|CLARK, MARTYN - National Center For Atmospheric Research (NCAR)|
|NIJSSEN, BART - University Of Washington|
|LUNDQUIST, JESSICA - University Of Washington|
|KAVETSKI, DMITRI - University Of Adelaide|
|RUPP, DAVID - Oregon State University|
|GUTMANN, ETHAN - National Center For Atmospheric Research (NCAR)|
|WOOD, ANDY - National Center For Atmospheric Research (NCAR)|
|GOCHIS, DAVID - National Center For Atmospheric Research (NCAR)|
|RASMUSSEN, ROY - National Center For Atmospheric Research (NCAR)|
|TARBOTON, DAVID - Utah State University|
|MAHAT, VINOD - Utah State University|
Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/1/2015
Publication Date: 4/1/2015
Citation: Clark, M., Nijssen, B., Lundquist, J., Kavetski, D., Rupp, D., Gutmann, E., Wood, A., Gochis, D., Rasmussen, R., Tarboton, D., Mahat, V., Flerchinger, G.N., Marks, D.G. 2015. A unified approach for process-based hydrologic modeling: Part 2. Model implementation and case studies. Water Resources Research. 51(4):2515-2542.
Interpretive Summary: This paper is the second of a two-part publication that first presents a unified approach to hydrologic modeling, and then uses that system to compare alternative processes representations. The effort represents an attempt to understand how hydrologic models are developed, and tested, and how this process is evolving as we understand more about climate instability.
Technical Abstract: Understanding and prediction of snowmelt-generated streamflow at sub-daily time scales is important for reservoir scheduling and climate change characterization. This is particularly important in the Western U.S. where over 50% of water supply is provided by snowmelt during the melting period. Previous studies reported that daily peak flow timing might shift earlier in some basins, but later in others during the melt season, and the shift of peak flow timing was attributed to three crucial processes: translation time of melt flux through snowpack, translation time in the river channels to stream gage stations and translation time from base of snow packs to river channels. However, no attempt has been made to simulate the sub-daily streamflow peak time and quantitatively explore the relative contribution from each individual factor. To fill in the blanks, we coupled a snowmelt model, iSnobal, with a delay function in the snow translation process, and a hydrology model, PIHM, to simulate the daily peak time in Reynolds Mountain East (RME) watershed. Our analyses show that the daily peak timing is dominantly controlled by melt translation time from the bottom of snowpack to the river channel, while the seasonal variation in daily peak is influenced the most by translation time through the snow pack. An additional factor, the increasing trend of temperature and radiation in melt season, is also discovered to be contributing to the peak streamflow timing and its variations.