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Comparison of GA-BP and PSO-BP neural network models with initial BP model for rainfall-induced landslides risk assessment in regional scale: a case study in Sichuan,China
Authors:Zhu  Chonghao  Zhang  Jianjing  Liu  Yang  Ma  Donghua  Li  Mengfang  Xiang  Bo
Institution:1.Department of Earth and Environmental Sciences, Vanderbilt University, Nashville, USA
;2.Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, USA
;
Abstract:

Communities everywhere are being subjected to a variety of natural hazard events that can result in significant disruption to critical functions. As a result, community resilience assessment in these locations is gaining popularity as a means to help better prepare for, respond to, and recover from potentially disruptive events. The objective of this study was to identify key vulnerabilities relevant to addressing rural community resilience through conducting an initial flood impact analysis, with a specific focus on emergency response and transportation network accessibility. It included a use case involving the flooding of a rural community along the US inland waterway system. Special consideration was given to impacts experienced by at-risk populations (e.g., low economic status, youth, and elderly), given their unique vulnerabilities. An important backdrop to this work is recognition that Federal Emergency Management Agency’s Hazus, a free, publicly available tool, is commonly recommended by the agency for counties, particularly those with limited resources (i.e., rural areas), to use in developing their hazard mitigation plans. The case study results, however, demonstrate that Hazus, as currently utilized, has some serious deficiencies in that it: (1) likely underestimates the flood extent boundaries for study regions in a Level 1 analysis (which solely relies upon filling digital elevation models with precipitation), (2) may be incorrectly predicting the number and location of damaged buildings due to its reliance on out-of-date census data and the assumption that buildings are evenly distributed within a census block, and (3) is incomplete in its reporting of the accessibility of socially vulnerable populations and response capabilities of essential facilities. Therefore, if counties base their flood emergency response plans solely on Hazus results, they are likely to be underprepared for future flood events of significant magnitude. An approach in which Hazus results can be augmented with additional data and analyses is proposed to provide a more risk-informed assessment of community-level flood resilience.

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