VIC (Variable Infiltration Capacity) is a so-called semi-distributed grid-based mesoscale to macroscale hydrologic model

   For modeling the entire state of Espirito Santo (including the entire Rio Doce),  the Variable Infiltration Capacity (VIC), is a so-called semi-distributed grid-based mesoscale to macroscale hydrologic model (Liang et al., 1994, 1996, Nijssen et al., 1997, 2001a, b), which represents explicitly the effects of vegetation, topography, and soils on the exchange of moisture and solar energy between land and atmosphere.  The core VIC model can then be coupled to other models, including reservoir models (below), and compared to independent data sources, to ultimately provide the basis for management-focused applications in the DSS.

   There is a broad international user community for VIC, with applications across diverse environments. It has been applied to the major river basins of the US (Abdulla et al., 1996; Cherkauer and Lettenmaier, 1999; Maurer et al., 2002; Nijssen et al., 1997); the entire country of China (Su and Xie, 2003); and the pan-Arctic region (Su et al., 2006).   Nijssen et al. (1997), evaluated VIC model performance for the Columbia and Delaware Rivers in the US, and demonstrated the ability of the model to reproduce observed stream flows. Maurer et al. (2002), applied the model over the continental US and evaluated its performance using observed stream-flow for many large US river basins. Nijssen et al. (2001a), applied the model globally, and showed good reproduction of observed stream-flow in many, though not all, cases. In particular, Nijssen et al.(2001a) demonstrated the ability of the VIC model to reproduce the observed seasonal cycle of soil moisture at a number of sites across Eurasia as well as its ability to reproduce seasonal variations in the part of the northern hemisphere covered by snow. The VIC model has been widely used for studies of land surface climate tele-connections (e.g. Zhu et al., 2005), climate change assessments (Payne et al., 2004; van Rheenen et al., 2004; Christensen et al., 2004), and land cover change studies (Matheussen et al., 2000), among other purposes. Dan et al (2012) used VIC to provide a basis for possible adaptation strategies under alternative climate conditions for NE China, where high population densities and intensive agriculture place high pressure on already marginal water resources, similar to the situation in the Aral basin.

     VIC, as applied here is essentially two sub-models, vertical and horizontal. The vertical component calculates the water and energy balance components for each individual grid cell, between the atmosphere and the soils and vegetation of the land surface, producing ET, soil moisture, and runoff from that grid cell.   A mosaic representation of land cover, and sub-grid parameterizations for infiltration and the spatial variability of precipitation and temperature, account for sub-grid scale heterogeneities in key hydrological processes. The model uses three soil layers and a single vegetation layer with energy and moisture fluxes exchanged between the layers. Sub-grid variations in precipitation rate and temperature, due to variations in elevation, are represented by sub-dividing each grid cell into elevation bands. Controls of vegetation on evapotranspiration are represented explicitly using a Penman–Monteith formulation. The top soil layer contributes to runoff via fast response mechanisms and the deepest soil layer produces baseflow.  The effects of snow accumulation and melt are represented using an energy balance snow model. 

   The second model simulates the routing of the runoff from each grid cell as streamflow along the stream network,   using a triangular unit hydrograph and linearized St. Venant’s equations. That is, the stream-flow from each individual grid cell is routed separately to the basin outlet through the channel network. Because of this partitioning between models, the computation of runoff from the land surface is independent of any structures (e.g., dams) along the river channel.

  Daily precipitation, maximum and minimum temperature, and wind speed are the primary meteorological variables that drive the model. The application of VIC requires the development of a set of input data files, including meteorological forcing (land surface climatology of daily precipitation, minimum and maximum temperature, and winds), vegetation attributes by vegetation class, a river network derived from a digital elevation model, and river discharge history at select stations.

     The detailed model description and the code download can be found at the  UW Land Surface Hydrology Group. The code is open-source, at no cost.