Precipitation Phase Partitioning with a Psychrometric Energy Balance: Model Development and Application

Abstract

Precipitation phase is fundamental to a catchment’s hydrological response to precipitation events in cold regions and is especially variable over time and space in complex topography. Phase is controlled by the microphysics of the falling hydrometeor, but microphysical calculations require detailed atmospheric information that is often unavailable and lacking from hydrological analyses. In hydrology, there have been many methods developed to estimate phase, but most are regionally calibrated and many depend on air temperature (Ta) and use daily time steps. Phase is not only related to Ta, but to other meteorological variables such as humidity. In addition, precipitation events are dynamic, adding uncertainties to the use of daily indices to estimate phase. To better predict precipitation phase with respect to meteorological conditions, the combined mass and energy balance of a falling hydrometeor was calculated and used to develop a model to estimate precipitation phase. Precipitation phase and meteorological data were observed at multiple elevations in a small Canadian Rockies catchment, Marmot Creek Research Basin, at 15-minute intervals over several years to develop and test the model. The mass and energy balance model was compared to other methods over varying time scales, seasons, elevations and topographic exposures. The results indicate that the psychrometric energy balance model performs much better than Ta methods and that this improvement increases as the calculation time interval decreases. The uncertainty that differing phase methods introduce to hydrological process estimation was assessed with the Cold Regions Hydrological Model (CRHM). The rainfall/total precipitation ratio, runoff, discharge and snowpack accumulation were calculated using a single and a double Ta threshold method and the proposed physically based mass and energy balance model. Intercomparison of the hydrological responses of the methods highlighted differences between Ta based and psychrometric approaches. Uncertainty of hydrological processes, as established by simulating a wide range of Ta methods, reached up to 20% for rain ratio, 1.5 mm for mean daily runoff, 0.4 mm for mean daily discharge and 160 mm of peak snow water equivalent. The range of Ta methods showed that snowcover duration, snow free date and peak discharge date could vary by up to 36, 26 and 10 days respectively. The greatest hydrological uncertainty due to precipitation phase methods was found at sub-alpine and sub-arctic headwater basins and the least uncertainty was found at a small prairie basin.