Abstract

Harmful algal blooms (HABs) occur frequently in the Seto Inland Sea, bringing significant economic and environmental losses for the area, which is well known as one of the world’s most productive fisheries. Our objective was to develop a quantitative model using in situ hyperspectral measurements in the Seto Inland Sea to estimate chlorophyll a (Chl-a) concentration, which is a significant parameter for detecting HABs. We obtained spectra and Chl-a data at six stations from 12 ship-based surveys between December 2015 and September 2017. In this study, we used an iterative stepwise elimination partial least squares (ISE-PLS) regression method along with several empirical and semi-analytical methods such as ocean chlorophyll, three-band model, and two-band model algorithms to retrieve Chl-a. Our results showed that ISE-PLS using both the water-leaving reflectance (RL) and the first derivative reflectance (FDR) had a better predictive ability with higher coefficient of determination (R2), lower root mean squared error (RMSE), and higher residual predictive deviation (RPD) values (R2 = 0.77, RMSE = 1.47 and RPD = 2.1 for RL; R2 = 0.78, RMSE = 1.45 and RPD = 2.13 for FDR). However, in this study the ocean chlorophyll (OC) algorithms had poor predictive ability and the three-band and two-band model algorithms did not perform well in areas with lower Chl-a concentrations. These results support ISE-PLS as a potential coastal water quality assessment method using hyperspectral measurements.

Highlights

  • The Seto Inland Sea is an approximately 23,000 km2 semi-enclosed coastal sea in western Japan, with an average depth of 38 m

  • We found that iterative stepwise elimination Partial least squares (PLS) (ISE-PLS) using both indicated by R (0.77 for RL and 0.78 for first derivative reflectance (FDR)) and residual predictive deviation (RPD) (2.10 for RL and 2.13 for FDR) values in the datasets had better chlorophyll a (Chl-a) retrieval performance than other algorithms, which was indicated by R2 validation results

  • We developed various models for estimating water Chl-a concentration in the Seto

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Summary

Introduction

The Seto Inland Sea is an approximately 23,000 km semi-enclosed coastal sea in western Japan, with an average depth of 38 m. This sea is well-known as one of the world’s most productive fisheries due to its abundance of fish and variety of fish species [1]. 35 million people live around the Seto Inland Sea, bringing increased industrialization and urbanization that have made the. Seto Inland Sea one of Japan’s most industrialized regions [2]. Eutrophication of coastal waters has affected fishing and other activities by contributing to harmful algal blooms (HABs), known as red tides. HABs frequently occurred in the Seto Inland Sea during a period of high economic growth in the

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