# Impact Assessment of a Major River Basin in Bangladesh on Storm Surge Simulation

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

_{2}, along with the southern open boundary of the bay model omitting wind stress. The developed model was then applied to foresee the sea-surface elevation associated with the catastrophic cyclone of 1991 and cyclone MORA. A comparative study of the water levels associated with a storm was made through model simulations with and without the inclusion of the river system. We found that the surge height in the bay-river junction area decreased by 20% and the surge height reduced by about 3–8% outside the junction area from this study. The obtained results were found to have a satisfactory similarity with some of the observed data.

## 1. Introduction

## 2. Study Area and Cyclones

#### 2.1. Study Area

#### 2.2. Cyclones

#### 2.2.1. Cyclone 1991 (BoB 01)

#### 2.2.2. Cyclone MORA

## 3. Numerical Model

#### 3.1. Data and Materials

^{3}/s (yearly average) and tidal elevation were collected from the study of [32] and the Bangladesh Inland Water Transport Authority (BIWTA), respectively. The friction coefficient C

_{f}= 0.0026 and the drag coefficient C

_{d}= 0.0028 were taken as uniform from the study of [22]. The drag coefficient could be calculated from the relation ${C}_{d}={\rho}_{w}g{n}^{2}/{H}^{1/3}$, where ${\rho}_{w}$ is the seawater density, g is the gravitational acceleration, n is the Manning roughness coefficient, and $H$ represents the water depth. The friction coefficient can be calculated from the relation ${C}_{f}=\tau /{D}_{p}$, where $\tau $ represents the shear stresses and ${D}_{p}$ represents the dynamic pressure. The cyclone track data were 3-h interval data that were collected from the Bangladesh Meteorological Department observed data. Figure 3 represents the track information of cyclones 1991 and MORA.

#### 3.2. Model Description

#### 3.2.1. Parent Model (Bay Model)

_{d}= 2.8 × 10

^{‒3}is the surface drag coefficient used by [22]; ${\rho}_{a}$ is the density of the air; and ${u}_{a}$, ${v}_{a}$ are the $x$ and $y$ components, respectively, of the wind stress. The circulatory wind field based on the available information at the Bangladesh Meteorological Department (BMD) can then be generated by the empirical formulae of [2], being given by

#### 3.2.2. River Model

#### 3.3. Boundary Conditions

#### 3.3.1. Boundary Condition of the Parent Model

#### 3.3.2. Boundary Condition for the River Model

#### 3.3.3. Matching Boundary Condition

## 4. Numerical Procedure

#### 4.1. Nested Model Set Up

#### 4.2. Numerical Procedure

#### 4.3. Numerical Conditions

_{2}was used in the study with a period of 12.42 h, speed of 28.98 deg/h and the Doodson number of this constituent was 255.55. The tide-surge interaction process in this study was similar to the study by Roy [21]. In our model simulation, the M

_{2}tide was calculated from Equation (10) and the tidal oscillation was taken as 12.42 h. Commonly, the M

_{2}tide was dominant our study region, so we selected this as the major constituent in this study. To generate the pure oscillation of the M

_{2}tide, it was important to calculate the amplitude and phase of the constituent. Therefore, the process of Roy [21] was used to find the precious specifications of the values.

## 5. Model Validation and Outcomes

#### 5.1. Model Results

_{2}tide was introduced here. From this simulation, the water level was found to be (3–6.8 m).

#### 5.2. Results Discussion

^{3}/s. The left figure of Figure 12 shows the time series result of river discharge impact on the water level elevation due to a storm near the junction are Monpura island (see Figure 1). The right figure of Figure 12 shows the discharge impact at some reported location near the coast. Obviously, the surge height fluctuation near the junction area depends upon the characteristics of cyclone behavior like strength and landfall direction of a cyclone. Maybe the reason behind this, we have found a negligible impact of the river in another storm (MORA) surge simulation. We have mostly focused on the cyclone 1991, because of the huge study has been done on this storm by the researcher. We have run our model for the recent cyclone MORA and found the result reported in Figure 13. This figure shows the maximum water level height at Cox’s-Bazar tide station and the Junction area (Sona char). The result represents the water level height due to the tide and surge interaction under the condition of considering the river and without a river.

## 6. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## Appendix A

Sl | Date | Time | Status | Area of the System | Latitude/Longitude | Bulletin | Distance (km) | Signal |
---|---|---|---|---|---|---|---|---|

01. | 26.05.2017 | Afternoon | Low | SE Bay and adjoining Central Bay | - | - | - | - |

02. | 27.05.2017 | Afternoon | WML | SE Bay and adjoining Central Bay | - | - | - | - |

03. | 28.05.2017 | 9:00 a.m. (03 UTC) | Depression | SE Bay and adjoining Central Bay | 15.2° N/90.6° E | SWB: 01 | Ctg:790; Cxb:710; Mgl:815; Payra:755 | DC-I for all maritime ports |

04. | 28.05.2017 | 12 Noon (06 UTC) | Depression | SE Bay and adj Ctl Bay | 15.2° N/90.6° E | SWB: 02 | Ctg:790; Cxb:710; Mgl:815; Payra:755 | DC-I for all maritime ports |

05. | 28.05.2017 | 3:00 p.m. (09 UTC) | Deep Depression | SE Bay and adj Central Bay | 15.4° N/90.6° E | SWB: 03 | Ctg:770; Cxb:690; Mgl:790; Payra:735 | DC-I for all maritime ports |

06. | 28.05.2017 | 6:00 p.m. (12 UTC) | Deep Depression | SE Bay and adj Central Bay | 15.7° N/90.7° E | SWB: 04 | Ctg:735; Cxb:655; Mgl:760; Payra:700 | DC-I for all maritime ports |

07. | 28.05.2017 | 9:00 p.m. (15 UTC) | Deep Depression | SE Bay and adj Central Bay | 15.8° N/90.8° E | SWB: 05 | Ctg:720; Cxb:640; Mgl:750; Payra:690 | DC-I for all maritime ports |

08. | 29.05.2017 (28.05.2017) | Midnight (18 UTC) | Cyclone ‘Mora’ | EC Bay and Adj area | 16.2° N/91.2° E | SWB: 06 | Ctg:670; Cxb:590; Mgl:715; Payra:650 | DW-II for all maritime ports |

09. | 29.05.2017 (28.05.2017) | 3:00 a.m. (21 UTC) | Cyclone ‘Mora’ | EC Bay and Adj area | 16.7° N/91.2° E | SWB: 07 | Ctg:615; Cxb:535; Mgl:665; Payra:595 | DW-II for all maritime ports |

10. | 29.05.2017 (28.05.2017) | 6:00 a.m. (21 UTC) | Cyclone ‘Mora’ | EC Bay and Adj area | 17.1° N/91.2° E | SWB: 08 | Ctg:570; Cxb:490; Mgl:620; Payra:555 | LW-IV for all maritime ports |

11. | 29.05.2017 (29.05.2017) | 9:00 a.m. (03 UTC) | Cyclone ‘Mora’ | EC Bay and Adj area | 17.5° N/91.3° E | SWB: 09 | Ctg: 525; Cxb: 445; Mgl: 580; Payra:510 | Ctg, Cxb- DS-VIIMgl, Pyra- DS-V |

12. | 29.05.2017 (29.05.2017) | 12 Noon (06 UTC) | Cyclone ‘Mora’ | EC Bay and Adj North Bay | 17.9° N/91.3° E | SWB: 10 | Ctg: 480; Cxb: 400; Mgl: 540; Payra:470 | Ctg, Cxb- DS-VIIMgl, Pyra- DS-V |

13. | 29.05.2017 (29.05.2017) | 3:00 p.m. (09 UTC) | Cyclone ‘Mora’ | EC Bay and Adj North Bay | 18.4° N/91.3° E | SWB: 11 | Ctg: 425; Cxb: 345; Mgl: 490; Payra:415 | Ctg, Cxb- DS-VIIMgl, Pyra- DS-V |

14. | 29.05.2017 (29.05.2017) | 6:00 p.m. (12 UTC) | SCS ‘Mora’ | North Bay and adj EC Bay | 18.8° N/91.3° E | SWB: 12 | Ctg: 385; Cxb: 305; Mgl: 450; Payra:370 | Ctg, Cxb- GDS-XMgl, Pyra- GDS-VII |

15. | 29.05.2017 | 9:00 p.m. (15 UTC) | SCS ‘Mora’ | North Bay and adj EC Bay | 19.0° N/91.3° E | SWB: 13 | Ctg: 360; Cxb: 280; Mgl: 430; Payra:350 | Ctg, Cxb- GDS-XMgl, Pyra- GDS-VII |

16. | 30.05.2017 (29.05.2017) | Midnight (18 UTC) | SCS ‘Mora’ | North Bay and adj EC Bay | 19.5° N/91.3° E | SWB: 14 | Ctg: 305; Cxb: 230; Mgl: 380; Payra:300 | Ctg, Cxb- GDS-XMgl, Pyra- GDS-VII |

17. | 30.05.2017 (29.05.2017) | 3:00 a.m. (21 UTC) | SCS ‘Mora’ | North Bay and adj EC Bay | 20.2° N/91.4° E | SWB: 15 | Ctg: 230; Cxb: 150; Mgl: 320; Payra:235 | Ctg, Cxb- GDS-XMgl, Pyra- GDS-VII |

18. | 30.05.2017 (30.05.2017) | 6:00 a.m. (00 UTC) | SCS ‘Mora’ | North Bay | Started Crossing Cox’s Bazar-Chittagong Coast near Kutubdia | SWB: 16 | - | Ctg, Cxb- GDS-XMgl, Pyra- GDS-VII |

19. | 30.05.2017 (30.05.2017) | 12 Noon (06 UTC) | Land Deep Depression | Rangamati and adjoining area | Crossed Cox’s Bazar-Chittagong Coast during 06:00 a.m. to 12 Noon | SWB: 17 | - | Ctg, Cxb- GDS-XMgl, Pyra- GDS-VII |

## Appendix B. River Model Discretization

_{k}is represented by:

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**Figure 1.**Study domain and the investigated area. The red dots represent the investigated tidal station locations operated by the Bangladesh Inland Water Transport Authority (BIWTA).

**Figure 2.**The river model domain near the estuary known as lower Meghna. This lower Meghna River consists of the three big rivers Ganges–Brahmaputra–Meghna.

**Figure 3.**Track information of cyclones 1991 and MORA. The landfall location and time are presented at the right side of the track.

**Figure 4.**Different nested scheme areas. The nested schemes are CGM, FGM and VFGM. The small mesh grid area was VFGM, the outer of VFGM was FGM and the big grid area was CGM. (reproduced from [19], with permission from Elsevier, 2018).

**Figure 5.**A staggered grid represented with a proper stair step for the finite difference solution technique. Staggered grid system (

**left**). Stair-step representation of the coastline (

**right**).

**Figure 6.**Water level due to a storm at some tidal stations represented on the Google map. The surge height was multiplied by an arbitrary value 100 to clearly understand the elevation in the map.

**Figure 7.**Water level elevation due to a storm at some of the locations near the coastal area of Bangladesh. (

**left**) The simulation result when the river was incorporated in the model. (

**right**) The simulation result when there was no river in the model. Both of the simulations were performed without the tidal effect. The different colors represent the different locations of the water level elevation.

**Figure 8.**Nonlinear interaction of the tide and surge results are presented in this figure. The different colors represent the surge height at the same reported station. There was no river considered in the simulation result in the right figure and the left figure shows the result that incorporates the river. With river (

**left**), Without river (

**right**).

**Figure 9.**The comparison result of the model simulation of the influence of the lower Meghna river near the junction area and outside the junction area. (

**left**) The result of the outside junction area. (

**right**) The result of the near junction area.

**Figure 10.**The combined result represents the bay and river model data with the observed data. Due to the data scarcity, only a few observed data are represented.

**Figure 11.**The figure shows the distribution result of surge height simulation at the land fall time 30 April 2:00 a.m. (local time) under different conditions. (

**a**) represents the surge height distribution when the river has existed in the simulation. (

**b**) represents the surge height distribution when the there is no river included in the simulation. (

**c**) represents the surge height difference.

**Figure 12.**River discharge effect on the water level elevation due to a storm. The left figure shows the time series result of water level elevation (

**left side**) and the right figure show the river discharge effect on water level at some locations near the coast (

**right side**).

**Figure 13.**Maximum wave peak statistic of cyclone MORA and the model-simulated result at the Cox’s Bazar tide station.

Model | Domain | Grid Spacing along x Axis | Grid Spacing along y Axis | Number of Computational Points |
---|---|---|---|---|

CGM | 15° N to 23° N and 85° E to 95° E | 15.08 km | 17.52 km | 60 × 61 |

FGM | 21°15′ N to 23° N and 89° E to 92° E | 2.15 km | 3.29 km | 92 × 95 |

VFGM | 21.77° N to 23° N and 90.40° E to 92° E | 720.73 m | 1142.39 m | 190 × 145 |

VFGMR | 23° N to 23.25° N and 90.40° E to 90.68° E | 720.73 m | 1142.39 m | 40 × 27 |

Coastal Location | Overall Max. Water Level (m) by [25] | Simulated Overall Max. Water Level (m) by [22] | Simulated Overall Max. Water Level (m) by FDM [38] | Simulated Overall Max. Water Level (m) (without River) | Simulated Overall Max. Water Level (m) (with River) | Observed Overall Max. Water Level (m) |
---|---|---|---|---|---|---|

Cox’s Bazar | -- | -- | 6.14 | 5.98 | 5.89 | 6.00 |

Moheshkhali | -- | -- | 4.12 | 4.59 | 4.57 | -- |

Banshkhali | -- | -- | 3.58 | -- | -- | -- |

Chittagong | 6.25 | 5.45 | 4.50 | 4.60 | 4.61 | 5.4 |

Sitakunda | 5.78 | -- | 4.48 | 5.15 | 5.11 | -- |

Sandwip | 5.63 | 5.33 | 4.38 | 5.21 | 5.20 | -- |

Mirsharai | -- | -- | 5.66 | 5.05 | 5.03 | -- |

Companiganj | 7.28 | -- | 6.15 | 5.90 | 5.89 | 6.1 |

Chital Khali | -- | -- | 4.50 | -- | -- | -- |

Char Jabbar | 6.35 | 5.18 | 5.69 | 5.51 | 5.47 | -- |

Char Changa | 5.81 | 4.31 | 4.12 | 4.60 | 4.58 | -- |

Char Madras | 5.81 | -- | 4.32 | 4.99 | 4.95 | -- |

Rangabali | 4.50 | -- | 4.07 | 3.56 | 3.56 | -- |

Kuakata | 3.86 | -- | 3.96 | 3.60 | 3.58 | -- |

Patharghata | -- | -- | 4.36 | 3.55 | 3.57 | -- |

Tiger Point | 4.57 | -- | 4.21 | 4.30 | 4.30 | -- |

Hiron Point | 4.01 | 0.70 | 3.80 | 3.48 | 3.45 | 3.5 |

Monpura Island | -- | -- | -- | 5.20 | 4.88 | -- |

Sona Char | -- | -- | -- | 4.51 | 3.61 | -- |

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Mohit, M.A.A.; Yamashiro, M.; Hashimoto, N.; Mia, M.B.; Ide, Y.; Kodama, M. Impact Assessment of a Major River Basin in Bangladesh on Storm Surge Simulation. *J. Mar. Sci. Eng.* **2018**, *6*, 99.
https://doi.org/10.3390/jmse6030099

**AMA Style**

Mohit MAA, Yamashiro M, Hashimoto N, Mia MB, Ide Y, Kodama M. Impact Assessment of a Major River Basin in Bangladesh on Storm Surge Simulation. *Journal of Marine Science and Engineering*. 2018; 6(3):99.
https://doi.org/10.3390/jmse6030099

**Chicago/Turabian Style**

Mohit, Md. Abdul Al, Masaru Yamashiro, Noriaki Hashimoto, Md. Bodruddoza Mia, Yoshihiko Ide, and Mitsuyoshi Kodama. 2018. "Impact Assessment of a Major River Basin in Bangladesh on Storm Surge Simulation" *Journal of Marine Science and Engineering* 6, no. 3: 99.
https://doi.org/10.3390/jmse6030099