Matthew Knowling Michael N. Fienen Daniel T. Feinstein Garry W. McDonald Catherine R. Moore Jeremy T. White 2020 <div id="abstracts" class="Abstracts u-font-serif"><div id="abs0010" class="abstract author" lang="en"><div id="abssec0010"><p id="abspara0010">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.</p></div></div></div><ul id="issue-navigation" class="issue-navigation u-margin-s-bottom u-bg-grey1"></ul> application/pdf 10.1016/j.envsoft.2020.104657 en Elsevier A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support article