297 
contrast between north and south facing 
slopes. Slopes 1 and 2 are the first slopes 
on the left and right, respectively, looking 
upstream from the watershed outlet. Their 
seasonal trajectories of ET (figure 4) are 
driven by contrasts in their radiation 
environments, SWC and LAI. 
Validation of the distributed model 
results can effectively be accomplished by 
outlining a suite of model products that can 
be periodically observed on different slopes 
through the growing season. This amounts 
to replicating standard sampling schemes for 
model validation usually carried out for 
point models, with the added benefit of 
gaining spatial patterns of either agreement 
or disagreement of model predictions with 
field observations. Unfortunately, this also 
increases the effort and difficulty of field 
sampling in proportion to the number of 
observation points taken to gain that pattern. 
Another possibility for model validation 
using the geographic pattern of model 
performance would be to use satellite or 
airbomed imagery taken at different key 
parts of the growing season, using spectral 
bands or combinations of bands that could 
be correlated with model output. As an 
example, LWP or ET may be correlated with 
thermal bands on a very detailed and 
observable landscape level (from hillslope to 
hillslope or within hillslopes) as variations in 
the spatial patterns of the latent heat flux 
over the season pick up those areas 
experiencing progressive moisture stress. 
DISCUSSION 
We have briefly outlined the basic 
structure of RESSYS. The system automates 
the raw geographic data processing and the 
parameterization and execution of a forest 
ecosystem model, FOREST-BGC. We are 
currently expanding the capabilities of the 
ecosystem model, and therefore the 
corresponding functions of geographic 
information processing components of 
RESSYS. The hydrologic submodel of 
FOREST-BGC is being supplanted with a 
version of TOPMODEL (Beven and Kirkby, 
1979) to simulate lateral flux of soil water 
down the hillslopes. Other subcomponents 
are also being modified or added to in order 
to generalize the model to different 
environments. This results in a situation in 
which a given environment will require a 
given set of submodels and geographic 
information processors to be activated within 
RESSYS. 
Currently, RESSYS can flexibly 
partition a landscape into different numbers 
of elemental data and simulation units, 
giving us the ability to choose the 
appropriate scale of landscape representation 
and simulation or allowing us to explore the 
impact of surface representation detail on 
simulation behaviour. Using naturally 
occuring, functional hydrologic units 
(hillslopes) as our basic landscape units 
rather than arbitrarily located grid cells also 
allows us to preserve greater detail in 
landscape patterns that would otherwise be 
averaged out by aggregating over distinctly 
different local microenvironments (e.g. 
averaging over north and south facing 
slopes.) The range of model outputs that are 
observable or measurable in the field, 
coupled with the preservation of distinct 
microenvironments through the analysis and 
simulations should enhance our ability to 
validate these distributed models. 
So far, we have used the method on 
watersheds up to 1600 square kilometers in 
western Montana and are currently in the 
beginning phase of assembling a detailed 
representation of an area comparable in size 
to a GCM grid cell, or a number of 
mesoscale circulation model cells in order to 
produce surface hydroecologic models that 
can be run over regional to subcontinental 
scales, but can also be locally validated by 
redefinition of the landscape across this scale 
range. 
Acknowledgements: This research was 
supported by funding from the Land Surface 
Processes Branch of NASA, NAGW-1234.