C33D-0855
Understanding the variations in the timing of daily streamflow peak during melt season

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Mukesh Kumar1, Xing Chen1, Adam H Winstral2, Rui Wang1 and Danny G Marks3, (1)Duke University, Nicholas School of the Environment, Durham, NC, United States, (2)WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland, (3)USDA Agriculture Research Serv, Boise, ID, United States
Abstract:
Previous studies have shown that gauge-observed daily streamflow peak times (DPT) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes that affect the timing of snowmelt arrival: 1) melt flux translation through the snowpack or percolation, 2) surface and subsurface flow of melt from the base of snowpacks to streams, and 3) translation of water flux in the streams to streamgage stations. The goal of this study is to evaluate and quantify how these processes affect observed DPT variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, USA. To accomplish this goal, DPT was simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, PIHM. The influence of each controlling process was then evaluated by simulating the DPT with and without the process under consideration. Both intra- and inter-seasonal variability in DPT were evaluated. Results indicate that the average DPT is dominantly influenced by subsurface flow, whereas the seasonal variations in DPT are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the time for ripening of the snowpack are identified as additionally influencing DPT variability. Results also indicate that the relative dominance of each control varies through the melt season, and between wet and dry years. The results could be used for supporting DPT prediction efforts and for prioritization of observables for DPT determination.