HR: 14:30h
AN: CG13B-03    [Abstracts]
TI: A Coupled Energy and Water Balance Model for Snow-Vegetation-Soil Systems
AU: * Marks, D
EM: ars.danny@gmail.com
AF: USDA/ARS Northwest Watershed Research Center, 800 Park Blvd, Suite 105, BoiseID, ID 83712-7716, United States
AU: Sandells, M
EM: mjs@mail.nerc-essc.ac.uk
AF: National Centre for Earth Observation, University of Reading, Reading, RG6 6AL, United Kingdom
AU: Flerchinger, G
EM: gerald.flerchinger@ars.usda.gov
AF: USDA/ARS Northwest Watershed Research Center, 800 Park Blvd, Suite 105, BoiseID, ID 83712-7716, United States
AB: In mountainous and cold regions of the world snowmelt dominates the water balance, yet is quantified poorly despite the wealth of available remote sensing observations. Field measurements of snow cover and soil moisture are limited to experimental sites while the accuracy of soil moisture measurements from passive and active microwave sensors such as the upcoming SMOS and SMAP missions depends on a good physical understanding of the soil system. An improved approach to interpret remote sensing observations is to use a physically - based model in conjunction with the observations. However, many of the models currently available are either too complex for use across a range of scales, or lack elements that govern the energy and mass balance of the system (for example, snow, soil or vegetation). A new coupled energy and water balance model that integrates snow and soil moisture has been developed to simulate the evolution of the snow cover in addition to soil temperature and moisture profiles. The model was formed by coupling Snobal, a physically - based two-layer snow model, with a simplified version of SHAW, a multi-layer soil heat and water balance model that also simulates soil freezing. We present a point test of the model for a snow covered bare soil using hourly measurements of meteorological conditions, from an experimental site within the Reynolds Creek Experimental Watershed in Idaho, USA. These data were used to drive the model, which was then evaluated against hourly measured snow deposition and melt, as well as soil temperature and moisture profiles from the same site. Later research will focus on the vegetation component of the coupled system. The coupled model is computationally simple enough for regional simulations and could be used to form the basis of a data assimilation framework to retrieve snow and soil parameters from remote sensing measurements.
DE: 0704 Seasonally frozen ground
DE: 0736 Snow (1827, 1863)
DE: 0740 Snowmelt
DE: 0762 Mass balance (1218, 1223)
DE: 0764 Energy balance
SC: Canadian Geophysical Union [CG]
MN: 2009 Joint Assembly