Chen et al., 2016

Paper/Book

Assessment of the timing of daily peak streamflow in a snow dominated watershed

Chen, X., Kumar, M., Wang, R., Winstral, A., and D. Marks (2016)
Journal of Hydrometeorology 17: 2225-2244  Cross-CZO

Abstract

Previous studies have shown that gauge-observed daily streamflow peak times (DPTs) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes: 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 stream gauging stations. The goal of this study is to evaluate and quantify how these processes affect observed DPTs variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, United States. To accomplish this goal, DPTs were simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, the Penn State Integrated Hydrologic 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 interseasonal variability in DPTs were evaluated. Results indicate that the magnitude of DPTs is dominantly influenced by subsurface flow, whereas the temporal shifts within a season are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the snowpack ripening time 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 DPTs prediction efforts and for prioritization of observables for DPT determination.

Citation

Chen, X., Kumar, M., Wang, R., Winstral, A., and D. Marks (2016): Assessment of the timing of daily peak streamflow in a snow dominated watershed. Journal of Hydrometeorology 17: 2225-2244. DOI: 10.1175/JHM-D-15-0152.1

This Paper/Book acknowledges NSF CZO grant support.