Integrating risk perceptions into flood risk management: Trinidad case study

被引:10
作者
Thongs, Gabrielle [1 ]
机构
[1] Univ West Indies, Dept Geog, St Augustine, Trinidad Tobago
关键词
Flood risk; Flood susceptibility; Risk perception; Social vulnerability; SEA-LEVEL; LANDSLIDE SUSCEPTIBILITY; GIS; VULNERABILITY; RESILIENCE; SUPPORT; RIVER;
D O I
10.1007/s11069-019-03720-2
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Flooding disasters are frequent and devastating events in Trinidad. Moderate amounts of precipitation burst riverbanks in central business districts, cities, and towns within the country. These burst riverbanks result in flooding disasters that negatively impact the economic, social, and physical environmental facets of development in this small island developing state. As the severity and frequency of flooding disasters increase, there is a greater need to increase Trinidad's risk reduction initiatives towards the flood risk. With the continued shrinking of Trinidad's economy, there is an absence of sustainable disaster reduction initiatives. Therefore, every dollar that is spent on the implementation of disaster risk reduction initiatives should be efficient, effective, and sustainable. Flood risk models play a fundamental role in the implementation of efficient, effective, and sustainable disaster risk reduction initiatives. Most flood risk models primarily utilize quantitative methods in their analysis. The goal of efficient, effective, and comprehensive disaster risk reduction initiatives, however, may not be achievable through the sole use of quantitative methods since most formulae are unable to embody the social, psychological, or cultural components of risk. A more effective approach is to broaden the analysis process by integrating qualitative indigenous knowledge with quantitative methods. This research sought to present a methodology that integrates qualitative information and quantitative geomatic methods to create a comprehensive flood assessment method. Results indicate that this integration can positively influence risk modelling since pertinent information concerning potential risks, excluded by past statistical summaries, can now be included, analysed, and modelled.
引用
收藏
页码:593 / 619
页数:27
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