Assessing and Predicting Nearshore Seawater Quality with Spatio-Temporal Semivariograms: The Case of Coastal Waters in Fujian Province, China

Abstract

The scientific assessment and prediction of nearshore water quality are crucial for marine environment protection efforts. This study is based on a comprehensive analysis of existing assessment and prediction methods and considers the regular and random characteristics of nearshore seawater quality due to both natural and anthropogenic influences. It proposes a new method that applies the kriging interpolation algorithm to empirically generated spatio-temporal semivariograms to assess and predict seawater quality. The application of this method in Fujian coastal areas shows that it is able to flexibly and scientifically estimate the variations in various indicators in the region. Combined with GIS spatial data overlay analysis operations, it can be used to quantitatively evaluate different qualities of seawater and provide scientific guidance for marine environmental protection.