NYC's Operations Support Tool: Proactive Reservoir Management using Ensemble Streamflow Forecasts
OST currently accepts four different types of hydrologic forecasts as input: historical climatology, a monthly AR1 model otherwise known as the “Hirsch method”, a generalized linear model (GLM) utilizing historical daily correlations (“Extended Hirsch method” or “eHirsch”), and post-processed hydrologic forecasts from the National Weather Service (NWS) including the Advanced Hydrologic Prediction Service (AHPS) and the Hydrologic Ensemble Forecast Service (HEFS). Early versions of OST were outfitted with historical climatology and the Hirsch method as input forecasts. These initial ensemble forecast products helped DEP water managers learn to view operations decisions from a probabilistic standpoint and paved the way for adoption of forecast-based reservoir release rules, including the improved Flexible Flow Management Policy (FFMP) for the Delaware River Basin, which provide enhancements to environmental releases without increasing NYC's vulnerability to drought risk.
Since the initial deployment of OST, the ensemble forecast systems have been significantly upgraded. The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail end of high flow periods. These improvements allowed DEP to more effectively manage water quality control and spill mitigation operations immediately after storm events. The implementation of the post-processed NWS forecasts further increased the predictive skill over the initial statistical models as current basin conditions (e.g. soil moisture, snowpack) and meteorological forecasts (with HEFS) are now explicitly represented. With the post-processed HEFS forecasts, DEP may now truly quantify impacts associated with wet weather events on the horizon, rather than relying on statistical representations of current hydrologic trends. With these recent advancements in forecast technology, DEP expects to further their confidence and reliability in proactive reservoir management.