Flood risk analysis using fuzzy models
Risk is a combination of the factors that determine vulnerability and exposure potential for people to a hazard. The computation of flood extents and the identification of vulnerable elements help to determine high‐risk zones due to floods in advance, which helps to take mitigatory measures effectiv...
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Veröffentlicht in: | Journal of flood risk management 2011-06, Vol.4 (2), p.128-139 |
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creator | Nandalal, H.K. Ratnayake, U.R. |
description | Risk is a combination of the factors that determine vulnerability and exposure potential for people to a hazard. The computation of flood extents and the identification of vulnerable elements help to determine high‐risk zones due to floods in advance, which helps to take mitigatory measures effectively and efficiently. This study examines how effectively the risk with respect to floods can be assessed using a fuzzy approach taking the frequently flooding Kalu‐Ganga River basin in Sri Lanka as the study area. Flood extent for a 100‐year return period rainfall was determined using Hydrologic Engineering Center's Hydrologic Modelling System (HEC‐HMS)‐ and HEC‐River Analysis System‐based models. Flood extent and mean flood depth were taken as hazard indicators while population density and dependency ratio were used as vulnerability indicators. Based on these indicators, flood risk was determined for the lowest administrative divisions within the inundated area using conventional risk assessment approaches. A methodology was proposed and applied to assess risk assuming the above indicators as fuzzy variables. Comparison of the results obtained from the two approaches indicates the proposed fuzzy‐based method, which takes uncertainty in the determination of hazard, vulnerability and risk levels into account, as providing more accurate results. |
doi_str_mv | 10.1111/j.1753-318X.2011.01097.x |
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The computation of flood extents and the identification of vulnerable elements help to determine high‐risk zones due to floods in advance, which helps to take mitigatory measures effectively and efficiently. This study examines how effectively the risk with respect to floods can be assessed using a fuzzy approach taking the frequently flooding Kalu‐Ganga River basin in Sri Lanka as the study area. Flood extent for a 100‐year return period rainfall was determined using Hydrologic Engineering Center's Hydrologic Modelling System (HEC‐HMS)‐ and HEC‐River Analysis System‐based models. Flood extent and mean flood depth were taken as hazard indicators while population density and dependency ratio were used as vulnerability indicators. Based on these indicators, flood risk was determined for the lowest administrative divisions within the inundated area using conventional risk assessment approaches. A methodology was proposed and applied to assess risk assuming the above indicators as fuzzy variables. Comparison of the results obtained from the two approaches indicates the proposed fuzzy‐based method, which takes uncertainty in the determination of hazard, vulnerability and risk levels into account, as providing more accurate results.</description><subject>Flood modelling</subject><subject>flood risk</subject><subject>Freshwater</subject><subject>fuzzy models</subject><subject>hazard</subject><subject>vulnerability</subject><issn>1753-318X</issn><issn>1753-318X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqNkEFLw0AQhRdRsFb_Q07iJXEna7KbiyDFVktVKIq9DZtkV9Jum7rbYNJfb2KkeHQuMzDve_AeIR7QANq5XgbAI-YzEIsgpAABBZrwoD4ig8Pj-M99Ss6cW1Iac8FvBuRybMoy92zhVp7cSNO4wnmVKzYfnq72-8Zbl7ky7pycaGmcuvjdQ_I2vn8dPfizl8nj6G7mZ0xE3E91yCXPNXAZ56kARmMhtQozzrNEah0lYSp5llPQNFcizVTSIkKpmMUgQ2BDctX7bm35WSm3w3XhMmWM3KiycghtwhBCTjup6KWZLZ2zSuPWFmtpm1aEXTW4xC41dqmxqwZ_qsG6RW979Kswqvk3h9Px_Kk7WwO_NyjcTtUHA2lXGHPGI3x_nmAiFvNoyiKM2Dc-anm7</recordid><startdate>201106</startdate><enddate>201106</enddate><creator>Nandalal, H.K.</creator><creator>Ratnayake, U.R.</creator><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7U1</scope><scope>7U2</scope><scope>7U6</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>H97</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>201106</creationdate><title>Flood risk analysis using fuzzy models</title><author>Nandalal, H.K. ; Ratnayake, U.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3857-bf27a7df17a6db813068afe2c77c9aff592ba7cd01f0de8bce9bf28ee6361a213</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Flood modelling</topic><topic>flood risk</topic><topic>Freshwater</topic><topic>fuzzy models</topic><topic>hazard</topic><topic>vulnerability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nandalal, H.K.</creatorcontrib><creatorcontrib>Ratnayake, U.R.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Sustainability Science Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of flood risk management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nandalal, H.K.</au><au>Ratnayake, U.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Flood risk analysis using fuzzy models</atitle><jtitle>Journal of flood risk management</jtitle><date>2011-06</date><risdate>2011</risdate><volume>4</volume><issue>2</issue><spage>128</spage><epage>139</epage><pages>128-139</pages><issn>1753-318X</issn><eissn>1753-318X</eissn><abstract>Risk is a combination of the factors that determine vulnerability and exposure potential for people to a hazard. The computation of flood extents and the identification of vulnerable elements help to determine high‐risk zones due to floods in advance, which helps to take mitigatory measures effectively and efficiently. This study examines how effectively the risk with respect to floods can be assessed using a fuzzy approach taking the frequently flooding Kalu‐Ganga River basin in Sri Lanka as the study area. Flood extent for a 100‐year return period rainfall was determined using Hydrologic Engineering Center's Hydrologic Modelling System (HEC‐HMS)‐ and HEC‐River Analysis System‐based models. Flood extent and mean flood depth were taken as hazard indicators while population density and dependency ratio were used as vulnerability indicators. Based on these indicators, flood risk was determined for the lowest administrative divisions within the inundated area using conventional risk assessment approaches. 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source | Wiley Online Library Journals Frontfile Complete; EZB-FREE-00999 freely available EZB journals |
subjects | Flood modelling flood risk Freshwater fuzzy models hazard vulnerability |
title | Flood risk analysis using fuzzy models |
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