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Mapping of tide-dominated Hooghly estuary water quality parameters using Sentinel-3 OLCI time-series data

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Abstract

The study explores the spatio-temporal variation of water quality parameters in the Hooghly estuary, which is considered an ecologically-stressed shallow estuary and a major distributary for the Ganges River. The estimated parameters are chlorophyll-a, total suspended matter (TSM), and chromophoric dissolved organic matter (CDOM). The Sentinel-3 OLCI remote sensing imageries were analyzed for the duration of October 2018 to February 2019. We observed that the water quality of the Hooghly estuaries is comparatively low-oxygenated, mesotrophic, and phosphate-limited. Ongoing channel dredging for maintaining shipping channel depth keeps the TSM in the estuary at an elevated level, with the highest amount of TSM observed during March of 2019 (41.59g m−3) at station A, upstream point. Since the pre-monsoon season, TSM data shows a decreasing trend towards the mouth of the estuary. Chl-a concentration is higher during pre-monsoon than monsoon and post-monsoon periods, with the highest value observed in April at 1.09 mg m−3 in station D during the pre-monsoon period. The CDOM concentration was high in the middle section (January–February) and gradually decreased towards the estuary’s head and mouth. The highest CDOM was found in February at locations C and D during the pre-monsoon period. Every station shows a significant correlation among CDOM, TSM, and Chl-a measured parameters. Based on our satellite data analysis, it is recommended that SNAP C2RCC be regionally used for TSM, Chl-a, and CDOM for water quality product retrieval and in various algorithms for the Hooghly estuary monitoring.

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Data Availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

References

  • Alikas, K., & Kratzer, S. (2017). Improved retrieval of Secchi depth for optically-complex waters using remote sensing data. Ecological Indicators, 77, 218–227.

    Article  Google Scholar 

  • Bandyopadhyay, J., Mondal, I., & Samanta, N. (2014). Shore line shifting of Namkhana Island of Indian Sundarban, South 24 Parganas, West Bengal, India, using remote sensing &GIS techniques. International Journal of Engineering Sciences & Research Technology, 3(5), 162–169.

    Google Scholar 

  • Bag, R., Mondal, I., & Bandyopadhyay, J. (2019). Assessing the oscillation of channel geometry and meander migration cardinality of Bhagirathi River, West Bengal, India. Journal of Geographical Sciences, 29(4), 613–634. https://doi.org/10.1007/s11442-019-0000-0

    Article  Google Scholar 

  • Biswas, H., Dey, M., Ganguly, D., De, T. K., Ghosh, S., & Jana, T. K. (2010). Comparative analysis of phytoplankton composition and abundance over a two-decade period at the land–ocean boundary of a tropical mangrove ecosystem. Estuaries and Coasts, 33(2), 384–394. https://doi.org/10.1007/s12237-009-9193-5

    Article  CAS  Google Scholar 

  • Bricaud, A., Morel, A., & Prieur, L. (1981). Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains 1. Limnology and Oceanography, 26(1), 43–53.

    Article  CAS  Google Scholar 

  • Chauhan, P., Mohan, M., Nayak, S. R., & Navalgund, R. R. (2002). Comparison of ocean color chlorophyll algorithms for IRS-P4 OCM sensor using in-situ data. Journal of the Indian Society of Remote Sensing, 30(1-2), 87–94. https://doi.org/10.1007/BF02989980

    Article  Google Scholar 

  • Chugh, R. S. (1961). Tides in Hooghly river. Hydrological Sciences Journal, 6(2), 10–26. https://doi.org/10.1080/02626666109493212

    Article  Google Scholar 

  • Cifuentes, L. A., Schemel, L. E., & Sharp, J. H. (1990). Qualitative and numerical analyses of the effects of river inflow variations on mixing diagrams in estuaries. Estuarine, Coastal and Shelf Science, 30(4), 411–427.

    Article  CAS  Google Scholar 

  • Das, S., Das, I., Giri, S., Chanda, A., Maity, S., Lotliker, A.A., Kumar, T. S., Akhand, A., & Hazra, S. (2017). Chromophoric dissolved organic matter (CDOM) variability over the continental shelf of the northern Bay of Bengal. Oceanologia, 59(3), 271-282. https://doi.org/10.1016/j.oceano.2017.03.002

  • De, T. K., Raman, M. S., Mukherjee, S. K., & A. (2021). Ecological assessment of Hooghly River considering a few of the more perturbed sites based on some relevant physico-chemical and biological variables—A part of the AVIRIS-NG (NASA-ISRO) ground truth verification. Regional Studies in Marine Science, 41(2021), 101598. https://doi.org/10.1016/j.rsma.2020.101598

    Article  Google Scholar 

  • Dutta, S., Chanda, A., Akhand, A., & Hazra, S. (2016). Correlation of phytoplankton biomass (chlorophyll-a) and nutrients with the catch per unit effort in the PFZ forecast areas of Northern Bay of Bengal during simultaneous validation of winter fishing season. Turkish Journal of Fisheries and Aquatic Sciences, 16(4), 767–777. https://doi.org/10.4194/1303-2712-v16403

    Article  Google Scholar 

  • Gao, C., Wang, Z., Ji, X., Wang, W., Wang, Q., & Qing, D. (2023). Coupled improvements on hydrodynamics and water quality by flowing water in towns with lakes. Environmental Science and Pollution Research, 30(16), 46813–46825. https://doi.org/10.1007/s11356-023-25348-3

    Article  Google Scholar 

  • Hong, H., Yang, L., Guo, W., Wang, F., & Yu, X. (2012). Characterization of dissolved organic matter under contrasting hydrologic regimes in a subtropical watershed using PARAFAC model. Biogeochemistry, 109(1-3), 163–174. https://doi.org/10.1007/s10533-011-9617-8

    Article  CAS  Google Scholar 

  • ISO 7887. (1994). Water quality. In Examination of water colour. European Committee for Standardization.

    Google Scholar 

  • Keith, D. J., Yoder, J. A., & Freeman, S. A. (2002). Spatial and temporal distribution of colored dissolved organic matter (CDOM) in Narragansett Bay, Rhode Island: Implications for phytoplankton in coastal waters. Estuarine, Coastal and Shelf Science, 55(5), 705–717. https://doi.org/10.1006/ecss.2001.0922

    Article  CAS  Google Scholar 

  • Kirk, J. T. (1994). Light and photosynthesis in aquatic ecosystems. Cambridge university press. https://catalogue.nla.gov.au/Record/229672

  • Kim, Y., Kimball, J. S., Zhang, K., Didan, K., Velicogna, I., & McDonald, K. C. (2014). Attribution of divergent northern vegetation growth responses to lengthening non-frozen seasons using satellite optical-NIR and microwave remote sensing. International Journal of Remote Sensing, 35(10), 3700–3721. https://doi.org/10.1080/01431161.2014.915595

    Article  Google Scholar 

  • Kostoglidis, A., Pattiaratchi, C. B., & Hamilton, D. P. (2005). CDOM and its contribution to the underwater light climate of a shallow, microtidal estuary in south-western Australia. Estuarine, Coastal and Shelf Science, 63(4), 469–477. https://doi.org/10.1016/j.marchem.2005.03.002

    Article  CAS  Google Scholar 

  • Kowalczuk, P., Stoń-Egiert, J., Cooper, W. J., Whitehead, R. F., & Durako, M. J. (2005). Characterization of chromophoric dissolved organic matter (CDOM) in the Baltic Sea by excitation-emission matrix fluorescence spectroscopy. Marine Chemistry, 96(3-4), 273–292.

    Article  CAS  Google Scholar 

  • Kutser, T. P., Kallio, D. C., Reinart, K. Y., Sobek, A., & S. (2005). Mapping lake CDOM by satellite remote sensing. Remote Sensing of Environment, 94(4), 535–540. https://doi.org/10.1016/j.rse.2004.11.009

    Article  Google Scholar 

  • Lee, Z., Wei, J., Voss, K., Lewis, M., Bricaud, A., & Huot, Y. (2015). Hyperspectral absorption coefficient of “pure” seawater in the range of 350–550 nm inverted from remote sensing reflectance. Applied Optics, 54, 546–558. https://doi.org/10.1364/AO.54.000546

    Article  Google Scholar 

  • Liu, Z., Xu, J., Liu, M., Yin, Z., Liu, X., Zheng, W., & Yin, L. (2023). Remote sensing and geostatistics in urban water-resource monitoring: a review. Marine and Freshwater Research. https://doi.org/10.1071/MF22167

    Article  Google Scholar 

  • Misra, A., Murali, R. M., Sukumaran, S., & Vethamony, P. (2014). Seasonal variations of total suspended matter (TSM) in the Gulf of Khambhat, west coast of India. Indian Journal of Geo-Marine Sciences, 43(7), 1202–1209 http://drs.nio.org/drs/handle/2264/7635

    Google Scholar 

  • Mitra, S., Ghosh, S., Satpathy, K. K., Bhattacharya, B. D., Sarkar, S. K., Mishra, P., & Raja, P. (2017). Water quality assessment of the ecologically stressed Hooghly River Estuary, India: A multivariate approach. Marine Pollution Bulletin, 126, 592–599. https://doi.org/10.1016/j.marpolbul,2017.09.053

    Article  Google Scholar 

  • Mondal, I., & Bandyopadhyay, J. (2014a). Coastal zone mapping through geospatial technology for resource management of Indian Sundarban, West Bengal, India. International Journal of Remote Sensing Applications, 4(2), 103–112. https://doi.org/10.14355/ijrsa.2014.0402.04

    Article  Google Scholar 

  • Mondal, I., & Bandyopadhyay, J. (2014b). Environmental change of trans international boundary Indo-Bangladesh border of Sundarban Ichamati River catchment area using geoinformatics technology. Universal Journal of Environmental Research and Technology, 4, 143–154.

    Google Scholar 

  • Mondal, I., Bandyopadhyay, J., & Paul, A. K. (2016). Water quality modeling for seasonal fluctuation of Ichamati river, West Bengal, India. Modeling Earth Systems and Environment, 2(3), 113. https://doi.org/10.1007/s40808-016-0153-3

    Article  Google Scholar 

  • Mondal, I., Bandyopadhyay, J., & Dhara, S. (2016). Detecting shoreline changing trends using principle component analysis in Sagar Island, West Bengal, India. Journal of Spatial Information Research, Springer Nature, 25, 67–73. https://doi.org/10.1007/s41324-016-0076-0

    Article  Google Scholar 

  • Mondal, I., Thakur, S., Ghosh, P. B., De, T. K., & Bandyopadhyay, J. (2018). Land use/land cover modeling of Sagar Island, India using remote sensing and GIS techniques, Springer Advances in Intelligent Systems and Computing (AISC). Emerging Technologies in Data Mining and information Security, 755. https://doi.org/10.1007/978-981-13-1951-8_69:771-785

  • Mondal, I., Thakur, S., & Bandyopadhyay, J. (2019). Delineating lateral channel migration and risk zones of Ichamati River, West Bengal, India. Journal of Cleaner Production, 244, 118740. https://doi.org/10.1016/j.jclepro.2019.11874

    Article  Google Scholar 

  • Mondal, I., Thakur, S., Juliev, M., Bandyopadhyay, J., & De, T. K. (2020). Spatio-temporal modelling of shoreline migration in Sagar Island, West Bengal, India. Journal of Coastal Conservation, 24(50), 1–20. https://doi.org/10.1007/s11852-020-00768-2

    Article  Google Scholar 

  • Mondal, I., Thakur, S., Juliev, M., & De, T. K. (2021). Comparative analysis of forest canopy mapping methods for the Sundarban biosphere reserve, West Bengal, India. Environment, Development and Sustainability, 23, 15157–15182. https://doi.org/10.1007/s10668-021-01291-6

    Article  Google Scholar 

  • Mondal, I., Thakur, S., Ghosh, P. B., & De, T. K. (2021). Assessing the impacts of global sea level rise (SLR) on the mangrove forests of Indian Sundarbans using geospatial technology. Geographic Information Science for Land Resource Management, 11, 209–228. https://doi.org/10.1002/9781119786375.ch11

    Article  Google Scholar 

  • Mondal, I., De, A., Nandi, S., Thakur, S., Raman, M., Jose, F., & De, T. K. (2023). Estimation of chlorophyll-a, TSM and salinity in mangrove dominated tropical estuarine areas of Hooghly River, north east coast of Bay of Bengal, India using sentinel-3 data. Journal: Acta Geophysica. https://doi.org/10.1007/s11600-023-01040-5

  • Monachou, S., Alexandridis, T. K., Kalopesa, E., Antoniadis, A., Zalidis, G. C., & Misopolinos, N. (2014). Remotely sensed time series of chlorophyll-α, total suspended matter and sea surface temperature for monitoring water quality of Thermaikos gulf (Greece). Fresenious Environmental Bulletin, 23, 2636–2644.

    CAS  Google Scholar 

  • Mukherjee, J., Banerjee, M., Banerjee, A., Roy, M., Ghosh, P. B., & Ray, S. (2014). Impact of environmental factors on the carbon dynamics at Hooghly estuarine region. Journal of Ecosystems. https://doi.org/10.1155/2014/607528

  • Mukhopadhyay, S. K., Biswas, H. D. T. K., De, T. K., & Jana, T. K. (2006). Fluxes of nutrients from the tropical River Hooghly at the land–ocean boundary of Sundarbans, NE Coast of Bay of Bengal, India. Journal of Marine Systems, 62(1-2), 9–21. https://doi.org/10.1016/j.jmarsys.2006.03.004

    Article  Google Scholar 

  • Nieke, B., Reuter, R., Heuermann, R., Wang, H., Babin, M., & Therriault, J. C. (1997). Light absorption and fluorescence properties of chromophoric dissolved organic matter (CDOM) in the St. Lawrence Estuary (Case 2 glasses of water). Continental Shelf Research, 17(3), 235–252. https://doi.org/10.1016/S0278-4343(96)00034-9

    Article  Google Scholar 

  • Padhy, P. C., Nayak, R. K., Dadhwal, V. K., Salim, M., Mitra, D., Chaudhury, S. B., Rao, P. R., Rao, K. H., & Dutt, C. B. S. (2016). Estimation of partial pressure of carbon dioxide and air-sea fluxes in Hooghly estuary based on in situ and satellite observations. Journal of the Indian Society of Remote Sensing, 44(1), 135–143. https://doi.org/10.1007/s12524-015-0459-z

    Article  Google Scholar 

  • Pastor-Guzman, J., Brown, L., Morris, H., Bourg, L., Goryl, P., Dransfeld, S., & Dash, J. (2020). The Sentinel-3 OLCI terrestrial chlorophyll index (OTCI): Algorithm improvements, spatiotemporal consistency and continuity with the MERIS archive. Remote Sensing, 12(16, 2652). https://doi.org/10.3390/rs12162652

  • Pegau, W. S., & Zaneveld, J. V. (1993). Temperature-dependent absorption of water in the red and near-infrared portions of the spectrum [Electronic version]. Limnology and Oceanography, 38(1), 188–192.

    Article  CAS  Google Scholar 

  • Poddar, S., Chacko, N., & Swain, D. (2019). Estimation of chlorophyll-a in northern coastal Bay of Bengal using Landsat-8 OLI and Sentinel-2 MSI sensors. Frontiers in Marine Science, 6, 98. https://doi.org/10.3389/fmars.2019.00598

    Article  Google Scholar 

  • Preisendorfer, R. W. (1986). Secchi disk science: Visual optics of natural waters. Limnology and Oceanography, 3(5), 909–926.

    Article  Google Scholar 

  • Rakshit, D., Biswas, S. N., Sarkar, S. K., Bhattacharya, B. D., Godhantaraman, N., & Satpathy, K. K. (2014). Seasonal variations in species composition, abundance, biomass and production rate of tintinnids (Ciliata: Protozoa) along the Hooghly (Ganges) River Estuary, India: A multivariate approach. Environmental monitoring and assessment, 186(5), 3063–3078. https://doi.org/10.1007/s10661-013-3601-9

    Article  CAS  Google Scholar 

  • Ramaiah, N., Fernandes, V., Paul, J. T., Jyothibabu, R., Gauns, M., & Jayraj, E. A. (2010). Seasonal variability in biological carbon biomass standing stocks and production in the surface layers of the Bay of Bengal Indian. Journal of Marine Sciences, 39(3), 369–379 http://drs.nio.org/drs/handle/2264/3751

    Google Scholar 

  • Regnier, P., & O'kane, J.P. (2004). On the mixing processes in estuaries: The fractional freshwater method revisited. Estuaries, 27(4), 571–582.

    Article  CAS  Google Scholar 

  • Retamal, L., Vincent, W. F., Martineau, C., & Osburn, C. L. (2007). Comparison of the optical properties of dissolved organic matter in two river-influenced coastal regions of the Canadian Arctic. Estuarine, Coastal and Shelf Science, 72(1-2), 261–272. https://doi.org/10.1016/j.ecss.2006.10.022

    Article  Google Scholar 

  • Rose, L., Bhaskaran, P. K., & Kani, S. P. (2015). Tidal analysis and prediction for the Gangra Location, Hooghly estuary in the Bay of Bengal. Current Science, 109(4), 745–758.

    Google Scholar 

  • Sarangi, R. K. (2011). Impact of cyclones on the Bay of Bengal chlorophyll variability using remote sensing satellites. Indian Journal of Geo-Marine Sciences, 40(6), 794–801.

    Google Scholar 

  • Sentinel-3. (2021). https://sentinel.esa.int/web/sentinel/missions/sentinel-3. (Accessed Date: 05/01/2021)

  • Song, K., Li, L., Wang, Z., Liu, D., Zhang, B., Xu, J., Du, J., Li, L., Li, S., & Wang, Y. (2012). Retrieval of total suspended matter (TSM) and chlorophyll-a (Chl-a) concentration from remote-sensing data for drinking water resources. Environmental monitoring and assessment, 184(3), 1449–1470. https://doi.org/10.1007/s10661-011-2053-3

    Article  CAS  Google Scholar 

  • Stedmon, C. A., Markager, S., & Kaas, H. (2000). Optical properties and signatures of chromophoric dissolved organic matter (CDOM) in Danish coastal waters. Estuarine, Coastal and Shelf Science, 51(2), 267–278. https://doi.org/10.1006/ecss.2000.0645

    Article  CAS  Google Scholar 

  • Strickland, J. D., & Parsons, T. R. (1972). A manual of seawater analysis. Fisheries Research Board Canada, 167, 310.

    Google Scholar 

  • Tian, Y., Yang, Z., Yu, X., Jia, Z., Rosso, M., Dedman, S., & Wang, J. (2022). Can we quantify the aquatic environmental plastic load from aquaculture? Water Research, 219https://doi.org/10.1016/j.watres.2022.118551

  • Thakur, S., Mondal, I., Ghosh, P. B., Das, P., & De, T. K. (2019). A review of the application of multispectral remote sensing in studying mangrove ecosystems with particular emphasis on image processing techniques. Journal of Spatial Information Research, 28, 39–51. https://doi.org/10.1007/s41324-019-00268-y

    Article  Google Scholar 

  • Thakur, S., Maity, D., Mondal, I., Basumatary, G., Ghosh, P. B., & De, T. K. (2020a). Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environment, Development, and Sustainability, 22(3), 1–29. https://doi.org/10.1007/s10668-020-00656-7

    Article  Google Scholar 

  • Thakur, S., Mondal, I., Bar, I., Nandi, S., Ghosh, P. B., Das, P., & De, T. K. (2020b). Shoreline changes and its impact on the mangrove ecosystems of some islands of Indian Sundarbans. North-East coast of India, Journal of Cleaner Production, 124764. https://doi.org/10.1016/j.jclepro.2020.124764

  • Toming, K., Kutser, T., Uiboupin, R., Arikas, A., Vahter, K., & Paavel, B. (2017). Mapping water quality parameters with sentinel-3 ocean and land colour instrument imagery in the Baltic Sea. Remote Sensing, 9(10), 1070. https://doi.org/10.3390/rs9101070

    Article  Google Scholar 

  • Tian, H., Huang, N., Niu, Z., Qin, Y., Pei, J., & Wang, J. (2019). Mapping Winter Crops in China with Multi-Source Satellite Imagery and Phenology-Based Algorithm. Remote sensing (Basel, Switzerland), 11(7), 820. https://doi.org/10.3390/rs11070820

    Article  Google Scholar 

  • Tian, H., Pei, J., Huang, J., Li, X., Wang, J., Zhou, B., & Wang, L. (2020). Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China. Remote sensing (Basel, Switzerland), 12(3539), 3539. https://doi.org/10.3390/rs12213539

    Article  Google Scholar 

  • Vuolo, F., Żółtak, M., Pipitone, C., Zappa, L., Wenng, H., Immitzer, M., Weiss, M., Baret, F., & Atzberger, C. (2016). Data service platform for Sentinel-2 surface reflectance and value-added products: System use and examples. Remote Sensing, 8(11), 938. https://doi.org/10.3390/rs8110938

    Article  Google Scholar 

  • Wattayakorn, G., Wolanski, E., & Kjerfve, B. (1990). Mixing, trapping, and outwelling in the Klong Ngao mangrove swamp, Thailand. Estuarine, Coastal and Shelf Science, 31(5), 667–688.

    Article  CAS  Google Scholar 

  • Zhou, L., & Sun, J. (2022). Integrated ecosystem management and regulation strategies in the South China Sea. Journal of Sea Research, 190, 102300. https://doi.org/10.1016/j.seares.2022.102300

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Abirup Ranjan Bar and Ismail Mondal: conceptualization, writing—original draft, software, formal analysis, visualization. Sourav Das, Bratin Biswas, Sourav Samanta, Felix Jose, Ali Najah Ahmed, and Van Nam Thai: data curation, formal analysis; writing—original draft, visualization, writing, review and editing, supervision. All authors read and approved the final manuscript.

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Bar, A.R., Mondal, I., Das, S. et al. Mapping of tide-dominated Hooghly estuary water quality parameters using Sentinel-3 OLCI time-series data. Environ Monit Assess 195, 975 (2023). https://doi.org/10.1007/s10661-023-11552-8

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