1. Powerpoint Templates Estimating Nutrient Concentrations in Wetlands and Biofilters Using Proxy Data Norma Galaviz, Emily Parker, and Cameron Patel August 1, 2013 NSF PIRE

2. Powerpoint Templates Estimating Nutrient Concentrations in Wetlands and Biofilters Using Proxy Data Norma Galaviz, Emily Parker, and Cameron Patel August 1, 2013 NSF PIRE

3. Powerpoint Templates Estimating Nutrient Concentrations in Wetlands and Biofilters Using Proxy Data Norma Galaviz, Emily Parker, and Cameron Patel August 1, 2013 NSF PIRE

4. Powerpoint Templates Estimating Nutrient Concentrations in Wetlands and Biofilters Using Proxy Data Norma Galaviz, Emily Parker, and Cameron Patel August 1, 2013 NSF PIRE

5. Powerpoint Templates Outline Background Introduction Hypothesis Methods Data Analysis Results Discussion

6. Powerpoint Templates

7. Background The Millennium Drought threatened water security in Melbourne, Australia Stormwater capture, treatment, and harvesting provide a new source of water for Melbourne, and reduce nitrogen input to Port Phillip Bay

8. Powerpoint Templates Introduction Two treatment approaches are evaluated in this study -- biofilters and constructed wetlands Stormwater treatment is affected by flow path, vegetation, and filter media The fate of nitrate and phosphate in wetlands and biofilters is evaluated using multiple linear regression (MLR)

9. Hypothesis Phosphate and nitrate in constructed wetlands and biofilters can be estimated using sensor measurements and other proxy data.

10. Powerpoint Templates Methods Sampling took place at a total of six sites in Melbourne, Victoria, Australia. Two constructed wetlands: Royal Gardens and Hampton Park

11. Powerpoint Templates Methods Sampling took place at a total of six sites in Melbourne, Victoria, Australia. Two constructed wetlands: Royal Gardens and Hampton Park Two biofilters: Wicks Reserve and Hereford Road

12. Powerpoint Templates Methods Sampling took place at a total of six sites in Melbourne, Victoria, Australia. Two constructed wetlands: Royal Gardens and Hampton Park Two biofilters: Wicks Reserve and Hereford Road One bioretention/ constructed wetland system: Lynbrook Estates

13. Powerpoint Templates Methods Sampling took place at a total of six sites in Melbourne, Victoria, Australia. Two constructed wetlands: Royal Gardens and Hampton Park Two biofilters: Wicks Reserve and Hereford Road One bioretention/ constructed wetland system: Lynbrook Estates One natural wetland system: Edithvale-Seaford Wetlands

14. Powerpoint Templates Methods Measurements and water samples were collected at multiple locations within each site (including outflow and inflow locations)

15. Powerpoint Templates Methods Measurements and water samples were collected at multiple locations within each site (including outflow and inflow locations) Temperature (T), dissolved oxygen (DO), and pH measurements were recorded ten times per location using portable instruments

16. Powerpoint Templates Methods Measurements and water samples were collected at multiple locations within each site (including outflow and inflow locations) Temperature (T), dissolved oxygen (DO), and pH measurements were recorded ten times per location using portable instruments Water samples taken in triplicate were analyzed for chlorophyll (CHL), pheophytin (PHEO), nitrate, and phosphate (spectrophotometry), and total suspended solids (TSS; weight measurements) as outlined in Standard Methods for the Examination of Water and Wastewater

17. Powerpoint Templates Data Analysis MLR models were developed using Virtual Beach 2.3 with: nitrate or phosphate as the dependent variable T, DO, pH, CHL, PHEO, and TSS as independent variables

18. Powerpoint Templates 4 groups were evaluated:

19. Powerpoint Templates Results MLR models created for each group, ranked by AICc The R 2 values for phosphate models are greater than for nitrate models Nitrate and phosphate were most highly correlated with TSS and DO

20. Powerpoint Templates

21. Discussion Phosphate DO and TSS were the strongest correlates Consistent with the fact that phosphate binds to suspended solids Highlights the importance of solids removal as a wetland function

22. Powerpoint Templates

23. Discussion Nitrate Nitrate models explained less variance than phosphate models

24. Powerpoint Templates Discussion Nitrate Nitrate models explained less variance than phosphate models DO, TSS, and PHEO were explanatory variables

25. Powerpoint Templates Discussion Nitrate Nitrate models explained less variance than phosphate models DO, TSS, and PHEO were explanatory variables Nitrate/inverse PHEO relationship suggests nutrient uptake by phytoplankton Phytoplankton Chlorophyll Pheophytin

26. Powerpoint Templates Phytoplankton Chlorophyll Pheophytin Discussion Nitrate Nitrate models explained less variance than phosphate models DO, TSS, and PHEO were explanatory variables Nitrate/inverse PHEO relationship suggests nutrient uptake by phytoplankton Phytoplankton NO 3 -

27. Powerpoint Templates Discussion Nitrate Nitrate models explained less variance than phosphate models DO, TSS, and PHEO were explanatory variables Nitrate/inverse PHEO relationship suggests nutrient uptake by phytoplankton Note: It is unclear why DO is a correlate. We noticed that DO tended to be low in shallower areas that had higher TSS.

28. Powerpoint Templates Conclusion Phosphate can be reasonably estimated using proxy data Nitrate analysis reveals weak relationship Further study needed, or perhaps nitrate cannot be reasonably predicted using proxy data.

29. Powerpoint Templates References 1.Andrieux-Loyer, F.; Aminot, A. Phosphorus forms related to sediment grain size and geochemical characteristics in French coastalA areas. Estuarine, Coastal, Shelf Sci. 2001, 52, 617 − 629. 2.Eaton, A. D.; Franson, M. A. H.; American Public Health Association (Eds.). (2005) Standard Methods for the Examination of Water and Wastewater. (21st ed.) American Public Health Association. 3.Koike, I.; Furuya, K.; Otobe, H.; Nakai, T.; Menoto, T.; Hattori, A. Horizontal distributions of surface chlorophyll a and nitrogenous nutrients near Bering Strait and Unimak Pass. Deep-Sea Res., Part A 1982, 29, 149 − 155. 4.Rippy, M.; Franks, P.; Feddersen, F.; Guza, R.; Warrick, J. Beach Nourishment Impacts on Bacteriological Water Quality and Phytoplankton Bloom Dynamics. Environ. Sci. Technol. 2013, 47, 6146-6154. 5.Rocha, R. R.; Thomaz, S. M.; Carvalho, P.; Gomez, L. C. Modeling chlorophyll a and dissolved oxygen concentration in tropical floodplain lakes (Parana River Brazil). Braz. J. Biol. 2009, 69, 491 − 500.

30. Acknowledgements This project was funded through a Partnerships for International Research Education grant from the National Science Foundation. Special thanks to the University of Melbourne Engineering Department for lab and equipment accommodations, and to Melbourne Water for site access and cooperation. Thanks also to Dr. Stanley Grant, Dr. Sunny Jiang, Dr. Andrew Mehring, Dr. Meg Rippy, and Alexander McCluskey for their assistance and advice.