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| Computer model simulations are used widely in the investigation of complex biophysical systems. In particular, hydrological and water quality models are tools that can help to both better understand and manage the water resources. Currently the typical simulation approach is to treat hydrological models as deterministic. In other words, it is assumed that model outputs are exact and do not incorporate uncertainty. However, it is important to remember that models are just simplifications of the reality and incorporate different sources of uncertainty (i.e. from model input data, parameters, structure, etc.). These uncertainties need to be accounted for in the modeling and in the decision-making process through formal uncertainty analysis. This is particularly critical for all applications informing decisions related to extreme events like drought or flooding. Global Uncertainty and Sensitivity Analysis (GUA/SA) are formal tools for statistical evaluation of models which contribute to models' quality and application. While the role of the uncertainty analysis is to propagate uncertainties in input factors onto the model outputs of interest, sensitivity analysis studies how the uncertainty in the output can be apportioned to different sources of uncertainty from the model input factors. Local and global types of SA can be distinguished. Local, one-at-a-time (OAT) methods are only effective for the purpose of assessing the relative importance of input factors if the model is linear and additive. In contrast, global techniques enable exploration of the entire interval of definition for each input factor and do not require any assumptions on the model nature. |
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Final Report |
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| Title: | Simulating the fate of Florida Snowy Plovers with sea-level rise: exploring potential population management outcomes with a global uncertainty and sensitivity analysis perspective. Ecol Modelling 224(1):33-47. |
| Authors: | Chu-Agor, M.L., Munoz-Carpena, R., Kiker, Aiello-Lammens, M.E., Akçakaya, H.R., Convertino, M., and I. Linkov |
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