Journal
ESTUARIES AND COASTS
Volume 44, Issue 1, Pages 70-87Publisher
SPRINGER
DOI: 10.1007/s12237-020-00761-w
Keywords
Emulator; Metamodel; Chesapeake Bay; Climate change; Sensitivity analysis; Uncertainty analysis
Funding
- National Science Foundation [CBET-1360286]
- PA Sea Grant [NA10OAR4170063]
- National Oceanic and Atmospheric Administration, U.S. Department of Commerce [NA18OAR4320123]
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This study develops and tests a computationally inexpensive statistical model as a surrogate for numerical model simulations of estuarine physics and water quality under future climate conditions. The simulations suggest that future salinity, stratification, and circulation are likely to be higher than present-day averages, with model projections highly sensitive to uncertainty about future tidal amplitudes along the shelf.
Numerical models are often used to simulate estuarine physics and water quality under scenarios of future climate conditions. However, representing the wide range of uncertainty about future climate often requires an infeasible number of computationally expensive model simulations. Here, we develop and test a computationally inexpensive statistical model, or metamodel, as a surrogate for numerical model simulations. We show that a metamodel fit using only 12 numerical model simulations of Chesapeake Bay can accurately predict the early summer mean salinity, stratification, and circulation simulated by the numerical model given the input sea level, winter-spring streamflow, and tidal amplitude along the shelf. We then use this metamodel to simulate summer salinity and circulation under sampled probability distributions of projected future mean sea level, streamflow, and tidal amplitudes. The simulations from the metamodel show that future salinity, stratification, and circulation are all likely to be higher than present-day averages. We also use the metamodel to quantify how uncertainty about the model inputs transfers to uncertainty in the output and find that the model projections of salinity and stratification are highly sensitive to uncertainty about future tidal amplitudes along the shelf. This study shows that metamodels are a promising approach for robustly estimating the impacts of future climate change on estuaries.
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