Simulation-based modeling of urban waterlogging in Khulna City

Abstract

Khulna City is extremely vulnerable to the effects of climate change. The city experiences frequent waterlogging during extreme rainfall events. This research prepared a drainage simulation model considering climate change issues for investigating the extent of waterlogging in the city. Watershed and precipitation were analyzed to examine the existing scenario of the study area. Finally, a Mike Urban-based hydrological simulation model was formulated to investigate the severity of waterlogging. As found by precipitation analysis, 180 mm, 346 mm, and 396 mm rainfall might occur for the 5-year, 50-year, and 100-year return period, respectively. This research identified that volume of overland flow might be affected by climate change-induced rainfall. According to the simulation, 62.52% of the study area was waterlogged with different inundation depths. It was found that traffic movements were severely disrupted and structures were hampered due to waterlogging. 45% paved, 77% brick soling, and 65% unpaved roads were inundated by different inundation levels. On the other hand, 61.1% of structures of the study area were affected by waterlogging. The findings of the research might help the concerned authority in decision-making, especially for the drainage and water-related issues, to solve the waterlogging.

Spatial modeling of COVID-19 transmission in Bangladesh

“…Bangladesh is already one of the world’s most vulnerable country to climate change induced natural disasters [ 9 , 10 ]. In terms of the risk of transmission of COVID-19, Haider et al [ 11 ] have classified Bangladesh into the 4th quantile (highest risk) based on the destinations of the passengers travelling from four major cities of China from January onwards.…”

Understanding the Use of Heterogenous Data in Tackling Urban Flooding: An Integrative Literature Review

“…For intensity, most estimates an average from historical data, and the timespan for consideration can be annual [23], daily [23], or hourly [15]. For duration, minute-based [16,17], hourly [21,31,32,[60][61][62], daily [18,33,63], and multi-day-based [23] models are all reported. It is also noticed all studies made use of historical data, and realtime precipitation are only addressed in theoretical studies on data and system integration models [5,8,38].…”

Waterlogging Risk Assessment: An Undervalued Disaster Risk in Coastal Urban Community of Chattogram, Bangladesh

“…In 2014, more than 65,000 households were affected by rainfall-induced waterlogging disasters in the southern coastal districts only [7]. Sarkar et al [9] reported that 38% of coastal inhabitants in southern Khulna City experience short-term waterlogging every year. More recently, Chattogram, the most prosperous economic region of Southern Bangladesh, suffered its highest recorded economic damage of US $71 million caused by several waterlogging events in the single financial year of 2017 [10].…”

“…Smith et al [20] applied a hydrodynamic model in Carlisle, Northwest England to assess the impact of a sustainable drainage system design for urban flood modeling. Sarkar et al [9] utilized a MIKE hydrological model for Khulna, Bangladesh and showed that both the existing drainage area and capacity are inadequate to mitigate waterlogging risk. Inspired by these previous studies of the dependence of waterlogging on various factors, including meteorological and hydrological, that have advanced the understanding of the waterlogging risk of many cities worldwide, the present study investigated the potential waterlogging risk in Chattogram City, Bangladesh.…”