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The continuous investigation of water resources is essential to assess pollution risks. This study investigated a groundwater assessment in the coastal belt of Tamil Nadu’s Kovilpatti Taluk, Thoothukudi district. Twenty-one groundwater samples were collected during the pre-monsoon and post-monsoon seasons, analyzing water quality parameters, namely pH, EC, Cl−, SO42−, Ca2+, Mg2+, HCO3−, TH, Na2+, and K+. The Water Quality Index (WQI) was computed and it is observed that 5% of pre-monsoon and 9% of post-monsoon samples were unsuitable for drinking. SAR, MHR, RSC, %Na and Kelley’s index were used to determine irrigation suitability. Pre-monsoon shows 29% (MHR) and 71% (RSC) unsuitable, and post-monsoon shows 59% (MHR) and 9% (RSC) unsuitable. Coastal activity, urbanization, and industrialization in Kovilpatti resulted in the degradation of groundwater quality. Solving this coastal issue requires sustainable wastewater treatment and strict industrial discharge guidelines. Spatial distribution plots, Box plots, Gibbs plots, Piper plots, Wilcox plots and Correlation Matrices had similar results to the computed WQI and its physical–chemical parameters. According to the human health risk assessment, the Mooppanpatti, Illuppaiurani, and Vijayapuri regions show high health risks due to the nitrate and fluoride concentration in the groundwater. Kadambu, Melparaipatti, Therkuilandhaikulam, and Vadakku Vandanam have low levels, posing a minimal health risk.

The agro waste briquettes produced from sorghum panicle and pearl millet with corn starch as the binder with varied proportions were compared with the other agro briquettes, and the elemental analysis of SP-PM briquettes was compared with the agro waste, palm kernel shell, soybean waste, mango leaves, rice husk, spruce, and coffee husk briquettes. The TGA results of SP-PM briquettes were compared with the corn leaf, baggase, almond shell, banana leaves, banana pseudostem, pineapple leaf, stem and root, low rank coal, bituminous coal, cotton stalk, and wheat straw. The DSC analysis that was carried out for SP-PM briquettes were compared with the rice husk char, spent coffee ground, wood chips, saw dust, wood straw, Tomsk peat, Sukhovskoy peat, Arkadievsky peat, nutshell, and bran. Thus, the briquettes made out of sorghum panicle and pearl millets are compared with the other biomass briquettes for its efficiency and its quality. Thus, the briquettes made out of sorghum panicle and pearl millets are compared with the other biomass briquettes for its efficiency and its quality.

The aim of this research is to remove malachite green (MG) from a created water environment utilising tamarind fruit shell (TFS) and a fixed-bed reactor (FBR) technology at room temperature. Biosorption is the finest method for dye removal among the several approaches available. It produces excellent results and may be used to remove a wide range of colouring components. It is used to weigh different options for firm things. The option which balances other ones on various counts is the finest one. Various studies have found that eating malachite green-contaminated fish poses a major health risk to people. From the FBR studies, the effect of various factors such as flow rate, initial sorbate concentration, biosorbent size, and bed depth on breakthrough of MG is assessed. The study was carried out to fix the flow rates. This is done by varying the biosorbent size with constant bed depth of 30 cm. The trend in flow rate variation appears to be similar for 0.33 and 0.6 mm sizes, whereas for 0.13 mm size, it is slightly different. The head loss and swelling of TFS particles are insignificant, during the fixed-bed studies. It is estimated that 30.9 T of crude TFS is required to get 8300 kg of 0.6 mm size of TFS. The service time obtained from design was more than the experimental breakthrough time, and calculated bed efficiency was >90%. The biosorption of MG by TFS can be well explained by the BDST approach. Acid regenerants such as 0.5 N H2SO4 and 0.5 N HCl can satisfactorily regenerate the spent TFS in the FBR system, with 0.5 N HCl being a better one.

This study utilized GIS and remote sensing data to forecast areas of spatiotemporal drought risk affecting agriculture and meteorology in the southern Coimbatore region. Drought risk has been evaluated using Landsat 8 OLI/TIRS and 7 ETM+ temporal photographs, utilizing the Normalized Difference Vegetation Index, for the years 2000 and 2020. This assessment was complemented by the utilization of the meteorologically derived standardized precipitation indicator as a drought index. Finally, spatiotemporal drought risk maps were produced using a weighted overlay method using NDVI, seasonal rainfall, and SPI values. The study area has been split into five classes: none, slight drought, moderate drought, extreme drought, and very high drought. The entire area and proportion for each category are then given for both years. In addition to this study, changes in land use and land cover were examined. Comparing the drought changes based on the land use and cover patterns of both years 2000 and 2020. The comparative results demonstrate that when land is developing like built-up areas, it becomes drier, which causes drought in that region. In contrast, other regions have well-planned irrigation systems and have converted fallow land into active agricultural land, increasing the number of wet land conditions in such regions.

Evaluations of probable environmental impacts of point and diffuse source pollution at regional sizes are essential to achieve sustainable development of natural resources such as land and water. This research focused on how nitrate and phosphorus load varied over time and space in the Vamanapuram River Basin (VRB). Phosphorus and nitrate loads have been evaluated in the VRB using the semi-distributed Soil and Water Assessment Tool (SWAT) hydrological model. SWAT Calibration and Uncertainty Programs (SWAT-CUP) have simulated the developed model using the Sequential Uncertainty Fitting, version 2(SUFI-2). The developed model was simulated for 2001 to 2008, and it was split into two-phase calibration and validation phases. Model performance was evaluated by the percentage of bias (PBAIS) and Nash–Sutcliffe efficiency coefficient (NSE). The simulated performance of nitrate was indicated as NSE = 0.22–0.59 and PBIAS = 51.86–65.88. The simulated performance of phosphorus showed NSE = 0.06–0.33 and PBIAS = 15.14–33.97. Total Phosphorus load was most sensitive to the organic Phosphorus enrichment ratio (ERORGP) and CH_N2 for streamflow simulation. This study concluded that the South-western region was a high potential for nutrient loads. This study will explain the nutrient load and guidelines for land management practice in the study area.

The groundwater is very precious in the world. Rapid urbanization and industrialization create tremendous stress on groundwater quality and quantity. Unscientific groundwater extraction and waste disposal methods impact the groundwater aquifer’s susceptibility in the coastal area. This research examines how industrial waste, seawater intrusion, and solid waste dumping affect the Thoothukudi District, located on the southwest coast of Tamil Nadu, India. The groundwater vulnerability potential is determined using the DRASTIC and analytical hierarchy process (AHP)-based DRASTIC model. DRASTIC-AHP method’s weights and ranks are determined using multi-criteria decision analysis (MCDA)-based pairwise comparison method. Remote sensing (RS) and geographical information system (GIS) are implemented to prepare the input layers for DRASTIC and DRASTIC-AHP. The findings reveal a very high category of vulnerability along the coastline that is covered in sand and loose sediments from an aquifer. Similar conditions exist on the southeast side, which is covered with gravel, sand, and sandstone with shale and has relatively low-slope topography. This enables higher contaminant percolation into the groundwater and raises the possibility for pollution. The DRASTIC-AHP method’s results reveal that the southeast side has a significant possibility of contamination. The water table, net recharge, vadose zone, and conductivity greatly impacted the DRASTIC vulnerability assessment due to their stronger weight than theoretical weight. It may be stated that the DRASTIC technique is more cost-effective and time-efficient in analyzing a wide range of regional groundwater risks while avoiding sloppy, uncontrolled land development and other unwanted activities.

The aim of the study was to determine the groundwater characteristics of rural and industrial zones in the Kannur region. In 2011, 25 groundwater data were collected from the centre for water resource development management (CWRDM), and in 2019, 25 groundwater samples from rural and near-industrial areas were collected and analysed for major anions (HCO 3 -, CO 3 2− , Cl − , NO 3 - and SO 4 2− ), and cations (TH, Ca 2+ , Mg 2+ , Na + , K + and Fe 2+ ) using APHA standards. To better understand the link between water quality parameters, multivariate statistical analysis approaches such as principal component analysis (PCA), hierarchical cluster analysis (HCA), correlation matrix analysis (CMA), and Pearson correlation bivariate one-tailed analysis (PCBOTA) were used to analyse the inter-relationship of data. The Inverse Distance Weighed (IDW) method was used to generate the spatial distribution of the groundwater quality index (GWQI). In 2011, the water quality index (WQI) value of groundwater samples was excellent at 24.42% and good at 54.14%, which were used for drinking purposes and moderate at 17.22% and poor at 4.22% for irrigation purposes in this study area. In 2019, excellent 21.62%, good 51.56% were used for drinking purpose, and moderate at 18.14%, and poor at 8.68% for irrigation purposes. By comparing the data with BIS and WHO standards, it is clear that groundwater in Kannur district is of good quality. In groundwater samples, the PCA eigen values were reported in 2011 (84.7%) and 2019 (73.4%) for statistical approaches. This study uses HCA and PCBOTA to analyse the elements, resulting in a better understanding of groundwater quality development. GIS based WQI maps were obtained and utilised to gain a better knowledge of the study area’s past and present water quality status. We observed that the quality of groundwater in the study region’s north-western portion is insufficient for drinking water.

Groundwater in the Coimbatore region is very much essential for irrigation and human beings’ day-to-day life activities. This research focuses on the impact of anthropogenic activities on the surface water quality of four tanks in Coimbatore city and its influences on disturbing the groundwater quality as well. Water quality is degrading as a result of encroachment and other anthropogenic activities. The disposal of municipal garbage and waste from other enterprises into the nearby tank degrades the quality of the water in the tanks. This pollutant-concentrated surface water, together with the leech organism, may percolate via the pore spaces between soil particles, where it will interact with groundwater. The quality of groundwater will be impacted as a result of this interaction. As a result, water quality metrics for both surface and groundwater have been assessed in this study, and spatial interpolation was performed using ArcGIS. The map of the spatial distribution of water quality was produced using ArcGIS. This spatially interpolated water quality map helped researchers understand how the quality of surface and groundwater changed over time. Visual MODFLOW and MT3D were used to simulate the groundwater flow. The MODFLOW program is used to simulate the direction of groundwater flow based on groundwater level and rainfall data. The output of MT3D allowed for accurate calculation of the pollutant movement’s amount and direction. In this study, chloride was used as the pollutant transport parameter. A semi-structured interview has been done in the study region to find out more about the availability of drinking water, how waste is disposed of, and how diseases are spread among residents who live close to the tanks.

Flooding stands as the most prevalent and financially burdensome natural disaster impacting nations worldwide. This study focuses on flood risk assessment within the Cuddalore taluk, aiming to leverage Geographic Information System (GIS)-based Analytic Hierarchy Process (AHP) techniques for analyzing flood hazards, vulnerabilities, and risks in the region. Seven key causal factors—elevation, slope, drainage density, river distance, rainfall, soil, and geology—were utilized to construct the flood hazard map. Results indicate that the taluk encompasses very low, low, moderate, high, and very high flood hazard zones, covering 7%, 22%, 34%, 25%, and 12% of its total area, respectively. Additionally, a flood vulnerability map was generated using five spatial layers: land use/cover, population density, distance to road, literacy rate, and population under the age of 6. Integration of the flood hazard and vulnerability maps facilitated the creation of a comprehensive flood risk map. The findings reveal that within the Cuddalore Taluk, zones classified as very low, low, moderate, high, and very high flood risk constitute 51%, 6%, 12%, 18%, and 12%, respectively. While the majority of the coastal region faces susceptibility to flooding within the very low, low, and moderate ranges, select areas are at risk of high and very high flooding. Disseminating flood hazard, vulnerability, and risk maps to relevant authorities is imperative for raising awareness regarding flood-prone locations. The coastal regions, along with adjacent areas, predominantly fall under the category of very high-risk zones, necessitating effective mitigation strategies. Specific locales such as Pillayarkuppam, Cuddalore, Tiruvandipuram, Kayalpattu, Nellikuppam, and Punjimangattuvalkkai demand focused efforts to mitigate high flood risks. Conversely, areas with very low and low flood risks, including Vadakuthu, Neyveli T.S., Sorathur, Panruti, Aierpali, and Pewndur, require preservation measures. Additionally, zones such as Arunam and Mettukuppam, exhibiting moderate flooding risks, warrant attention for preservation efforts in their immediate surroundings.

This study utilized GIS and remote sensing data to forecast areas of spatiotemporal drought risk affecting agriculture and meteorology in the southern Coimbatore region. Drought risk has been evaluated using Landsat 8 OLI/TIRS and 7 ETM+ temporal photographs, utilizing the Normalized Difference Vegetation Index, for the years 2000 and 2020. This assessment was complemented by the utilization of the meteorologically derived standardized precipitation indicator as a drought index. Finally, spatiotemporal drought risk maps were produced using a weighted overlay method using NDVI, seasonal rainfall, and SPI values. The study area has been split into five classes: none, slight drought, moderate drought, extreme drought, and very high drought. The entire area and proportion for each category are then given for both years. In addition to this study, changes in land use and land cover were examined. Comparing the drought changes based on the land use and cover patterns of both years 2000 and 2020. The comparative results demonstrate that when land is developing like built-up areas, it becomes drier, which causes drought in that region. In contrast, other regions have well-planned irrigation systems and have converted fallow land into active agricultural land, increasing the number of wet land conditions in such regions.