Articles | Volume 26, issue 4
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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Cited articles

Benhamou, E.: A few properties of sample variance, arXiv: preprint, (last access: 1 November 2021), 2018. 
Berrar, D.: Cross-Validation, in Encyclopedia of Bioinformatics and Computational Biology, Elsevier, 542–545, ISBN 9780128114322, 2019. 
Bianchi, T. S., DiMarco, S. F., Cowan, J. H., Hetland, R. D., Chapman, P., Day, J. W., and Allison, M. A.: The science of hypoxia in the Northern Gulf of Mexico: A review, Sci. Total Environ., 408, 1471–1484,, 2010. 
Bianucci, L., Balaguru, K., Smith, R. W., Leung, L. R., and Moriarty, J. M.: Contribution of hurricane-induced sediment resuspension to coastal oxygen dynamics, Sci. Rep.-UK, 8, 15740,, 2018. 
Craig, J.: Aggregation on the edge: effects of hypoxia avoidance on the spatial distribution of brown shrimp and demersal fishes in the Northern Gulf of Mexico, Mar. Ecol. Prog. Ser., 445, 75–95,, 2012. 
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.