Md. Bodrud-Doza

Characterization of groundwater quality using water evaluation indices, multivariate statistics and geostatistics in central Bangladesh

Abstract This study investigates the groundwater quality in the Faridpur district of central Bangladesh based on preselected 60 sample points. Water evaluation indices and a number of statistical approaches such as multivariate statistics and geostatistics are applied to characterize water quality, which is a major factor for controlling the groundwater quality in term of drinking purposes. The study reveal that EC, TDS, Ca2+, total As and Fe values of groundwater samples exceeded Bangladesh and international standards. Ground water quality index (GWQI) exhibited that about 47% of the samples were belonging to good quality water for drinking purposes. The heavy metal pollution index (HPI), degree of contamination (Cd), heavy metal evaluation index (HEI) reveal that most of the samples belong to low level of pollution. However, Cd provide better alternative than other indices. Principle component analysis (PCA) suggests that groundwater quality is mainly related to geogenic (rock–water interaction) and anthropogenic source (agrogenic and domestic sewage) in the study area. Subsequently, the findings of cluster analysis (CA) and correlation matrix (CM) are also consistent with the PCA results. The spatial distributions of groundwater quality parameters are determined by geostatistical modeling. The exponential semivariagram model is validated as the best fitted models for most of the indices values. It is expected that outcomes of the study will provide insights for decision makers taking proper measures for groundwater quality management in central Bangladesh.

Assessing groundwater quality and its sustainability in Joypurhat district of Bangladesh using GIS and multivariate statistical approaches

Sustainable groundwater quality is a key global concern and has become a major issue of disquiets in most parts of the world including Bangladesh. Hence, the assessment of groundwater quality is an important study to ensure its sustainability for various uses. In this study, a combination of multivariate statistics, geographical information system (GIS) and geochemical approaches was employed to evaluate the groundwater quality and its sustainability in Joypurhat district of Bangladesh. The results showed that the groundwater samples are mainly Ca–Mg–HCO3 type. Principal component analysis (PCA) results revealed that geogenic sources (rock weathering and cation exchange) followed by anthropogenic activities (domestic sewage and agro-chemicals) were the major factors governing the groundwater quality of the study area. Furthermore, the results of PCA are validated using the cluster analysis and correlation matrix analysis. Based on the groundwater quality index (GWQI), it is found that all the groundwater samples belong to excellent to good water quality domains for human consumption, although iron, fluoride and iodide contaminated to the groundwater, which do not pose any significant health hazard according to World Health Organization’s and Bangladesh’s guideline values. The results of irrigation water quality index including sodium adsorption ratio (SAR), permeability index and sodium percentage (Na %) suggested that most of the groundwater samples are good quality water for agricultural uses. The spatial distribution of the measured values of GWQI, SAR, Fe (iron), EC (electrical conductivity) and TH (total hardness) were spatially mapped using the GIS tool in the study area.

Spatio-Temporal Assessment of Groundwater Quality and Human Health Risk: A Case Study in Gopalganj, Bangladesh

A set of hydrochemical analysis, drinking water evaluation indices along with multivariate statistics and geostatistical model are applied to evaluate the groundwater quality of Gopalganj District, Bangladesh. A total of 46 groundwater samples are analyzed for the pre and postmonsoon seasons to assess the possible consumptive human health risk among the adults and children of the study area. It is found that most of the studied hydrochemical parameters (pH, EC, TDS, Na+, Cl−, HCO3−, CO3−, As, Mn, Fe, B, NO3−, etc.) exceeded the limits stipulated by different standards for drinking water. From multivariate statistical analysis, high-salinity characteristic of groundwater resulting from seawater intrusion is observed. Spatial extensions of EC, Cl−, As, Fe, and Mn vary significantly around the study area. Strong, moderate, and weak spatial dependences are found for both seasons. The exponential semivariogram model is found to be dominant when considering the best-fit model analyzed for both seasons. In addition, mean Hazard Quotient and Hazard Index values based on As, Fe, Mn, B, NO3−, and F− imply that the groundwater poses substantial health risk for both adults and children and fluctuates in accordance with seasonal variation. The carcinogenic risk among adults and children due to As is high in the study area during both seasons. The groundwater of the study area was characterized by high salinity possessing high level of noncarcinogenic as well as cancer-risk (As) vulnerability of the local community.

Evaluation of Water Quality for Sustainable Agriculture in Bangladesh

Sustainable groundwater quality has become a major concern for the agro-based country like Bangladesh. Integrated approaches of various irrigation water quality indices and geostatistical modeling were applied to evaluate the suitability and for spatial mapping of groundwater quality of Faridpur District in central Bangladesh. The irrigation water quality index (IWQI) revealed that majority of the samples were suitable for irrigation. Similar outcomes were recorded from other indices including Na%, sodium adsorption ratio (SAR), residual sodium bicarbonate (RSBC), total hardness (TH), Kelley’s ratio (KR), and magnesium adsorption ratio (MAR). Classifications based on Wilcox diagram and permeability index (PI) plot indicated a similar conclusion wherein almost all the samples were safe for agricultural uses without posing considerable effect on the soil fertility and overall crop yield. Principal component analysis (PCA) grouped the major cations and anions into three principal components including dissolution of calcite minerals, leaching of silicate sediments, and ion exchange process. Spatial mapping of IWQI identified that groundwater in the northern side of Faridpur region were more suitable for irrigational uses relative to central and southern side, possibly due to gradients of domestic discharges and agricultural activates from north to south side. These findings would provide useful information to water distributors, managers, and decision makers for taking adaptive measures in irrigation water quality management systems.

Characterizing groundwater quality ranks for drinking purposes in Sylhet district, Bangladesh, using entropy method, spatial autocorrelation index, and geostatistics

Drinking water is susceptible to the poor quality of contaminated water affecting the health of humans. Thus, it is an essential study to investigate factors affecting groundwater quality and its suitability for drinking uses. In this paper, the entropy theory, multivariate statistics, spatial autocorrelation index, and geostatistics are applied to characterize groundwater quality and its spatial variability in the Sylhet district of Bangladesh. A total of 91samples have been collected from wells (e.g., shallow, intermediate, and deep tube wells at 15–300-m depth) from the study area. The results show that NO3−, then SO42−, and As are the most contributed parameters influencing the groundwater quality according to the entropy theory. The principal component analysis (PCA) and correlation coefficient also confirm the results of the entropy theory. However, Na+ has the highest spatial autocorrelation and the most entropy, thus affecting the groundwater quality. Based on the entropy-weighted water quality index (EWQI) and groundwater quality index (GWQI) classifications, it is observed that 60.45 and 53.86% of water samples are classified as having an excellent to good qualities, while the remaining samples vary from medium to extremely poor quality domains for drinking purposes. Furthermore, the EWQI classification provides the more reasonable results than GWQIs due to its simplicity, accuracy, and ignoring of artificial weight. A Gaussian semivariogram model has been chosen to the best fit model, and groundwater quality indices have a weak spatial dependence, suggesting that both geogenic and anthropogenic factors play a pivotal role in spatial heterogeneity of groundwater quality oscillations.

An investigation of coastal vulnerability and internal consistency of local perceptions under climate change risk in the southwest part of Bangladesh

Climatic threats force disruption on community lifestyles by impairing social factors, the fundamental components of ensuring social sustainability. This study investigates the situational factors affecting the consequences on coastal livelihoods, and social activities; it also considers the effectiveness of traditional knowledge in reducing possible risks. Both qualitative and quantitative methods were employed, including questionnaire survey for identifying the local perception of climatic impacts alongside the impacts on daily activities. Interviews, field observations, and multivariate analyses were performed to explain the vulnerability status in coastal communities. Results show that most livelihood sectors were severely affected by the long-term and repeated actions of climatic hazards, such as cyclones, associated with a number of unavoidable risks making people susceptible to damages in social wellbeing. In addition, saltwater intrusion damages drinking water supply and crop farming, which can cause diseases among coastal communities, but very few attempts have been made to provide alternative sources of drinking water at a household level. Moreover, principal component analysis (PCA) and cluster analysis (CA) revealed significant interfaces between local perceptions and the socio-and agro-environmental factors changing the overall status of regional hazards. Thus, the situation exhibits coastal hazards, social vulnerability, and social crisis. Local people use their traditional knowledge to cope with various levels of crisis under vulnerable conditions, but sometimes doing so exceeds their capacity owing to the unwanted changes in climatic variables and knowledge gaps or uncertainties. Challenges on the basis of the problematic points should be noted, however, it would be more significant to achieve social sustainability under adverse climatic conditions.

Assessment of arsenic health risk and source apportionment of groundwater pollutants using multivariate statistical techniques in Chapai-Nawabganj district, Bangladesh

This study assessed arsenic health risk to the local residents through oral and dermal exposure pathways of drinking water and to investigate source apportionment of groundwater pollutants using multivariate statistical techniques in the Chapai-Nawabganj district, Bangladesh. Groundwater samples collected from shallow tube well and dug well at the depth ranges (15-60 m) were analyzed for physio-chemical parameters and trace elements. Most of the studied physio-chemical parameters were found within their respective permissible limits. However, total As, Fe and Mn concentrations exceeded Bangladesh and WHO guideline values. The assessment of arsenic health risk reveals that children as compared to adults are found at a higher risk as the values of hazard quotients (HQ) >1 in the most of the groundwater samples. This level of arsenic contamination should have medium to high chronic risk and medium carcinogenic risk when compared with US EPA guidelines which can cause serious health hazard. The results of principal component analysis (PCA) and factor analysis (CA) indicate that geogenic (interaction of water and basement rock) and anthropogenic (agrochemicals, agricultural fertilizer and domestic sewage) sources are responsible for variation in arsenic and other physio-chemical parameters in the groundwater aquifer of the study area. Furthermore,the inter-correlation of arsenic with metals and ions were also calculated by correlation matrix and linear regression analysis. The outcomes of this study will help to meet the challenge of sustainable groundwater quality management in Bangladesh and enhancing better vision of potential health risk of local inhabitants in the study area.