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Verification of Ensemble Water Supply Forecasts for Sierra Nevada Watersheds

This study verifies the skill and reliability of ensemble water supply forecasts issued by an innovative operational Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service (NWS) at eight Sierra Nevada watersheds in the State of California. The factors potentially influencing the forecast skill and reliability are also explored. Retrospective ensemble forecasts of April–July runoff with 60 traces for these watersheds from 1985 to 2010 are generated with the HEFS driven by raw precipitation and temperature reforecasts from operational Global Ensemble Forecast System (GEFS) for the first 15 days and climatology from day 16 up to day 365. Results indicate that the forecast skill is limited when the lead time is long (over three months or before January) but increases through the forecast period. There is generally a negative bias in the most probable forecast (median forecast) for most study watersheds. When the mean forecast is investigated instead, the bias becomes mostly positive and generally smaller in magnitude. The forecasts, particularly the wet forecasts (with less than 10% exceedance probability) are reliable on the average. The low April–July flows (with higher than 90% exceedance probability) are forecast more frequently than their actual occurrence frequency, while the medium April–July flows (90% to 10% exceedance) are forecast to occur less frequently. The forecast skill and reliability tend to be sensitive to extreme conditions. Particularly, the wet extremes show more significant impact than the dry extremes. Using different forcing data, including pure climatology and Climate Forecast System version 2 (CFSv2) shows no consistent improvement in the forecast skill and reliability, neither does using a longer (than the study period 1985–2010) period of record. Overall, this study is meaningful in the context of (1) establishing a benchmark for future enhancements (i.e., newer version of HEFS, GEFS and CFSv2) to ensemble water supply forecasting systems and (2) providing critical information (on what skill and reliability to expect at a given lead time, water year type and location) to water resources managers in making uncertainty-informed decisions in maximizing the reliability of the water supply.