Kasprzyk, JosephÌý1
1ÌýÀÖ²¥´«Ã½ Boulder
Due to climatic and land use change, water managers are increasingly interested in the influence of uncertainty in their systems. Current hydrologic forecasting frameworks often consider variable initial conditions to represent a range of potential conditions, and use statistical models to predict the effect of climatic variables on streamflow. Similarly, water management and reservoir operations have considered scenarios of inflow and mapped these onto management decisions. However, little work has been done to directly connect uncertainties in hydrologic modeling to reservoir operations outcomes. For example, there is a need to better understand how parametric uncertainty in rainfall-runoff modeling transforms optimal decision making for reservoir management, especially given the possibility that specific decisions could be more or less sensitive to particular rainfall-runoff parameters. This paper seeks to introduce a framework in which parameteric uncertainty can be linked to reservoir operations. The proposed framework builds on previous work in sensitivity analysis of hydrologic models and in bottom-up decision making approaches such as many objective robust decision making.