Project Team:

Dr. Dennis P. Lettenmaier
Professor of Civil Engineering, University of Washington, Seattle, WA

Dr. Fayez A. Abdulla
now Assistant Professor of Civil Engineering, Jordan University of Science and Technology, Irbid, Jordan - formerly at Department of Civil Engineering, University of Washington

Dr. Xu Liang
now Postdoctoral Research Associate, Civil Engineering & Operations Research, Princeton University, Princeton, NJ - formerly at Department of Civil Engineering, University of Washington

Bart Nijssen
Graduate student of Civil Engineering, University of Washington,Seattle, WA

Dag Lohmann
Graduate student, GKSS Forschungszentrum, Institut fur Atmosphaerenphysik, Geesthacht, Germany - currently at Department of Civil Engineering, University of Washington


Dr. Eric F. Wood
Professor of Civil Engineering & Operations Research, Princeton University, Princeton,NJ

Funding Agencies:

National Science Foundation
NOAA Office of Global Programs
Western Center for Global Environmental Change


The land surface plays an important role in partitioning incoming radiation at the land surface into latent and sensible heat, and in partitioning precipitation into runoff and evaporation. The representation of the land surface in numerical weather prediction and climate models must, of necessity, be highly parameterized due to inconsistencies between the spatial scales at which these models operate (several tens to hundreds of km) and the length scale over which important variations in soil moisture, or instance, occur (meters). Considerable progress has been made in the last few years in understanding the spatial variability of water and energy fluxes over natural catchments. Field studies have addressed the spatial patterns of soil moisture and associated runoff production at the catchment (tens or so of square km) scale. Remote sensing of soil moisture has contributed to understanding of the spatial distribution of soil moisture at larger scales. The result is a better appreciation for the role of topography and heterogeneities in soil properties on the distribution of soil moisture, runoff production, and evaporation. These results have been confirmed through large scale land-atmosphere field experiments like FIFE, the First ISLSCP Field Experiment, conducted in central Kansas in 1987 and 1989.

The current state of understanding of land surface hydrology has not, however, found its way into the land surface parameterizations used in global general circulation models (GCMs) used for numerical weather prediction and climate studies. It is our contention that the current generation of water-energy-biospheric models that have been advanced for this purpose are inappropriate for determining large scale energy and water fluxes due to their inconsistency between vertical and horizontal resolution. This lack of horizontal variability (which has lead to their characterization as 'big-leaf' models) can result in significant biases in soil moisture and evaporation when estimated over large areas.

VIC-2L Model

To address this problem, we have developed a two-layer generalization of the VIC (Variable Infiltration Capacity) model (Wood et al., 1992), which in turn is a generalization of the Xanianjing model originally used for flood forecasting and other hydrologic purposes in China (Zhao, 1977) and elsewhere. The revised version of the model, termed VIC-2L, is described in detail by Liang et al. (1994). The distinguishing feature of VIC-2L is that it represents the spatial variability of infiltration, and hence runoff production, as a spatial probability distribution . The model, in its one-layer form, has been used to model the land surface in GCMs by Stamm et al (1994) and Dumenil and Todini (1992). The two-layer version of the model incorporates a nonlinear drainage (baseflow) representation, and an explicit energy-driven Penman-Monteith representation of vegetation. Multiple land cover types, including bare soil, are modeled using a "tile" approach (aggregates all occurrences of a given land cover type within the area to a single equivalent subarea) .

Validation of VIC-2L for FIFE (Central U.S. grassland) and ABRACOS (Brazilian cleared forest) is reported by Liang (1994). Generally, the model reproduces observed latent and sensible heat fluxes quite well. Errors in ground heat flux predictions sometimes occur, some of which can be attributed to measurement errors. Nonetheless, recent improvements in the model's ground heat flux algorithm have improved its performance in this respect.


VIC-2L has been a participant in the GEWEX project PILPS, Project for Intercomparison of Land Surface Parameterizations (Henderson-Sellers et al., 1995). The goal of PILPS is to assess the performance of current land surface schemes used in the current generation of climate and numerical weather prediction models, with the ultimate aim of better predicting soil moisture, and hence the partitioning of energy at the land surface. In its first phase, some 30 land surface schemes were tested using prescribed surface forcings for two hyopthetical sites: a tropical forest and a northern mid-latitude grassland. A series of consistency tests were imposed on each of the models, including long-term balancing of energy and water at the land surface. Although there was no "right" answer, useful information about the range of model performance in terms annual, seasonal, and diurnal partitioning of net radiation into sensible, latent, and ground heat fluxes, and partitioning of precipitation into evaporation and runoff, was obtained. The long-term partitioning of net radiation into latent and sensible heat by VIC-2L for both the tropical forest and grassland sites was near the middle of the range for the models tested. In Phase 2, the models were tested using data from an experimental agricultural field site at Cabauw, the Netherlands. Results of a similar set of experiments show that VIC-2L performed quite well in this environment as well, both for the energy balance, and the water balance.

In November, 1994, a subset of fifteen PILPS participants attended a soil moisture simulation workshop held at Macquarie University. At this workshop, each of the models was applied to data collected during the HAPEX-MOBILHY experiment in France. Although the annual water balance predicted by VIC-2L matched the observations reasonably well, the upper soil layer tended to dry more rapidly than the observations in the spring and summer. This problem was attributed to a) the absence of a mechanism to move soil water from the lower to the upper layer, and b) the inability of the model to evaporate water quickly following small summer rainfall events, due to the damping effect resulting from depth-averaging of soil moisture in a relatively thick surface layer. As a result, modifications to the model, described by Liang et al. (1995) were made which greatly improved model performance for the HAPEX-MOBILHY site.

GRID-based Version of VIC-2L for Large Rivers

Wetzel (1994) and Abdulla (1995) have implemented VIC-2L to simulate the water and energy balances of large river basins. Essentially, the river basin is overlain by a rectangular grid, typically of size one or one-half degree. These grid cells are then linked to form an equivalent channel network. The VIC-2L model is then run for each grid cell, using one of two formulations: a) water balance only, in which case the driving variables are precipitation and surface air temperature; b) full energy balance, in which case the driving variables are precipitation, downward short- and longwave radiation at the surface, and surface meteorology, including wind, pressure, and vapor pressure deficit. Flow generated within a grid cell is routed to the cell outlet using a unit hydrograph routing scheme. A separate unit hydrograph is used to route flow entering and crossing a grid cell.

The water balance scheme has been successfully applied to the Arkansas-Red, Colorado, Missouri, Delaware, and Columbia River systems.

VIC-2L Regional Parameter Estimation

Abdulla et al. (1995) and Abdulla and Lettenmaier (1995a; b) have developed and tested a regional parameter estimation scheme for the VIC-2L model. Using a set of 40 catchments in the Arkansas-Red River basin with drainage areas in the range 100 to 10,000 km 2 for which historical streamflow and meteorological records exist, the parameters of the VIC-2L model were estimated using a search procedure. Regional regression equations were then developed to relate the estimated VIC-2L parameters for the gaged catchments to catchment characteristics derivable from digital elevation, soils, climatalogical, and land cover data. The prediction equations were tested using observed streamflow data for test catchments not in the training data set, and to predict streamflow hydrographs for the entire Arkansas-Red River system. Model performance for the humid and sub-humid test catchments was comparable to that for the training catchments . However, the model did not perform as well for the arid and semi-arid test catchments . This is attributable in part to structural problems with application of the VIC-2L model in such climates (notably the absence of an infiltration excess runoff production mechanism). At the scale of the entire Arkansas-Red basin, the model performed quite well with regional parameters, especially for the more humid, eastern part of the catchment. Finally, spatially averaged evaporative fluxes for the entire Arkansas-Red River basin predicted by the VIC-2L model were compared with evapotranspiration estimated over the same area using an atmospheric water budget. The results were shown to agree quite closely, especially during the spring and summer months, when evaporation is highest.


Abdulla, F., D.P. Lettenmaier, E.F. Wood, and J.A. Smith, "Application of a macroscale hydrologic model to estimate the water balance of the Arkansas-Red River basin", in press, Journal of Geophysical Research, 1995.

Abdulla, F.A., and D.P. Lettenmaier, "Development of regional parameter estimation equations for a land surface hydrologic model", in review, Journal of Hydrology, 1995.

Abdulla, F.A., and D.P. Lettenmaier, "Application of a regionalized land surface hydrologic model to a continental river", in review, Journal of Hydrology, 1995.

Abdulla, F.A., "Regionalization of a macroscale hydrological model", Water Resources Series Technical Report No. 144, Department of Civil Engineering, University of Washington, July, 1995.

Dumenil, L., and E. Todini, "A rainfall-runoff scheme for use in the Hamburg climate model", in Advances in theoretical hydrology, A tribute to James Dooge. P. O'Kane, ed., European Geophysical Society Series on Hydrological Sciences 1, Elsevier, Amsterdam, 1992.

Henderson-Sellers, A., A.J. Pitman, P. Irannejad, and T.H. Chen, "The Project for Intercomparison of Land Surface Parameterization Schemes (PILPS): Phases 2 and 3", Bulletin of the American Meteorological Society 76(4), 489-503, Apr., 1995.

Liang, X., "A two-layer variable infiltration capacity land surface representation for general circulation models", Water Resources Series Technical Report No. 140, Department of Civil Engineering, University of Washington, 1994.

Liang, X., D.P. Lettenmaier, E.F. Wood, and S.J. Burges, "A simple hydrologically based model of land surface water and energy fluxes for GCMs", Journal of Geophysical Research 99(D7), 14,415-14,428, 1994.

Wetzel, S., "A hydrological model for predicting the effects of climate change", B.S. Thesis, Department of Civil Engineering and Operations Research, Princeton University, Apr., 1994.

Wood, E.F., D.P. Lettenmaier, and V.G. Zartarian, "A land surface hydrology parameterization with subgrid variability for general circulation models", Journal of Geophysical Research, Vol. 97, No. D3, Feb., 1992, pp. 2717-2728.

Zhao, R.J., "Flood forecasting method for humid regions of China", East China College of Hydraulic Engineering, 1977.

Links to Related Sites

PILPS WWW home page


Dennis P. Lettenmaier
Department of Civil Engineering
University of Washington
Seattle, Washington 98195
Fax: 206-685-3836

Eric F. Wood
Department of Civil Engineering and Operations Research
Princeton University
Princeton, New Jersey 08544
Fax: 609-258-1270

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