|Abstract or Summary
- Despite advances in the understanding of rain-on-snow storms and their resulting peak flows, little is understood about the response of snowmelt to precipitation and the relative timing of the two at multiple temporal scales within such events. To address this issue, climate, snowmelt, and streamflow data were analyzed for 26 large storms in the H.J. Andrews Experimental Forest in the western Cascades of Oregon. Cumulative net snowmelt was plotted against precipitation for each storm to identify net snowmelt response categories, which were then used to summarize climatic and streamflow data, while the timing of precipitation and net snowmelt was assessed at multiple temporal scales and time ranges with wavelet coherence.
Five precipitation-net snowmelt response categories were identified: flat; persistent melt; persistent accumulation; late melt; and late accumulation. Persistent melt events, which were characterized by concomitantly increasing cumulative net snowmelt and precipitation, had the highest mean peak flow and water available for runoff values of the response categories. Large, contiguous regions of significant wavelet coherence at multiple temporal scales were observed in both the persistent melt and persistent accumulation categories, but the phase difference distributions indicated differing snowpack dynamics with pulses of precipitation leading pulses of snowmelt in the former and precipitation being absorbed by the snowpack in the latter.
High water available for runoff totals and peak flows were observed in each of the five response categories, but a dewpoint temperature consistently above 0.5°C, elevated wind speeds, and a high fraction of precipitation falling as rain in the persistent melt category facilitated rapid snowmelt rates which were often synchronized with precipitation. Wavelet coherence showed this synchronization to be significant across all temporal scales and time periods for the two largest peak flows in the study, indicating that tightly coupled rainfall-synchrony is essential in generating an extreme rain-on-snow flood. By quantifying the amount and timing of net snowmelt, the categorization scheme provides a means of distinguishing among rain-on-snow events and predicting peak discharge magnitude.