Search

Your search keyword '"Rashetnia, Samira"' showing total 7 results
Start Over Author "Rashetnia, Samira"
7 results on '"Rashetnia, Samira"'

3. List of Contributors

Author

Beecham, Simon, primary, Begbie, Don, additional, Beza, Beau B., additional, Bustami, Rosmina, additional, Byrne, Josh, additional, Catchlove, Rob, additional, Cilliers, Elizelle Juanee, additional, Cook, Stephen, additional, Dallas, Stewart, additional, Dandy, Graeme C., additional, Dillon, Peter, additional, Di Matteo, Michael, additional, Dobbie, Meredith, additional, Dodson, Jago, additional, Edith Rohr, Hildegard, additional, Ehrenfried, Lisa, additional, Furlong, Casey, additional, Gardner, Ted, additional, Gehrmann, Simon, additional, Goonetilleke, Ashantha, additional, Green, Melissa, additional, Hadwen, Wade, additional, Hamlyn-Harris, David, additional, Hanson, Frank, additional, Hawley, Robert J., additional, Hoban, Alan, additional, Iftekhar, Sayed, additional, Jamei, Elmira, additional, Ladson, Anthony, additional, LaGro, James, additional, Lampard, Jane-Louise, additional, Leigh, Catherine, additional, Leonard, Rosemary, additional, Lucke, Terry, additional, Ma, Yanan, additional, Maier, Holger R., additional, McAlister, Tony, additional, Morison, Peter, additional, Mullaly, Jack, additional, Myers, Baden R., additional, Neilan, Wendy, additional, Newham, Michael, additional, O'Bannon, Deborah J., additional, Pendergast, Micah, additional, Pezzaniti, David, additional, Phillips, Sam, additional, Pitt, Robert, additional, Polson, Carolyn, additional, Radcliffe, John C., additional, Rashetnia, Samira, additional, Razzaghmanesh, Mostafa, additional, Rowlands, Leon, additional, Rudolph-Cleff, Annette, additional, Schramm, Engelbert, additional, Sharma, Ashok K., additional, Sheldon, Fran, additional, Talebi, Leila, additional, Tapper, Nigel, additional, Tjandraatmadja, Grace, additional, van de Meene, Susan, additional, van Roon, Marjorie, additional, Vietz, Geoff J., additional, Walker, Christopher, additional, Walton, Andrea, additional, Ward, James, additional, Whiteoak, Kym, additional, Winker, Martina, additional, Yu, Qian, additional, Zeunert, Joshua, additional, and Zimmermann, Martin, additional

Published
2019
Full Text
View/download PDF

7. Flood Vulnerability Assessment by Applying a Fuzzy Logic Method: A Case Study from Melbourne

Author

Rashetnia, Samira

Subjects
0103 Numerical and Computational Mathematics, 0502 Environmental Science and Management, College of Science and Engineering, fuzzy systems, floods, FVI, flood vulnerability index, modelling
Abstract

Flood is known as the most common natural destructive phenomenon, which can cause severe physical, social and economic damages and losses in both rural and urban regions. Flood vulnerability assessment is essential to identify high risk areas and develop cost-effective flood mitigation and/or adaptation strategies, particularly for urban areas. In the recent past, vulnerability of floods has been assessed using vulnerability indicators consisting of components from various elements of flood damages, especially hydrological, social and economic components. This study presents a model based on a fuzzy rule-based system to assess the flood vulnerability of suburbs under the jurisdiction of Moreland City (MC) area in Melbourne, Australia to identify the most and the least vulnerable suburbs. The area is densely populated and consists of major waterways and creeks that increase the flood vulnerability and thus endangering the safety of people and property. Findings of the study showed that 51.6 % of the area in MC (26.21 km2 in total) falls under very low and low flood vulnerability zones. The suburbs that fall under these 2 classes include Brunswick, Pascoe Vale and Coburg. These are the areas which have the least population density and/or have higher range of social and economic resilience (based on susceptibility indicators such as presence of broadband connection, number of low income and high income households, unemployed and low educated households). The very highly populated areas are classified into high and very high vulnerability classes, which have 4.6% and 0.3% of the total area, respectively. The suburbs that fall under these 2 vulnerable classes include Brunswick West, Gowanbrae, and Pascoe Vale South. For these parts of the study area that are vulnerable to floods, this study recommends to the relevant authorities that some range of steps need to be taken to increase the social and economic resilience in order to enhance the system’s ability to cope with and recover from the negative impacts of floods.

Published
2016

Catalog

Books, media, physical & digital resources
See catalog results