![Page 1: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/1.jpg)
Water Quality Program
Using Uncertainty Reduction Analysis to Inform Water Quality Modeling,
Monitoring, and Restoration
March 27, 201911th National Water Quality Monitoring Conference
Denver, CO
Daniel Sobota, Kevin Brannan, Ryan Shojinaga, and David Waltz | Oregon Department of Environmental Quality
![Page 2: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/2.jpg)
Total Maximum Daily Loads (TMDLs)
TMDL = LA + WLA + RC + MOS
• LA – Load Allocation (nonpoint sources)
• WLA – Waste Load Allocation (point sources)
• RC – Reserve Capacity
• MOS – Margin of Safety
![Page 3: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/3.jpg)
Total Maximum Daily Loads (TMDLs)
TMDL = LA + WLA + RC + MOS
• LA – Load Allocation (nonpoint sources)
• WLA – Waste Load Allocation (point sources)
• RC – Reserve Capacity
• MOS – Margin of Safety
![Page 4: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/4.jpg)
Implicit vs. Explicit MOS
• Implicit: Conservative assumptions• Model
• Targets
• Implementation activities
• Other
• Explicit: Portion of loading capacity set aside • Often a percent of loading capacity
• “Black box” approach
![Page 5: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/5.jpg)
Alternative approach for explicit MOS
• Utilize uncertainty in water quality modeling
• Use to inform TMDL Monitoring
![Page 6: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/6.jpg)
Uncertainty reduction analysis
• Identify important parameter and structural uncertainties
• Quantify these uncertainties to optimize models
• Design monitoring to address these uncertainties
Kevin BrannanSM
![Page 7: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/7.jpg)
Upper Yaquina River - 1710020401
![Page 8: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/8.jpg)
Field data and model development
• Continuous water quality data and supporting chemistry grab samples in July 2016
• QUAL2Kw water quality model• 130 parameters to calibrate (!)
• Calibrated with PIKAIA genetic algorithm (Pelletier et al. 2006)
![Page 9: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/9.jpg)
QUAL2Kw model calibration
![Page 10: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/10.jpg)
Parameter Estimation and Uncertainty Analysis (PEST) Software
• Model-Independent Parameter Estimation and Uncertainty Analysis
• Automated system for optimizing model parameter values
• Minimizes difference between observed and simulated values of User specified goodness-of-fit criteria
• Used throughout the world on many different types of environmental models
• More information at:• http://www.pesthomepage.org/Home.php• http://pubs.usgs.gov/sir/2010/5169/• http://pubs.usgs.gov/sir/2010/5211//
![Page 11: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/11.jpg)
PEST-QUAL2Kw setup
• Adjusted 89 parameters
• 15 groups by similar processes
• 668 measured values used for comparisons
• Critical observation: minimum DO
QUAL2Kw
PEST
R
![Page 12: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/12.jpg)
Analysis methods
• Parameter “Identifiability”
• Contribution of parameters to predictive uncertainty
• “Information worth” of data for calibration
![Page 13: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/13.jpg)
Identifiability
Inorganicphosphorusprocesses
Benthicalgal
dynamics
BenthicAlgal
coverage
Phytoplankton
Detritus
![Page 14: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/14.jpg)
Predictive uncertaintyBenthic
algalprocesses
Inorganicphosphorusprocesses
Station 12301:Lowest recordeddissolved oxygen
![Page 15: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/15.jpg)
Information worth
Dissolved oxygen
Inorganic P
Station 12301:Lowest recordeddissolved oxygen
Un
cert
ain
ty v
aria
nce
dec
reas
e d
ue
to o
bse
rvat
ion
s
BODpH
TemperatureStreamflow
Weather
Organic P
![Page 16: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/16.jpg)
Takeaways thus far
• For future model refinements and monitoring, improve measurement of benthic algal characteristics
• Improve frequency and/or timing of water quality monitoring for nutrients (phosphorus)• Less focus on streamflow, weather, and temperature data
![Page 17: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/17.jpg)
Next steps
• Reduce the number of parameters to estimate• Tikhonov – prior information and relationships among
parameters integrated into optimization process
• Singular Value Decomposition (SVD) – solution space dimensions and super parameters
• Pareto analysis (“Biggest bang for the buck”):• Allocation scenarios
• Monitoring locations
![Page 18: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/18.jpg)
Acknowledgements
• Oregon DEQ Watershed Management Section
• US EPA Region 10
• Washington Department of Ecology
![Page 19: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/19.jpg)
Documents can be provided upon request in an alternate format for individuals with disabilities or in a language other than English for people with limited English skills. To request a document in another
format or language, call DEQ in Portland at 503-229-5696, or toll-free in Oregon at 1-800-452-4011, ext. 5696; or email [email protected].
Questions?
![Page 20: Using Uncertainty Reduction Analysis to Inform …Water Quality Program Using Uncertainty Reduction Analysis to Inform Water Quality Modeling, Monitoring, and Restoration March 27,](https://reader030.vdocuments.mx/reader030/viewer/2022011819/5e943a8cfb76b70d7f08576e/html5/thumbnails/20.jpg)
Test approach
• Parameter and model uncertainty
• Information worth of observations
• Predictive uncertaintyThe Inverse Problem