RipStream: Quantifying stream temperature response to Oregon timber harvest practices
Jeremy Groom1, Liz Dent2, Lisa Madsen3
1OSU Dept. of Forest Engineering Resources & Management2Oregon Dept. of Forestry, 3OSU Dept. of Statistics
In a time before streams…
Oregon Department of Forestry Monitoring
LandslidesPesticidesLeave-treeHAPShadeStream Temperatures
Private Forests Division
Clean Water Act & OR Forestry
Clean Water Act
EPA
DEQ (Water Quality Rules)
Monitoring
Forest Practices ActBoard of Forestry
RipStream – Riparian Function and Stream Temperature
State and Private Forests joint effort
• Objective: Evaluate effectiveness of forest practices rules & strategies at protecting stream temperature, promoting riparian structure
• 33 Sites (18 Private, 15 State, Medium and Small F)
• Dent et al. 2008 JAWRA 44(4):803-813
Rules and Strategies
Private: Forest Practices ActState: Northwest Oregon State Forest
Management Plan
State ForestsPrivate Forests
170 ft25 ft20 ft50 ft70 ft
Limited Entry No Cut
No Cut
Limited Entry
Small & Medium FSmall F
Medium F
RipStream Study Design
Design: 2 years pre-harvest, 5 years post harvest
1W
4W
Control Treatment
Downstream
2W
POINT OF MAXIMUM IMPACT
3W
RipStream – Data and Questions
What questions do we address first?– Regulatory: do our streams meet DEQ
temperature standards post-harvest?– Function: what site characteristics are related to
temperature change post-harvest?
Years of data collection- Stream temperature- Shade- Channel morphology
(gradient, widths, etc.) - Riparian vegetation
(trees, shrubs)
DEQ Water Temperature Standard
Biologically-Based Numeric Criteria – were stream temperatures raised above 16 C or 18 C?
• Not really• Analysis: Relatively straightforward
Protecting Cold Water (PCW) – were streams warmed by > 0.3 C?
• Yes, on private (not State) streams• Analysis: Complex
• 7DayMax
• “Temperature” = 7-day moving average of maximum daily temperatures
Day: 1 2 3 4 5 6 7 8 9 10 11Temp: 11 12 10 11 9 8 9 9 10 10 9
9.7 9.4 10.07DayMax:
Numeric Criteria
Is analysis guidance available? YES
Numeric Criteria exceedance = Any single summer 7DayMax temperature value exceeds 16 C or 18 C
Natural: Control probes 1W & 2WPotential harvest effect: Treatment probe 3W
Numeric Criteria – What’s the big deal?
• Widespread WQ rule type
• EPA guidance (2003) for PNW states
• Lots of effort & research
• Opportunity for evaluation
Numeric Criteria Results: 16 C• Total Number of Sites: 33
– 18 sites exceeded 16 C
• Of those 18 sites:– 3 sites = pre-harvest only
– 10 sites = control (1W, 2W) and treatment (3W) probes during the same year or years
– 3 sites = control probes during pre-harvest years; treatment probes during post-harvest year(s)
– 2 sites = treatment probe post-harvest only
No strong indication that standards exceeded
Protecting Cold Water (>0.3 C)
• Is analysis guidance available? NO.
Lacking in other states
Collaboration with DEQ
Analysis question: For a specific day, has
stream temperature increased by > 0.3 C?
PCW analysis
Looking for change in relationship (e.g., Treatment Reach = 2W and 3W)
Comparing pairs of years (e.g., 2002 & 2004) within a reach (e.g., Upstream Control)
Years are either pre-harvest or post-harvest (can compare pre-pre, pre-post, post-post)
PCW – Analysis Path
1) Which reach year-pair comparison “exceeded” PCW?
2) Created & compared explanatory models of exceedance patterns
– Examined combinations of regulatory distinctions (medium & small streams, State and Private lands)
– Also examined comparison timings (e.g., pre-harvest to post-harvest)
• 3 reaches X 3 time periods = 9 groups
Study Design and the PCW
Pre-pre Pre-post Post-post
UpstreamControl
Treatment
Downstream
1W
4W
2W3W
FLOW
614 comparisons total 65 exceedances
Models
Main Models
1) Null (all categories equal)
2) Reaches differ
3) Timing differs
4) Everything differs
5) Pre-post treatment differs
6) Pre-post Private treatment differs
UpstreamControl
Treatment
Downstream
Pre-pre Pre-post Post-post
Best State Forest Model ?
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Private Pre-PostTreatment
All Other Categories
Pro
bab
ility
of
Exc
eed
ance
Best models
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Private Pre-Post Treatment All Other Categories
Pro
bab
ility
of
Exc
eed
ance Small Streams
Medium Streams
TOP MODEL
40.2%
4.6%
Conclusions (Regulatory)• Numeric Criteria – OK(?)
• PCW – increase in exceedance frequency on Private streams in general
• PCW – State OK
Functional Analysis
Study scope:Preharvest and two years postharvest
33 sites
Questions:
What factors influence changes in Treatment Reach temperature?
Magnitude of temperature change?
What are we quantifying?
• Changes in temperature (downstream – upstream)
• Averaged daily values (July 15 – Aug 23)
– Maximum– Minimum– Average– Flux
1W2W 3W
FLOW
2W-1W = Change in Control Reach
3W-2W = Change in Treatment Reach
What factors control Treatment Reach temperature change?
Gradient
Elevation
Reach length
Control reach temperature change
Azimuth
Watershed area
1W2W 3W
FLOW
Shade
Approach1) Determine appropriate statistical analysis
Linear mixed-effects regression
2) Develop competing explanations (models) of how temperature change controlled18 models, ranked AIC
3) Determine which explanation performed best
4) Examine model results
Best model: Change in maximum temperatures explained by:
-Temperature change in control reach-Treatment reach length-Gradient-Shade
Random: ~ Intercept + Control Temperature|Site
Model values statistically significantModels without shade performed poorly
Maximum Temperatures
0.5 0.6 0.7 0.8 0.9
-10
12
3Shade (95% CI)
Shade Values (%)
Est
imat
ed T
empe
ratu
re C
hang
e (C
)
500 1000 1500
-10
12
3Treatment Reach Length (95% CI)
Treatment Reach Length (m)
Est
imat
ed T
empe
ratu
re C
hang
e (C
)
2 4 6 8 10 12 14
-10
12
3Gradient (95% CI)
Average first quartile of gradient (deg)
Est
imat
ed T
empe
ratu
re C
hang
e (C
)
Other Temperature Metrics
Minimum Temperature: Same top model, same behavior of variables (not as strong)
Average Temperatures: ditto
Flux: Increased daily fluctuations with less shade
Implication: Reductions in shade occurred, linked to increase in daily temperature maximum, minimum, average, and flux
Shade Pre & Post Harvest50
6070
8090
100
Ave
rage
Sha
de P
re-H
arve
st (
%)
PrivateState
5060
7080
9010
0
Ave
rage
Sha
de P
ost-
Har
vest
(%
)
PrivateState
Preharvest and Postharvest
De
gre
es
C
-3-2-1012
-1.0 -0.5 0.0 0.5 1.0
7453 5207
-1.0 -0.5 0.0 0.5 1.0
5103 5558
-1.0 -0.5 0.0 0.5 1.0
5201
5101 5557 5102 5204
-3-2-1012
5202-3-2-1012
7454 5355 5354 5503 5506
7803 5106 5560 7353
-3-2-1012
5104-3-2-1012
5301 5302 5206 5561 5556
5205 5203 7452 5253
-3-2-1012
7854-3-2-1012
7801
-1.0 -0.5 0.0 0.5 1.0
5502 5559
Partial Residual Plot for 33 Sites
Results summary
1) Shade changed and related to temperature change
2) Other parameters seem reasonable
3) Shade is important & needs further exploration-BA, height, blowdown
Next steps• Complete & publish current analysis
• Next analysis: 5 yrs post harvest– Did temperature patterns remain?– Did shade recover?– More detailed examination of
vegetation and shade
Liz Dent (ODF) & Joshua Seeds (DEQ) Private landowners PF monitoring staff (Marganne Allen, Jerry
Clinton, Kevin Nelson, Kyle Abraham, Seasonal Work Force, Stewardship Foresters)
State Forests Program Staff (Jeff Brandt, District Foresters, Field Foresters)
Review Committee Members EPA 319 program
Acknowledgements