Salinity intrusion is one of the major problems in coastal regions in Bangladesh which affects crop production and livelihood. This study examines the impact of salinity intrusion from the Pasur River on soil quality and agricultural productivity in the coastal region of Bangladesh. For this study, both water and soil collections and field surveys were carried out in seven unions that are directly impacted by the river in Dacope and Mongla Upazilas. Physicochemical analyses of water and soil samples revealed significant variations in salinity levels, with higher concentrations observed in southern regions’ spatial distribution. A strong positive relationship between water and soil salinity indicates a direct influence of river salinity on soil quality from the Pearson correlation analysis. Survey data from 240 respondents, predominantly farmers, corroborated these results, with widespread recognition of salinity’s detrimental effects on crop yields, especially rice. So, smaller farms focus on vegetables, medium on rice, and larger ones on high-value crops like watermelon. Mitigation strategies such as freshwater irrigation, drainage systems, and salt-tolerant crop cultivation were identified as potential remedies. Additionally, experts suggested implementing sluice gates to control saltwater intrusion from tributary rivers like Chila Khal. These results emphasize the immediate requirement for proactive actions to reduce the negative effects of salt-induced soil degradation and ensure sustainable agricultural practices in the vulnerable region.

Groundwater is one of the world’s most important sources of fresh drinking water. Various contaminants mix with groundwater and alter its natural composition, such as arsenic. This study aimed to ascertain the present condition of arsenic concentration, its spatial pattern, and its relationship with tube well depth in the Gangni Union in the Chuadanga district of Bangladesh. Additionally, the study tried to assess the associated noncarcinogenic health risks imposed by oral ingestion of arsenic. Systematic sampling was used to collect water samples $$(n=100)$$( n = 100 ) along with depth information from the sample tube wells. Water samples were analyzed with the pre-calibrated Hach EZ, Dual-Range Arsenic Test Kit (Range: 0.00–0.5 mg/l). Both geostatistical (spatial autocorrelation, Hotspot analysis, and IDW) and statistical (descriptive and correlation statistics) methods were used. The resultant arsenic content of the samples tested ranges from 0.0004 (mg/l) to 0.10 (mg/l). Arsenic levels in almost 42% of the samples exceeded the WHO standard, 21% exceeded the Bangladesh standard, and 37% were within the tolerable standard. Geostatistical analysis shows that approximately 63% of the total area is arsenic contaminated. Furthermore, hotspot analysis reveals that the northeastern and southeastern parts of the study area are more arsenic-contaminated than the other parts. Noncarcinogenic health risk assessment shows that children have a higher average daily dose (ADD) range (8.33E-06-0.00181) than adults (2.78E-06-0.0006). Similarly, the hazard quotient (HQ) value is also higher for children (0.0277–6.033) than for adults (0.0092–2.011). The result of Pearson’s correlation coefficient, r (98) = − 0.7580, p = 0.000, shows a negative linear relationship between concentration values and depth, meaning that increasing depth will reduce arsenic contamination from tube well water.

Water and vegetation are the two most important land cover features of any natural setting. The Jhenaidah District of Bangladesh is known for its remarkable physical geography, featuring diversified vegetation cover and numerous oxbow lakes. Due to several anthropogenic causes, this majestic land cover is degrading rapidly. This study examines the study area's spatiotemporal water and vegetation cover change from 1990 to 2020. Freeware Satellite imageries from the USGS data archive were used as the main secondary data source, ensuring consistency by collecting dry season images. In addition, open discussions with the residents provided valuable insights into the situation. Remote sensing (RS) based Soil Adjusted Vegetation Index (SAVI) was used to detect the water and vegetation cover from the preprocessed satellite imageries. Furthermore, the water and vegetation cover were classified based on a scheme developed by field observation and discussion with the residents. The analysis reveals an overall 84.47% decline in dense vegetation, 63.01% decline in deep water cover, 185.69% increase in shallow water cover, and 16.08% increase in agricultural lands within the mentioned time frame. Almost all the upazila of Jhenauidah district experience the criticality of the land cover change. Among the upazila, Shailkupa faced an unprecedented decline in deep water (95.29%), and Kaliganj faced a heavy decrease in forested vegetation (92.40%). In contrast, shallow water expanded significantly in Sadar Upazila (251.37%), and agricultural land experienced the most increasing trend (32.70%) in Shailakupa Upazila. JEL Classification Codes: C21, Q24, Q25.

Pipeline water supply, a primary source in urban areas, delivers treated water from water treatment plants (WTPs) directly to consumers. This study comprehensively evaluates water quality in Kushtia Municipality, Bangladesh, focusing on untreated water, treated water, and freely available public water point (PWP) samples. Twelve water samples were collected from March 1 to 7, 2024, and analyzed for physicochemical and microbiological parameters using standard methods. The treatment efficiency, water quality index (WQI), Nemerow pollution index (NPI), and hazard quotient were calculated based on the analytical measurements. Findings indicate that, among the 12 assessed parameters, only three comply with Bangladesh’s water quality standards. The mean cumulative efficiency shows that WTP 2 exhibits the highest treatment efficiency (30.76%), whereas WTP 1 has the lowest (12.34%). While WQI scores classify all treated and PWP samples as “unfit” for consumption, treated water demonstrates comparatively better quality than PWPs. The NPI analysis identifies the primary contributing pollutants in the following order: Biochemical oxygen demand>hardness>alkalinity>iron>temperature>electrical conductivity. The health risk assessment reveals no significant risk of iron ingestion or dermal exposure for adults and children. However, long-term ingestion of arsenic-contaminated water presents a moderate health risk for both groups, while dermal contact poses no risk.

Chalan Beel, Bangladesh’s largest inland wetland, is experiencing rapid ecological degradation under rising anthropogenic pressure. This study examines spatiotemporal land use/land cover (LULC) change and associated landscape ecological risk from 2000 to 2023 using multispectral satellite imagery for 2000, 2010, and 2023. After preprocessing, images were classified in ENVI 5.3 into five classes: deep water, shallow water, agricultural land, settlement–vegetation mix, and vegetation. LULC transitions were quantified for 2000–2010, 2010–2023, and 2000–2023 using Change Detection Statistics and the Thematic Change Workflow. Landscape ecological risk was then evaluated in Fragstats 4.2 using an ecological risk index and categorized from lowest to highest. Results show substantial LULC change over the study period: around 40% of vegetation cover was converted to settlement–vegetation mixed areas (indicative of rural settlement expansion), 22.88% of deep water shifted to shallow water, and 31.83% of shallow water converted to agricultural land; agricultural land also showed a 28.76% conversion to rural settlements. During 2000–2010, major transitions included vegetation to rural settlements (41.63%), agricultural land to rural settlements (28.78%), and deep water to shallow water (23.76%). From 2010–2023, key changes were deep water to shallow water (31.67%) and shallow water to agricultural land (28.29%). Ecological risk varied over time, and by 2023 more than half of the area fell into the middle-to-high risk classes. High-risk zones are concentrated in the southeast and northwest, whereas low-risk zones are mainly in the central and northern parts, indicating an overall increase in ecological risk.