Hydrological model uncertainty due to precipitation‐phase partitioning methods

• Published in: Hydrological processes 2014-07, Vol.28 (14), p.4311-4327
• Main Authors: Harder, Phillip, Pomeroy, John W
• Format: Article
• Language: English
• Subjects: air temperature; algorithms; arctic; basins; cold region hydrology; energy balance; frozen soils; humidity; hydrologic models; meteorological data; model uncertainty; mountains; prairies; precipitation phase; prediction; rain; snow; snow hydrology; snowfall-rainfall transition; snowmelt; snowpack; stream flow; uncertainty estimation; western Canada
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.10214

Precipitation‐phase partitioning methods (PPMs) that are used in simulating cold‐region hydrological processes vary significantly. Typically, PPMs are based on empirical algorithms that are driven by readily available near‐surface air temperature but ignore the physical processes controlling precipitation phase by not incorporating humidity. Because these lack any physical basis, there is uncertainty in their spatial and temporal transferability. Recently, humidity‐based methods that have a stronger physical basis and smaller uncertainty have been developed. To quantify the uncertainty that empirical PPMs introduce into hydrological simulations, a cold‐region hydrological modelling platform was used with a physically based PPM and a selection of empirical PPMs to calculate a set of snow regime and streamflow regime indices. The empirical PPMs included a single air temperature threshold and a double air temperature threshold, whereas the physically based PPM used a psychrometric energy balance model. All calculations were run with near‐surface meteorological observations that typically drive hydrological models. Intercomparison of the hydrological responses to the PPMs highlighted substantial differences between the wide range of responses to empirical algorithms and the very small uncertainty due to physically based methods. Uncertainty of hydrological processes, quantified by simulating over a range of air temperature thresholds, reached 20% for the rainfall fraction, 0.4 mm/day for basin discharge, 160 mm of peak snow water equivalent, 36 days for hydrological uncertainty snow cover duration, 26 days for snow‐free date and 10 days for peak discharge date. The implication of this research is that the reduced uncertainty derived from implementing physically based PPMs, for operational or research purposes, are greatest for snowpack prediction in mountain basins. However for streamflow discharge calculations, the reduced uncertainty was greatest in prairie and alpine basins due to the additional effects of precipitation phase calculations on frozen soil infiltration and summer snowmelt processes respectively. Copyright © 2014 John Wiley & Sons, Ltd.