HR: 0800h
AN: C21A-1070    [Abstracts]
TI: Vadose Zone Effects on Snowmelt Generated Streamflow
AU: * Seyfried, M
EM: mseyfrie@nwrc.ars.usda.gov
AF: Agricultural Research Service, 800 Park Blvd, Boise, ID 83712 United States
AU: Grant, L
EM: contributary@gmail.com
AF: University of California, 853 Fellowship Road, Santa Barbara, CA 93109 United States
AU: Marks, D
EM: dmarks@nwrc.ars.usda.gov
AF: Agricultural Research Service, 800 Park Blvd, Boise, ID 83712 United States
AB: Processes of evaporation, transpiration and absorption of water within the root zone constitute a secondary control on the amount and timing of snowmelt-generated streamflow. Even in relatively small watersheds the timing and amount of snowmelt inputs to the root zone may be highly variable due to uneven snow distribution and melt dynamics related to topographic and vegetative influences. Since most streamflow from snowmelt results from subsurface flow, a complete characterization of streamflow generation processes requires knowledge of subsurface hydraulic properties, which is rare even in small watersheds. We investigate the potential for estimating root zone impacts on streamflow generation using a spatially distributed, one dimensional modeling approach, thus accounting for variability of inputs and root zone processes, but regarding the watershed as highly "connected" in the subsurface. We combined a snowmelt model that accounts for input variability with a simple soil water balance model that accounts for plant uptake, evaporation and drainage. The approach was tested on the 0.36 km² Reynolds Mountain experimental watershed in Idaho. We found that the one dimensional modeling approach accurately captured the dynamics of streamflow initiation and reduction, indicating a high degree of subsurface connectivity. The amount of runoff estimated from one dimensional deep drainage, however, was substantially overestimated. This appears to be due to transpiration of subsurface water that reemerges in the root zone down slope from the input. Subsequent simulations, accounting for this, are consistent with this explanation.
DE: 0740 Snowmelt
DE: 0772 Distribution
DE: 1847 Modeling
DE: 1860 Streamflow
DE: 1866 Soil moisture
SC: Cryosphere [C]
MN: Fall Meeting 2005