Assessment of an ocean-ecosystem model in simulating the Indian coastal marine ecosystem dynamics. Issue 3 (2nd September 2022)

• Record Type: Journal Article
• Authors: Chakraborty, Kunal; Lotliker, Aneesh A.; Gupta, G.V.M.; Narayanan Nampoothiri S., Vishnu; Paul, Arya; Ghosh, Jayashree; Bhattacharya, Trishneeta; Baliarsingh, Sanjiba Kumar; Samanta, Alakes
• Is Part Of: Journal of operational oceanography. Volume 15:Issue 3(2022)
• Page Start: 137
• Page End: 155
• Publication Date: 2022-09-02
• Subjects: Indian coastal waters -- ROMS -- SATCORE -- phytoplankton bloom -- coastal hypoxia; Oceanography -- Periodicals; Climatology -- Periodicals; Periodicals; 551.4605
• DOI: 10.1080/1755876X.2020.1843298
• Languages: English
• ISSNs: 1755-876X

Abstract

ABSTRACT: This study describes an assessment of an ocean-ecosystem model in simulating marine ecosystem dynamics in the Indian coastal waters. Long-term sustained in-situ observations of temperature, salinity, chlorophyll-a and dissolved oxygen (DO) collected in the coastal waters of India, and ship-based observations are used for this assessment. The model captures observed trend of temperature, salinity and chlorophyll-a with high correlation in both eastern and western shelf waters except for salinity and DO along west and DO along east coast. The model performs very well in simulating the Indian coastal shelf ecosystem dynamics. The seasonal occurrence of prominent phytoplankton bloom in the central-east coast during pre-monsoon, south-west coast during monsoon and north-west coast during post-monsoon is realistically reproduced by the model. The model also reproduces the seasonal presence of significantly low DO content in the upwelled water at a shallow depth leading to coastal hypoxia in the south-west and central-east coast of India during summer monsoon. A fine-tuned model is useful in understanding better Indian coastal shelf ecosystem and predicting future changes in time and space, like the occurrence of coastal hypoxia or anticipating phytoplankton blooms. Such information is useful for predicting potential fishing grounds in coastal waters and fisheries management.