Freezing Level Forecast Error Can Consume Reservoir Flood Control Storage: Potentials for Lake Oroville and New Bullards Bar Reservoirs in California

July 20, 2020

CW3E hydrologist, Edwin Sumargo, CW3E researchers, F. Martin Ralph, Forest Cannon and Brian Henn (CW3E alumnus) published a paper in Water Resources Research, titled “Freezing Level Forecast Error Can Consume Reservoir Flood Control Storage: Potentials for Lake Oroville and New Bullards Bar Reservoirs in California” (Sumargo et al., 2020). As part of CW3E’s 2019-2024 Strategic Plan to support Forecast Informed Reservoir Operations, CW3E researches the impacts of atmospheric rivers (ARs) on water management and public safety and to improve the prediction capability. In particular, this study assesses the sensitivities reservoirs in the Yuba-Feather watershed, Lake Oroville and New Bullards Bar reservoirs, to freezing-level (Z_FL) forecast uncertainty. Specifically, it quantifies what percentages of the two reservoirs’ flood pools would be consumed by the prescribed Z_FL forecast error, with varying Z_FL altitudes and precipitation event magnitudes. This study offers a “guide curve” on the reservoir sensitivity to Z_FL forecast uncertainty for reservoir operations in the Yuba-Feather watershed. Ultimately, this work supports the ongoing collaborations involving CW3E, Yuba Water Agency, California Department of Water Resources, NOAA, and U.S. Army Corps of Engineers.

The atmospheric Z_FL determines the rain‐snow transition zone at the surface, how much rainfall is available for runoff, and the flood risk during a precipitation event (Figure 1). An accurate Z_FL forecast is thus critical for reservoir operations, especially in mountain watersheds with narrow elevation bands like the Feather and North Fork Yuba in Northern California, where a 500‐m elevation gain can amount to >50% of the watershed area. Using a ±350‐m Z_FL forecast error, we find inflow volume uncertainties of <10% to >50% of the flood pool storages at Lake Oroville and New Bullards Bar reservoirs, depending on the Z_FL, antecedent moisture, and the precipitation magnitude (Figure 2). In other words, the uncertainties can increase by up to >3% per inch (25.4 mm) of precipitation, depending on the Z_FL and antecedent moisture condition. This result substantiates the significant impact of Z_FL forecast error and the critical need of Z_FL forecast accuracy to support reservoir flood control operations in the two watersheds.

Figure 1. (Figure 4 in the manuscript) Schematic description of the impact of Z_FL forecast uncertainty on (a) storm runoff from the watershed and (b) the associated inflow to reservoir flood pool. The ±350-m ambient Z_FL forecast uncertainty in (a) is based on Henn et al. (2020) finding for up to 72-hour forecast lead time, which is used throughout this paper. The 0-500-m downward bending of Z_FL over the mountain topography in (a) is based on Minder & Kingsmill (2013) estimate.

Figure 2. (Figure 3 in the manuscript) Feather River (a-c) and North Fork Yuba River (d-f) Watersheds runoff uncertainties associated with a Z_FL forecast error of ±350 m in percent of the reservoir flood pool capacities as functions of Z_FL and event return periods based on the 1981-2018 daily PRISM precipitation (colors). The top-to-bottom panels represent the runoff uncertainties corresponding to (a and d) dry, (b and e) average, and (c and f) wet antecedent moisture conditions (AMCs). The gray horizontal lines denote the mean, the -1*standard deviation (?) from the mean, and the minimum CNRFC Z_FL of the top 10th percentile precipitation events since 2010 (see Appendix A in the manuscript)..

Sumargo, E., Cannon, F., Ralph, F. M., & Henn, B. (2020). Freezing Level Forecast Error Can Consume Reservoir Flood Control Storage: Potentials for Lake Oroville and New Bullards Bar Reservoirs in California. Water Resources Research, 56, e2020WR027072. https://doi.org/10.1029/2020WR027072