Factors Determining Thresholds of Reliable Change Detection in Water Quality Resulting from Stream RestorationMelia_Greg_CC_Session1

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Factors Determining Thresholds of Reliable Change
Detection in Water Quality Resulting from Stream
Restoration: A question of signal to noise.
Greg Melia –Presenting
NC Department of Environmental Quality
Division of Mitigation Services
2022 WRRI Conference
March 23-24, 2022
Raleigh, NC
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History and Drivers for Water Quality Measurement
in Restoration/Mitigation in NC
•Water quality improvement is often stated as a goal in
restoration, but infrequently measured Palmer et al., (2007)
•The functional efficacy of restoration for pollutant attenuation
absent watershed controls has been questioned, particularly in
urban settings. Walsh et al., 2005; Bernhardt and Palmer, 2007;
Selvakumar et al., 2010.
•The last decade has shown a range of results, but understanding
efficacy considering scale, setting, and specific practices still
requires attention. (Craig et al., 2008; Palmer et al. (2014); Newcomer
Johnsen et al., (2016); Lammers and Bledsoe (2017)
•2008 Federal Mitigation rule requiring “ecological performance
standards” USACE 33CFR 325, 332; USEPA 40CFR 230
•NCIRT encourages/incentivizes water quality assessment
USACE Federal Public Notice October 24, 2016
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DMS Resources and Opportunity to Evaluate WQ in
Mitigation
1. Large provider of Mitigation in NC.
2.Opportunity for long term observation and monitoring.
3.Tied to a robust watershed planning approach.
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DMS Objectives for Water Quality Monitoring of Mitigation
1.Provide case examples of water quality response to restoration
for settings and mitigation practices in NC.
2.Gain understanding of the relative efficacy of different practices.
3. Gain understanding of the time frames of improvement and their
sustainability.
4.Utilize data collected to potentially refine current models in use
in mitigation plans for pollutant reduction estimates.
5.Gain an understanding of the reach and watershed
attributes that inform detection of change in water quality to
help refine stated mitigation plan goals (i.e. examine a
gradient of “signal to noise”)
6. Gain understanding of sampling regime necessary
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General Concept of Signal to Noise
to the background variation (Noise)
The separation or relative magnitude of what
you want to measure (Signal).
Larger the difference in magnitude (i.e. larger the signal to noise
ratio), the greater resolving power for detecting differences/changes)
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1.Spatial Distribution / Proportions of Stressor Areas
Treated
2. Stressor Intensity
3. Stressor Types
Categories of Reach and Watershed Attributes that
Characterize Signal to Noise
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Concept of Signal to Noise in Restoration Context
1.Distributions of Stressor Areas
2.Stressor Intensity
The combination of these can be viewed as
the overall stressor load at the downstream
‘treatment’ station for a reach. The greater
the proportion of items 1 and 2 that exists
within the treatment area (i.e. protected and
treated via restoration) the greater the
likelihood of reliable detection in change or
improvement. High signal to low noise.
Better resolving power
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Differences in Pre-Restoration water quality
distributions as stressor intensity varies
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•LULC history to help document stressor intensity
and distribution
•Historical orthoimagery
•Landowner discussions
e.g. Livestock densities
e.g. Rotation schedules
e.g. Application rates
Supporting LULC data DMS is Collecting
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Type of Stressor –Effects on change detection
expectations in mitigation timeframes
e.g. Row crop versus pasture
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DMS WQ Study Sites
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DMS WQ Study Sites
Project
# of
Reaches Param
Years
Pre
Years
Post
Heath Dairy*2 F,N,S,M 3 1.7
Millstone*2 F,N,S,M 1.3 1/0.5
Pen Dell 1 F 1 2
Buckwater 1 F,N,S 0.8 2
Big Harris**13 F,N,S,FS,M 5 3
Cross Crk. Ranch 1 F,N,S 1 0
Crane Creek 1 F,N,S 1.3 0
Stinking Quarter 4 F,N,S,M 0.1 0
Indicates a year or more of post restoration data
*Dan Line P.E. NCSU **Dr. Jerry Miller WCU
F –Fecal; N –Nutrients; S –Total Suspended Solids;
M–Macrobenthos FS –Fish
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•DMS will continue to add reaches of varying scale and
complexity to provide an adequate gradient of signal to
noise in order to:
-Identify factors of scale, stressor distributions, and
treatment proportions that could inform change
detection expectations.
-Assist mitigation practitioners in grouping reaches and
sub-watersheds within a project into coarse bins of
‘likelihood’ in terms of reliable change detection.
-Add spatial granularity to the development of goals
and performance standards within
Mitigation Plans.
In Conclusion
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Acknowledgements
•DMS S&A Staff
Periann Russell
Danielle Mir
Joe Famularo
Lin Xu
•Academic Partners
NCSU Bio and Ag Engineering (Dan Line)
Heath Dairy and Millstone
WCU (Dr. Jerry Miller)
Big Harris Project
•Mitigation Provider Partners
Land and Water Solutions (Pen Dell)
Restoration Systems (Crane Creek, Stinking Quarter)
Wildlands Engineering (Buckwater, Cross Creek, Big Harris)
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Citations
Bernhardt, E.S., Palmer, M.A., Allan, J.D., Alexander, G., Barnas, K., Brooks, S., Carr, J., Clayton, S., Dahm, C., Follstad-
Shah, J., and Galat, D. (2005). Synthesizing U.S. river restoration efforts. Science 308, 636–637.
Bernhardt, E.S. and Palmer, M.A. (2007). Restoring streams in an urbanizing world. Freshwater Biol., 52, 738–751. DOI:
10.1111/j.1365-2427.2006.01718.x
Craig, L.S., Palmer, M.A., Richardson, D.C., Filoso, S., Bernhardt, E.S., Bledsoe, B.P., Doyle, M.W., Groffman, P.M.,
Hassett, B.A., Kaushal, S.S., and Mayer, P.M. (2008). Stream restoration strategies for reducing river nitrogen loads. Front.
Ecol. Environ., 6, 529–538. DOI: 10.1890/070080
Lammers, R.W. and Bledsoe, B.P. (2017) What role does stream restoration play in nutrient management?, Critical Reviews
in Environmental Science and Technology, 47:6, 335-371, DOI: 10.1080/10643389.2017.1318618.
Palmer, M.A., Hondula, K.L., and Koch, B.J. (2014). Ecological restoration of streams and rivers: shifting strategies and
shifting goals. Annu. Rev. Ecol., Evol. Syst., 45, 247–272. DOI: 10.1146/ annurev-ecolsys-120213-091935.
Palmer, Margaret & Allan, J. David & Meyer, Judy & Bernhardt, Emily. (2007). River Restoration in the Twenty-First Century:
Data and Experiential Future Efforts. Restoration Ecology. 15. 472 -481. 10.1111/j.1526-100X.2007.00243.x.
Newcomer Johnson, T.A., Kaushal, S.S., Mayer, P.M., Smith, R.M., and Sivirichi, G.M. (2016). Nutrient retention in restored
streams and rivers: A global review and synthesis. Water, 8, 116. DOI: 10.3390/w8040116.
Selvakumar, A., O’Connor, T.P., and Struck, S.D. (2010). Role of stream restoration on improving benthic
macroinvertebrates and in-stream water quality in an urban watershed: case study. J. Environ. Eng., 136, 127–139. DOI:
10.1061/(ASCE)EE.1943-7870.0000116
Walsh, C.J., Fletcher, T.D., and Ladson, A.R. (2005). Stream restoration in urban catchments through redesigning
stormwater systems: looking to the catchment to save the stream. J. NorthAm. Benthol. Soc., 24, 690–705. DOI:
10.1899/0887-3593(2005)024\[0690:SRIUCT\]2.0.CO;2
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Questions?