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Artículos de revistas sobre el tema "Netravati"

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Publicado: 6 de septiembre de 2023

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1

P, Raveesha, K. E. Prakash y B. T. Suresh Babu. "Investigational Studies on Quantity of Salinity in Netravati River Estuary Sand-Coastal Karnataka". International Journal of Emerging Research in Management and Technology 6, n.º 6 (29 de junio de 2018): 46. http://dx.doi.org/10.23956/ijermt.v6i6.243.

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The salt water mixes with fresh water and forms brackish water. The brackish water contains some quantity of salt, but not equal to sea water. Salinity determines the geographic distribution of the number of marshes found in estuary. Hence salinity is a very important environmental factor in estuary system. Sand is one major natural aggregate, required in construction industry mainly for the manufacture of concrete. The availability of good river sand is reduced due to salinity. The quality of sand available from estuarine regions is adversely affected due to this reason. It is the responsibility of engineers to check the quality of sand and its strength parameters before using it for any construction purpose. Presence of salt content in natural aggregates or manufactured aggregates is the cause for corrosion in steel. In this study the amount of salinity present in estuary sand was determined. Three different methods were used to determine the salinity in different seasonal variations. The sand sample collected nearer to the sea was found to be high in salinity in all methods. It can be concluded that care should be taken before we use estuary sand as a construction material due to the presence of salinity.
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2

Chaitra, Mysooru R. Yadupathi Putty y H. S. Prasanna. "Subsurface Drainage and Storage Properties in the Western Ghats – A Study in the Basin of Netravati". Aquatic Procedia 4 (2015): 617–24. http://dx.doi.org/10.1016/j.aqpro.2015.02.080.

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3

Aedla, Raju, G. S. Dwarakish y D. Venkat Reddy. "Automatic Shoreline Detection and Change Detection Analysis of Netravati-GurpurRivermouth Using Histogram Equalization and Adaptive Thresholding Techniques". Aquatic Procedia 4 (2015): 563–70. http://dx.doi.org/10.1016/j.aqpro.2015.02.073.

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4

Parthasarathy, C. R., T. G. Sitharam y S. Kolathayar. "Geotechnical considerations for the concept of coastal reservoir at Mangaluru to impound the flood waters of Netravati River". Marine Georesources & Geotechnology 37, n.º 2 (15 de febrero de 2018): 236–44. http://dx.doi.org/10.1080/1064119x.2018.1430194.

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5

Sinha, Rakesh Kumar y T. I. Eldho. "Assessment of Soil Erosion Susceptibility Based on Morphometric and Landcover Analysis: A Case Study of Netravati River Basin, India". Journal of the Indian Society of Remote Sensing 49, n.º 7 (25 de marzo de 2021): 1709–25. http://dx.doi.org/10.1007/s12524-021-01354-1.

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6

Fernandes, Dearlyn, Ying Wu, Prabhaker Vasant Shirodkar, Umesh Kumar Pradhan, Zhuo‐Yi Zhu, Jing Zhang y Samwel Mchele Limbu. "Spatial and temporal variations in source, diagenesis, and fate of organic matter in sediments of the Netravati River, India". Hydrological Processes 33, n.º 20 (5 de agosto de 2019): 2642–57. http://dx.doi.org/10.1002/hyp.13516.

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7

Kumar, Avinash, K. S. Jayappa y B. Deepika. "Application of remote sensing and geographic information system in change detection of the Netravati and Gurpur river channels, Karnataka, India". Geocarto International 25, n.º 5 (agosto de 2010): 397–425. http://dx.doi.org/10.1080/10106049.2010.496004.

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8

Sudhakaran, Sandhya, Harsha Mahadevan, Vijayan Arun, Appukuttan Pillai Krishnakumar y Krishnan Anoop Krishnan. "A multivariate statistical approach in assessing the quality of potable and irrigation water environs of the Netravati River basin (India)". Groundwater for Sustainable Development 11 (octubre de 2020): 100462. http://dx.doi.org/10.1016/j.gsd.2020.100462.

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9

Satish, Misal Suraj, Kharbade Sattappa Bhambhar, Wankhede Sachin Yadavrao, Abdul Aziz Shaikh, R. Balasubramanian y Jadhav Jaywant Dadaji. "Agro Meteorological Indices Influenced by Varying Sowing Environment and Varieties of Wheat in Western Maharashtra Plain Zone". International Journal of Environment and Climate Change 13, n.º 8 (29 de mayo de 2023): 511–20. http://dx.doi.org/10.9734/ijecc/2023/v13i82076.

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An agro-meteorological investigation was undertaken during rabi, 2016 and 2017 at Farm, Department of Agricultural Meteorology, College of Agriculture, Pune, Maharashtra State (India). The experiment was laid out in split plot design with three replications. The treatment comprised of four varieties viz. V1: NIAW-301 (Trymbak ) V2: NIAW-917 (Tapovan), V3: NIAW-1415 (Netravati) and V4:NIAW-1994 (Phule Samadhan) as main plot and four sowing windows viz., S1: 43rd MW (22-28 October), S2: 45th MW (5-11November), S3: 47th MW (19-25 November) and S4: 49th MW (3-9 December) as sub plot treatments. The agrometeorological indices indicated more values for 45th MW (5-11November) and 47th MW (19-25 November) sown wheat crops and lowest values in late sown crop. Days to crown root stage, tillering stage, ear emergence stage, 50% flowering stage, milking stage, dough stage and physiology maturity matched closely with observed values for all sowing environments. It revealed that the grain yields were significantly higher in NIAW-1994 (51.07 and 48.52 qha-1) and significantly superior to the rest of the wheat varieties. This was followed by NIAW-917(45.72 and 43.43 q ha-1), NIAW-301(43.57 and 41.27 q ha-1). The variety NIAW-1415 recorded significantly lower grain yield (40.89 and 38.84 qha-1) during 2016 and 2017, respectively. The grain yield was maximum at 47th MW sowing window (50.40 and 47.88 qha-1), the grain yield of 45th MW (47.94 and 45.42 qha-1) were at par with 47th MW sowing window. This was followed by 43rd MW sowing window (43.88 and 41.68 q ha-1), 49th MW sowing window (39.04 and 37.07 q ha-1) during 2016 and 2017, respectively.
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10

Satish, Misal Suraj, Kharbade Sattappa Bhambhar, Wankhede Sachin Yadavrao, Abdul Aziz Shaikh, R. Balasubramanian y Jadhav Jaywant Dadaji. "Assessment of Crop Weather Relations in Wheat (Triticum aestivum) in Western Maharashtra Plain Zone". International Journal of Environment and Climate Change 13, n.º 8 (29 de mayo de 2023): 502–10. http://dx.doi.org/10.9734/ijecc/2023/v13i82000.

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Wheat (Triticum aestivum L.) is a thermo-sensitive long-day crop. Temperature is a major determinant of its growth and productivity. Late sown wheat exposes preanthesis phenological events to high temperature that influence grain development and ultimately the yield [1]. Comprehensive assessments of the influence of climate variability on crop yields at local and regional scales can be highly beneficial. With an aim to assess the weather influences on wheat at local scale this study was taken up. An experiment was conducted at Department of Agricultural Meteorology Farm, College of Agriculture, Pune, Maharashtra State (India) in a split-plot design with three replications and sixteen treatment combinations of four different varieties and four sowing windows. Four varieties used were NIAW-301 (Trymbak ), NIAW-917 (Tapovan), NIAW-1415 (Netravati) and NIAW-1994 (Phule Samadhan). Four sowings were taken up on 43rd MW (22-28 October), 45th MW (5-11November), 47th MW (19-25 November) and 49th MW (3-9 December). The grain yield of wheat was influenced significantly by wheat varieties. The grain yields were significantly higher in NIAW-1994 (51.07 and 48.52 qha-1) and significantly superior to the rest of the wheat varieties. This was followed by NIAW-917(45.72 and 43.43qha-1), NIAW-301(43.57 and 41.27 q ha-1). The variety NIAW-1415 recorded significantly lower grain yield (40.89 and 38.84 qha-1) during 2016 and 2017, respectively. Correlation analysis with weather parameters e.g. Temperature (Maximum and Minimum), Relative humidity (Morning and Evening), Rainfall and bright sunshine hours and yield showed that from tillering to 50% flowering stage, maximum temperature (-0.962*) was significantly negatively correlated with grain yield (r = -0.980**), (r =-0.950**) during 2016 and 2017, respectively in NIAW-301 (Trymbak ). The same trend was observed in the remaining varieties also. Regression equations were developed to predict the yield.
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11

Singh, R. Kr y A. Garg. "LECTOTYPIFICATION OF THE CRITICALLY ENDANGERED SUBSHRUB PHYLLANTHUS TALBOTII (PHYLLANTHACEAE)". Edinburgh Journal of Botany 73, n.º 1 (marzo de 2016): 133–38. http://dx.doi.org/10.1017/s096042861500030x.

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The critically endangered Phyllanthus talbotii Sedgw. (Phyllanthaceae) is endemic to the northern part of the Western Ghats in Goa and Karnataka, India. The species was described in 1921 from collections made in 1883, 1918 and 1919, and then rediscovered in 1969. We report here a new locality, Netravali Wildlife Sanctuary, South Goa district, Goa. The species is lectotypified and a detailed description is provided, including distribution, IUCN threat status, conservation measures and nomenclatural notes.
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12

VIJAYAKRISHNAN, BALAJI y JAYASIMHAN PRAVEENRAJ. "Mystus irulu, a new species of bagrid catfish from the Western Ghats of Karnataka, India (Teleostei: Bagridae)". Zootaxa 5120, n.º 3 (28 de marzo de 2022): 443–48. http://dx.doi.org/10.11646/zootaxa.5120.3.10.

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Mystus irulu, new species, is described from the Netravathi River system from the Western Ghats of Karnataka. It differs all South Asian congeners in having a uniformly black colour pattern, a long-based adipose fin reaching the base of the last dorsal-fin ray anteriorly, dorsal fin with convex dorsoposterior margin, and the following combination of characters: body depth at anus 19.9–22.3 % SL, dorsal-fin spine length 17.5–18.7 % SL, adipose-fin base 34.2–38.4 % SL, caudal peduncle depth 10.6–11.9 % SL and eye diameter 27.2–37.1 % HL.
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13

Darshan, M. S., Shivanna, K. Siddaraju y P. Madesh. "Quartz surface microtextural studies of netravathi estuary sediments, Karnataka, India". Bulletin of Pure & Applied Sciences- Geology 41f, n.º 1 (2022): 24–31. http://dx.doi.org/10.5958/2320-3234.2022.00003.8.

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14

Sealy, Cordelia. "‘Fully green’ composites ready to take off – An interview with Anil Netravali". Reinforced Plastics 63, n.º 6 (noviembre de 2019): 288–90. http://dx.doi.org/10.1016/j.repl.2019.01.001.

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15

Jain, Kshiteeja, Dhamija Kamakshiw y M. Netravathi. "Letter to editors: – Multiple sclerosis and related disorders – Netravathi et al., 2022". Multiple Sclerosis and Related Disorders 76 (agosto de 2023): 104828. http://dx.doi.org/10.1016/j.msard.2023.104828.

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16

Avvannavar, Santosh M. y S. Shrihari. "Evaluation of water quality index for drinking purposes for river Netravathi, Mangalore, South India". Environmental Monitoring and Assessment 143, n.º 1-3 (3 de octubre de 2007): 279–90. http://dx.doi.org/10.1007/s10661-007-9977-7.

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17

Avvannavar, Santosh M. y Surathkal Shrihari. "DETERMINATION OF WATER QUALITY DETERIORATION AT PILGRIMAGE CENTRE ALONG RIVER NETRAVATHI, MANGALORE USING WQI APPROACH". Environmental Engineering and Management Journal 6, n.º 2 (2007): 123–31. http://dx.doi.org/10.30638/eemj.2007.017.

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18

Kumar M, Ratheesh, Anoop Krishnan K, Revathy Das y Vimexen V. "Seasonal phytoplankton succession in Netravathi – Gurupura estuary, Karnataka, India: Study on a three tier hydrographic platform". Estuarine, Coastal and Shelf Science 242 (septiembre de 2020): 106830. http://dx.doi.org/10.1016/j.ecss.2020.106830.

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19

Shetty, Ateeth, K. S. Jayappa y D. Mitra. "Shoreline Change Analysis of Mangalore Coast and Morphometric Analysis of Netravathi-Gurupur and Mulky-pavanje Spits". Aquatic Procedia 4 (2015): 182–89. http://dx.doi.org/10.1016/j.aqpro.2015.02.025.

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20

Narshivudu, Daggula y A. T. Ramachandra Naik. "Spatio-temporal Distribution and Biochemical Composition of Phytoplankton along the Coastal Waters of Dakshin Kannada District, Karnataka, India". International Journal of Environment and Climate Change 13, n.º 8 (9 de junio de 2023): 1077–89. http://dx.doi.org/10.9734/ijecc/2023/v13i82046.

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The phytoplankton distribution and biochemical composition concerning water quality parameters were studied in the coastal waters off Mangalore, Monthly sampling was carried out from October 2020 to May 2022 at selected stations of Netravathi-Gurupura estuary, latitude 12°50'38.56" N, longitude 74°50'0.23° to coastal waters off Padubidri latitude 13° 8'0. 57" N longitude 74°42'9.47° with an average depth of 8 meters. Spatiotemporally the phytoplankton, chlorophyll-a and phytoplankton biochemical composition showed a significant difference for the entire duration. During the present investigation, 35 different phytoplankton genera belonging to 3 groups were observed with complete domination from diatoms with 27 genera followed by Dinoflagellates 7 and blue-green algae. distribution and abundance of the phytoplankton were mainly Chaetoceros sp., Ceratium sp., Thallasiocera sp., Biddulphia sp., Coscinodiscus sp., Rhizosolenia sp., Ditylum sp., Triceratium sp., Nitzschia sp. and blue-green algae under Chrysophyta, Bryophyta, Chlorophyta, Cyanophyta were observed, while in biochemical composition of phytoplankton, the carbon contributed to the highest percentage and hydrogen constitute to the lowest percentage. Crude protein and Lipid contents are maximum during post-monsoon and carbohydrates showed their highest content during pre-monsoon for phytoplankton. There is a direct relationship between the biochemical composition and the physiochemical and environmental conditions including nutrients, especially nitrates and phosphates.
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21

Kolathayar, Sreevalsa, T. G. Sitharam, R. Ramkrishnan R Ramkrishnan y R. Subba Rao. "Feasibility of creating a fresh water reservoir in the Arabian Sea impounding the flood waters of Netravathi River". Journal of Sustainable Urbanization, Planning and Progress 2, n.º 2 (2017): 38–42. http://dx.doi.org/10.26789/jsupp.2017.02.006.

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22

Saha, Ajoy, M. E. Vijaykumar, B. K. Das, S. Samanta, M. Feroz Khan, Tania Kayal, Chayna Jana y Arnab Roy Chowdhury. "Geochemical distribution and forms of phosphorus in the surface sediment of Netravathi-Gurupur estuary, southwestern coast of India". Marine Pollution Bulletin 187 (febrero de 2023): 114543. http://dx.doi.org/10.1016/j.marpolbul.2022.114543.

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23

Langdon, Glen G. "Book Rvw: Digital Video: An Introduction to MPEG-2. By Barry G. Haskell, Atul Puri, and Arun N. Netravali". Journal of Electronic Imaging 7, n.º 01 (1 de enero de 1998): 265. http://dx.doi.org/10.1117/1.jei.7.1.bookreview.

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24

Sylus, K. J. y H. Ramesh. "The Study of Sea Water Intrusion in Coastal Aquifer by Electrical Conductivity and Total Dissolved Solid Method in Gurpur and Netravathi River Basin". Aquatic Procedia 4 (2015): 57–64. http://dx.doi.org/10.1016/j.aqpro.2015.02.009.

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25

Honnanagoudar, S. S. y Girish K. H. "GEOLOGICAL AND GEOMORPHOLOGICAL ANALYSIS AND HYDROGEOCHEMICAL ENVIRONMENT OF AQUIFERS OF THE SOUTHERN WEST COAST OF KARNATAKA, INDIA". INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH, 1 de marzo de 2021, 54–57. http://dx.doi.org/10.36106/9239808.

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Dakshina kannada district is situated in peninsular region. The peninsula is composed of geologically ancient rocks of diverse original and most of them have undergone metamorphism. The early Precambrian tonalitic gneisses invaded by granites, granulites and dolerite dykes. Granulites are mostly restricted to areas south of Mangalore. High grade alumina rich (corundum bearing) metamorphic schists have been encountered and younger alkaline intrusive rocks like Aegerine syenites have been reported. There are ve rivers and estuaries. Number of lineaments cut across each other and some lineaments are parallel to each other. The Arabian sea class is the largest among other land cover features in the study area. The river/tidal creek land cover appear as long irregular and sinous in outline. Mulki river, Netravati river, Gurupur river at southern terrain. The qualities of groundwater at sandy aquifer are good, lateritic/weathered gneissic rocks it is sweet.
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26

Gayathri, S., K. Anoop Krishnan, A. Krishnakumar, T. M. Vishnu Maya, Vinu V. Dev, Sibin Antony y V. Arun. "Monitoring of heavy metal contamination in Netravati river basin: overview of pollution indices and risk assessment". Sustainable Water Resources Management 7, n.º 2 (23 de febrero de 2021). http://dx.doi.org/10.1007/s40899-021-00502-2.

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27

Vandana, M., Shiekha E. John, Syam Sunny, K. Maya y D. Padmalal. "Environmental impact assessment of laterite quarrying from Netravati–Gurpur river basin, South West Coast of India". Environment, Development and Sustainability, 9 de noviembre de 2022. http://dx.doi.org/10.1007/s10668-022-02741-5.

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28

Sinha, Rakesh Kumar y T. I. Eldho. "Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin, Western Ghats, India". Environmental Earth Sciences 77, n.º 3 (febrero de 2018). http://dx.doi.org/10.1007/s12665-018-7317-6.

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29

Prabhu, Prathiksha P., Koustav Pan y Jegatha Nambi Krishnan. "Microplastics: Global occurrence, impact, characteristics and sorting". Frontiers in Marine Science 9 (27 de septiembre de 2022). http://dx.doi.org/10.3389/fmars.2022.893641.

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Stressors like microplastics (MPs) cause proliferating environmental pollution globally. Since plastics are continuously introduced into water bodies through numerous paths, novel solutions are required to segregate as well as decline their quantity in various environmental sectors. Numerous techniques have been used and proposed in the last 10 years to screen and enumerate MPs, define the particle’s properties, for instance form, color, or size, and recognize the polymer material. This critical review aims to provide an overview of advanced procedures in MP investigation, provides illustrations of probable routes forward and lingering challenges, and categorizes present approaches as per their underlying research question. Methods presently employed for MP sampling, extraction, identification, characterization, and quantification were evaluated. Studies proposing use of precursors for removal of MPs from water via the sol–gel process were reviewed. Research on microfluidics systems finds application in environmental and industrial fields and has gained momentum in concentrating, sorting, classifying, focusing, and desegregating MPs. This review briefly discusses active and passive label-free microfluidic methods that are efficient in executing the desired particle separation and are gaining momentum in the ecological analysis of MPs. Although some sets of preliminary data of MPs at selected regions across the globe have been studied and obtained, the degree of MP contamination in most important rivers, nearshore inland areas, and air is yet to be understood completely. Along the Charleston Harbor Estuary, the MP concentration in intertidal sediment was found to be 0 to 652 MPs/m2. In Asia, at the South Korean region, western Pacific Ocean, a high plastic concentration of 15–9,400 particles/m3 was reported. In India, the MP concentration was identified as 288 pieces/m3 in the Netravati River. In Turkey, ingestion of MPs was reported to be found in 458 out of 1,337 fish samples, indicating the polluted situation of the Mediterranean Sea. Despite the rapid development in MP analysis, no standardized technique for sampling along with separation has been approved. Therefore, for attaining a more inclusive picture of MPs’ fate and abundance, this study highlights the importance of a standardized procedure for MP research that can be used globally and adequately enables comparisons around the world.
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30

Lotliker, Aneesh Anandrao, Sanjiba Kumar Baliarsingh, R. Venkat Shesu, Alakes Samanta, R. Chandrasekhar Naik y T. M. Balakrishnan Nair. "Did the Coronavirus Disease 2019 Lockdown Phase Influence Coastal Water Quality Parameters off Major Indian Cities and River Basins?" Frontiers in Marine Science 8 (1 de abril de 2021). http://dx.doi.org/10.3389/fmars.2021.648166.

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The end of the current decade experienced an outbreak of a new strain of coronavirus classified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) [coronavirus disease 2019 (COVID-19)] that spread across the globe within a short span of time and was declared as a global pandemic by the World Health Organization. In order to contain the spread of COVID-19, the Indian Government imposed lockdown in various phases, namely, the strict lockdown period (SLP) and relaxed lockdown period (RLP). The present study addresses changes in the magnitude of satellite-derived water quality parameters in the coastal waters off major Indian cities (Mumbai and Chennai) and river basins (Narmada, Mandovi-Zuari, Netravathi, Periyar, Kaveri, Krishna-Godavari, Mahanadi, and Hooghly) along the eastern Arabian Sea (EAS) and western Bay of Bengal (WBoB) during SLP and RLP. The daily climatology (2003–2019) and anomaly (2020) of different water quality parameters, viz., chlorophyll-a (chl-a), downwelling diffused attenuation coefficient (kd490), and particulate organic carbon (POC) were used in the present study to eliminate seasonal biases and to unravel the signature of lockdown-induced changes in the magnitude of the above water quality parameters. During the total lockdown period, the magnitude of the above parameters reduced significantly in the coastal waters of both the EAS and the WBoB. However, this reduction was more significant in the coastal waters of the WBoB, attributed to a reduction in the supply of anthropogenic nutrients. Among different studied locations, the magnitude of water quality parameters significantly decreased off Chennai and Hooghly, during SLP, which subsequently increased during RLP probably due to reduction in anthropogenic material influx during SLP and increase during RLP. During RLP, the coastal waters off Mahanadi showed a maximum decrease in the magnitude of water quality parameters followed by Mandovi-Zuari, irrespective of these regions’ quantum of anthropogenic material input, possibly due to the higher response time of the ecosystem to reflect the reduction in anthropogenic perturbations. The satellite-retrieved water quality parameters have provided valuable insight to efficiently describe the changes in the health of the Indian coastal environment in terms of phytoplankton biomass and water clarity.
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