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Conventionally, volcanic margins have been considered devoid of hydrocarbon, but many discoveries and research in recent past have proved the presence of hydrocarbon prospects within them. However, hydrocarbon exploration within volcanic margin is constrained by seismic imaging. Further, identification of continent to oceanic boundary (COB) is critical to hydrocarbon search as hydrocarbon is found mostly over continental crust. Seaward dipping reflectors, associated with volcano-sedimentary sequences, located along rifted continental margins and represented by highly dipping strong amplitude seismic reflectors, play an important role to study volcanic margins. Keeping in view the problems of hydrocarbon exploration within volcanics, seaward dipping reflectors (SDRs) in Indian context have been studied in detail in this paper. It facilitates mapping of continent-oceanic boundary (COB). It has impact on hydrocarbon prospectivity in volcanic margins as it can provide formidable seal and secondary induced maturity. In India, several discoveries have been made in volcanic margins along west coast, from weathered, fractured basalt and sub-basalt sediments. In the present work, long offset regional seismic data (18 dip lines and 1 cross line), along east coast, have been interpreted. SDRs help in hydrocarbon prospectivity assessment for both discrimination of interbedded sediments and preferential accumulation of hydrocarbon. Mapping of linear features not only helped to demarcate COB but also their presence at 6–10 km depth. For the first time, such comprehensive study on SDRs has been done along Indian peninsular region with indications for hydrocarbon prospectivity at deeper levels along Indian peninsular region. [ABSTRACT FROM AUTHOR]

Coastal lakes and estuaries are considered economic drivers for coastal communities by delivering invaluable economic and ecosystem services. The coastal ecosystems are facing recurrent hypoxia events (dissolved oxygen; DO < 2.0 mg L−1) and are emerging as a major threat to ecosystem structure and functioning. The Ashtamudi Lake, (area = 56 km2), is one of the Ramsar sites in the State of Kerala and located on the SW coast of India. The waterways are extensively used for backwater tourism and for fishery activities. This paper discusses the spatio-temporal variation of water quality attributes with emphasis on hypoxia during non-monsoon and monsoon seasons. The extent of hypoxia on fishery diversity was discussed. The Southern Zone, adjacent to the urban area, shows the hypoxic condition with higher concentration of BOD, NO3-N, and NH4-N. The hypoxic condition is largely limited to the Southern Zone in both seasons. The occurrence of low DO in the lake is highly related to salinity and organic load in the lake system. The tracking of pollution sources in the lake system was also done through identification of pollution potential zones and found that catchments adjacent to Southern and Western Zones (urban regions) are the major source of pollution. The study suggests that hypoxia is chiefly attributed to anthropogenic interventions in the form of discharge of wastes into the lake causing overloading of nutrients and organic effluents, decrease in the freshwater supply, the absence of proper freshwater mixing or dilution, and effluent discharge from nearby urban centers. [ABSTRACT FROM AUTHOR]

This paper describes the prevalence of indicator and pathogenic bacterial groups in water and sediments in OSZ—offshore, ISZ—inshore, IEZ—inner estuary, and UEZ—upper estuary along the river Chapora, central west coast of India, which is influenced by anthropogenic inputs. The abundance of indicator bacterial groups such as total coliforms and Escherichia coli–like organisms in water ranged from non-detectable (ND) to 103 colony-forming units (CFU)/mL. In contrast, their abundance in the sediments was six orders magnitude higher than water (ND to 109 CFU/g). The abundance of potential pathogenic bacteria in water and sediment samples ranged from ND to 103 CFU/mL and from ND to 109 CFU/g respectively, with Shigella-like organisms (SHLO) being the most abundant. In the surface waters, SHLO and Pseudomonas aeruginosa–like organisms (PALO) and in bottom waters, Vibrio parahaemolyticus–like organism and PALO increased progressively from OSZ to UEZ. In contrast, Proteus/Klebsiella-like organisms (PKLO) showed a reverse trend. Amongst all four zones, IEZ was the most contaminated in terms of the higher abundance of indicator and potential pathogenic bacterial populations as corroborated by significantly lower water quality index value. Principal component analysis performed using physico-chemical variables and bacterial groups to reduce data set variability revealed that a different set of parameters contributed differently to the total variation in each zone. Considering the eco-sensitivity of the river Chapora, the results of the present study call for precautionary measures to minimize the degree of anthropogenic inputs. [ABSTRACT FROM AUTHOR]

The Krishna-Godavari coastal region in east coast of India has a 525.15-km-long coastline with low-lying tidal mudflats, beaches, mangrove swamp, creek and tidal channels. Recently, the increasing frequency of tropical cyclones in the Bay of Bengal, i.e., Phylin and Hudhud in Andhra Pradesh coast, and the devastating impact of the 2004 tsunami in India increased the significance in assessing the vulnerability of the coastal lands to inundation and flooding, notably in the context of climate change-induced sea level rise. This study aims to estimate a coastal vulnerability index (CVI) for the coastal subregion of Krishna-Godavari delta and to use the calculated index to evaluate the vulnerability of 14 coastal talukas of the Krishna-Godavari delta region. This CVI is calculated by using four geological and three physical parameters characterizing the vulnerability of the study coastal region, including regional slope, coastal elevation, geomorphology, significant wave height, mean tidal range and relative sea level using different conventional and remotely sensed data. Using a composite coastal vulnerability index based on the relative risk rating of those parameters, each of the 14 coastal talukas was classified according to their vulnerability. The CVI results depict that coasts are least and most vulnerable to inundation, flooding and erosion of coastal lands where geological parameters are more efficient to CVI. The paper alerts to decision makers and planners to mitigate the natural disaster and manage the coastal zone and is a primary step toward prioritizing coastal lands for climate change adaptation strategies in the view of increased storminess and projected sea level rise. [ABSTRACT FROM AUTHOR]

In this study, the abundance of microplastics (MPs) in the Uppanar and Gadilam estuaries in Cuddalore, on the southeast coast of India, is reported. In the estuarine sediments, MP abundance ranged from 36.3 ± 3.39 to 51.6 ± 2.05 particles/Kg dw. Different types of MP shapes, such as fibers (41.7–47.9%), films (21.2–27.2%), and fragments (18.3–25.5%) were observed in the size range of 100–1000 µm. Diverse colours of MPs were observed, among which red (30.1–34.5%) was predominantly noticed in the estuarine sediments. Six polymers were identified by µ-FTIR, among which LDPE (39%) and PP (35%) were dominant. MPs pollution in these estuaries is composed of domestic, industrial, and fishing wastes. Risk assessments show that the area falls under hazard categories I to III, indicating low to high risk. This study improves knowledge on MPs contamination in Uppanar and Gadilam estuaries and provides impetus for further research to identify the actual sources and impacts of MPs on aquatic systems along the east coast of India. [ABSTRACT FROM AUTHOR]

Many tourists have been recently attracted towards the coasts around the world, especially to the large urban centres and economically significant areas. In the last four decades, there is a significant increase in the key coastal developments and tourist's attractions like major ports, minor ports, fishing harbours, desalination plants, shore protection structures, and many more along the southeast coasts of India, in particular, northern Tami Nadu coastal stretches. The shoreline change study of these regions were carried out using the geospatial technologies (satellite remote sensing and geographical information system) to examine potential modifications occurred during the last 32 years between March 1990 and May 2022. This study used Landsat satellite images of spatial resolution 30 m to track the shoreline changes which was extracted using the Digital Image Processing software and techniques. In addition, the United States Geological Survey (USGS) developed Digital Shoreline Analysis System (DSAS) v5.2 software, an add-on tool to ArcGIS used for the statistical analysis to compute the shoreline rate of change. The linear regression rate (LRR) and end point rate (EPR) statistics were used to identify the eroding, accreting, and stable shoreline between Kattupalli coast and Kalpakkam coast of the northern Tamil Nadu coasts. This shoreline study of 106 km was carried out by dividing it into six zones (zone 1 to zone 6), and the DSAS analysis conveys that the shoreline of zone 1 (Kattupalli) and zone 2 (Ennore) shows erosion compared to other four zones. In locations where the coast is vulnerable, national mitigation measures must be implemented. [ABSTRACT FROM AUTHOR]

Defining the ecological quality of estuaries is challenging because of the inadequacy of available methods and indices to characterise the ecosystem. In Indian estuaries, there are no scientific attempts to establish multi-metric fish index to determine the ecological status. A multi-metric fish index (EMFI) was customised for twelve predominantly open estuaries on India's western coast. The index was established at the individual estuary level to ensure uniformity and contrast from sixteen metrics that designate the fish community and diversity, composition and abundance, estuarine use and trophic integrity from 2016 to 2019. A sensitivity study was followed to measure the responses of the EMFI under different metric varying scenarios. There were seven metrics identified as the most prominent for the EMFI in metric alteration scenarios. We also deduced a composite pressure index (CPI) based on the anthropogenic pressures described for the estuaries. The ecological quality ratios (EQR) defined based on EMFI (EQRE) and the CPI (EQRP) for all the estuaries were positively correlated. The EQRE values calculated based on the regression relationship (EQRE on EQRP) showed the divisions from 0.43 (bad) to 0.71 (high) for the Indian west coast estuaries. Similarly, the standardised CPI (EQRP) values for different estuaries indicated that the values range from 0.37 to 0.61. Our results based on the EMFI suggest four estuarine systems (33%) as 'good', seven (58%) as 'moderate' and one (9%) as 'poor'. Generalised Linear Mixed Model for EQRE showed that EQRP and estuary influenced EQRE; however, the effect of year was not significant. This comprehensive study based on the EMFI is the first record for predominantly open estuaries along the Indian coast. Therefore, the EMFI established in this study could be reliably advocated as a sound, effective and composite tool of ecological quality for tropical open transitional waters. [ABSTRACT FROM AUTHOR]

Health of an ecosystem is very much important as we depend on its goods and services for our existence. Because of this, we need to continuously monitor its health for human benefit and for identifying areas for improvement of our natural systems. The present study tries to assess the condition of a coastal ecosystem within the Vembanad Lake, Kerala, India, using key water quality parameters at micro-level. Principal component analysis identified the minimum required water quality dataset for further analysis and was scored using linear scoring functions. The weighted additive method was used to integrate the individual scores to arrive at a final score representing the ecosystem health. Spline interpolation was applied to develop the ecosystem health map of the study area. Using this method, 35.8% area of the aquatic ecosystem studied was characterized as good, 32.2% as moderate, 26.2% as fair and 5.8% as poor. The assessment results can help the policymakers/managers to make appropriate decisions for the better management of the coastal ecosystems studied. Moreover, this methodology can be replicated for the assessment of coastal regions with similar ecosystem characteristics. [ABSTRACT FROM AUTHOR]

Environmental pollution and climate change are causing major changes in the marine environment. Coastal zones around the world are experiencing changes such as nutrient influx, resulting in altered plankton communities. The aim of this study was to determine the response of zooplankton to the changes in the environmental variables in the coastal zone of the Arabian Sea, Southwest Coast of India, over 10 years. Zooplankton abundance, chlorophyll-a concentrations, and water quality variables (rainfall, nitrates, phosphates, pH, water temperature, and salinity) were quantified from January 2010 to December 2019. Water temperature, pH, salinity, and phosphates increased steadily across the sites during the study period whereas chlorophyll-a and nitrates decreased. Rainfall abundance was not exhibiting any patterns or trends. The effects of the sampled environmental variables on zooplankton abundance were tested using generalized linear mixed models. Salinity and phosphates negatively affected the zooplankton abundance whereas water temperature, pH, and chlorophyll-a concentration had a positive effect. Coastal zones in southwest India are experiencing declining phytoplankton abundance due to a number of environmental factors. Reduced phytoplankton combined with altered environmental variables are having declining effects on zooplankton. This decline in zooplankton population has far reaching effects on biota in higher trophic levels including economically important organisms such as fishes. [ABSTRACT FROM AUTHOR]

The present study highlights that seasonal salinity variability plays a significant role in meiobenthic distribution with special reference to nematode assemblages. Sediment and water samples were collected from Pulicat Lake, a hypersaline lake along the southeast coast of India during two seasons (Southwest Monsoon (SWM) and Northeast Monsoon (NEM)). Based on the salinity distribution, the lake is categorized into four regions, viz., southern inlet, central region, middle inlet, and northern inlet. Meiobenthic abundance was higher during SWM (226–12,206 Ind/10 cm2) than in NEM (640–10,424 Ind/10 cm2). The meiofaunal abundance was high in the central region during both the seasons, followed by the southern, northern, and middle inlet. The nematode was the dominant meiobenthic group, followed by copepod, polychaete, and foraminifera. Due to high organic matter, the central region was dominated by deposit feeding nematode species like Halalaimus longicaudatus and Terschellingia longicaudata. The southern and northern regions were dominated by free-living nematodes Rhabditis olitoria, Mesorhabditis capitata, Mononochus bastian, Paramononchus sp., Piranchulus sp., and Diploscapter cylindricus. Oncholaimus sp., a hypersaline indicator species, was reported from the middle inlet location. Statistical analysis suggests salinity as a critical parameter for the distribution and diversity of nematodes. [ABSTRACT FROM AUTHOR]

The lesser known coastal upwelling in the North Eastern Arabian Sea (NEAS) during summer monsoon, its associated dynamics and forcing mechanisms is elucidated for the first time using basin scale monthly time-series in-situ and satellite data. The presence of cool upwelled waters along northwest coast of India from July to early October with an associated increase in productivity was evident in both data. The low level Findlater jet blows towards west coast of India with high wind magnitude (10–12 m/s) during summer monsoon generates strong Ekman transport (1416 kg/m/s) at offshore and Ekman pumping velocity (1.349 m/s) at coastal region initiates upwelling. It was identified that the currents and remote forcing also regulate upwelling along the region. Although upwelling seems to exist along the northwest coast, it was weaker (25.5 °C) compared to the southwest coast where the SST dropped to 24 °C. The upwelling was observed in the south during June as a surface process, while it was observed along the northwest coast of India by the end of August. Even though the onset of upwelling in the NEAS and South Eastern Arabian Sea (SEAS) had a lag of two months, the recession of upwelling happened during late and early September respectively. The cause for the lag in the onset and cessation of upwelling between SEAS and NEAS is attributed to the propagation of Kelvin waves and southwest monsoon winds. The study also reveals that temperature and chlorophyll profiles show bi-modal peaks of high and low associated with winter cooling (winter) and upwelling (summer). [ABSTRACT FROM AUTHOR]

Compound extremes exhibit greater adverse impacts than their univariate counterparts. Studies have reported changes in frequency and the spatial extent of extremes in India; however, investigation of compound extremes is in the infancy state. This study investigates the historical variation of compound dry and hot extremes (CDHE) and compound wet and cold extremes (CWCE) during the Indian summer monsoon period from 1951 to 2019 using monthly data. Results are analyzed for 10 identified homogeneous regions for India. Our results unravelled that CDHE (CWCE) frequency has increased (decreased) by 1–3 events per decade for the recent period (1977–2019) relative to the base period (1951–1976). Overall, the increasing (decreasing) pattern of CDHE (CWCE) is high across North-central India, Western India, North-eastern India and South-eastern coastlines. Our findings help in identification of the parts of the country affected by frequent and widespread CDHE during the recent period, which is alarming. More detailed assessments are required to disentangle the complex physical process of compound extremes to improve risk management options. [ABSTRACT FROM AUTHOR]

Benthic biotic indices are important ecological tools extensively used to understand the ecological quality of coastal wetlands. The present study aimed to assess the ecological status of Kodungallur-Azhikode estuary for the first time by using widely used benthic indices such as species richness (S), Shannon diversity index (H′log2), BENTIX, benthic opportunistic polychaetes amphipods (BOPA), AZTI's Marine Biotic Index (AMBI) and multivariate AMBI (M-AMBI). In the canonical correspondence analysis, salinity, dissolved oxygen, organic matter, sediment Eh, sediment pH and sand were identified as important variance descriptors. A single species of an opportunist, Americorophium triaeonyx, an amphipod belonging to the ecological group (EG) III, significantly contributed to the total macrofaunal density. Other dominant opportunistic species included Obelia bidentata (EGII), Arcuatula senhousia (EGIII), Cirolana fluviatilis (EGII), Prionospio cirrifera (EGIV) and Capitella sp. (EGV). The overall assessment indicated a 'good to moderate' condition in AMBI, 'good to poor' condition in M-AMBI, 'high to moderate' condition in BENTIX, 'high to poor' condition in BOPA and 'moderate to poor' condition in univariate Shannon diversity index. All the multivariate indices tested in the study were correlated with each other except BOPA and M-AMBI. The group of stations dominated with a sandy substrate and a moderate level of organic content indicated high to good conditions while other stations demonstrated moderate to poor conditions. However, no significant variation in indices tested between seasons was observed. The present study recommends long-term monitoring of benthic macroinvertebrate assemblages with proper taxonomic identification and functional trait analysis for better calibration of indices, which is the key factor for getting better results. [ABSTRACT FROM AUTHOR]

The vulnerabilities of coastal communities have increased in recent years, as more people have to live in hazard-prone areas due to population growth. The east coast of India is one such vulnerable area that faces the combined challenge of climate risks and poverty. This study identifies the environmental and socioeconomic factors contributing to the resilience building that helped the communities in the study area to cope with cyclone Phailin in 2013 and cyclone Hudhud in 2014. We used questionnaire surveys, GIS and satellite data, and econometric analysis to identify these features. The damage suffered by the households, and the time needed by them to return to the pre-cyclone situation were used as indicators of resilience. We found that factors such as high education, decision-making power of women, and presence of coastline vegetation of local species such as cashew and palmyra helped the communities to build resilience toward cyclones. [ABSTRACT FROM AUTHOR]

Shale is the primary rock type in the shallow marine section of the Mahanadi Basin, East Coast of India. Shale, being intrinsically anisotropic, always affects the seismic data. Anisotropy derived from seismic and VSP has lower resolution and mostly based on P wave. The workflow discussed here uses Gardner equation to derive vertical velocity and uses a nonlinear fitting to extract the Thomsen's parameters using both the P wave and S wave data. These parameters are used to correct the sonic log of a deviated well as well as anisotropic AVO response of the reservoir. The presence of negative delta was observed, which is believed to be affected by the presence of chloride and illite in the rock matrix. This correction can be used to update the velocity model for time–depth conversion and pore pressure modelling. [ABSTRACT FROM AUTHOR]

Rice is generally grown under completely flooded condition and providing food for more than half of the world’s population. Any changes in weather parameters might affect the rice productivity thereby impacting the food security of burgeoning population. So, the crop yield forecasting based on weather parameters will help farmers, policy makers and administrators to manage adversities. The present investigation examines the application of stepwise multiple linear regression (SMLR), artificial neural network (ANN) solely and in combination with principal components analysis (PCA) and penalised regression models (e.g. least absolute shrinkage and selection operator (LASSO) or elastic net (ENET)) for rice yield prediction using long-term weather data. The R2 and root mean square error (RMSE) of the models varied between 0.22-0.98 and 24.02-607.29 kg ha−1, respectively during calibration. During validation with independent dataset, the RMSE and normalised root mean square error (nRMSE) ranged between 21.35-981.89 kg ha−1 and 0.98-36.7%, respectively. For evaluation of multiple models for multiple locations statistically, overall average ranks on the basis of R2 and RMSE of calibration; RMSE and nRMSE of validation were calculated and non-parametric Friedman test was applied to check the significant difference among the models. The ranking of the models revealed that LASSO (2.63) was the best performing model followed by ENET (3.07) while PCA-ANN (4.19) was the worst model which was found significant at p < 0.001. The reason behind good performance of LASSO and ENET is that these models prevent overfitting and reduce model complexity by penalising the magnitude of coefficients. Then, pairwise multiple comparison test was performed which indicated LASSO as the best model which was found similar to SMLR and ENET. So, for prediction of rice yield, these models can very well be utilised for west coast of India. [ABSTRACT FROM AUTHOR]

Seasonal and spatial phytoplankton distribution in relation to environmental factors was investigated in New Mangalore Port, a major port along the west coast of India. A well-mixed water column characterized the non-monsoon seasons, whereas it was weakly stratified during monsoon. Water quality index (TRIX) scores indicated good water quality except during pre-monsoon (inner zone surface) and monsoon (near bottom waters). Surface abundance of tychopelagic diatoms (Paralia sulcata, Melosira nummuloides, Cylindrotheca closterium, and Nitzschia sigma) was higher during non-monsoon seasons. Certain centric diatoms, e.g., Leptocylindrus danicus, P. sulcata, and Rhizosolenia imbricata, dominated during pre-monsoon (inner zone) and positively correlated with TRIX. High Skeletonema costatum and dinoflagellate abundance during the monsoon season coincided with high nutrient concentrations. Five potential toxic and fourteen harmful/bloom forming algal species were encountered at abundances below the level that can be considered as harmful to the ecosystem. In addition to a baseline database, this study highlights the potential use of certain diatom species as indicators of hydrography and water quality for monitoring dynamic coastal marine ecosystems. [ABSTRACT FROM AUTHOR]

The present study attempts to understand the seasonal and spatial variations in the physico-chemical (temperature, pH, salinity, dissolved oxygen, and nutrients) and productivity characteristics of the northern Arabian Sea off the Indian coast. Samples were collected from four different sites off the Veraval coast. The values of the physical and chemical variables were higher during the summer season, whereas nutrient concentrations were high during the winter season due to the maturity of intake nutrients during post-monsoon and winter convective mixing during the northeast monsoon. The dissolved oxygen (DO) concentration was strongly and positively correlated with the net primary productivity (NPP) and chlorophyll a (Chl-a) content to support productivity along the region. Dissimilarity in study variables was observed between the inshore and offshore locations. Principal component analysis revealed a strong relationship between nutrients and productivity variables (Chl-a and NPP). Nutrient levels were high at inshore sites, which can be attributed to the heavy nutrient load from land-based anthropogenic activities and impact due to natural processes like water mixing, sedimentation, and wave activities. Nutrients were strongly and positively correlated with the productivity variables, i.e., Chl-a and NPP. Chl-a positively correlated with NPP (r = 0.90), which indicates that it is a principle productivity pigment in the marine ecosystem. [ABSTRACT FROM AUTHOR]