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.

在不确定性（OUU）下使用物理动力的数值模型（例如地下水流和运输模型）进行概率影响评估和优化通常会导致计算量大，以至于无法在决策过程中使用这些工具。与这些模型相关的计算挑战可以通过仿真解决。在土地利用/水质的背景下，硝酸盐负荷与地表水/地下水硝酸盐浓度之间的线性关系为通过脉冲响应矩阵的应用提供有效的模型仿真器提供了机会。当与一阶第二阶矩技术结合使用时，仿真策略将产生“随机冲激响应仿真器”（SIRE）。显示SIRE有助于非介入式，近实时，以及基于风险的硝酸盐负荷变化情景评估以及硝酸盐负荷OUU受高决策变量和参数维的地表水/地下水浓度约束。使用两个案例研究来证明硝酸盐负荷情况下的SIRE。