An effective process-based modeling approach for predicting hypoxia and blue tide in Tokyo Bay

Abstract

ABSTRACT Hypoxia and blue tide are the most significant environmental issues in Tokyo Bay as they have been damaging fisheries for a long time. Although studies on modeling these two associated phenomena have been conducted for decades, the scarcity of relevant observational datasets has greatly hindered the progress, and no study has successfully reproduced the entire processes of blue tide or predicted the time and place of its outbreak. To address the problems from limited data, this study proposed a relatively conventional benthic flux model and developed a novel method that converts the total organic carbon content into the fluxes of sediment oxygen consumption and sulfide release to represent the spatial differences in benthic fluxes. A pelagic sulfur model with only three key chemical reactions of blue tide that includes the disproportionation of elemental sulfur was proposed. The method significantly improved the results of dissolved oxygen in bottom water, as seen by the root mean square error decreasing by 15.9% and 18.9% in two simulations with largely different forcings. The sulfur model also accurately predicted the outbreaks of blue tides in each simulation, which is significant to the stakeholders as it facilitates the forecast of blue tides in Tokyo Bay.