The water quality study of Salem district, Tamil Nadu has been carried out to assess the water quality for domestic and irrigation purposes. For this purpose, 59 groundwater samples were collected and analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), major anions (HCO₃⁻, CO₃⁻, F⁻, Cl⁻, NO₂⁻ + NO₃⁻, and SO₄²⁻), major cations (Ca²⁺ Mg²⁺, Na⁺, and K⁺), alkalinity (ALK), and hardness (HAR). To assess the water quality, the following chemical parameters were calculated based on the analytical results, such as Piper plot, water quality index (WQI), sodium adsorption ratio (SAR), magnesium hazard (MH), Kelly index (KI), and residual sodium carbonate (RSC). Wilcox diagram represents that 23% of the samples are excellent to good, 40% of the samples are good to permissible, 10% of the samples are permissible to doubtful, 24% of the samples are doubtful unsuitable, and only 3% of the samples are unsuitable for irrigation. SAR values shows that 52% of the samples indicate high-to-very high and low-to-medium alkali water. KI values indicate good quality (30%) and not suitable (70%) for irrigation purposes. RSC values indicate that 89% of samples are suitable for irrigation purposes. MH reveals that 17% suitable and 83% samples are not suitable for irrigation purposes and for domestic purposes the excellent (8%), good (48%), and poor (44%). The agricultural waste, fertilizer used, soil leaching, urban runoff, livestock waste, and sewages are the sources of poor water quality. Some samples are not suitable for irrigation purposes due to high salinity, hardness, and magnesium concentration. In general, the groundwater of the Salem district was polluted by agricultural activities, anthropogenic activities, ion exchange, and weathering.

The world’s groundwater resources are under tremendous strain due to overuse and significant climatic changes. The need for potable water for industrial, agricultural, and domestic use is increasing worldwide, necessitating an assessment of aquifer productivity and groundwater potential. Therefore, the present study aimed to evaluate groundwater potential zones (GWPZ) in Natham Taluk, Dindigul district, a hard rock area, to promote sustainable development. The GWPZ was delineated using the Analytical Hierarchy Process (AHP) in conjunction with Remote Sensing (RS) and Geographic Information Systems (GIS), which have become essential techniques for groundwater resource retrieval, monitoring, and conservation. A total of ten thematic maps of lithology, land use/land cover, lineament density, geomorphology, soil, slope, rainfall, drainage density, Topographic Wetness Index (TWI), and curvature, all layers were integrated to define Groundwater Potential Zones (GWPZs) by weighted overlay analysis using ArcGIS and Analytical Hierarchy Process (AHP). Five types of groundwater potential were found in the study region as a consequence of the classification: very good (7.61%), good (39.70%), moderate (17.70%), low (33.03%), and very low (1.95%). The groundwater potential map (GWPM) accuracy is evaluated using the area under the curve (AUC) method; an AUC value of 0.830 indicates a reliable result. This spatial study provides a vital geospatial database for strategically planning and constructing groundwater recharge structures. In addition to supporting the long-term sustainable management of groundwater resources, the delineated zones offer practical insights for improving aquifer recharge. The study also identifies possible locations for artificial recharge, especially well-suited to areas with hard rock and semi-arid conditions.

The coastal region is one of the most sensitive areas on earth. This region has a diversified ecosystem. Erosion and accretion are common natural phenomena that can be seen in this region. In some circumstances, these changes become hazardous to the coastal ecosystem. Natural processes such as rainfall, flood, cyclone, longshore drift, and tectonic shifts can trigger irregular coastal changes. Similarly, anthropogenic factors such as urbanization, unscientific land usage, mining, etc., enhance coastal dynamics and make larger changes. Hence identification of such region has great importance. Geospatial technology has brought various advanced methods for shoreline change studies. It has decreased the huge effort for getting an accurate result for a larger area. Landsat satellite imageries with 30 m spatial resolution have been used for studying the changes in the shoreline of Ramanathapuram for the years 2000, 2005, 2010, 2015 and 2020. In Geographic Information System (GIS) software, the Digital Shoreline Analysis System (DSAS) tool is added for shoreline change analysis. DSAS will build the baseline transects. The rate of shoreline change was calculated using the MATLAB feature runtime function for ArcGIS. Based on the DSAS output, the region of high erosion, low erosion, stable, and low accretion, high accretion zones have been identified on the shore. The results reveal that 5.1% of the shoreline, around 9.3 km is under high erosion, 11.5% of the shoreline, which is around 20.8 km, is under low erosion, 71% of the shoreline, around 128 km, is a stable region, 6.7% of shorelines, around 12 km, have low accretion, and 5.6% of shorelines, around 10.1 km, have high accretion. The coastal villages, namely, Mayakulam, Keelakakrai, Periapattinam, Mandapam, West-Pamban, and East-Rameswaram, have a high erosion with a maximum rate of change between 2.29 to 5.11 m/y. The coastal villages Ervadi, Kalimankund, Sattankonvalsai, South-Pamban and South-Rameswaram have high accretion with a maximum rate of change between 2.34 to 5.24 m/y.

This research aims to define the potential of using natural networks for groundwater mapping. While neural networks have proven effective for various perceptual tasks, the difficulty in identifying data points below the surface remains a key challenge. The area under study encompasses a mountainous region in the Western Ghats. The most efficient, practical, along sensible methods for defining the GWPZ (Groundwater Potential Zones) in the Nilgiri’s hard rock terrain are Geographic Information Systems (GIS) as well as analytic hierarchy process (AHP) of multicriteria decision making. To create various thematic layers, we utilized Indian topographical maps, satellite imagery, and field observations. We collected data on ten factors influencing groundwater(GW), including LULC(Land Use Land Cover), elevation, slope, soil type, geomorphology(GM), rainfall(RF), geology(GL), LD(lineament density), as well as DD(drainage density). Based on the weight assignment, all the thematic maps influencing GW events were assessed and compiled using GIS analysis. The weighted index overlay (WIO) approach and PCM (pairwise comparison matrix) within the AHP were used for a hierarchical ranking to identify the possible GW zones. The outcome revealed that the sample region could be divided into 5 separate groundwater potential (GWP) areas, i.e., very good (10%), good (32%), moderate (21%), low (26%), as well as very low (11%) potentials. Well and spring data were used to validate the model, and the ROC (Receiver Operating Characteristic) curve method was applied. The results showed a good accuracy of 70.03%. chance of correctly distinguishing a randomly chosen true positive from a false positive. This research is useful for improved preparation and control of GW supplies and offers swift guidelines for the discovery of GW in the hard rock aquifer region.