Articles | Volume 26, issue 4
https://doi.org/10.5194/hess-26-1131-2022
https://doi.org/10.5194/hess-26-1131-2022
Research article
 | 
28 Feb 2022
Research article |  | 28 Feb 2022

Temporally resolved coastal hypoxia forecasting and uncertainty assessment via Bayesian mechanistic modeling

Alexey Katin, Dario Del Giudice, and Daniel R. Obenour

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Latest update: 18 May 2024
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Short summary
Low oxygen conditions (hypoxia) occur almost every summer in the northern Gulf of Mexico. Here, we present a new approach for forecasting hypoxia from June through September, leveraging a process-based model and an advanced statistical framework. We also show how using spring hydrometeorological information can improve forecast accuracy while reducing uncertainties. The proposed forecasting system shows the potential to support the management of threatened coastal ecosystems and fisheries.