvaz Sayyahi and Eyn-e Do Neighbourhoods)

Extended Abstract

Introduction

In recent decades, population growth, urban sprawl, urban environmental change and related issues are some important issues in proper planning for urban management. One of the issues in urban management is the issue of floods and flooding due to heavy rains. Predicting the hydraulic behaviour of waterways and rivers, especially urban waterways in the face of possible floods, to control and reduce damage to existing farms, cities, buildings and facilities or under construction in their area is of particular importance. In recent decades, the increase in world population, especially in urban areas as an essential phenomenon, has created many complexities and problems in various fields. The city is significant as a breeding ground for accidents. In the last few years, the world has witnessed unforeseen natural disasters such as the Asian tsunami, Hurricane Katrina, and the Wenchuan earthquake in China. Dealing with these natural hazards is one of the main challenges for most countries. Today, cities and residential communities have been built in places exposed to natural hazards in terms of natural hazards or due to technological advances due to various human-made accidents. Not only does it cause death and their emotional suffering, but it has also damaged their local economy. In some cases, these hazards, sometimes as catastrophes, may affect the vulnerable urban population. The hazards are considered as challenges for developing countries. The vulnerability caused by these hazards is increasing globally. The impacts to the cities are severe and widespread in the physical, economic, social development, loss of life, property, resources, and overall destruction indicators.Urban flood is the volume of water outside a city's drainage capacity, leading to a series of problems and damages . Compensation for flood risks in human development areas, especially cities, imposes high costs. Urban development, especially along rivers, has increased the risk of floods in recent years The present study investigates the dimensions and classification of flood resilience indicators of Ahvaz Sayyahi and Eyn-e Do neighbourhoods

Methodology

The present research employed an applied-theoretical research design and descriptive-analytical research method. It also used survey research to collect and analyse the data. To achieve research objectives, the two institutional and economic indicators and their eight sub-indicators, i.e. knowledge of organisational performance, institutional context, institutional relations, institutional performance, the amount of damages, ability to compensate damages, ability to return to normal conditions, and disaster risk insurance were extracted. Via a purposive sampling method, 380 heads of households living in these neighbourhoods were selected, and copies of a standard questionnaire were distributed among them to be completed.

A one-sample t-test, independent t-test, and the Friedman test were employed to explore the resilience pattern trend for the classification of flood resilience indicators. To evaluate the effects of flood resilience in the study areas, regression analysis, and to weigh the healthcare, hospital, arterial roads, fire stations, construction type, neighbourhood texture type indicators and spatial data from the spatial autocorrelation method of the Weights Manager instrument in Geoda software and ArcGis software were used.

Results and discussion

The research results show a difference between the studied areas in terms of flood resilience indicators. The institutional resilience mean of Eyn-e Do neighbourhood was 79.49, and of Sayyahi neighbourhood was 84.22, indicating that the institutional resilience of Sayyahi neighbourhood was higher than that of Eyn-e Do neighbourhood. Also, according to the t-test results and based on the significance level (Sig.) less than 0.05, there is a significant difference between Sayyahi and Eyn-e Do neighbourhoods regarding the economic-institutional resilience indicator.

Conclusion

The study of spatial comparisons of resilience and priorities shows that significant parts of the two neighbourhoods' texture are in very poor and poor resilience conditions. The main parts of the two flood-prone neighbourhoods' texture are in very poor and poor flood resilience conditions. Analytical results of the study areas show that access to fire stations and crisis management centres, medical centres and hospitals, and the location of Ahvaz and especially Eyn-e Do and Sayyahi neighbourhoods necessitate the revision in urban prioritisation. Accordingly, these areas should be the priority of resilience planning.

The difference between Sayyahi and Eyn-e Do neighbourhoods in terms of the flood resilience indicator shows that the mean of economic resilience for Eyn-e Do neighbourhood is 66.67, and of Sayyahi neighbourhood is 74.56. In other words, in this study, the economic resilience rate of Sayyahi neighbourhood is higher than that of Eyn-e Do neighbourhood. The mean of institutional resilience of Eyn-e Do neighbourhood is 79.49, and of Sayyahi neighbourhood is 84.22, indicating that institutional resilience of Sayyahi neighbourhood is higher than that of Eyn-e Do neighbourhood. Also, according to the t-test results (Sig. less than 0.05), there is a significant difference between Sayyahi and Eyn-e Do neighbourhoods in terms of economic-institutional resilience.