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Chris Miles, Olivia Miller, and Sophie Potoczak18 August 2011
A Probabilistic Model of Large Woody Debris Movement
and Distribution in Small Mountain Streams[Chris Gabrielli, 7/11]
•Entry modes•LWD accumulation types•Historic snagging efforts•River restoration efforts and Engineered Log Jams (ELJ’s)
Large Woody Debris (LWD): A History
Why is wood good?
Impacts of LWD
Geomorphologic:• Pools• Migrating bars• Steps, slope• Bank erosion• Median grain size
Ecological:• Protective fish
habitat and spawning grounds
• Organic matter storage
Infrastructural:• Damaging
bridges, scientific monitoring stations
ELJ at Quartz Creek near Blue River, OR
[Sophie Potoczak, 6/11]
Research Objectives:
•Remap sections 1-14 of Lower Lookout to observe changes in wood distributions and channel feature migration between 1977 and today, focusing specifically on changes after the 5-year flood in January 2011
•Design model to predict what conditions are required for a single piece of woody debris to be mobilized during a flood event
•Ultimately develop a model using the movement model to characterize the distribution of wood in a reach in time
•Potentially simulate future years of wood distribution using the large scale model
[Sophie Potoczak, 7/11]
•5th order stream•Stream gradient 1.5%•470 m stretch of stream•14 irregularly spaced transects
[H.J
. And
rew
s]
Wood Mapping:•Measurements taken for pieces > 1m length and 0.1m diameter at breast height (DBH)
•DBH taken 1.3m from thickest end
•Length, width, height dimensions taken for jams with porosity adjustment
•Compass orientations taken for key pieces
Channel Mapping:•Low gravel bars <1m above lowest flow
•High gravel bars >1m above lowest flow
•Deep, slow-moving or stagnant pools
•Secondary or vegetated abandoned channels considered for low-flow conditions
[Chris Gabrielli, 7/11]
[Chris Gabrielli, 7/11]
Cross-Sectional Profiles:
•Level tape strung from X to Z datum
•Depth below line measured every 1 m on bank and gravel bars and every 0.5 m in stream bed
•Profiles used to calculate wetted perimeter and cross-sectional area
[Sophie Potoczak, 7/11]
Mathematical Model
•Quantify the probability that a given piece of woody debris of volume V will move in a discharge Q
V< 1 m3
V > 1 m3
•integro-differential equation is used to model the dynamics of the LWD distribution on a river stretch of length
• is the density of the volume of wood per unit length at point x and time t
• is the probability that a log of volume V will move from y to x in the stream reach
• is the percent of the volume of wood that enters and exists the stream reach per unit length
Mathematical Model Cont’d
•Integrate equation over range of volumes to represent all of the volume classes observed to obtain:
•Where
and
• is quantified by the 2010 wood data through normalizing the volumes over the total volume per cross section length
Mathematical Model Cont’d
is frequency at which certain volume classes occur in LOL and the histogram is fit to a log-normal distribution
Mathematical Model Cont’d
•The equation is integrated over the length of the stream reach to represent the change on wood volume over the entire reach for one year
• is the total change in wood volume in LOL•After integration:
the full model for change in wood volume is the following:
Mathematical Model Cont’d
Lower Lookout Creek 2011: Wood and Channel Map
Outline of map courtesy of EISI 2010(Not a precise scale)
Adobe Illustrator CS5.1 used to overlay and refine wood and channel feature maps.
Low-flow channelSecondary channelLower barHigher bar
Channel and Wood Distribution Changes from 2010 to 2011
(following January 2011 flood)
•Large dam near XS 11 washed out •Channel-spanning log at XS 4 and XS 1 snapped•New large accumulations at XS 8 and XS 4
•Migrating gravel bars between XS 7-8 and XS 3-4
Sequential maps of LOL over the last 34 years show changes in wood budgets for each section of stream and how channel features are determined by and change in response to presence of LWD
Map sources: George Lienkaemper (1977 and 1984); Futoshi Nakamura (1990); John Faustini (1996); Jung-il Seo, Kristin Kirkby (2010). Figure: Jung-il Seo
Results: Flood Frequency Analysis
0 50 100 150 200 2500.00
0.20
0.40
0.60
0.80
1.00
1.20
f(x) = exp( − 0.0247097028563452 x )R² = 0.994302322751026
Flood Frequency Analysis for Lower Lookout Creek
Series1Exponential (Series1)
Discharge (m3/s)
1/RI(1/yr)
Flood Frequency analysis performed via Log-Pearson Type III Analysis from 54 years of annual peak flow data for Lower Lookout Creek
Results: Model
Solutions for the relation between the mean travel distance and the input rate using the known change in volume for 2011
Values for the total change in volume (normalized) in one year as a function of the mean travel distance and the input rate
Discussion
Movement Model: Volumes of wood: rootwad? porosity? Density of wood Wood probably isn’t always parallel Critical discharges abnormally low: 89% of
wood able to mobilize in 2011 flood, 100% in 1996
Lack of recent cross section data Manning’s n estimate potentially off
Distribution Density model: Not enough data to split into good volume
classes Many things not a function of Q (due to
only having 2011 data)
Conclusion
Distribution density model can be used to simulate future years
Can be used as a better representation of wood movement for simulations (Streamwood) that influence policy\management
EISI Reflection
•Eco-Informatics▫Computer Science▫Mathematics▫Geology▫Ecology
•Future Groups▫Current model is very simplified and can be
improved with more accurate data collection
Acknowledgements:
Dr. Julia JonesDr. Jorge RamirezDr. Desiree Tullos
Travis RothDr. Fred SwansonDr. Mark SchulzeTheresa Valentine
Matt CoxChris Gabrielli
Dr. John FaustiniGreg Downing
Dr. Stan GregoryDon Henshaw
National Science FoundationEco-Informatics Summer InstituteH.J. Andrews Experimental Forest
Oregon State University
References
"Andrews Experimental Forest LTER: Data Abstract Detail GS002." Andrews Experimental Forest LTER: Andrews Experimental Forest. 4 Dec. 1990. Web. 15 Aug. 2011. <http://andrewsforest.oregonstate.edu/data/abstractdetail.cfm?dbcode=GS002>. Braudrick C.A. & Grant G.E. (2000) When do logs move in rivers? Water Resources Research, 36, 571–583. Braudrick C.A., Grant G.E., Ishikawa Y. & Ikeda H. (1997) Dynamics of wood transport in streams: a flume experiment. Earth Surface Processes and Landforms, 22, 669–683. Czarnomski N.M., Dreher D.M., Snyder K.U., Jones J.A. & Swanson F.J. (2008) Dynamics of wood in stream networks of the western Cascades Range, Oregon. Canadian Journal of Forest Research, 38, 2236–2248. Faustini, J.M., 2000. Stream channel response to peak flows in a fifth-order mountain watershed. PhD Dissertation, Oregon State University, Corvallis. 339 pp. H. J. Andrews Experimental Forest Brochure. 2003. U.S. Forest Service. Web. 14 Aug. 2011. <http://andrewsforest.oregonstate.edu/lter/pubs/pdf/pub3654.pdf>.
Manners RB, Doyle MW. 2008. A mechanistic model of woody debris jam evolution and its application to wood-based restoration and management. River Research and Applications 24: 1104–1123. Martin D.J. & Benda L.E. (2001) Patterns of instream wood recruitment and transport at the watershed scale. Transactions of the American Fisheries Society, 130, 940–958. Meleason, M. A. 2001. A simulation model of wood dynamics in Pacific Northwest streams. Dissertation. Oregon State University, Corvallis, Oregon, USA. Montgomery, D. R., Collins, B. D., Abbe, T. B., and J. M. Buffington. 2003. Geomorphic effects of wood in rivers. Pages 21–47 in S. V. Gregory, K. L. Boyer, and A. Gurnell (Eds.) The Ecology and Management of Wood in World Rivers. American Fisheries Society Symposium 37, Bethesda, MD. Ramirez, Jorge M. 2011. Population persistence under advection-diffusion in river networks. Journal of Mathematical Biology. Accepted, not yet published. "USGS Real-Time Water Data for USGS 14161500 LOOKOUT CREEK NEAR BLUE RIVER, OR." USGS Water Data for the Nation. Web. 15 Aug. 2011. <http://waterdata.usgs.gov/ nwis/dv/?site_no=14161500>.