Watershed
- Catchment Classification
Goal
Monitoring
is an essential component of watershed management. However,
it is often difficult to link watershed components with instream
monitoring projects. Advances in computer technology have
provided a tool, geographic information systems, which can be used
to develop watershed-wide perspective on factors that affect aquatic
resources such as salmon and water quality. The goal of this
project is to build a monitoring framework by characterizing catchments
(subbasins) MidCoast Region of Oregon. We used GIS to summarize
the physical and biologic properties of topographically defined
catchments approximately 300 acres in size. Descriptive multivariate
statistics were used to objectively classify catchments into meaningful
categories. Monitoring can then be planned for catchments
sharing similar characteristics.
Tasks
1)
Generation of ArcView Catchment Layer:
We began by deriving catchments smaller than the 6th field watersheds.
The average 6th field watershed is 1,718 hectares within our study
area (MidCoast Region of Oregon). In order to examine the
landscape at a finer spatial scale we used 10 m DEM’s (digital elevation
models) to derive a new layer of catchments with an average area
of 100 hectares. Our final layer contained 3,649 catchments.
2)
Analysis of Data Matrix I: We
constructed a data matrix by summarized the following attribute
for each catchment: land cover, slope, elevation, aspect, hillshade,
and stream density. The parameters elevation, aspect, and
hillshade were added after a discussion of the potential interest
in examining stream temperature. These data were analyzed
using descriptive multivariate statistics (i.e., cluster, ordination).
Our initial runs described 32 groups of distinct catchment types.
We
examined current instream monitoring programs to determine how well
existing study sites capture the range of catchment types.
This information will be useful in guiding the selection of future
monitoring locations.
3) Analysis
of Data Matrix II: We constructed
a second data matrix that included information on stream gradient
and confinement. Currently, these data do not exist for the
entire study area.
4) Comparison
of catchment types with biological data.
Finally, determined if catchment types covary with patterns
in the abundance and distribution of important instream biota.
Timeline
October-
December 1999
Publications
Schooler,
S. and R. Garono. In preparation. Watershed-Catchment classification
with an emphasis on salmon and lamprey populations in the MidCoast
region of Oregon. To be submitted to Conservation Biology.
