Variable Infiltration Capacity (VIC) Model

The Variable Infiltration Capacity model (VIC; Liang et al. 1994) is a large-scale, semi-distributed hydrologic model that simulates the hydrology in land-surface processes by incorporating variable vegetation, soil types and topography. The VIC model has been used in numerous studies of the hydrologic effects of climate variability and change on regional (e.g. in the Northwest, Payne et al. 2004; Elsner et al. 2010; Hamlet et al. 2013) and global scales (Nijssen et al. 2001). In 2014, VIC was used in the Integrated Scenarios project to evaluate the hydrologic impacts of climate projections from the IPCC’s CMIP5 (Coupled Model Inter-comparison Project, phase 5) global climate models.

VIC Land Model

VIC’s land surface is modeled as a grid of large model cells (typically larger than 20 km2), with sub-grid variability in land use represented as the fraction of the cell covered by different land cover types. Topographic influences on precipitation and temperature are represented by subdividing grid cells into elevation bands, primarily for estimating mountain snow pack. VIC has a snow model that accounts for snow accumulation and melt on the ground and in the canopy For the Integrated Scenarios project, VIC was configured with three soil layers to simulate infiltration, evapotranspiration, and the generation of fast- and slow-response runoff.

VIC Meteorological Inputs

Meteorological drivers for the model are input as time series of daily variables such as precipitation, air temperature and wind speed. The grid cells are simulated independently of each other for the entire time series where water can only enter a grid cell via the atmosphere (non-channel flow between cells is ignored and water cannot flow back into the soil but stays in the channel network). The model is run at a subdaily time step, with subdaily forcings generated internal to the model from the daily inputs.

VIC Outputs

VIC outputs time series of many different variables from the simulation process. These include variables related to snow (snow water equivalent, snow melt), soil (moisture, temperature), runoff (fast response, slow response and total runoff), streamflow, evapotranspiration, turbulent heat fluxes (sensible and latent heat) as well as radiative fluxes (shortwave and longwave).

References

Elsner, M. M., L. Cuo, N. Voisin, J. Deems, A. F. Hamlet, J. A. Vano, K. E. B. Mickelson, S. Y. Lee, and D. P. Lettenmaier, 2010. Implications of 21st century climate change for the hydrology of Washington State. Climatic Change, 102, 225-260, doi: 10.1007/s10584-010-9855-0.

Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs, J. Geophys. Res., 99(D7), 14,415-14,428.

Nijssen, B., G. M. O’Donnell, D. P. Lettenmaier, D. Lohmann, E. F. Wood, 2001. Predicting the discharge of global rivers, J. Climate, 14, 3307-3323.

Payne, J. T., A. W. Wood, A. F. Hamlet, R. N. Palmer, D. P. Lettenmaier, 2004. Mitigating the effects of climate change on the water resources of the Columbia River basin, Climatic Change, 62, 233-256.