A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support. (April 2020) - White, Jeremy T.; Knowling, Matthew J.; Fienen, Micheal N.; Feinstein, Daniel T.; McDonald, Garry W.; Moore, Catherine R.
Abstract: 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. Highlights: A computationally efficient approach to emulation and optimization under uncertainty is presented. The linear relation between nitrate loading and resulting concentrations is exploited. The emulation approach is shown to facilitate spatially-explicit and risk-based land-used scenario evaluation in near real time.