Sensitivity and uncertainty analysis of model hypoxia estimates for the Texas-Louisiana shelf

Authors

  • Jann Paul Mattern,

    Corresponding author
    1. Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada
    2. Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
    • Corresponding author: J. P. Mattern, Department of Mathematics and Statistics, Dalhousie University, PO Box 15000, Halifax, NS B3H 4R2, Canada. (paul.mattern@dal.ca)

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  • Katja Fennel,,

    1. Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
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  • Michael Dowd

    1. Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada
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Abstract

[1] Numerical ocean models are becoming increasingly important tools for marine research and for management of marine resources. It is therefore crucial that uncertainty in model predictions and model sensitivity to errors in the model inputs be quantified. We performed a combined sensitivity and uncertainty analysis for a realistic physical-biological model of the Texas-Louisiana shelf in the northern Gulf of Mexico. The model simulates the major physical and biological processes involved in the formation of the hypoxic zone that develops on the shelf every summer. With the help of a statistical emulator technique, we introduced uncertainty in selected model inputs and assessed the effects of these uncertainties on the predicted development and spatial distribution of bottom hypoxia. The uncertain inputs we examined belong to two categories: (i) biological inputs including river nutrient concentration, phytoplankton growth rate and initial and boundary conditions of biological variables, and (ii) physical inputs including freshwater river runoff, wind forcing, and mixing coefficients. We show that uncertainty in different inputs has distinct effects on model output which vary in magnitude, time, and space. Uncertainty in physical inputs was found to have a strong impact on estimates of hypoxia, e.g., hypoxic area estimates vary by more than 40%, due to a 20% variation in the freshwater river runoff.

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