Physically Based Estimation of Maximum Precipitation over American River Watershed, California

Abstract

A methodology for maximum precipitation (MP) estimation that uses a physically based numerical atmospheric model is proposed in this paper. As a case study, the model-based 72-h MP was estimated for the American River watershed (ARW) in California for the December 1996–January 1997 flood event. First, a regional atmospheric model, MM5, was calibrated and validated for the December 1996–January 1997 historical major storm event for the ARW, on the basis of the U.S. National Center for Atmospheric Research (NCAR) reanalysis data to demonstrate the model capability during the historical period. Then, the model-simulated historical storm event was maximized by modifying its boundary conditions. The model-simulated precipitation field in the ARW was successfully validated at nine individual rain gauge stations in the watershed. The computed basin-averaged precipitation was somewhat higher than observations obtained by the spatial interpolation of the rain gauge observations. This result suggests a limitation of the spatial interpolation of ground rain gauge observations because they are mostly located in valleys, and the distribution of precipitation is highly heterogeneous over the mountainous terrain of the ARW. Next, to maximize precipitation over the watershed, the initial and boundary conditions in the outer nesting domain of the atmospheric model were modified. In this demonstrative study, the boundary conditions were modified by three methods: (1) maximizing the atmospheric moisture by setting the relative humidity at 100%; (2) maintaining the atmospheric boundary conditions corresponding to the state of the heaviest precipitation (maintaining equilibrium conditions); and (3) spatially shifting the atmospheric conditions to render the atmospheric moisture flux to hit the watershed. Because these modifications significantly increased the precipitation over the ARW, they clearly show the importance of wind and moisture conditions at the boundary of the atmospheric modeling domain. These different maximization methods produced similar 72-h precipitation depths, which were 549 mm by the combination of 100% relative humidity and equilibrium high precipitation conditions at the outer boundary of the model domain, and 541 mm from shifting the historical atmospheric conditions to the south by 5.0°. Accordingly, the 72-h maximum precipitation over the ARW was estimated to be approximately 550 mm. Although this study presents only a demonstrative maximization work, it shows that the presented modeling approach can be a potential alternative to standard probable maximum precipitation (PMP) estimation without depending on the linear relationships required in the standard PMP method. Also, because the proposed modeling approach is based on the initial and boundary atmospheric conditions from a synoptic scale that may be obtained from the NCAR/National Centers for Environmental Prediction reanalysis data for the historical period and from the general circulation model (GCM) climate projections, it can account for any nonstationarity that may be present in the hydro-climate system.