A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support
Use of physically-motivated numerical models like groundwater flow-and-transport models for probabilistic impact assessments and optimization under uncertainty (OUU) typically incurs such a computational burdensome that these tools cannot be used during decision making. The computational challenges associated with these models can be addressed through emulation. In the land-use/water-quality context, the linear relation between nitrate loading and surface-water/groundwater nitrate concentrations presents an opportunity for employing an efficient model emulator through the application of impulse-response matrices. When paired with first-order second-moment techniques, the emulation strategy gives rise to the “stochastic impulse-response emulator” (SIRE). SIRE is shown to facilitate non-intrusive, near-real time, and risk-based evaluation of nitrate-loading change scenarios, as well as nitrate-loading OUU subject to surface-water/groundwater concentration constraints in high decision variable and parameter dimensions. Two case studies are used to demonstrate SIRE in the nitrate-loading context.
Citation Information
Publication Year | 2020 |
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Title | A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support |
DOI | 10.1016/j.envsoft.2020.104657 |
Authors | Jeremy T. White, Matthew Knowling, Michael N. Fienen, Daniel T. Feinstein, Garry W. McDonald, Catherine R. Moore |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | Environmental Modelling and Software |
Index ID | 70218295 |
Record Source | USGS Publications Warehouse |
USGS Organization | New York Water Science Center; Wisconsin Water Science Center; Upper Midwest Water Science Center |