期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 109, 期 -, 页码 191-201出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2018.06.009
关键词
Modeling; Uncertainty; Iterative ensemble smoother; Gauss-Levenberg-Marquardt
类别
资金
- Waikato Regional Council
An open-source, scalable and model-independent (non-intrusive) implementation of an iterative ensemble smoother has been developed to alleviate the computational burden associated with history-matching and uncertainty quantification of real-world-scale environmental models that have very high dimensional parameter spaces. The tool, named pestpp-ies, implements the ensemble-smoother form of the popular Gauss-Levenberg-Marquardt algorithm, uses the pest model-interface protocols and includes a built-in parallel run manager, multiple lambda testing and model run failure tolerance. As a demonstration of its capabilities, pestpp-ies is applied to a synthetic groundwater model with thousands of parameters and to a real-world groundwater flow and transport model with tens of thousands of parameters. pestpp-ies is shown to efficiently and effectively condition parameters in both cases and can provide means to estimate posterior forecast uncertainty when the forecasts depend on large numbers of parameters.
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