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Flood is one of the most common hazards in many countries, affecting both life and properties. The recent climatic changes have brought a rise in both flood frequency and intensity making this phenomenon more devastating to people. Especially, the riparian communities of Jamalpur along the Jamuna river suffer at least once every year accounting for this natural hazard. In a scenario like this, precaution is a crucial task to fight against this natural phenomenon. Therefore, this study attempts to identify the flood vulnerable zones of Jamalpur district situating beside Jamuna river with a multi-criteria analysis. Assessment of flood vulnerability included consideration of physical indicators like rainfall, drainage density, distance from river, slope, land use land cover, elevation, soil classes as well as social indicators like population density, female density, literacy rate, number of shelters, unmetalled road and number of health personnel. All these parameters were analyzed in Geographic Information System (GIS) and assigned weightage with a multi-criteria decision-making technique namely- Analytic Hierarchy Process (AHP). Finally, a flood vulnerability map was generated for the seven Upazilas of Jamalpur district. Very high, high, moderate and low vulnerable zones were identified after overlaying all physical and social indicator maps under consideration. 45.96% portion of a total of 2115.2 sq. Km. Area was under very high and highly vulnerable zones in the final vulnerability map of Jamalpur. Such type of assessment process is significant for flood mitigation projects with a view to providing the greatest concern to the most vulnerable zones. The vulnerability maps can also help the policymakers to provide emergency aids and other privileges to those who are in most need of it.

Solid waste generation is rising consequently with the increasing population growth in Sylhet city. Mogla Bazar, an only dumping zone is affecting the surrounding environment enormously. This study aims to determine the surface water quality of the adjacent water bodies that lie within the 500 m buffer zone of the landfill utilizing multivariate statistical methods. Physicochemical and microbial parameters along with anions were considered for evaluating water quality. Multivariate statistical techniques viz. Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) were applied to assess the water quality. Besides, the Pearson correlation matrix was performed to detect the interrelation among the variables and water quality index (WQI) was also used to classify the pollution sources. All the parameters were compared with the established acceptable limit given by the World Health Organization (WHO)/ Bureau of Indian Standards (BIS). PCA/FA resulted in three principal components with a total variance of 59.89 % and 57.14 % for haor and fishing zone, wetland respectively. Factor analysis derived from principal components shows that organic substances, anthropogenic activity, fertilization, chemical waste, and wastewater runoff are responsible for deteriorating the water quality. CA and WQI detect that sampling sites of haor and fishing zone that lies on the 200 m buffer zone were highly susceptible to water pollution. Besides, topographical variation, changes in slope, and seasonal variation were also treated as an influencing factor. Finally, all the analysis implied that the declining water quality would be dangerous to the neighbourhood of the landfill and there is a high chance of exposure to the dwellers residing nearby.