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Warship INS Chennai Set To Sail.

Chennai: 40 to 70 deaths of nesting turtles daily.

Oil Spill Spreads To Chennai Beaches After Ships Collide Off Ennore Port In India.

Coastal waters are inherently dynamic due to river discharge, industrial effluents, shipping, dredging, waste dumping, and sewage disposal. Population growth in urban cities, climate change and variability, and changes in land-use practices all contribute to pressure on coastal water quality (SKOVSKI et al., 2012; MILLER and HUTCHINS, 2017; KUMAR et al., 2020; Vijay PRAKASH et al., 2021). Anthropogenic activity is evident around these estuaries and coastal and open ocean environments. Hence, it is important to assess the water quality on a regular basis and provide mitigation measures for coastal pollution (YUVARAJ et al., 2018). Improving water quality and variability in coastal waters is necessary and should be prioritized. Observational programs, which are more expensive and time-consuming, aid in understanding the status of water quality and its trends. Many countries have coastal programs that use predictive systems to inform the public and stakeholders about coastal health. Hydrodynamic processes are an integral part of complex surface water systems. The main factor that determines the concentration of pollutants is hydrodynamic transport, which includes advection, dispersion, vertical mixing, and convection (James, 2002). The flow and circulation patterns have a great influence not only on the distribution of temperature, nutrients, and dissolved oxygen (DO) but also on the aggregation and distribution of sediments and pollutants. When a load of pollutants is discharged into coastal waters, it is affected by the fate and transportation processes that change its concentration. Several studies have been conducted to evaluate the coastal water quality spatiotemporally along the east coast of Indian coastal waters using site-specific data and model configuration (PANDA et al., 2006; BHARAHTI et al., 2017; NAIK et al., 2020; MOHANTY et al., 2021). Through numerical modeling and remote sensing, estimation is user-friendly and low-cost in evaluating any water quali

The productivity and sustainability of coastal, marine, and estuarine ecosystems are heavily reliant on the quality of coastal waters (JHA et al., 2013; JHA et al., 2015; DHEENAN et al., 2016). These locations are thought to have greater biodiversity than open ocean zones (GRAY, 1997). Among the biological components of soft bottom sediments, macrobenthic organisms are essential for ecosystem functioning (Pandey et al., 2022). They play a vital role in secondary production and nutrient exchange between the pelagic and benthic realms and therefore constitute essential elements of estuarine and coastal habitats (SNELGROVE, 1998) and are a reliable indicator for assessing the biotic integrity of the coastal ecosystem (RYU et al., 2011; Pandey et al., 2021). Due to their sedentary lifestyle, long life cycle, and differential response against the perturbation, they also serve as useful bio-indicator (GESTEIRA-GOMEZet al., 2003) for health monitoring and assessment of coastal ecosystems (GANESH et al., 2014) and evaluating the success of conservation efforts (WINBERGT et al., 2007). Identification of factors responsible for spatiotemporal patterns in macrofaunal assemblages is the primary goal amongst many marine benthic ecological studies (BOLAM et al., 2008; DUTERTRE et al., 2013; PANDEY and GANESH , 2019b). However, such pattern in the benthic community is often hard to predict due to the complex interplay between environmental parameters and biological interactions (ELLIS et al., 2006). The relationship between natural environmental factors and macrobenthos is reported to help delineate faunal distribution patterns, characterising benthic habitats, establish baseline knowledge, and enabling the detection of spatial and temporal variations (BOLAM et al., 2008; SHUMCHENIA and King, 2010; Dutertre et al., 2013). Numerous studies (Van Hoey et al., 2004; Hily et al., 2008; DUTERTRE et al., 2013; Pandey and Ganesh, 2019b) have identified sediment properties as a significan

The Swarnamukhi river estuary (SRE), and the surrounding sea in Nellore, southeast coast of India, is one of the least studied marine environments, notably for physicochemical characteristics. Seawater samples were collected from five stations every month from 2014 to 2017 to assess physicochemical characteristics. The open sea (OS) station was significantly different from the inner stations, according to non-metric multidimensional scaling and cluster analysis. The variability was shown by strong factor loadings of atmospheric temperature (0.87), water temperature (0.84), biochemical oxygen demand (0.77), ammonia (0.85), and total nitrogen (0.78). Furthermore, one-way ANOVA and box-whisker plots facilitated simplifying and corroborating multivariate results that showed high concentration in the inner stations. Based on the N/P and Si/N ratios, nitrate and silicate were the key limiting factors in this study. The findings are critical for establishing reference conditions for comparison studies with other comparable ecosystems in the tropical region for better environmental conservation and management.

A planned artificial reef (AR) deployment program as part of a fisheries enhancement might be a useful tool for managers to supplement traditional ways to utilize available space and augment local productivity. Several AR deployment initiatives have been carried out globally, but they are rarely subjected to a rigorous site selection process. We created a site selection procedure in this study that includes systematic stages including exclusion mapping, underwater visual transect, benthic composition, seawater quality, and comparative visual mapping. This research focused on restoring the fishing grounds for artisanal fishermen by deploying AR along the southeast coast of India. The results of each stage in the procedure enabled us to choose suitable locations at a target depth with low wave action, no slope, and a good substrate capable of supporting an AR. Analysis of variance (ANOVA-one way) showed significant (p < 0.05) spatial variation for depth, slope, seawater current, salinity, chlorophyll-a, benthic density, and diversity. The geographical information system (GIS) based model output showed space allocation for AR deployment. The GIS methodology for site selection was developed to be easily adaptable to the demands of diverse artificial reef programs. The integrated strategy has proven to be a successful regulatory intervention for AR deployment practices in order to facilitate coastal restoration and management.

Dead whale shark washes ashore in TN.

Pollution: Microplastics and colourants found in mussels from India's southeast coast.

Three tonne of sea cucumbers seized in Tamil Nadu.

Rescue efforts continue after dolphins wash ashore in Tamil Nadu.

Brit pirate hunters jailed in India could be home for Christmas after spending four years behind bars.

India warships sent to strategic Gulf waters: navy.