HR: 09:15h
AN: NB21G-04    [Abstracts]
TI: "Desktop Watersheds" in River Restoration: Static to Dynamic Digital Terrain-based Modeling
AU: * Dietrich, W E
EM: bill@geomorph.berkeley.edu
AF: University of California at Berkeley, 301 McCone Hall , Berkeley, CA 94720 United States
AU: Ligon, F K
EM: frank@stillwatersci.com
AF: Stillwater Sciences, 850 G Street #K, Arcata, CA 95521 United States
AB: A "Desktop Watershed" is the goal of developing a process-based model, which uses digital topographic and surface attributes (such as geology, vegetation, and land use) to predict the linkages between land use and ecosystem function; such predictions would then guide management decisions. The central hypothesis is that with accurate topography, spatially referenced information on material and biological properties, and simple process-based models, digital terrain-based analyses can assist resource managers in three ways. First, a Desktop Watershed model could be used to develop broad predictions about the expected spatial distribution of resource properties (e.g., landslide location, river bed grain size, and stream temperature) before going to the field. These predictions then become expected states that field observations can test; the results can then be used to gain deeper insight on how management activities control these properties. Second, a Desktop Watershed model could be used to extrapolate local field measurements to entire watersheds. Third, a Desktop Watershed digital terrain model could model the dynamic linkages between land use and resource state. We propose that much can be learned from the use of an analytical reference state calculation, in which an idealized quantitative statement of an expected condition is made based on simple observable properties such as topography and general climate setting. A key assumption is that relatively immutable properties of a specific watershed (such as topography, drainage area to a point, local slope, aspect, and climatic setting) can be quantified and used in simple mechanistic models to calculate an expected condition in the system. This reference watershed model becomes a theoretical condition that can be calculated for any watershed, but will differ between watersheds depending on the watershed's intrinsic properties. Importantly, the reference model also becomes a null hypothesis by which we can guide fieldwork: it is a state against which to detect and measure deviations from predictions that are caused by processes not included in the model. An example of an analytical reference state is the prediction of the median grain size of river bed throughout a channel network. Other examples include channel and bed morphology estimates, shallow landslide locations, and stream temperatures. These physical attributes can then be linked to habitat conditions that allow an estimate of potential fish abundance. What is now needed-and many groups are working on this--are dynamic models that route water, sediment, wood, heat, and nutrients through the watershed; the models must also link these attributes to ecosystem processes. Gaps in current knowledge make this linkage difficult and currently necessarily crude. Nonetheless, such models would generate hypotheses that would guide further fieldwork.
DE: 1803 Anthropogenic effects
DE: 1824 Geomorphology (1625)
SC: North American Benthological Society [NB]
MN: 2005 Joint Assembly