Abstract
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.
Highlights
The economic and social value of reliable water supply forecasts have been long recognized and extensively reported in the literature, including more effective water supply planning [1,2,3], increased hydropower revenues [4,5,6], better management of agricultural water supply [7], and improvedHydrology 2016, 3, 35; doi:10.3390/hydrology3040035 www.mdpi.com/journal/hydrologyHydrology 2016, 3, 35 drought assessment and mitigation [8,9,10], among others
This study focuses on eight Sierra Nevada watersheds draining into eight major reservoirs in California
A general increasing tendency is evident in rank correlation (Figure 3a), mean absolute error skill score (Figure 3c), and Nash–Sutcliffe efficiency (Figure 3d) as forecast date approaches the end of the target forecast period (31 July)
Summary
The economic and social value of reliable water supply forecasts have been long recognized and extensively reported in the literature, including more effective water supply planning [1,2,3], increased hydropower revenues [4,5,6], better management of agricultural water supply [7], and improvedHydrology 2016, 3, 35; doi:10.3390/hydrology3040035 www.mdpi.com/journal/hydrologyHydrology 2016, 3, 35 drought assessment and mitigation [8,9,10], among others. These methods range from straightforward statistical regression or index techniques to hydrologic model based approaches The former generally relates the target period runoff volume to, for instance, observed precipitation, runoff, and snow information [11,12,13,14] or climatic indices (e.g., El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific North American Index (PNA), Sea Surface Temperatures (SSTs), etc.) [15,16,17,18,19,20,21,22]. Climate change and population growth pose further challenges on the current system, while constructing new water storage and conveyance systems is often environmentally and economically prohibitive Under such circumstances, conducting forecast-informed operations of existing water facilities remains a viable approach for the more efficient use of existing water supplies. Foremost among these is seasonal water supply forecasting with lead times up to months
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