Flood Hazard Assessment of the Bangshi River Floodplain using an Integrated 1D/2D Coupled Hydraulic Model

Abstract

In the present study, the flood hazard of the Bangshi River, located in the Savar Industrial Area of Dhaka District, has been evaluated. The historical flood extent analysed from the Landsat satellite images suggests that most parts of the study area were flooded during the major flood events in Bangladesh. The flood flow data were fitted with different analytical frequency distribution functions, and it is found that the Pearson III distribution function best fits with the observed data based on the Chi-Squared statistical test. Then, the flood flow model of the Bangshi River as well as the surrounding floodplain area was developed using the HEC-RAS 1D-2D coupled hydraulic model. The model was simulated with an estimated flow of 100-year and 500-year return periods. The analysis of the historical flood data shows that the water level exceeds the danger level at the nearby monitoring station of the study area in different years. In the study area, devastating floods occurred in the years 1988 and 1998. The maximum flood level was 9.9 m during the flood event of 1988. The analysis of Landsat satellite images also shows that about 69% and 58% of the study area were flooded during the floods of 1988 and 1998, respectively. The roadways provide flood protection barriers in the western side of the study area for the flood water coming from the Bangshi River system unless the road is overtopped. The simulated result shows that about 68% and 79% of the study area will be inundated for the 100-year and 500-year return periods, respectively. The simulated maximum flood velocity for the 100-year and 500-year return period is 2.31 m/s and 4.52 m/s, and the flood duration for the same return periods is about 32.5 days and 48.95 days, respectively. The simulated flood depth, duration, and velocity maps can be used for any development activities within the study area.

The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(3), Special Issue 2022: 167-186