Validation and Calibration of Riparian Shade Prediction Models

www.fishsciences.netOregon • California • Washington • Idaho • Alaska

2013 Western Mensurationists Meeting Leavenworth, WA

Validation and Calibration of Riparian Shade Prediction Models

Kevin CederMark Teply

Cramer Fish Sciences


Background• Alternative stream management zone (SMZ)

management can change stream shading– Impact T&E species– Exceed TMDL clean water standards– Shade models used to assess shade loss

• Idaho Forest Practices Act Advisory Committee (FPAAC) testing new riparian management prescriptions– Want to ensure shade prediction accuracy– Independent studies used to validate and calibrate models– Resulting calibration models used in shade assessments

2013 Western Mensurationists MeetingLeavenworth, WA



Shade Models• Physics-based models

– “Chen” (Chen et al 1998)– “ODEQ” (Boyd 1996)– Included in Shade.xls (WA

Dept. of Ecology)• Calculate shade to stream

based on light extinction– Input canopy cover and

mean height for each zone– Solar paths are known– Assumes continuous cover

within zone



Validation Data Studies

• Janisch et al. (2012)– 6 sites in western WA– 50-foot no-cut buffers to

WFPA rules• Groom et al. (2011)

– 12 sites in western OR– 50- and 75-foot to OAR rules

• Cupp (pers. Comm. 2012)– 8 sites in eastern WA– 75-foot to WFPA rules

• Sugden & Steiner (2005)– 9 sites on Plum Creek lands– 50-foot



Biases in Shade Reduction Predictions



Correlations with Stand Variables Chen ODEQ Combined 50-foot 75-foot Combined 50-foot 75-footTPA > 3” -0.11 -0.02 -0.45 -0.07 0.04 -0.43BA > 3” 0.41 0.57 -0.08 0.38 0.54 -0.11QMD > 3” 0.46 0.49 0.58 0.39 0.43 0.51Avg. HT > 3” 0.59 0.64 0.46 0.50 0.57 0.34%HWD > 3” 0.45 0.55 0.39 0.43 0.54 0.30Avg. LCR > 3” -0.72 -0.77 -0.28 -0.63 -0.69 -0.14TPA > 8” 0.38 0.62 -0.19 0.36 0.60 -0.26BA > 8” 0.49 0.60 0.09 0.44 0.56 0.04QMD > 8” 0.30 0.30 0.50 0.26 0.26 0.51Avg. HT > 8” 0.39 0.43 0.25 0.32 0.36 0.21%HWD > 8” 0.46 0.56 0.38 0.43 0.55 0.29Avg. LCR > 8” -0.70 -0.75 -0.32 -0.60 -0.67 -0.18RDSUM 0.50 0.63 0.03 0.45 0.59 -0.03



Correlations with Stand Variables Chen ODEQ Combined 50-foot 75-foot Combined 50-foot 75-footTPA > 3” -0.11 -0.02 -0.45 -0.07 0.04 -0.43BA > 3” 0.41 0.57 -0.08 0.38 0.54 -0.11QMD > 3” 0.46 0.49 0.58 0.39 0.43 0.51Avg. HT > 3” 0.59 0.64 0.46 0.50 0.57 0.34%HWD > 3” 0.45 0.55 0.39 0.43 0.54 0.30Avg. LCR > 3” -0.72 -0.77 -0.28 -0.63 -0.69 -0.14TPA > 8” 0.38 0.62 -0.19 0.36 0.60 -0.26BA > 8” 0.49 0.60 0.09 0.44 0.56 0.04QMD > 8” 0.30 0.30 0.50 0.26 0.26 0.51Avg. HT > 8” 0.39 0.43 0.25 0.32 0.36 0.21%HWD > 8” 0.46 0.56 0.38 0.43 0.55 0.29Avg. LCR > 8” -0.70 -0.75 -0.32 -0.60 -0.67 -0.18RDSUM 0.50 0.63 0.03 0.45 0.59 -0.03



Shade Loss Calibration Model

• Shade reduction error related to average crown ratio with 50’ buffers

• No relationships with stand conditions found for 75’ buffers– 3.7% underprediction



Reasons for Biases

• 50-foot buffers:– Lower crown ratio stands have more crown to

intercept light than higher crown ratio stands.– Extinction coefficient calculation does not

take this into account.• 75- foot buffers:

– Sufficient width for light extinction regardless of canopy

– Calculation slightly off.







Idaho FPAAC SMZ management alternatives• We provided

support to the FPAAC for several iterations of SMZ management alternatives

• Learning at each iteration resulted in choosing an alternative that met all their needs



Summary

• Shade models are important tools for assessing SMZ management alternatives but show consistent biases

• Biases can be partially corrected with stream-adjacent stand information

• It may be time to revisit these models to make them better fit forest conditions



Questions?Comments?

Kevin Ceder: [email protected]

Mark Teply: [email protected]


References• Boyd, M.S. 1996. Heat Source: stream temperature prediction. Master’s

Thesis. Departments of Civil and Bioresource Engineering, Oregon State University, Corvallis, Oregon.

• Chen, Y.D., R.F. Carsel, S.C. McCutcheon, and W.L. Nutter. 1998. Stream temperature simulation of forested riparian areas: I. watershed-scale model development. Journal of Environmental Engineering. April 1998. pp 304-315.

• Groom J. D., L. Dent, L. Madsen, J. Fleuret. 2011. Response of western Oregon (USA) stream temperatures to contemporary forest management. Forest Ecology and Management 262(8):1618-1629.

• Janisch, J. E., S. M. Wondzell, and W. J. Ehinger. 2012. Headwater stream temperature: Interpreting response after logging, with and without riparian buffers, Washington, USA. Forest Ecology and Management, doi:10.1016/j.foreco.2011.12.035.

• Sugden, B. and R. Steiner. 2005. Effectiveness of native fish HCP buffers for stream temperature control: 5-year review report to US Fish and Wildlife Service. Plum Creek Timber Company, Columbia Falls, MT.


Documents

Validation and Calibration of Riparian Shade Prediction Models