369910 WRF-Hydro Streamflow Simulations in the Lake Mendocino Watershed During Extreme Precipitation Events

Tuesday, 14 January 2020
Rachel Weihs, Scripps Institution of Oceanography, University of California San Diego, San Diego, CA; and E. Sumargo, H. McMillan, and F. M. Ralph

The Lake Mendocino watershed is a key area of interest for hydrological modeling as its end point drains into a regulated reservoir operated for flood risk and critical water supply in Northern California. This regional area is also susceptible to frequent widespread flooding in the wintertime mainly due to orographic precipitation from atmospheric rivers. The Center for Western Weather and Water Extremes (CW3E) has installed a suite of meteorological and hydrologic observing instrumentation at several sites in the upper Russian River in order to better capture the spatial and temporal variability of extreme precipitation and flooding in the area. During 2017, 6 new soil moisture, 6 new streamflow, and 10 new precipitation instruments were deployed within the watershed while considering spatial variability in topography, soil type, stream geometry, etc.

These observations will be used to evaluate characteristic behavior of the Lake Mendocino watershed land surface using WRF-Hydro during and after atmospheric river generated precipitation. Important characteristics include hydrograph rise and fall rates, 3-day total inflow volumes, soil moisture spatial variations, antecedent evaporation-transpiration (ET) processes, and runoff vs groundwater partitioning. The model configuration is adopted from the National Water Model design and parameter set and run with the National Land Data Assimilation System v2 (NLDAS-2) forcing and the California-Nevada River Forecast Center (CNRFC) Quantitative Precipitation Estimate (QPE). Preliminary results during water years 2017-2018 show that, although the model is uncalibrated specifically for Lake Mendocino, the soil moisture temporal variations are high correlated to observations (mean correlation = 0.81). The bias and standard deviation, however, at certain sites can be as large as 50% of the mean volumetric soil moisture. Diagnosing these types of criteria will help to inform overall model skill of the streamflow predictions and future efforts to improve the model physics and calibration in similar watersheds in the West.

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