PhD Thesis

Development of Disaster Demand Matrix for Bangladesh

2026-10-18T00:00:00Z

Development of Disaster Demand Matrix for Bangladesh Kibria, Md. Golam Bangladesh, as one of the world's most hazard-vulnerable nations, experiences recurrent cyclone disasters that devastate coastal populations, livelihoods, and critical infrastructure, particularly in its densely populated littoral regions. While conventional disaster response mechanisms have achieved notable successes in casualty mitigation over recent decades, multifaceted gaps persist across the disaster management continuum, encompassing mitigation, preparedness, response, and recovery phases. These operational deficiencies reflect misalignment between national disaster management capacities and internationally established best practices, creating systematic barriers to comprehensive risk reduction and resilience augmentation. This doctoral research addresses this fundamental challenge through development of an evidence-based Disaster Demand Matrix (DDM) framework, systematically identifying and quantifying critical unmet demands across Bangladesh's cyclone disaster management architecture. The study employs an integrative methodological approach combining multiple investigative dimensions. First, empirical analysis of four decades of cyclone data (1982–2024) establishes contemporary cyclone activity patterns and intensity trends affecting Bangladesh's coastal zone. Second, systematic comparative analysis of Bangladesh's existing disaster management practices against globally established best practices across thirteen cyclone-prone nations identifies substantive implementation gaps, institutional coordination deficiencies, and policy-practice divergences. Third, the research develops a comprehensive Disaster Demand Matrix encompassing nine major disaster management domains, comprising mitigation, preparedness, early warning, evacuation, emergency response, damage assessment, healthcare provision, recovery operations, and long-term reconstruction that systematically quantifies performance gaps between optimal operational standards and prevailing local realities. To establish strategic prioritization among ninety multifaceted disaster management sub-activities, the research applies the Fuzzy Analytical Network Process (FANP) methodology, a sophisticated multi-criteria decision-making technique accommodating criterion interdependencies, decisionmaker uncertainty, and complex priority interactions. This rigorous prioritization exercise synthesizes expert professional judgment from academicians, government functionaries, and iii emergency management practitioners, yielding analytically derived hierarchical rankings of critical interventions requiring prioritized resource allocation and institutional development. The prioritization results reveal that information dissemination and community risk communication systems constitute the paramount intervention priority, followed sequentially by spatially resolved evacuation coordination mechanisms, continuous meteorological monitoring with predictive analytics capabilities, and comprehensive community-level hazard awareness programming. These priority activities, representing foundational demand-driven interventions, collectively address systemic preparedness deficiencies, reduce information asymmetries, and enhance population protective action capacity, thereby generating multiplicative risk reduction benefits across all subsequent disaster management phases. Beyond these principal findings, the research identifies priority institutional capacity-building requirements, governance-level coordination mechanisms, and policy-implementation frameworks necessary for effective DDM operationalization. The framework explicitly acknowledges methodological limitations, including constraints regarding empirical field-level validation, expert-judgment subjectivity, geographic specificity to coastal cyclone contexts, technical accessibility barriers for frontline practitioners, and data integration limitations, while simultaneously delineating prospective research trajectories for methodological extension and practical framework advancement. Ultimately, this research contributes a novel, systematically derived decision-support instrument enabling Bangladesh's disaster management community to allocate resources strategically, prioritize institutional development investments, and align policy interventions toward addressing the most consequential unmet demands within the disaster management system. By facilitating demand-driven, evidence-based disaster management planning, the Disaster Demand Matrix framework supports sustainable resilience enhancement, accelerated emergency response effectiveness, and expedited recovery processes benefiting Bangladesh's climate-vulnerable coastal populations and contributing toward attainment of global Sendai Framework disaster risk reduction objectives. This thesis is submitted for the degree of Doctor of Philosophy.

A COMPARATIVE STUDY ON EPIDEMIOLOGICAL MAPPING FOR DENGUE CASES IN SINGAPORE AND BANGLADESH

2025-02-11T00:00:00Z

A COMPARATIVE STUDY ON EPIDEMIOLOGICAL MAPPING FOR DENGUE CASES IN SINGAPORE AND BANGLADESH Islam, Md Tauhedul Establishing the causal relations of any disease or health event is crucial as to its prediction and protection is concerned. Taking dengue as a model case in the city of Dhaka, Bangladesh and Singapore, this study has ventured to apply an innovative step-by-step approach to find out the causal correlations within the climate-vector-disease associations as well as ecological and human variables in the cities of Dhaka and Singapore. The study has discovered a significant correlation amongst climatic variables and vector availability, ecological factors and vector abundance and between vector concentration and dengue occurrence in temporal and spatial dimensions. Also, the study has been able to establish the variation of dengue incidence in different seasons accounted for 30 years, and long-term trends of climate and dengue incidence over a 10-year period, the study developed a bank of applicable data set which could be used by the enthusiastic researches in the field of the effects of climate change as well as ecology on dengue transmission in Dhaka and Singapore and in the regions of the South and South East Asia at large. Based on the findings, a model mapping system was envisioned to predict the future incidence of dengue and thereby, to predict any such disease or health event and devising prevention guidelines thereto at local, national, regional and global level. In one hand, differences of variables in different cities and regions have been proved as to applying one regional model for another region, on the other hand, incorporating crucial variables in one model through a compare and contrast study enabled to frame a relatively common model mapping system applicable for any given entity of a region. It is a huge enabler on global and regional scale to address the outbreak of any given disease in entities with different economic and geographical setting. Devising this technique of mapping and modelling by addressing Spatial variations is an important novelty of this study. Finding out Temporal variations of variables over time, particularly decadal impact of variables is another xi crucial attribute of the Model to apply it effectively in preventive medicine and urban planning. This research also found that city areas having more built and paved areas and areas with unplanned urbanization had the highest abundance/density of Aedes mosquitoes-the vector of dengue. These results demonstrate that alteration of the ecology in city area is one of the major reasons for the increase of dengue incidence, especially in metropolitan areas. This is a crucial inference as to the dengue prediction and prevention mapping is concerned that, unplanned urbanization, particularly development of shanty slum area is crucial to dengue fever spread. Again, the mapping results of this study has mentionable contributory function to assist in drafting appropriate, differentiated plan, policies and strategies for controlling vectors, i.e. aedes mosquito and preventing the spread of the resultant disease-dengue in the Dhaka city of Bangladesh and Singapore and other vulnerable areas of the regions and the globe at large. A Thesis Submitted to the Department of Disaster Science and Climate Resilience, University of Dhaka in Fulfillment of the Requirements for the Degree of Doctor of Philosophy.

Exploring the Possibilities of Mariculture for Promoting Blue Economy of the St. Martin's Island, Bangladesh

2024-02-07T00:00:00Z

Exploring the Possibilities of Mariculture for Promoting Blue Economy of the St. Martin's Island, Bangladesh Alam, Md. Jobaer Bangladesh, a nation situated on the northern coast of the Bay of Bengal, has been endowed with a wide range of natural resources. The ocean has a crucial role in driving socio-economic advancement through stimulating economic activities throughout the country, particularly in coastal regions. The notion of the ocean’s economy, commonly known as the blue economy, is a multifaceted approach that aims to foster economic expansion, ensure environmental sustainability, promote social inclusivity, and enhance the resilience of marine ecosystems. St. Martin's Island, the sole island that bears coral in Bangladesh, is unquestionably among the most cherished possessions and has been chosen as the study area due to its unique geography, size and location within the coastal zone. Furthermore, this region serves as an appropriate pilot model location due to its abundance of readily accessible data resources. This study emphasizes the potential of mariculture in promoting the growth of the blue economy on the island. The objectives of the study were to determine the best site, season, and species of fish and seaweed to be cultivated in the coastal waters adjacent to the Island. In order to accomplish the study's goal, the present research work examined the composition, abundance, and distribution of physiochemical properties, plankton, nutrients and heavy metals in the coastal waters of the Bay of Bengal in the vicinity of St. Martin's Island, Bangladesh. Twelve distinct sampling stations were visited at various seasons between 2019 and 2021 to collect samples. Physicochemical properties were quantified to analyze water quality fluctuation by season. Three seasons specifically pre-monsoon, monsoon and cool dry winter season’s temperature, salinity, pH, DO, EC, TDS, and transparency were measured. The average temperature from the stations ranged from 24.16ºC to 27.4ºC. Mean seasonal temperatures for the pre-monsoon, monsoon and dry cool winter seasons are 26.83±0.21ºC, 27.06±0.22ºC, and 24.61±0.39ºC respectively. The salinity ranged from 24.42 ppt to 33.76 ppt, with the highest salinity (32.91±0.51) being measured in the pre-monsoon season. The value of pH was rather consistent throughout the year, ranging from 7.71 to 8.22, with the highest value (8.18±0.02) being measured in the pre-monsoon season. The amount of dissolved oxygen ranged from 4.82 to 6.74 mg/L, with the highest in the dry cool winter season (6.47±0.21 ppm) while the minimum dissolved oxygen was measured in the monsoon season (4.95±0.09 ppm). The value of electric conductivity ranged from 39.0 mS/cm to 53.46 mS/cm, with the highest value (52.06±0.90) being measured in the pre-monsoon season. The value of total dissolved solids ranged from 20.35 to 27.9 g/l, with the highest value (27.51±0.23) being measured in the pre-monsoon season while the lowest (20.98±0.35) was in the rainy monsoon season. The water around the island was clearer in the cool dry winter season with a range of 4.14±02 m. Furthermore, the water is least (1.45± 0.03) clear in the rainy season. A thorough examination of the season resulted in the identification of 55 unique phytoplankton species. The overall number of phytoplankton ranged from 75,000 to 450,000 individuals per cubic meter, with the maximum abundance observed at station 10. Coscinodiscus sp. dominates all stations with cell densities of 12,500–87,500 ind/m 3 and other dominant species were Chaetoceros, Thalassiosira, and Thalassionema. Another investigation disclosed the presence of 34 distinct species of zooplankton. Most species were copepods, and station 8 had the most species. The observed range for the standing crop of zooplankton was between 55,000 and 125,000 individuals per cubic meter. Additionally, the community included Polychaeta and Cirripedia. The species of utmost significance encompassed Oithona, Canthocalanus, Balanus, Euterpina, and Microsetella sp. The levels of plankton abundance were found to be maximum during the pre-monsoon season, whereas moderately lower abundance was seen during the cool dry winter season. All the nutrient concentrations exhibited highest mean values during the cool winter season (Nitrate: 0.673±0.074; Nitrite: 0.139±0.015; Silicate: 8.66±0.253; Ammonium: 0.275±0.046; and Phosphate: 0.165±0.029 mg/L) while during the pre-monsoon season the values were slightly lower (Nitrate: 0.336±0.041; Nitrite: 0.012±0.010; Silicate: 7.757±0.389; Ammonium: 0.163±0.046; and Phosphate: 0.120 ± 0.019 mg/L). During both seasons silicate and nitrate are the prime contributor of the nutrients followed by ammonium and phosphate, respectively. The study found that heavy metal concentrations (μg/L) for Lead (Pb) 76.825±37.91, Copper (Cu) 27.478±2.78, Arsenic (As) 0.990±0.19, Chromium (Cr) 3.475±1.92, Cadmium (Cd) 6.365±4.08 and Zinc (Zn) 44.534±12.09 in pre-monsoon hot season and for Lead (Pb) 24.909±9.28, Copper (Cu) 23.987±1.71, Arsenic (As) 1.0591±0.31, Chromium (Cr) 3.033±2.23, Cadmium (Cd) 3.727±1.26, and Zinc (Zn) 21.097±11.44 in cool dry winter season are still safe for any living organism. Based on physiochemical qualities, plankton distribution, nutrients and heavy metal distribution, and pollution indexes (HPI, HEI, NPI, TERI), site, season and suitable species of fish and seaweed were chosen. As a result of the collective findings, it could be stated that the pre-monsoon season was strongly suitable for cage culture and cool dry winter season was strongly suitable for seaweed culture in the coastal waters of St. Martin’s Island. For cage culture, stations 10, 8 and 9 were selected to cultivate herbivore, omnivore and carnivore fish respectively, based on physiochemical attributes, nutrients, heavy metals and plankton abundance and distribution. On the other hand, based on physiochemical attributes, nutrient and heavy metal distribution station 1 was chosen for seaweed culture. However, it is also plausible to consider stations 10 and 12. The suitability of mariculture in a coastal region is contingent upon a comprehensive assessment that considers various aspects, including environmental, economic, social, and regulatory concerns. In this study the benefit cost ratio (BCR) was taken into account as the basis of suitability of mariculture (BCR > 1 suitable, BCR < 1 unsuitable, BCR =1 marginally suitable). According to the results of a thorough investigation of all of the studies, John’s Snapper (Lutjanus johnii), a carnivorous fish species was chosen as a representative species for cultivation and the monoculture technique of fish farming was used in this study. Lutjanus johnii, had a Benefit cost ratio (BCR) value of 1.1651 after being caged in coastal waters. BCR value showed that cage-growing of John’s Snapper at St. Martin's Island is profitable. The study suggests that the large- scale commercial cage culture of L. johnii has the potential to yield extremely significant profit. Based on the comprehensive analysis of all the studies, Padina gymnospora (Brown algae) was selected as a commercially important algae to be cultivated in the coastal waters adjacent to St. Martin’s Island. BCR for Padina gymnospora was 2.75, using the long line method and 3.364 using the floating net method respectively which indicates cultivation of this species using both methods are profitable in the Island. BCR analysis also suggests that floating net culture is superior to long line cultivation for the purpose of growing seaweed. Nonetheless, the study suggests that cage and seaweed farming in St. Martin’s Island and adjacent coastal areas can promote the country's blue economy by increasing fish and seaweed production. Therefore, the cultivation of fish and seaweed in the coastal waters of the island has the potential to enhance the socio-economic well-being of the island's residents and contribute to the overall economic growth of the country. Water quality, diseases outbreak, habitat alternation, genetic homogenization, feed dependency, market volatility, technology and lack of regulations are some of the key limitations associated with mariculture research and practice. These limitations must be carefully considered and addressed to ensure the success of research efforts. A dissertation submitted to the Department of Disaster Science and Climate Resilience, University of Dhaka as partial fulfillment of the degree of Doctor of Philosophy (PhD).

Development of Open Space Management System to Response Scenario Earthquake in Dhaka Metropolitan Area

2023-01-29T00:00:00Z

Development of Open Space Management System to Response Scenario Earthquake in Dhaka Metropolitan Area Haque, A K M Aminul The urbanized areas of Bangladesh are subjected to potential earthquake hazards and risks due to the proximity of seismically active zones. Dhaka Metropolitan Area, the capital of Bangladesh, is ill-planned and highly urbanized with a large population. The inhabitants of the city contribute thirty-six percent of the national GDP. These factors make the city highly vulnerable to earthquakes. The seismic hazard assessment carried out by the Comprehensive Disaster Management Program (CDMP) showed significant risks, yet preparedness measures for the city are lacking. Open spaces are essential in earthquakes as they can provide various options, from immediate evacuation to long-term sheltering of the resulting homeless population. Cases worldwide have benefitted from utilizing open spaces, and even the contingency plans suggest its use. Nonetheless, no comprehensive research or data is available regarding the open spaces. This study addressed that gap in the immediate response to urban mega-disaster. The present study aimed to develop an open space management system for responding to a scenario earthquake in Dhaka. The first step was to assess the suitability of existing open spaces in the Dhaka Metropolitan Area to serve as emergency shelters using the modified Comprehensive Open Space Suitability Index (COSI). For that, the available open space footprints were mapped using satellite imagery. Then, these open spaces were ranked according to their area, connectivity, accessibility, hazard exposure, and nearness to facilities. Among the one thousand one hundred and ninety-seven identified open spaces, two hundred and seventeen were found to be suitable. At the same time, hundred and fifty-one were moderately suitable, and the rest were deemed less suitable (not to be interpreted as unusable). Out of the two hundred and seventeen suitable sites, fourteen sites had to be left out of consideration since they are within the Key Point Installation premises and include National Parliament, Airport, Prime Minister’s Office, various country’s High Commissions/Embassies, and High Court. After that, generalized liquefaction analysis based on geomorphological classes revealed that thirty-seven sites had to be excluded as they exhibited high to very high liquefaction potential. It means only one hundred and sixty-six open spaces were selected as safe sites for long-term shelter establishment. Given that liquefaction may render potential sites unusable due to earthquakes, much importance was emphasized on its effect in the study area. Furthermore, eight sites across the city were selected as a case study for detailed liquefaction potential investigations. Probabilistic seismic hazard assessment and site response analysis were conducted, and all eight sites showed less than 0.15g Peak Ground Acceleration (PGA) value for a ten percent probability of exceedance in fifty years. The results were used to calculate liquefaction potential through deterministic, probabilistic, and artificial neural network approaches. All results stated that the eight sites were safe for post-earthquake shelter placement. The deterministic approach was basically used for safety-based analysis. In contrast, the probabilistic approach is the likelihood of liquefaction, meaning it is probability-based. Still, the artificial neural network approach is more robust than the three approaches and gives realistic results by establishing precise nonlinear relationships. All eight sites revealed a very low (less than five) liquefaction potential index value in an earthquake of 7.5 magnitude scenario with PGA 0.15g. This was followed by establishing standard requirements of the shelters that would be placed in the open spaces, including living space per person (2.3 m2 per person, considering population density), appropriate shelter materials (waterproof, lightweight and strong), essential water, sanitation and hygiene services (accounting for gender sensitivity), health and nutrition Out of the two hundred and seventeen suitable sites, fourteen sites had to be left out of consideration since they are within the Key Point Installation premises and include National Parliament, Airport, Prime Minister’s Office, various country’s High Commissions/Embassies, and High Court. After that, generalized liquefaction analysis based on geomorphological classes revealed that thirty-seven sites had to be excluded as they exhibited high to very high liquefaction potential. It means only one hundred and sixty-six open spaces were selected as safe sites for long-term shelter establishment. Given that liquefaction may render potential sites unusable due to earthquakes, much importance was emphasized on its effect in the study area. Furthermore, eight sites across the city were selected as a case study for detailed liquefaction potential investigations. Probabilistic seismic hazard assessment and site response analysis were conducted, and all eight sites showed less than 0.15g Peak Ground Acceleration (PGA) value for a ten percent probability of exceedance in fifty years. The results were used to calculate liquefaction potential through deterministic, probabilistic, and artificial neural network approaches. All results stated that the eight sites were safe for post-earthquake shelter placement. The deterministic approach was basically used for safety-based analysis. In contrast, the probabilistic approach is the likelihood of liquefaction, meaning it is probability-based. Still, the artificial neural network approach is more robust than the three approaches and gives realistic results by establishing precise nonlinear relationships. All eight sites revealed a very low (less than five) liquefaction potential index value in an earthquake of 7.5 magnitude scenario with PGA 0.15g. This was followed by establishing standard requirements of the shelters that would be placed in the open spaces, including living space per person (2.3 m2 per person, considering population density), appropriate shelter materials (waterproof, lightweight and strong), essential water, sanitation and hygiene services (accounting for gender sensitivity), health and nutrition items, emergency infrastructures and service facilities, security and cultural considerations, and operation and maintenance of the shelters. The parameters were standardized based on literature review and expert opinions, thus ensuring an ideal model appropriated in the context of the Dhaka Metropolitan Area. Finally, a field demonstration was conducted on the Bangladesh University of Professionals Playground to validate the established model shelter standards. This study gives the main guidelines for identifying and establishing a network of open spaces according to suitability, ensuring the sites are safe and what standards the shelters must maintain to be effective in the post-earthquake scenario. Implementing that will be a significant step towards building an earthquake-resilient Dhaka Metropolitan Area from the viewpoints of response and recovery. This thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy (Ph.D.) in Disaster Science and Climate Resilience.