# Risk Assessment of Coastal Flooding under Different Inundation Situations in Southwest of Taiwan (Tainan City)

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## Abstract

**:**

## 1. Introduction

## 2. Study Area and Datasets

#### 2.1. Taiwan, Tainan City

^{2}. The topography of Taiwan is classified into two parts: the flat to gently rolling plains in the west, where 90% of the population lives, and the mostly rugged forest-covered mountains in the eastern two-thirds [32].

#### 2.2. Datasets

#### 2.2.1. Digital Elevation Model

#### 2.2.2. Satellite Altimetry

_{x}, can be obtained by multiplying the sea level trend and prediction time period, which can be expressed as:

_{x}(i.e., year), b is the sea level trend, t

_{0}is the baseline year (present), and t

_{x}is set to 100 years.

_{x}with respect to a 20-year mean; MSL

_{2012}is the sea level at the baseline year 2012, which is the annual average of the monthly sea level anomaly in 2012; MSS

_{2011}is the reference mean sea surface, which is associated with the vertical datum of the Topex/Poseidon ellipsoid, of MSL

_{2012}; $\Delta {e}_{ellips}$ is the difference between the Topex/Poseidon and WGS84 ellipsoids, and Geoid is the Taiwan Hybrid Geoid Model 2014. The Hybrid Geoid Model 2014 published by the National Land Surveying and Mapping Center, M.O.I. is applied in this study to represent the difference of orthometric height and ellipsoid height (geoid undulation).

#### 2.2.3. Tide Gauge Data and Regional Ocean Tide Model

#### 2.2.4. Vertical Land Motions Data

## 3. Method

#### 3.1. Region Growing Algorithm

_{x,y}is a real number, representing the inundation depth of flood at location (x, y), either a positive number depicts the new flooded depth (S

_{i}) or previous flood depth c, or not flooded (0), E

_{x,y}is DEM elevation at location (x, y), S

_{i}is the water level of coastline cell i, and C is connectivity, which is (1) for connected and (0) for unconnected. F

^{0}

_{x,y}are set as 0 and F

^{i}

_{x,y}is updated when each S

_{i}is applied.

#### 3.2. Probability of Exceedance and Return Periods

_{R}), which is the average number of time intervals between the occurrence of events equal to or greater than a given flood level, can be used to estimate the predicted probability of occurrence of an event. Then, T

_{R}is the opposite of p.

_{R}, f(x) is assumed to be the probability density function for the variable of interest (x). Then, f(x) represents the cumulative distribution function for this variable. The probability that x will not exceed an extreme event (z) in any one time period is presented by:

_{R}(z), is the opposite of p(z) [29,41]:

_{R}(z).

_{0}(t), tidal level X(t), and meteorologically induced level Y(t). The mean sea level corresponds to long-term fluctuations caused by climatologic and geologic impacts, and it can be defined using standard regression of the long-term record of observed sea level. However, this term is usually assigned a constant or a zero value, because it is generally small compared with tidal and meteorologically induced levels [12].

_{0}(t) = 0, the storm surge can be described as:

## 4. Results and Analysis

#### 4.1. Flood Risk Map

_{t}

_{(0)}. The VLMs are also derived from multiplying the annual subsidence rates in meters and 100-year predictions. So, the DEM at 2112 in response to vertical land motions can be expressed as:

_{t(x)}is the DEM in reference year t

_{x}, DEM

_{t}

_{(0)}is the DEM in reference year t

_{0}, and “s” is the VLM trend in meters, and it is considered as constant in a grid but spatially different. We assume that the VLM is linear and computed using 50 GPS continuous stations and 510 precise leveling point data from 2000 to 2008.

#### 4.2. Wetlands Loss in Tainan

#### 4.3. Extreme Sea Levels

## 5. Discussion and Conclusions

#### Limitations and Future Work

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Acronyms and Abbreviations

## References

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**Figure 2.**Wetlands of international importance (Zengwun Estuary Wetland and Sihcao Wetland (Zones A1–3)) in Tainan city with their important habitats for Black-faced Spoonbills in Zengwun and Black-winged Stilts in Sihcao wetland (retrieved from [35]).

**Figure 3.**The sea level rise (SLR) trend around Taiwan over a 20-year period (

**a**) and Digital Elevation Model (DEM) of Taiwan along with satellite altimetry crossovers (

**b**).

**Figure 4.**Representation of a Last-In-First-Out (LIFO) stack (

**left**) and a First-In-First-Out (FIFO) queue (

**right**).

**Figure 7.**Inundation map (m) for Tainan under different inundation situations: SLR (

**a**), Vertical Land Motion (

**b**), Highest Astronomical (

**c**), and Total Inudation (

**d**).

**Figure 9.**The spatial distribution of tide-gauge stations around Tainan and their extreme flood estimation (

**a**) Kaohsiung station, (

**b**) Boziliao station and (

**c**) Jiangjun station.

**Figure 10.**The 100-year flood map of Tainan under combined situations of vertical land motions (VLM), extreme SLR, and highest astronomical tide (HAT).

Name | Location | Importance Level | Area (ha) |
---|---|---|---|

Zengwun Estuary Wetland | Tainan City | International importance | 3218 |

Sihcao Wetland | Tainan City | International importance | 547 |

Beimen Wetland | Tainan City | National importance | 2447 |

Cigu Salt Pan Wetland | Tainan City | National importance | 2997 |

Yanshuei Estuary Wetland | Tainan City | National importance | 635 |

Bajhang Estuary Wetland | Chiayi County and Tainan City | National importance | 634 |

^{1}Vertical land motions.

No. | Station | Record | Period | Lon | Lat | Instrument Type |
---|---|---|---|---|---|---|

1156 | Boziliao | 6 min | August 2004–May 2014 | 120°08′15″ E | 23°37′07″ N | Aquatrak Acoustic Tide Gauge |

1176 | Jiangjun | 6 min | January 2002–May 2014 | 120°04′59″ E | 23°12′45″ N | Aquatrak 4100 series Acoustic Tide Gauge |

1486 | Kaohsiung | 6 min | March 2004–December 2013 | 120°17′18″ E | 22°36′52″ N | Aquatrak Acoustic Tide Gauge |

Name | SLR(%) | VLM ^{1} (%) | HAT(%) | Total Inundation (%) |
---|---|---|---|---|

Zengwun Estuary | 6.42 | 21.50 | 19.90 | 88.51 |

Sihcao | 0.32 | 89.16 | 58.77 | 99.47 |

Bajhang Estuary | 5.10 | 99.99 | 91.66 | 100 |

Beimen | 69.45 | 99.33 | 97.82 | 99.77 |

Cigu Salt Pan | 0.60 | 66.46 | 73.59 | 98.98 |

Yanshuei Estuary | 5.32 | 90.57 | 87.82 | 96.97 |

^{1}Vertical land motions.

Extreme Sea Level [m] | |||
---|---|---|---|

ReturnPeriod(year) | Boziliao | Jiangjun | Kaohsiung |

100 | 1.43 | 0.76 | 0.55 |

500 | 1.62 | 0.90 | 0.70 |

1000 | 1.70 | 0.95 | 0.75 |

Extreme Sea Level with Long-Term SLR (m) | |||

100 | 1.67 | 0.97 | 0.77 |

500 | 1.86 | 1.10 | 0.92 |

1000 | 1.93 | 1.15 | 0.97 |

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**MDPI and ACS Style**

Imani, M.; Kuo, C.-Y.; Chen, P.-C.; Tseng, K.-H.; Kao, H.-C.; Lee, C.-M.; Lan, W.-H. Risk Assessment of Coastal Flooding under Different Inundation Situations in Southwest of Taiwan (Tainan City). *Water* **2021**, *13*, 880.
https://doi.org/10.3390/w13060880

**AMA Style**

Imani M, Kuo C-Y, Chen P-C, Tseng K-H, Kao H-C, Lee C-M, Lan W-H. Risk Assessment of Coastal Flooding under Different Inundation Situations in Southwest of Taiwan (Tainan City). *Water*. 2021; 13(6):880.
https://doi.org/10.3390/w13060880

**Chicago/Turabian Style**

Imani, Moslem, Chung-Yen Kuo, Pin-Chieh Chen, Kuo-Hsin Tseng, Huan-Chin Kao, Chi-Ming Lee, and Wen-Hau Lan. 2021. "Risk Assessment of Coastal Flooding under Different Inundation Situations in Southwest of Taiwan (Tainan City)" *Water* 13, no. 6: 880.
https://doi.org/10.3390/w13060880