Sisira Bandara Wanninayake, R. Nianthi, Og Dayarathne Banda
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(2003) was used for the current study, but with some modifications. Accordingly, 16 variables were selected for the risk assessment. Descriptive data analysis methods were used in the study.\n\n\nFindings\nCommunity-level flood risk assessment method was introduced. Variable index, flood risk index and flood risk map were developed for the study area. The Grama Niladari Divisions (GNDs) were grouped into five categories from very high risk to very low risk. The GNDs named Wirakumandaluwa, Thimbilla, Deduru Oya, Bangadeniya and Elivitiya were ranked as the most flood-risk GNDs, respectively.\n\n\nOriginality/value\nThis paper produces a flood risk assessment method for the local context. Flood risk in the study area was assessed based on people’s perceptions. Accordingly, the flood risk index and flood risk map for the study area were developed based on the empirical data. GNDs were ranked based on the flood risk index.\n","PeriodicalId":45983,"journal":{"name":"International Journal of Disaster Resilience in the Built Environment","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of convenient flood risk assessment method to community level: the case in the Deduru Oya basin in Sri Lanka\",\"authors\":\"Sisira Bandara Wanninayake, R. Nianthi, Og Dayarathne Banda\",\"doi\":\"10.1108/ijdrbe-07-2022-0069\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nFloods have been identified as the most frequent and threatening disaster in Sri Lanka amidst an increasing trend of natural and man-made disasters in the world. 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引用次数: 0
摘要
在世界上自然灾害和人为灾害日益增加的趋势下,洪水已被确定为斯里兰卡最频繁和最具威胁性的灾害。学科专家指出,灾害风险管理应该基于风险评估的结果,但是斯里兰卡的洪水风险管理似乎不是基于社区一级的洪水风险评估。因此,本文的目的是将社区层面的洪水风险评估方法引入斯里兰卡的当地环境。设计/方法/方法采用分层随机抽样的方法,选取Deduru Oya盆地作为研究区域,样本数为425例。本研究采用Bollin et al.(2003)引入的风险评估模型,但做了一些修改。因此,选取16个变量进行风险评估。本研究采用描述性资料分析方法。研究结果:介绍了社区级洪水风险评估方法。对研究区进行了变量指数、洪水风险指数和洪水风险图的编制。Grama Niladari分部(gds)被分为五类,从非常高的风险到非常低的风险。Wirakumandaluwa、Thimbilla、Deduru Oya、Bangadeniya和Elivitiya分别被评为洪水风险最高的地区。原创性/价值本文提出了一种适合当地环境的洪水风险评估方法。根据人们的认知对研究区域的洪水风险进行了评估。据此,在实证数据的基础上,编制了研究区洪水风险指数和洪水风险图。根据洪水风险指数对gdp进行排名。
Development of convenient flood risk assessment method to community level: the case in the Deduru Oya basin in Sri Lanka
Purpose
Floods have been identified as the most frequent and threatening disaster in Sri Lanka amidst an increasing trend of natural and man-made disasters in the world. Subject experts state that disaster risk management should be based on the results of risk assessments, but flood risk management in Sri Lanka is seemingly not based on community-level flood risk assessments. Accordingly, the purpose of this paper is to introduce a community-level flood risk assessment method to the local context of Sri Lanka.
Design/methodology/approach
The sample (n = 425) for the study was selected using the stratified random sampling method, and the Deduru Oya basin was selected as the study area. The risk assessment model introduced by Bollin et al. (2003) was used for the current study, but with some modifications. Accordingly, 16 variables were selected for the risk assessment. Descriptive data analysis methods were used in the study.
Findings
Community-level flood risk assessment method was introduced. Variable index, flood risk index and flood risk map were developed for the study area. The Grama Niladari Divisions (GNDs) were grouped into five categories from very high risk to very low risk. The GNDs named Wirakumandaluwa, Thimbilla, Deduru Oya, Bangadeniya and Elivitiya were ranked as the most flood-risk GNDs, respectively.
Originality/value
This paper produces a flood risk assessment method for the local context. Flood risk in the study area was assessed based on people’s perceptions. Accordingly, the flood risk index and flood risk map for the study area were developed based on the empirical data. GNDs were ranked based on the flood risk index.