Research

This study assesses the sector-wise vulnerability and resilience of the island Hizla in Barishal, Bangladesh, a disaster-prone region. The research methodology involved conducting a questionnaire survey informed by a literature review with minor adjustments. Analysis of twenty-five vulnerability and capability markers indicates that the region faces higher vulnerability than capability in disaster response. 

Vulnerability is particularly pronounced in health issues, followed by ecosystem, shelter and settlement, and socioeconomic factors. However, the region demonstrates relatively stronger capability in WASH-related indicators. Furthermore, positive mitigation actions were observed, highlighting the importance of sector-specific disaster resilience strategies. Read the full article here.

The study analyzes climatological data from 1961 to 2019 in Barishal, Bangladesh, revealing significant trends. The yearly average maximum temperature has been increasing at 0.0055 ºC per year, reaching 30.38 ºC. The yearly average minimum temperature has risen by 0.0087 ºC per year to 21.29 ºC. Wind speed trends have shown a negligible increase of 0.001783 m/s per year, reaching an average of 2.149 m/s. Similarly, the average relative humidity has escalated by 0.342975 per year, reaching 70.855% at 2 meters.

Furthermore, rainfall patterns show a decrease in winter at an average rate of -0.01293 mm/year, and in the pre-monsoon and monsoon periods at rates of -0.01997 mm/year and -0.58508 mm/year, respectively. Conversely, post-monsoon rainfall has increased at an average rate of 0.11025 mm/year. These findings highlight the changing climatic conditions in Barishal and underscore the importance of adaptation strategies. Read the full article here.

The study employs the Statistical DownScaling Model (SDSM) to assess potential climate change impacts on temperature and precipitation in south-central Bangladesh under three Representative Concentration Pathways (RCPs: 2.6, 4.5, and 8.5), utilizing the CanESM2 General Circulation Model for downscaling. Results indicate that SDSM effectively downscales daily mean temperature and precipitation projections for the early, mid, and late twenty-first centuries. Under the RCP 8.5 scenario, an increase in both mean annual temperature and precipitation is expected, except in Barishal, where annual precipitation is projected to decrease despite a rise in mean temperature. The Khepupara weather station anticipates the most significant rainfall increase (585.09 mm) by the 2080s, while maximum temperatures could rise by 1.001°C at Patuakhali. The findings highlight the critical vulnerabilities of Barishal and Bhola districts, underscoring the need for targeted adaptation strategies to address the anticipated climate impacts.

This study aimed to assess the spatiotemporal morphological change, pattern and rate of shoreline movements, and erosion-accretion scenarios of the Bhasan Char Island using a combined approach of remote sensing, GIS, seismic, and DSAS techniques. The expected benefits from this research project include (a) Quantifying the spatiotemporal growth of the Bhasan Char Island and (b) Identifying the suitability and stability of this Island as an accommodation for the Forcibly Displaced Myanmar Nationals (FDMN). 

This project aimed to establish a comprehensive vulnerability mapping approach, illuminating the intricate spatial distribution of vulnerability in the expansive western coastal zone of Bangladesh, covering 9041 square kilometers. Beyond its immediate scope, the project played a pivotal role in advancing sustainable technology development, offering a Coastal Vulnerability Index (CVI) tailored for the Western Coast of Bangladesh. This index provides crucial insights into vulnerability, serving decision-makers and planners in coastal management. Beyond its direct impact, the project is poised to transcend its boundaries, becoming a guiding framework for future studies and offering insights for addressing multifaceted challenges posed by coastal vulnerability.

Rapid population growth with socio-economic development leads to the expansion of every urban city and town in Bangladesh, resulting in a vast change in Land Use and Land Cover (LULC) dynamics. This study evaluates the pattern of LULC changes in the Barishal City Corporation (BCC) area and its social and environmental impacts. Landsat satellite images from 1980 to 2020 with five/ten years intervals were used to classify the BCC area into six LULC classes based on maximum likelihood supervised classification. Changes between two separate classified images were detected using a Post-Classification Comparison (PCC) technique. Overall Accuracy and Kappa Coefficient for all the classified images were calculated considering 125 ground control points selected by a stratified random sampling method to perform the accuracy assessment. 

This study is driven by a set of primary objectives that intertwine to provide a comprehensive understanding of riverbank dynamics. The foremost goal was to identify areas vulnerable to erosion along both sides of the river, highlighting regions in urgent need of intervention. Concurrently, the study aims to track bank line changes spanning the last five decades, offering a historical perspective on riverbank alterations. Exploring the geotechnical properties of bank materials adds a layer of insight into erosion processes, contributing to a holistic comprehension. Lastly, by identifying factors contributing to bank instability, the study aspires to provide a well-rounded assessment of underlying causes. Together, these objectives form a cohesive framework that enriches our understanding of riverbank behavior and informs the implementation of effective management and mitigation strategies.

Solid waste, originating from households, industries, and businesses, poses a global environmental concern. Fueled by population growth and economic advancement, waste generation presents challenges worldwide, including in Bangladesh. The country, marked by dense urbanization and rapid population expansion, grapples with waste management due to limited resources and public awareness. Globally, innovative waste management techniques, including recycling, composting, combustion, and landfilling, have emerged. The fusion of Geographic Information System (GIS), Remote Sensing (RS), and Multi-Criteria Decision Analysis (MCDA) has proven effective in global landfill site selection. Remarkably, these tools are underutilized in Barishal, a coastal city prone to disasters. This project assessed current waste disposal practices and identified suitable landfill locations using GIS and RS-based MCDA, contributing to Barishal's waste management and environmental sustainability.