On the Sensitivity of Coastal Hypoxia to Its External Physical Forcings

Abstract

The development of low‐oxygen zones threatening marine life (hypoxia) occurs annually in multiple coastal regions of the world. The largest estuary of the continental United States, the Chesapeake Bay, typically has ≈10 km3 of water with dioxygen concentrations <3 mg L−1 in July. As numerical methods for refining model resolutions in targeted areas are becoming common, there is interest in assessing the feasibility of simulating coastal hazards such as hypoxia in Earth System Models (ESMs). These coupled models are typically not constrained by observations and thus likely to feature systematic biases in their land, atmosphere, or ocean components. This study relies on four numerical experiments to evaluate the sensitivity of Chesapeake Bay hypoxia to changes or biases in its external physical forcings. Hypoxia exhibits only a minor decrease (−1.6%) after reducing the Bay's terrestrial freshwater discharge by 9.5% (but keeping terrestrial nutrient loadings the same). Changes in freshwater discharges have their largest impact on hypoxia during one extreme event (−37% during 2011 tropical storm Lee). Similarly, changing oceanic conditions on the shelf or their temporal frequency impact hypoxia by only 5%–6%, indicating that the latter is predominantly dictated by local conditions. Although these results are promising from the perspective of ESMs, additional components of ESMs will need to be evaluated before general conclusions can be reached. We notably speculate that the Bay's hypoxia would exhibit higher sensitivity to other forcings not examined here, notably air temperatures and nutrient loadings.

Hypoxia Forecasting for Chesapeake Bay Using Artificial Intelligence

“…Hypoxia forecasts help resource managers and policymakers to make informed decisions about managing coastal ecosystems and fisheries, and allow stakeholders to take proactive measures to minimize the impact on fisheries and aquaculture operations. Current approaches to forecasting hypoxia in the Chesapeake Bay involve the use of numerical models such as the Chesapeake Bay Environmental Forecasting System (CBEFS) (St-Laurent et al 2020;Bever et al 2021;St-Laurent and Friedrichs 2024). This 3D mechanistic model simulates the physical and biogeochemical processes that lead to hypoxia and is forced with a wide range of real-time inputs including both terrestrial information (river discharge, nutrient loadings) and atmospheric data (air temperature, winds, humidity, precipitation, etc.).…”