ArticleEcological modelling2017
Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico.
Article in Ecological modelling, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Coastal generalized ecosystem model (CGEM) 1.0: Flexible model formulations for simulating complex biogeochemical processes in aquatic ecosystems.Ecological modelling · 2024Article
- Article
- Inter-model comparison of simulated Gulf of Mexico hypoxia in response to reduced nutrient loads: effects of phytoplankton and organic matter parameterization.Environmental modelling & software : with environment data news · 2022Article
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4 authors.
Funding
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.
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