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Proceedings of the Symposium on Global and Environmental Monitoring

Spatial Modelling of Forest Watershed Processes
Lawrence Band, Ramakrishna Nemani, University of Toronto
Steven Running, Joseph Coughlan, University of Montana
David Peterson, Jennifer Dungan, NASA/Ames Research Center
A geographic information processing and modelling system is under construction for the
simulation of forest watershed processes over a range of spatial scales. The system organizes
all environmental information by a formal landscape feature model, utilizing the hillslopes and
drainage lines of a watershed as the spatial framework for storage and manipulation of model
parameters. Parameters are derived from a combination of remotely sensed imagery, digital
terrain data, digitized soil maps and base station meteorologic data. Simulation is distributed
over the watershed area by seperately parameterizing and simulating hydroecologic processes for
each hillslope.
We describe a system for automating the
spatial data handling, model parameterization
and simulation of forest ecosystem processes
within watersheds of varying scales. We
link an existing ecosystem model, FOREST-
BGC, which simulates the cycles of water,
carbon and nitrogen between soil, canopy
and atmosphere (Running and Coughlan,
1988), with a set of algorithms specifically
designed to stratify and manipulate spatial
data in a watershed. The system is designed
to first identify and extract all stream
channels and hillslopes in a watershed as
data objects, and build a hierarchical
database in which the data objects are
explicitly defined in relation to all other
objects in the natural watershed hierarchy.
The data model used here includes all
hillslopes and stream channel links as the
most primitive objects, from which
composite objects of larger hillslopes,
subcatchments and watersheds can be easily
formed by use of a formal geomorphic
model of drainage basins.
FOREST-BGC simulates the net
primary productivity (NPP) and
évapotranspiration (ET) of a forest stand.
Extensive sensitivity analysis of FOREST-
BGC has shown the most important
parameters are net radiation (R), atmospheric
vapor pressure deficit (VPD), canopy leaf
area index (LAI), air temperature (T) and the
available soil water capacity (SWC). In
mountainous environments, the close
coupling of these parameters with the
topography suggests that use of hillslope
objects to spatially aggregate the parameters
results in lower internal parameter variance
and higher between unit (hillslope)
parameter variance. The relatively
conservative range of net radiation over a
hillslope facet compared to the range
expected over arbitrarily located grid cells
(such as AVHRR pixels) allows a much
greater discrimination of well expressed and
observable landscape patterns that otherwise
may be filtered out. In addition, hillslopes,
stream channels and watersheds are
functional hydrologic units as sources and
conveyors of water, and allow aggregation
into larger functional units, unlike arbitrarily
located grid cells.
In order to discriminate parameter
values between hillslopes, it is necessary that
parameters be estimated at significantly
higher spatial resolution than that of the
hillslopes. Consequently, high resolution
imagery and terrain data must be used to
produce initial parameter fields, from which
the hillslope parameterization is developed.
In this paper, RESSYS (Regional