The present study investigates the seawater quality of the Nizampatnam Bay–Lankavani Dibba coastal region along the East Coast of India, with a focus on seasonal variations in physico-chemical parameters during the pre-monsoon (July–August) and post-monsoon (January–March) periods between 2016 and September 2017. Seawater samples were collected from 30 sites within the study area to assess the suitability of the marine water for survival of the marine biota. Key water quality parameters including pH, temperature (°C), electrical conductivity (mS), organic matter (μg/mg) and silica (μg/mg) were analysed to understand seasonal fluctuations. Principal component analysis (PCA) was applied to the dataset to extract linear relationships among variables and identify the primary sources of variation. The study highlights the influence of monsoonal changes on water quality and the implications for marine ecosystem health. This multivariate statistical approach provides a comprehensive framework for interpreting complex environmental data and assessing the ecological condition of coastal waters.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Assessment of Water Quality of Nizampatnam Bay–Lankavai Dibba Coastal Region of India: A Statistical Approach

  • B. Lakshmanna,
  • Sreenivasulu Ganugapenta,
  • C. Sathiya,
  • N. Jayaraju,
  • T. Lakshmi Prasad,
  • K. Nagalakshmi,
  • M. Pramod Kumar

摘要

The present study investigates the seawater quality of the Nizampatnam Bay–Lankavani Dibba coastal region along the East Coast of India, with a focus on seasonal variations in physico-chemical parameters during the pre-monsoon (July–August) and post-monsoon (January–March) periods between 2016 and September 2017. Seawater samples were collected from 30 sites within the study area to assess the suitability of the marine water for survival of the marine biota. Key water quality parameters including pH, temperature (°C), electrical conductivity (mS), organic matter (μg/mg) and silica (μg/mg) were analysed to understand seasonal fluctuations. Principal component analysis (PCA) was applied to the dataset to extract linear relationships among variables and identify the primary sources of variation. The study highlights the influence of monsoonal changes on water quality and the implications for marine ecosystem health. This multivariate statistical approach provides a comprehensive framework for interpreting complex environmental data and assessing the ecological condition of coastal waters.