Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization

The study area is located in the southwestern part of Bangladesh. Twenty-six groundwater samples were collected from both shallow and deep tube wells ranging in depth from 20 to 60 m. Multivariate statistical analyses including factor analysis, cluster analysis and multidimensional scaling were applied to the hydrogeochemical data. The results show that a few factors adequately represent the traits that define water chemistry. The first factor of Fe and HCO₃ is strongly influenced by bacterial Fe (III) reduction which would raise both Fe and HCO₃ concentrations in water. Na, Cl, Ca, Mg and PO₄ are grouped under the second factor representing the salinity sources of waters. The third factor, represented by As, Mn, SO₄ and K is related to As mobilization processes. Cluster analysis has been applied for the interpretation of the groundwater quality data. Initially Piper methods have been employed to obtain a first idea on the water types in the study area. Hierarchical cluster analysis was carried out for further classification of water types in the study area. Twelve components, namely, pH, Fe, Mn, As, Ca, Mg, Na, K, HCO₃, Cl, SO₄ and NO₃ have been used for this purpose. With hierarchical clustering analysis the water samples have been classified into 3 clusters. They are very high, high and moderately As-enriched groundwater as well as groundwater with elevated SO₄.     

Understanding indigenous people’s perception on climate change and climatic hazards: a case study of Chakma indigenous communities in Rangamati Sadar Upazila of Rangamati District, Bangladesh

This study explores the relationship between perception on climate change as well as climatic hazards and socio-demographic characteristics such as age, gender, occupation, exposure to mass media, amount of land, education, and income. Following simple random sampling technique, a total of 384 households were sampled from Rangamati Sadar Upazila of Bangladesh and were interviewed through a predesigned semistructured questionnaire. The findings of the study reveal that a substantial number of respondents (61 %) perceive that climate is changing moderately over the years. The bivariate results indicate that age, gender, education, occupation, income, amount of land, and access to mass media are significantly associated with perception on climate change as well as climatic hazards. In addition, age, education, and exposure to mass media are also found as significant predictors of climate change perception. Education has been found as the single best predictor.     

The use of watershed geomorphic data in flash flood susceptibility zoning: a case study of the Karnaphuli and Sangu river basins of Bangladesh

Natural Hazards - The occurrence of heavy rainfall in the south-eastern hilly region of Bangladesh makes this area highly susceptible to recurrent flash flooding. As the region is the commercial...     

Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region

Natural Hazards - The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of...     

Exploring disaster preparedness of students at university in Bangladesh

Natural Hazards - Adequate and effective disaster preparedness in each sector is indispensable to abate disaster impacts and intensify disaster resilience in Bangladesh for achieving sustainable...     

Decision support for infrastructure planning: a comprehensive location–allocation model for fire station in complex urban system

Natural Hazards - Infrastructures are the most important aspect of any urban system. Properly planned infrastructures are critical for ensuring services and protecting an urban system from...     

Site amplification investigation in Dhaka, Bangladesh, using H/V ratio of microtremor

The degree of damage during earthquakes strongly depends on dynamic characteristics of buildings as well as amplification of seismic waves in soils. Among the other approaches, microtremor is, perhaps, the easiest and cheapest way to understand the dynamic characteristics of soil. Non-reference microtremor measurements have been carried out in 45 locations in and around the capital Dhaka city of Bangladesh. Subsoil investigations (Standard Penetration Test and Shear Wave Velocity) have also been executed in those locations. Soil model has been developed for those locations for site response analysis by means of the program SHAKE. Among those 45 locations, predominant frequency of microtremor observation varies from 0.48 to 3.65 Hz. Out of those 45, for 35 locations Transfer function obtained from the program SHAKE have higher frequency compared to microtremor H/V ratio and for one location it has lower predominant frequency. For six locations, frequencies obtained from two methods are identical. For three other locations, there are no similarities between predominant frequency obtained from microtremor and transfer function. The seismic Vulnerability Index (Kg) for 45 sites varies between 0.45 and 31.85. Ten sites have been identified as having moderate vulnerability of soil layers to deform.     

Community-based disaster risk and vulnerability models of a coastal municipality in Bangladesh

Bangladesh is one of the most natural hazard-prone countries in the world with the greatest negative consequences being associated with cyclones, devastating floods, riverbank erosion, drought, earthquake, and arsenic contamination, etc. One way or other, these natural hazards engulfed every corner of Bangladesh. The main aim of this research paper is to carry out a multi-hazards risk and vulnerability assessment for the coastal Matlab municipality in Bangladesh and to recommend possible mitigation measures. To this aim, hazards are prioritized by integrating SMUG and FEMA models, and a participation process is implemented so as to involve community both in the risk assessment and in the identification of adaptation strategies. The Matlab municipality is highly vulnerable to several natural hazards such as cyclones, floods, and riverbank erosion. The SMUG is a qualitative assessment, while FEMA is a quantitative assessment of hazards. The FEMA model suggests a threshold of highest 100 points. All hazards that total more than 100 points may receive higher priority in emergency preparedness and mitigation measures. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the SMUG system. The spatial distributions of hazard, risk, social institutions, land use, and other resources indicate that the flood disaster is the top environmental problem of Matlab municipality. Hazard-specific probable mitigation measures are recommended with the discussion of local community. Finally, this study tries to provide insights into the way field research combining scientific assessments tools such as SMUG and FEMA could feed evidence-based decision-making processes for mitigation in vulnerable communities.