Post-monsoon Period Research Articles

Psychological health declined during the post-monsoon season in communities impacted by sea-level rise in Bangladesh

Sea level rise affects the long-term psychological health of coastal communities. However, research on long-term and seasonal impacts on vulnerable communities’ psychological health is limited. Here, we explore the effect of sea-level rise on the psychological health of the coastal population in Satkhira and Khulna districts of southwest Bangladesh across two seasons: before monsoon (March to April) and post-monsoon months (October to November) in 2021. We leveraged the longitudinal research that involved 1144 participants. We collected data on psychological health using established scales for distress, depression, anxiety, and stress and also measured environmental factors and resource losses. Results indicate that psychological health, particularly distress, depression, anxiety, and stress, increased during the post-monsoon months in communities more vulnerable to sea-level rise. Highly vulnerable communities showed increased psychological distress post-monsoon. Environmental stressors and resource loss escalated during the post-monsoon period, especially in moderate and highly vulnerable communities. Our findings emphasize the urgent need for targeted support and resilience-building interventions in affected communities to alleviate the psychological health impacts of sea-level rise.

Variation characteristics and the influences of urbanization on hourly intense precipitation before and after monsoon onset over the Pearl River Delta.

The distinct spatiotemporal characteristics of the hourly intense precipitation (HIP) over the Pearl River Delta (PRD) and the impact of urbanization before and after the monsoon onset from 1972 to 2021 have been investigated using the hourly rain gauge data, nighttime lights data, and land use data. The results show a significant decreasing trend of HIP during the pre-monsoon onset period and a notable increasing trend during the post-monsoon onset period over the past five decades. However, compared to rural areas, rapid urbanization in the PRD after the mid-1990s weakens the HIP reduction, especially in the inland cities of PRD before the onset of the monsoon and enhances the HIP increase, particularly in the southeast inland and west coast cities after the onset of the monsoon. After rapid urbanization, the peak time of HIP has been postponed from 14 LST to 17 LST during the pre-monsoon onset period. HIP tends to occur more frequently in urban areas in the morning (10-12 LST) and evening (19-24 LST) compared to rural areas. In contrast, the impact of urbanization on the diurnal variation of HIP is not obvious during the post-monsoon period, despite higher frequencies of HIP occurring during the daytime (10-15 LST) in the urban areas after rapid urbanization. These findings provide valuable insights for forecasting HIP in urban agglomerations.

Multivariate statistical and hydrogeochemical analysis of seasonal groundwater quality variations in coastal villages of Trivandrum district, south India

This study attempts a detailed assessment of the quality of groundwater in the coastal region of Trivandrum District, Kerala where groundwater is the main source of drinking water. Forty groundwater samples were collected during the pre-monsoon and post-monsoon periods. The collected samples were analyzed for physical properties such as electrical conductivity (EC), pH, total dissolved solids (TDS), and total hardness, along with chemical properties, including major cations (Ca2⁺, Mg2⁺, Na⁺, K⁺) and anions (Cl⁻, SO₄2⁻, HCO₃⁻, NO₃⁻). The analysis of groundwater quality reveals significant spatial and seasonal variations caused by both natural and manmade influences. Water Quality Index (WQI), hydrogeochemical plots, and Principal Component Analysis (PCA) were used to analyses the data. The results show that Vakkom, Kazhakottam, Veli-Attipara, and Pozhiyoor show significant deterioration, and areas such as Varkala, Ayroor, and Edava generally maintain good water quality. The Water Quality Index (WQI) assessment indicates that approximately 22.5% of the studied area falls under excellent quality, while 17.5% is classified as poor. The WHO standard and BSI standards were used to derive the WQI. Principal Component Analysis (PCA) identified electrical conductivity, total dissolved solids, and total hardness as the primary factors affecting groundwater quality, explaining 65.17% and 61.03% of the total variance in the pre-monsoon and post-monsoon periods, respectively. Hydrochemical plots collaborate these results, emphasize the influence of rock-water interactions as the main geochemical process, further compounded by pollution from agricultural runoff and urban development. These findings highlight the need for sustainable groundwater management strategies in coastal communities. Effective measures, including pollution mitigation, sustainable agricultural practice, proper waste management, and preservation of freshwater ecosystems, are essential for ensuring the sustainability of groundwater resources.

Application of geospatial and machine learning algorithms to predict (under certain limitations) the quality of groundwater used for irrigation purposes

ABSTRACT The main objective of the present study is to evaluate groundwater quality for irrigation purposes in the central-western part of Haryana state (India). For this, 272 groundwater samples were collected during the pre- and post-monsoon periods in 2022. Several indices, including SAR, PI, Na%, KR, magnesium adsorption ratio (MAR), and IWQI were derived. The results of SAR, Na%, and KR values indicate that the groundwater is generally suitable for irrigation. On the other hand, PI and MAR exceeded the established limits, primarily showing issues related to salinity and magnesium content in the groundwater. Furthermore, according to the IWQI classification, 47.06 and 25% of the total collected samples fell under the ‘severe restriction for irrigation’ category during the pre-monsoon and post-monsoon periods, respectively. Spatial variation maps indicate that water quality in the western portion of the study area is unsuitable for irrigation during both periods. Three ML algorithms, namely RF, SVM, and XGBoost were integrated and validated to predict the IWQI. The results revealed that the XGBoost with random search achieves the best prediction performances. The approaches established in this study have been confirmed to be cost-effective and feasible for groundwater quality, using hydrochemical parameters as input variables, and highly beneficial for water resource planning and management.

Seasonal vertical accretion in different hydro-geomorphic environments of Indian Sundarban: Assessing the role of mangroves in mitigating sea level rise impacts

The Indian Sundarban, renowned for its unique hydro-geomorphic diversity, faces rising threats from sea level rise, necessitating an examination of the spatio-temporal variation of vertical accretion and the role played by mangroves in mitigating these impacts. As such, fifteen transects were chosen across buffer and transition zones of Indian Sundarban, each equipped with 4–6 sedimentation pins, to gauge accretion rates in premonsoon, monsoon, and postmonsoon season during period March 2020 to March 2022, considering diverse hydro-geomorphic attributes. The vertical accretion rate exhibits a curvilinear pattern, ascending from the lower seafront zone towards the middle of the estuarine region, reaching a peak, and subsequently declining towards the upper estuarine zones. Specifically, in the seafront zone, the yearly mean accretion (focusing solely on accretion and excluding subsidence) ranges between 5 and 10 mm/year, while in the middle estuarine region, it increases to an average of 38.1 ± 9.44 mm/year. However, in the upper zone, the yearly mean accretion decreases slightly to approximately 17.71 ± 9.54 mm/year. Similar patterns are observed when considering the distance from the riverfront to the interior of the mangrove zones. Seasonal analysis demonstrates that the postmonsoon period exhibits the highest accretion, followed by the premonsoon season, while the monsoon tends to be erosional in nature. Mangrove zonation, and subsequent distribution of root height, root diameter, root density, tree density, tree basal area, inundation frequency, current speed, variation in suspended sediment concentration were identified as influential factors affecting vertical accretion rates. Based on multiple regression analysis, root density, inundation frequency, and tree density demonstrated moderate-positive correlations with vertical accretion, whereas distance from the riverfront, root height, and root diameter displayed negative correlations. This study enhances our understanding of the intricate processes behind vertical accretion in the Sundarban, offering valuable insights for future research and advancing discussions on the broader implications of climate change in coastal regions.

Insights into the seasonal variation, distribution, composition and dynamics of microplastics in the Ganga River ecosystem of Varanasi City, Uttar Pradesh, India.

The current study explores the seasonal dynamics of microplastic (MP) pollution in the Ganga River of Varanasi City, Uttar Pradesh, India, focusing on water and sediment samples collected during pre-monsoon and post-monsoon periods. The analysis shows significant variations in MP occurrence, shape dynamics, color distribution, and size composition across diverse sampling sites. During the pre-monsoon season, MP concentrations ranged from 17 to 36 particles/L in water samples and 160 to 312 particles/kg in sediment, indicating a moderate to high level of contamination. Post-monsoon sampling showed higher MP concentrations at most sites, indicating the influence of seasonal hydrological changes on MP distribution. Shifts in MP shape dynamics were observed between seasons, with films, foams, fragments, and filaments showing variable distributions. Similarly, color variations in MPs exhibited site-specific patterns, with white, brown, blue, and other colors being predominant. These findings highlight the diverse sources and compositions of MPs in the river ecosystem, highlighting the complexity of MP pollution dynamics. Polymer-type distributions further elucidated the composition of MPs, with notable contributions from polyethylene terephthalate, rayon, polyester, and polyvinyl chloride. PCA analysis revealed significant shifts in particle size and shape distribution between pre-monsoon and post-monsoon periods in both water and sediment samples, with post-monsoon samples showing an increase in larger particles and filaments. These changes highlighted key factors driving the variance in microplastic contamination across different sites. The prevalence of these polymers features diverse sources of MP pollution, including textiles, packaging materials, and industrial waste. Ongoing monitoring and research are crucial to understanding its sources, distribution, and impact on river ecosystems, essential for protecting aquatic biodiversity and human health.

Seasonal Dynamics and Avian Diversity along the Adyar Riverbank: Insights from a Year-Long Survey

The avian survey conducted along the Adyar Riverbank (Manapakkam) from January 2023 to December 2023 documented a total of 3120 individual birds across 75 species from 16 avian orders, highlighting the significant biodiversity within this urban ecosystem. This study aimed to assess seasonal variations in bird diversity and abundance, emphasizing the river’s role as an important habitat. The highest diversity was observed during winter, specifically in February 2023, with a diversity index of 296.80 and a Simpson’s index of 0.22. A total of 36 species and 636 individuals were recorded. In contrast, the lowest diversity was observed in summer, particularly in July 2023, with a diversity index of 29.29 and a Simpson’s index of 0.05, corresponding to 18 species and 114 individuals. The monsoon and post-monsoon periods exhibited a prominent increase in diversity due to the arrival of migratory species and improved habitat conditions. Important species recorded throughout the year included the Paddy Field Pipit, House Crow, and Rufous Treepie, while conservation-significant species such as the Black-headed Ibis and Spot-billed Pelican were also observed. Thus, the present study underscores the Adyar River’s ecological importance and highlights the need for continuous monitoring and targeted conservation efforts to maintain avian biodiversity in urban river ecosystems.

Influence of future climate scenarios using CMIP 5 data on malaria transmission in India

BackgroundVector-borne diseases, such as malaria, pose a significant global threat, and climatological factors greatly influence their intensity. Tropical countries, like India, are particularly vulnerable to such diseases, making accurate estimation of malaria risk crucial.MethodsThis study utilized the well-known Vector-borne Disease Community Model, VECTRI, developed by the International Centre for Theoretical Physics in Trieste. The model was implemented to estimate malaria’s Entomological Inoculation Rate (EIR). Future climatic prediction datasets, including CMIP 5 and population data sets, were used as inputs for the analysis. Three RCP scenarios are considered (Representative Concentration Pathways are climate change scenarios that project radiative forcing to 2100 due to future greenhouse gas concentrations). The projections covered the period from 1 Jan, 2020, to 31 Dec, 2029.ResultsThe estimated mean EIR for the years 2020–2029 ranged, and a significant decline in malaria risk was observed with all RCP 2.6, 4.5, and 8.5 scenarios. Each year 0.3 to 2.6 [min–max] EIR/person/day decline is observed with a strong decline in man rainfall ranging from 5 to 17 [min–max] mm/year and associated high temperatures ranging from 0.03 to 0.06 [min–max] °C/year. During the post-monsoon period, August to November were identified as highly prone to malaria transmission. Spatial analysis revealed that the east coast of India faced a higher vulnerability to malaria risk, which kept increasing through RCP scenarios. Thus, it is essential to exercise caution, especially in areas with heavy rainfall.ConclusionThis research provides valuable insights for policy-makers, highlighting the need to implement future strategies to mitigate malaria risk effectively. By utilizing these findings, appropriate measures can be taken to combat the threat posed by malaria and protect public health.

Prevalence of canine renal insufficiency: A decade-long retrospective study in and around Patna, Bihar

This retrospective study investigates the prevalence and epidemiological factors associated with renal insufficiency in dogs within Patna, Bihar, India. Out of 5,700 dogs with various illnesses, 317 were diagnosed with renal insufficiency, identified by serum creatinine levels exceeding 5 mg/dL. The study assessed the incidence of renal insufficiency across different demographics, including age, sex, breed, and season. The highest incidence was observed in dogs aged 8-10 years, with males showing a higher prevalence than females. Pomeranians (32.18%), Labrador Retrievers (25.55%), and German Shepherds (20.82%) were the most affected breeds. Seasonally, the post-monsoon period (September-November) exhibited the highest incidence (37.85%) of renal disorders. Laboratory investigations revealed significant haematological and biochemical alterations in affected dogs, including lower haemoglobin, total erythrocyte count, and packed cell volume, alongside elevated serum levels of blood urea nitrogen (BUN), creatinine, potassium, and phosphorus. Ultrasonography indicated decreased renal size and increased echogenicity in dogs with renal insufficiency. The study concludes that renal insufficiency in dogs is most prevalent in older males and certain breeds, particularly during the post-monsoon season. Regular monitoring of serum BUN and creatinine levels is recommended for early diagnosis and management of this condition.

Seasonal variability of microplastic contamination in marine fishes of the state of Gujarat, India.

Seasonal variation in microplastics abundance, occurrence, and distribution in pelagic and demersal fishes was observed in this study during December 2021 to November 2022. One hundred percent presence of microplastic in inedible (gut and gills) tissue, while 82% and 54% in edible tissue (muscle) of pelagic and demersal fishes respectively were seen. Post-monsoon period showed high prevalence of microplastics followed by monsoon and the least during pre-monsoon in both pelagic and demersal fishes. In pelagic fishes, the edible tissue had microplastics abundance of 1.56 to 13.34 numbers per 10g of tissue whereas inedible tissue had 3.36 to 16.67 numbers per 10g of tissue. In demersal fishes, the edible tissue had microplastics abundance of 1.04 to 5.26 numbers per 10g of tissue while it was 2.67 to 8.34 numbers per 10g of inedible tissue. There was significant variation in abundance of microplastic in edible and inedible tissue of all the fishes (Mann-Whitney test, p < 0.05). The most dominant microplastics size was 0.005-0.05mm followed by 0.05-0.5mm and the least of greater than 0.5mm in pelagic and demersal fishes respectively. Taking microplastic shape into consideration, the most dominant was fiber followed by fragment and the film in inedible tissue of all the fishes. The edible tissue of all the fishes had only fiber in them (100% occurrence). The dominance of blue color microplastics was observed followed by red, green, yellow, and orange at least in edible as well as inedible tissues of the fishes. More than 99% microplastics polymer observed in this study include polyethylene (PE), polypropylene (PP), and polystyrene (PS); only less than 1% was unidentified. This is the first study done on seasonal variation of microplastic in the marine fish population of Gujarat waters, Northeast Arabian Sea. The study highlights the nature of micro-pollutant in marine environments, emphasizing the need for comprehensive monitoring and management strategies.

Inter-annual variability in the phytoplankton abundance and community structure of a tropical monsoonal estuary in response to variable monsoonal patterns

The study elucidates the inter-annual and seasonal variability in the phytoplankton abundance and community structure concurrent to variable rainfall patterns in Chettuva, a tropical monsoonal estuary along the southwest coast of India. The phytoplankton community exhibited statistically significant inter-annual variation with a 1.2-fold increase in abundance (av. 19.44 ×104cellsL-1) in 2021 in comparison with 2019 (av. 15.30 ×104cellsL-1). A total of 87 phytoplankton species were observed during the study, among which Bacillariophyceae dominated with 52 species, followed by Dinophyceae (20 species), and to a lesser extent by Chlorophyceae (11 species) and Cyanophyceae (2 species). Phytoplankton community structure also showed variation, with 71 species contributing to the diversity in 2021 and 62 species in 2019. Though Bacillariophycea dominated during both years, the community was more diverse in 2021comparatively a more saline year Biddulphia sp. Coscinodiscus sp., Cyclotella striata, Melosira sulcata, Pleurosigma sp., and Skeletonema costatum were the diatoms common to both the years, though with varied abundance. Dinophyceae did not show a conspicuous change in community structure in both years, with mostly the same species contributing to the total phytoplankton population but showed slight variation in abundance. Cyanophycea was observed exclusively during the year 2021. The abundance and community structure of the species varied from year to year, but they also changed seasonally, with lower numbers observed during the monsoon compared to the post-monsoon period in both years. CCA analysis identified two groups of phytoplankton assemblages in relation to the prevailing environmental conditions. The Group I species preferred lower temperature and salinity and elevated nutrient concentrations and they dominated during the monsoon season. Group II species preferred high saline well oxygenated, nutrient-poor waters and they dominated during the post-monsoon. Furthermore, the trophic state index analysis indicated mesotrophic conditions during the monsoon, while eutrophic conditions were observed in the post-monsoon period.

A clinicoepidemiological study of serologically diagnosed acute febrile illness in a teaching hospital, Kolkata

ABSTRACT Introduction: Similar presenting manifestations in early phase and lack of awareness of aetiology of acute febrile illness (AFI) are major challenges in management of AFI. Material and Methods: This was a retrospective observational cross-sectional study conducted in the Department of Microbiology, NRS Medical College, from 1 July 2022 to 30 June 2023 in serologically diagnosed febrile patients attending the outpatient department or admitted. Clinical and epidemiological data and laboratory parameters were recorded in a pretested structured questionnaire study tool, and collected data were analysed on MS-Excel sheets with various charts and tables. Results: A total of 1711 serologically diagnosed febrile patients showed preponderance of dengue (38.3%), followed by leptospirosis (25%), scrub typhus (23.9%), malaria (12.6%), and enteric fever (1.92%). A majority of cases were male, less than 40 years of age, and from the rural population (73.2%), except in malaria (urban = 79.6%). The mean duration of fever was 9 days. Febrile cases were recorded maximum during the monsoon and postmonsoon periods (66.5%). The common manifestations are fever, headache (46.2%), pain abdomen (7.8%), nausea, and vomiting (9.4%). Thrombocytopenia with bleeding manifestation was higher in dengue (18%) cases. Mortality in dengue cases was recorded with multiorgan dysfunction syndrome (MODS). Scrub typhus cases showed seizure (8.3%) and altered sensorium (5%) due to fatal meningoencephalitis. Fatality in leptospirosis was mostly due to acute kidney injury (29.5%) and Weil’s disease (4.4%). Conclusion: Misdiagnosis or incorrect diagnosis and delay in initiation of appropriate treatment results in increased morbidity and mortality in AFI. Determination of epidemiological features and clinical manifestations of AFI along with timely correct diagnosis will benefit clinicians in proper treatment initiation, thereby reducing morbidity and mortality.

Variability of bio-optical properties of Sundarbans mangrove estuarine ecosystem using elemental analysis, Sentinel 3 OLCI imageries and neural network models

Coastal water bodies face significant contamination risks stemming from various factors, such as growing populations, rapid urban development, dam construction, heightened industrial operations (notably in ports), and increasing tourism activities. The release of untreated sewage from municipalities, industrial discharges, and various recreational and commercial activities along the coast significantly deteriorates water quality and presents a serious risk to marine ecosystems, food chains, and human health. Hence, continual monitoring of coastal water quality is essential for the ecological sustainability of marine and aquatic ecosystems. This study examines the spatiotemporal variability of optical characteristics within the Sundarbans estuary system, a transboundary ecosystem shared by India and Bangladesh. The study employs Sentinel-3 OLCI satellite data alongside in-situ measurements of critical water quality parameters, including chlorophyll-a (Chl-a), total suspended matter (TSM), and chromophoric dissolved organic matter (CDOM), collected from 100 sampling sites across the Sundarbans estuarine system during the pre-monsoon, monsoon, and post-monsoon periods of 2021 and 2022.This study employs the sophisticated C2RCC model, a machine learning-based neural network-driven approach recognized for its robustness and precision. It examines the various bio-optical properties in tropical estuarine environments. The C2RCC model addresses this challenge directly. This advanced processor, powered by neural network technology, effectively interprets the complex optical signals found in Case-2 waters, offering essential insights into their quality. The findings indicate the highest TSM levels during the pre-monsoon seasons of both years. Additionally, the estimated Chl-a concentrations indicated a rise during the monsoon season (0.03–4 mg m3), whereas the intensified pre-monsoon CDOM levels showed consistency across both years. The strong positive correlation observed between in-situ and satellite data, with an average R2 value ranging from 0.90 to 0.99, underscores the reliability of the high-resolution remote sensing approach. The study illustrates the efficacy of OLCI data in observing near-shore and coastal ecosystems, clearly exceeding conventional methods for evaluating Chl-a, TSM, and CDOM. This study underscores the potential of high spatial and spectral resolution of Sentinel-3 Ocean color data for effective monitoring and management of the complex estuarine ecosystem of the Sundarbans. The findings of this study provide important insights to inform the development of sustainable coastal water resource management strategies. Furthermore, the findings will be crucial in achieving Sustainable Development Goal 14, which focuses on life below water, particularly in the conservation and management of marine and coastal biodiversity.

Hydrochemical insights, water quality, and human health risk assessment of groundwater in a coastal area of southeastern China.

Groundwater is a vital water supply worldwide, but its quality has gradually deteriorated with the development of society. In this study, a total of 40 groundwater samples were collected during the pre- and post-monsoon to analyze the hydrochemical process and assess the groundwater quality and human health risks in a coastal area of southeastern China. The results showed that the concentrations of major ions were in the order of Ca2+> Mg2+ > Na+ > K+ and HCO3- > SO42- > Cl- > NO3- > F- during the pre- and post-monsoon periods. A slight increase was observed during the post-monsoon period. The Piper diagram suggested that the hydrochemical type of groundwater was predominantly HCO3-Ca. Principal component analysis (PCA), ionic ratios, and saturation index (SI) determined that the water-rock interactions involving silicate and carbonate minerals played a significant role in the hydrochemical process. The results of the entropy-weighted water quality index (EWQI) and irrigation water quality index (IWQI) evaluations revealed that the general qualities of groundwater were suitable for both drinking and irrigation purposes. However, the excesses of NO3- and SO42- were observed locally. Human health risk assessment concluded that groundwater posed a low risk to human health, and infants faced higher risk compared with adults. The study would provide valuable information for groundwater environmental protection.

Land use & land cover dynamics and its relationship with nitrate pollution in groundwater around inactive mine areas using geospatial techniques, SW part of Cuddapah basin, Southern India

Geospatial maps can show how the ineffective operations of inactive mines affect water and aquifer quality. As such, the purpose of this study is to assess the impact of mining and irrigation on the aquifer ecosystem through the evaluation of LULC and slope maps through the application of Landsat 8 OLI/TIRS and DEM data. A total of 50 groundwater samples were prepared from villages in the close proximity to inactive mines during pre and post monsoon periods in 2021. The results of the analysis revealed alarming statistics, that 14% of groundwater samples exceeded the WHO nitrate limit in pre & post monsoon season, indicating a high-risk in the study area. According to guidelines (USEPA, 2014), 34% in pre-monsoon and 26% post-monsoon of samples exceeded the THI levels for adults and children respectively, indicating non-carcinogenic health risks. In addition, 80% of the samples in both seasons exhibited high NPI values, indicating nitrate contamination associated with blue baby syndrome. From the Geospatial analysis the findings from the LULC classification indicate that there has been a significant increase in cropland area from 2016 to 2021 due to changes in forest land, fallow land, and water resources. These problems have been exacerbated by the expansion of cultivated land, which has increased from 71.1 square kilometers in 2016 to 118 square kilometers in 2021, accounting for 13.1% of the total area. This expansion, coupled with elevated water body resource availability, has compounded the nitrate pollution including in intensely irrigated regions. The slope map analysis revealed that the inactive mines occur at low slope, high rainfall areas and these are compounded by runoff from other sources such as domestic and agricultural wastes. For these matters, sealing and remediating these inactive mines is essential so as to prevent further nitrate leakage.

Evaluating the dynamics of climate and anticipated snow cover changes on the hydrological response of rivers in the Hindu Kush Himalaya region

ABSTRACT The research aims to assess the interplay between climate dynamics and snow cover changes, informing water resource management. Utilizing the SWAT model with historical and future data, hydrological responses in the Marshyangdi River Basin are examined. The model's performance confirms its ability to simulate runoff components effectively. Projections indicate a concerning decrease in snow cover area for 2030, 2050, and 2090, with declines of 2.03, 4.03, and 14.20%, respectively, attributed to global warming and human activities. Isolating climate change reveals substantial increases in stream flow, notably pre-monsoon surges under different scenarios, with projected increments of 84 and 130% under SSP245 and SSP585, respectively. Analysis of snow cover impact shows a slight increase in annual stream flow, with a 3.54% anticipated decrease during the post-monsoon period, raising concerns for water availability in the dry season. Comparing both impacts reveals no significant differences in stream flow or precipitation. Annual stream flow increases under different scenarios, driven by precipitation, with varying impacts. Climate change emerges as the dominant driver, affecting surface runoff, groundwater, and evapotranspiration. This research unravels complex relationships between climate change, snow cover, and hydrological responses, providing valuable insights for water resource management in mountainous regions like the Hindu Kush Himalaya.

An in-depth Analysis of Soil Quality and Heavy Metal Contamination in the vicinity of the Visakhapatnam Municipal Solid Waste Dumpsite

The study conducts a comprehensive analysis of soil quality and heavy metal contamination in the vicinity of the Visakhapatnam Municipal Solid Waste Dumpsite, with a focus on the Gajuwaka municipality. The research addresses the escalating global concerns arising from improper waste disposal practices and their environmental repercussions. The Gajuwaka dumpsite, receiving diverse waste types, poses significant threats due to the leaching of heavy metals into the soil, impacting environmental components and human health. The study employs a robust experimental methodology involving soil sampling, metal extraction and Atomic absorption spectroscopy for elemental analysis. Waste characterization reveals the predominant presence of organic fractions and inert materials in the dumpsite. Seasonal physicochemical analysis of soil samples indicates variations in pH, moisture content, soil texture, organic matter and nutrient availability. Metal content generally decreases during the post-monsoon period. Phytotoxicity analysis of selected plant species demonstrates their capacity to accumulate heavy metals, particularly lead. The study emphasizes the urgent need for effective waste management practices, continuous soil monitoring and community engagement to mitigate environmental and health risks associated with waste dumping sites. The findings underscore the critical importance of sustainable waste management and environmental health. The study contributes valuable insights into the complex challenges posed by improper waste disposal practices and provides a foundation for the development of comprehensive strategies aimed at addressing environmental concerns.

Evaluation of contaminated groundwater for excessive heavy metal presence and its further assessment of the potential risk to public health.

Water plays a significant role in human life. However, the contamination of groundwater by heavy metals (HMs) has profound implications for public health. Industrialization, urbanization, and agricultural activities are turning out to be major causes for the increasing concentration of HMs in rapidly industrializing areas like Rohtak district, Haryana, India. The current study aimed at evaluating and predicting the health hazards associated with the radical rise of HMs in the groundwater of Rohtak district. For this purpose, 45 seasonal-based groundwater samples were collected from five blocks in Rohtak district, namely Kalanaur, Meham, Lakhan Majra, Rohtak City, and Sampla, both during pre- and post-monsoon seasons. Besides physicochemical analysis, these groundwater samples were analyzed for the contamination of HMs. The findings revealed that groundwater samples were relatively more contaminated during the post-monsoon period rather than pre-monsoon. The water quality index (WQI), devised to classify water quality into specific classes, depicted the Kalanaur region as "very poor." Another index named the HM pollution index (HPI) denoted the levels of HMs and categorized Kalanaur as most deteriorated, followed by Meham, Lakhan Majra, Sampla, and Rohtak City. Additionally, principal component analysis (PCA) was employed that showed a significant variation in the distribution pattern of HMs, with the major load being attributed to PC1 and PC2 for both seasons. Pearson's correlation analysis indicated a significant association of pH (R2 = 0.917) with HMs (specifically for Cd and Cr). In terms of health risk assessment, carcinogenic human health risk due to Pb and Cr was found to be higher in children than adults. Non-carcinogenic risk, indicative of harmful human health effects, apart from cancer, was calculated in terms of hazard quotient (HQ) and hazard index (HI). Results of the same, designated "children" as a vulnerable category compared with "adults," especially in the Kalanaur, Sampla, and Rohtak City blocks of the study area. The results thus reiterated that Kalanaur is the most contaminated block among the five blocks chosen and should be given urgent attention. The study holds importance as it provides a framework regarding the methodology that should be adapted for the evaluation, management, and protection of groundwater at a regional level, which could further be replicated by environmentalists and hydrogeologists across the world. PRACTITIONER POINTS: Water logging is one of the most common problems in Kalanaur block of Rohtak district, responsible for causing groundwater pollution. Cadmium and lead pollution was prevalent in Rohtak due to electroplating industries, paint industry, automobile sector, and industrial discharge. Bioremediation is one of the suitable techniques that can be used for the treatment of groundwater that involves the use of microorganisms. Efficient use of groundwater resources is necessary for sustainable development.

Comparative study on groundwater quality assessment of Chennai District, Tamil Nadu during 2019-2020

The groundwater usage for household, industrial and agricultural needs is largely depends upon the nature and composition of various dissolved components present in the water. A comparison of groundwater quality of Chennai district in 2019 and 2020 for its potability and its hydrogeochemical characteristics were studied using the physicochemical data of representative samples from 36 observation wells obtained during pre monsoon and post monsoon seasons. The chosen wells are spatially distributed in the study region. The present work was carried out using the water quality data consisting of various physicochemical parameters and major ions concentration pertaining to groundwater analysis of the study location obtained from State Groundwater and Surface Water Resources Data Centre (SGSRDC), Taramani, Chennai, India. Water quality parameters such as pH, total dissolved solids(TDS), total hardness(TH), total alkalinity(TA), Ca2+, Mg2+, Cl‒, SO42‒, and NO3‒,were used to calculate the water quality index (WQI) by weighted arithmetic method. The groundwater quality is ascertained from the calculated WQI values with reference to Bureau of Indian Standards (BIS). The results of WQI calculation reveals that in the pre monsoon period of both 2019 and 2020, around 30 % samples fall under good category and 55 % samples fall under poor quality. In the post monsoon period of 2019, 70 % samples are of good quality, whereas for 2020, 61 % samples are of poor quality. Correlation analysis of water quality parameters and bivariant plots of major ions were plotted to decipher the hydrogeochemical characteristics of groundwater. TDS, TH and electrical conductivity (EC) exhibits a strong positive correlations with Ca2+, Mg2+, Na+, Cl- and SO42- ions. The Piper diagrams of the ground water samples of the study area reveal its hydrochemical facies as Na-Cl type. The Gibbs diagram of the groundwater samples shows that water-rock interactions and evaporation are the predominant factors in controlling the ground water chemistry.

Assessing the Suitability of CCME WQI as a Groundwater Quality Monitoring Tool: An Environmental Ergonomics Case Analysis

This study was conducted with the aim of protecting groundwater, which plays a crucial role in ensuring food quality in the market, preserving public health, and safeguarding the ecosystem, as many regions rely on clean natural groundwater for their population’s survival. The objective of this study was to use the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for groundwater at 12 stations in the Okhla Industrial Area, Nangloi, and Karol Bagh in the Delhi Region. CCME WQI is an effective tool for assessing groundwater quality and communicating water conditions to various users. The research methodology involved fieldwork from June to October 2020 for three different periods in the year: pre-monsoon, monsoon, and post-monsoon, to observe variations in water quality and differences in various physicochemical properties of water. The CCME WQI was applied using sixteen water quality parameters, fourteen of which were physicochemical parameters and two of which were microbiological parameters. Among the physicochemical parameters were color, odor, pH, turbidity, nitrate, total hardness, iron, chloride, fluoride, total dissolved solids, calcium, magnesium, sulfate, and alkalinity, while the microbiological parameters included the total coliform and Escherichia coli counts. Based on the results obtained from the water quality index, station A9 scored between 0 and 44, indicating the lowest water quality index due to wastewater discharges and industrial contamination. The water quality at other stations also requires attention to achieve excellent ratings. The study concludes that serious measures should be taken for proper management of the area to protect the population from hazardous diseases. The research results show that stations 1, 2, and 10 were rated as excellent, station 12 as good, stations 4, 5, and 8 as moderate, stations 3, 6, and 11 as marginal, and station 9 as the poorest in terms of water quality in the year 2020 during the pre-monsoon, monsoon, and post-monsoon periods. To improve the parameters and groundwater quality, it would be necessary to reduce the impact of industry, anthropogenic–geogenic activities, and domestic activities.