Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

Abstract

Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables were responsive to changes in parameters that influenced planktonic growth rates and less sensitive to physical or chemical parameters. Variation in sensitivity had a direct correspondence with identifiability, such that only small subsets of the complete parameter set had unique effects on the model output. Selecting parameters by decreasing sensitivity demonstrated that only eight of 51 total parameters had a sufficiently unique effect on model output for accurate calibration. As a result, parameter selection heuristics were used to identify parameters for model calibration that depended on combined effects on output, relative sensitivity of each parameter, and ecological categories for the biogeochemical equations. The calibrated zero-dimensional (0-D) unit of the hypoxia model had improved fit to the observed data if sensitive phytoplankton parameters were included in an identifiable subset. Extension of results to a three-dimensional grid of the Gulf of Mexico showed that sensitive parameters for the 0-D model translated to non-trivial changes in the areal estimates of hypoxia.

Impact of carbon emissions factors on economic agents based on decisions modeling in complex systems

“…An essential part of the research is the development of methods for determining model parameters and software tools. A literature review was conducted to research the problems of constructing mathematical picture fuzzy rough sets for modeling the activities of various corporate structures [25].…”

Impact of Carbon Emission Factors on Economic Agents Based on the Decision Modeling in Complex Systems

“…An essential part of this research is the development of methods for determining model parameters and software tools. A literature review was conducted to research the problems of constructing mathematical picture fuzzy rough sets for modeling the activities of various corporate structures [25].…”

A plausible identifiable model of the canonical NF-κB signaling pathway

“…We found that a simple protocol with a continuous 2 hour long TNF stimulation followed by a 10 hour long TNF washout phase assures not only practical identifiability of the reduced model, but also allows to determine parameters with accuracy comparable to the more complex pulsatile protocols. We evaluated parameter identifiability using sensitivity analysis techniques [27][28][29][30] finding the parameters that may be determined with the lowest accuracy. We verified practical identifiability performing Monte Carlo simulations [31].…”