Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

The Study of Risk Assessment for Coastal Area Compound Disaster Under Climate Change
Lien-Kwei CHIEN, Hao-Ran SHU, Yu-Chi LI
Department of Harbor and River Engineering, National Taiwan Ocean University
Keelung City, Taiwan China

create a rating by converting data into a coordinate system and picking
points layer by layer. Because the process is cumbersome and timeconsuming, this study refers to the method developed by Wu (2017). Thismethod combines the Pareto rank analysis with the distance formula tograde by the distance between the coordinate points and the origin. And
then the Jenks natural breaks method is used to obtain the compound
hazard level of the coastal area.
In the part of vulnerability and resilience analysis, SPSS (StatisticalProduct and Service Solutions) software is used to calculate the weightof each factor by the principal component analysis method to represent
the importance of each factor. Combining the standardizing values ofeach vulnerability and resilience factor according to the weight analysis
will be results of the vulnerability grades and resilience scores of eachvillage on the coastal land in Yunlin County, Taiwan which will then be
divided into five levels by the Jenks natural breaks method. Finally, arisk matrix is used to combine the degree of hazard, vulnerability, andresilience to establish a compound disaster risk assessment model for thecoastal area under climate change.

ABSTRACTThis study considers the characteristics of climate change and time
variability, establishes two scenarios with and without consideration offlooding hazards, and sets up a compound disaster risk assessment model
to estimate the coastal compound disaster risk in 2030 and 2050 with2020 as the base period. Combined with GIS, a compound disaster risk
map is drawn to present the assessment results.

KEY WORDS: Climate Change, Coastal Area, Compound
Disaster, Risk Assessment, GIS
INTRODUCTION
Due to the high emission of greenhouse gases, global warming has
caused global climate change, and many studies have also pointed outthat the frequency and scale of various disasters also tend to increase.
From many major disaster cases, it can be found that these disasters often
do not exist and occur "individually", and different types of disasters will
combine to have compound characteristics. Such disasters are called"compound disasters."
However, most of the research on disasters took a single disaster as themain object of discussion in the past, and the research on compounddisasters still lacked a common risk assessment hierarchy. For coastal
areas, the definition of compound disasters focuses on the discussion of
sudden and intense conditions but ignores the potential disaster types
with long-term cumulative effects. Therefore, this study will consider thedisasters and compound types in coastal areas based on thecharacteristics and perspectives of compound disasters, and thenconstruct a risk assessment model of compound disasters that is suitablefor coastal areas in Taiwan.

COMPOUND HAZARD ANALYSIS
After risk identification, this study refers to Chien (2021) finally selects
stratum subsidence, coastal erosion, and flooding hazards as compound
hazard factors. After calculating and grading each hazard factor, acompound hazard level map is drawn with and without flooding hazard
in 2020, 2030, and 2050.

Stratum Subsidence Hazard
In the stratum subsidence hazard analysis, this study uses the"accumulated subsidence depth" to measure the current situation andfuture hazard degree of coastal area subsidence in Yunlin County. First,
the data are calculated to obtain the average accumulated subsidence ineach village from 1992 to 2019. Then the average subsidence rate from2001 to 2019 provided by the Water Resources Agency, Ministry of
Economic Affairs is used to calculate the average subsidence rate in eachvillage. And the average subsidence rate in each village in the past 10years is used as the future estimative subsidence rate. The "accumulated
subsidence depth" for each target year from 1992 can be obtained.
Then, the above-mentioned accumulated subsidence depth from 1992 to2020, 1992 to 2030, and 1992 to 2050 are divided into five levels. TheRESEARCH METHODSThis study uses 2020 as the base period to estimate the degree ofcompound hazard risk in coastal areas in 2020, 2030, and 2050. Aftercalculating and grading each factor in the hazard analysis, the concept ofPareto ranking analysis is used along with the distance formula of thehazard factors to obtain the compound hazard score of each village in thecoastal area. The original concept of the Pareto ranking analysis is to2609