# Determining the Risk Level of Heavy Rain Damage by Region in South Korea

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## Abstract

**:**

## 1. Introduction

## 2. Theoretical Background (Materials and Methodology)

#### 2.1. Characteristics of the Study Area

#### 2.2. Qualitative Risk Assessment Method

#### 2.2.1. Principle for Selecting Assessment Indicators

#### 2.2.2. Standardization Method for Assessment Indicators

#### 2.2.3. Method of Calculating Weights

#### 2.3. Hierarchical Cluster Analysis

## 3. Result of Analysis

#### 3.1. Risk Assessment of Heavy Rain Damage

#### 3.1.1. Selection and Construction of Assessment Indicators

#### 3.1.2. Standardization and Calculation of Weights of Assessment Indicators

#### 3.1.3. Definition of the Risk Level of Heavy Rain Damage by Region

#### 3.2. Classification of Heavy Rain Damage Types Based on Hierarchical Cluster Analysis

#### 3.3. Analysis for Heavy Rain Damage Risk and Damage Type in Each Region

## 4. Discussions and Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 4.**Conceptual diagram of dendrogram [31].

**Figure 5.**Normalized spatial distribution of each sub–index. (

**a**) Hazard index, (

**b**) Exposure index, (

**c**) Vulnerability index, and (

**d**) Capacity index.

**Figure 6.**Classification of risk level based on probability distribution. (

**a**) PDF of HDRI and (

**b**) classification of risk level using CDF.

Province | Abbreviation | City | Abbreviation |
---|---|---|---|

Gyeonggi-do | GG | Seoul | SO |

Gangwon-do | GW | Incheon | IC |

Gyeongsangbuk-do | GB | Busan | BS |

Gyeongsangnam-do | GN | Daegu | DG |

Chungcheongbuk-do | CB | Ulsan | US |

Chungcheongnam-do | CN | Daejeon | DJ |

Jeollabuk-do | JB | Sejong | SJ |

Jeollanam-do | JN | Gwangju | GJ |

JeJu-do | JJ |

Indicator Selection Principles | Abbreviations | Descriptions |
---|---|---|

Correlation | C | Examines whether the meanings of the components are similar |

Simplicity | S | Examines whether the meanings of individual indicators are easy to understand |

Quantitative | Q | Examines whether indicators can be quantified numerically |

Validity | V | Examines whether the conceptual basis of the relevant indicator is clear |

Redundancy | R | Examines whether any of the indicators have overlapping meanings |

Ease | E | Examines whether it is easy to continuously collect data |

**Table 3.**Features of standardization methods used in this study [22].

Methods | Equation | Description |
---|---|---|

Categorical scale | ${I}_{i}=\left\{\begin{array}{c}0.25,if{x}_{i}\in \left\{{p}^{25th}\right\}percentile\\ 0.5,if{x}_{i}\in \left\{{p}^{50th}-{p}^{25th}\right\}percentile\\ 0.75,if{x}_{i}\in \left\{{p}^{75th}-{p}^{50th}\right\}percentile\\ 1.00,if{x}_{i}\in \left\{{p}^{100th}-{p}^{75th}\right\}percentile\end{array}\right\}$ | A method of classifying categories by quantile and assigning scores even if the range of specific indicator values is very wide. |

${x}_{i}$means the value of the $i$th data, and scores are given according to the range to which the value belongs. | ||

Re-Scaling | ${I}_{i}=\frac{{x}_{i}-\mathrm{min}\left(x\right)}{\mathrm{max}\left(x\right)-\mathrm{min}\left(x\right)}$ | A transformation method based on the range of indicators. Standardized values are included in the range of 0 to 1. |

${x}_{i}$means the value of the $i$th data, and max(x) and min(x) represent the maximum and minimum values of the data, respectively. |

Framework | Components | Potential Assessment Indicators | Indicator Selection Principles | Final Selection | |||||
---|---|---|---|---|---|---|---|---|---|

C | S | Q | V | R | E | ||||

Hazard | Meteorological | Probable rainfall | ☓ | ○ | ○ | ○ | ○ | ○ | ☓ |

Number of days of rainfall of 80 mm | ○ | ☓ | ○ | ○ | ☓ | ○ | ☓ | ||

Maximum rainfall per day | ○ | ○ | ○ | ○ | ☓ | ○ | ☓ | ||

Maximum rainfall during the duration (24 h) | ○ | ○ | ○ | ○ | ○ | ○ | ○ (H1) | ||

Annual average rainfall | ○ | ○ | ○ | ○ | ○ | ○ | ○ (H2) | ||

Historical Damage | Flood damage | ○ | ○ | ○ | ○ | ○ | ○ | ○ (H3) | |

Scale of flood damage | ○ | ○ | ○ | ○ | ☓ | ○ | ☓ | ||

Frequency of flood damage | ○ | ○ | ○ | ○ | ○ | ○ | ○ (H4) | ||

Flooded area | ○ | ○ | ☓ | ☓ | ○ | ☓ | ☓ | ||

Exposure | Socio-economic | Total population | ○ | ○ | ○ | ○ | ○ | ○ | ○ (E1) |

GRDP | ○ | ○ | ○ | ○ | ○ | ○ | ○ (E2) | ||

Per capita income | ○ | ○ | ○ | ○ | ☓ | ○ | ☓ | ||

Average official land price | ○ | ○ | ○ | ○ | ☓ | ○ | ☓ | ||

Population density | ○ | ○ | ○ | ○ | ☓ | ☓ | ☓ | ||

Physical | Number of buildings | ○ | ○ | ○ | ○ | ○ | ○ | ○ (E3) | |

Infrastructure (road) | ○ | ○ | ○ | ○ | ○ | ○ | ○ (E4) | ||

Slope | ☓ | ○ | ○ | ○ | ☓ | ○ | ☓ | ||

River density | ○ | ○ | ○ | ○ | ○ | ○ | ○ (E5) | ||

Vulnerability | Social | Vulnerable population | ○ | ○ | ○ | ○ | ○ | ○ | ○ (V1) |

Poor population | ○ | ○ | ○ | ○ | ☓ | ☓ | ☓ | ||

Infant mortality | ○ | ○ | ○ | ○ | ☓ | ☓ | ☓ | ||

TV distribution rate | ☓ | ○ | ○ | ○ | ○ | ☓ | ☓ | ||

Number of semi-basement households | ○ | ○ | ○ | ○ | ○ | ☓ | ☓ | ||

Population in flooded areas | ○ | ○ | ☓ | ☓ | ○ | ☓ | ☓ | ||

Number of households not supplied with electricity | ☓ | ○ | ○ | ○ | ☓ | ☓ | ☓ | ||

Physical | Area of the lowland area | ○ | ☓ | ○ | ☓ | ☓ | ☓ | ☓ | |

Runoff curve index | ○ | ○ | ○ | ○ | ○ | ☓ | ☓ | ||

Disaster-prone districts | ○ | ○ | ○ | ○ | ○ | ○ | ○ (V2) | ||

Steep slope | ○ | ○ | ○ | ○ | ○ | ○ | ○ (V3) | ||

Old buildings | ○ | ○ | ○ | ○ | ○ | ○ | ○ (V4) | ||

Capacity | Disaster Prevention Capability | Number of disaster prevention facilities | ○ | ○ | ○ | ○ | ○ | ☓ | ☓ |

Preventive facilities | ○ | ○ | ○ | ○ | ☓ | ☓ | ☓ | ||

Drainage pump station | ○ | ○ | ○ | ○ | ○ | ○ | ○ (C1) | ||

Dam and reservoir | ○ | ○ | ☓ | ○ | ○ | ☓ | ☓ | ||

River management personnel | ☓ | ○ | ☓ | ○ | ○ | ☓ | ☓ | ||

Financial independence | ○ | ○ | ○ | ○ | ○ | ○ | ○ (C2) | ||

Disaster Prevention History | Cumulative disaster prevention budget | ○ | ○ | ○ | ○ | ○ | ○ | ○ (C3) | |

Promotion of preventive measures | ○ | ○ | ☓ | ○ | ☓ | ☓ | ☓ | ||

River embankment ratio | ☓ | ○ | ☓ | ☓ | ○ | ☓ | ☓ |

Assessment Indicators | Re-Scaling | The Percentage of Standardized Value | ||||
---|---|---|---|---|---|---|

Min | Max | 20% | 40% | 60% | 80% | |

H1 | 833.18 | 1443.75 | 0.2245 | 0.3503 | 0.4490 | 0.5518 |

H2 | 96.43 | 200.625 | 0.2906 | 0.3778 | 0.4889 | 0.6391 |

H3 | 0 | 156 | 0.2321 | 0.3654 | 0.4679 | 0.5923 |

H4 | 0 | 635,553,387 | 0.0024 | 0.0065 | 0.0161 | 0.0407 |

E1 | 16,993 | 1,194,465 | 0.0245 | 0.0709 | 0.1753 | 0.3181 |

E2 | 431,322 | 60,407,392 | 0.0171 | 0.0446 | 0.0853 | 0.1725 |

E3 | 2257 | 180,936 | 0.1184 | 0.1718 | 0.2508 | 0.3608 |

E4 | 0.000421 | 0.281286 | 0.0233 | 0.0346 | 0.0712 | 0.1614 |

E5 | 0 | 0.209904 | 0.0444 | 0.0712 | 0.1098 | 0.1740 |

V1 | 7382 | 258,384 | 0.0491 | 0.1038 | 0.2135 | 0.3627 |

V2 | 0 | 20 | 0.0250 | 0.0500 | 0.1500 | 0.3000 |

V3 | 0 | 71.76 | 0.0002 | 0.0025 | 0.0224 | 0.1015 |

V4 | 337 | 67,767 | 0.1235 | 0.1843 | 0.2463 | 0.3156 |

C1 | 0 | 283,740 | 0.0008 | 0.0016 | 0.0081 | 0.0250 |

C2 | 0 | 453,722.3 | 0.0176 | 0.0352 | 0.0851 | 0.1341 |

C3 | 8.5 | 69.2 | 0.1081 | 0.1951 | 0.2965 | 0.4870 |

Percentile | Score | Percentile | Score |
---|---|---|---|

$0\%\le {x}_{i}<20\%$ | 0.2 | $60\%\le {x}_{i}<80\%$ | 0.8 |

$20\%\le {x}_{i}<40\%$ | 0.4 | $80\%\le {x}_{i}<100\%$ | 1.0 |

$40\%\le {x}_{i}<60\%$ | 0.6 | - | - |

Framework | Assessment Indicators | Indicators Weight | Sub-Index Weight |
---|---|---|---|

Hazard | H1 | 0.0043 | 0.3198 |

H2 | 0.0075 | ||

H3 | 0.0867 | ||

H4 | 0.9014 | ||

Exposure | E1 | 0.139 | 0.1978 |

E2 | 0.1861 | ||

E3 | 0.0613 | ||

E4 | 0.189 | ||

E5 | 0.4245 | ||

Vulnerability | V1 | 0.123 | 0.186 |

V2 | 0.2937 | ||

V3 | 0.518 | ||

V4 | 0.0654 | ||

Capacity | C1 | 0.7646 | 0.2963 |

C2 | 0.1983 | ||

C3 | 0.0371 |

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**MDPI and ACS Style**

Kim, J.; Kim, D.; Lee, M.; Han, H.; Kim, H.S.
Determining the Risk Level of Heavy Rain Damage by Region in South Korea. *Water* **2022**, *14*, 219.
https://doi.org/10.3390/w14020219

**AMA Style**

Kim J, Kim D, Lee M, Han H, Kim HS.
Determining the Risk Level of Heavy Rain Damage by Region in South Korea. *Water*. 2022; 14(2):219.
https://doi.org/10.3390/w14020219

**Chicago/Turabian Style**

Kim, Jongsung, Donghyun Kim, Myungjin Lee, Heechan Han, and Hung Soo Kim.
2022. "Determining the Risk Level of Heavy Rain Damage by Region in South Korea" *Water* 14, no. 2: 219.
https://doi.org/10.3390/w14020219