High-frequency measurements reveal spatial and temporal patterns of dissolved organic matter in an urban water conveyance
Stormwater runoff in urban areas can contribute high concentrations of dissolved organic matter (DOM) to receiving waters, potentially causing impairment to the aquatic ecosystem of urban streams and downstream water bodies. Compositional changes in DOM due to storm events in forested, agricultural, and urban landscapes have been well studied, but in situ sensors have not been widely applied to monitor stormwater contributions in urbanized areas, leaving the spatial and temporal characteristics of DOM within these systems poorly understood. We deployed fluorescent DOM (FDOM) sensors at upstream and downstream locations within a study reach to characterize the spatial and temporal changes in DOM quantity and sources within an urban water conveyance that receives stormwater runoff. Baseflow FDOM decreased over the summer season as seasonal flows upstream transported less DOM. FDOM fluctuated diurnally, the amplitude of which also declined as the summer season progressed. During storms, FDOM concentrations were rapidly elevated to values orders of magnitude greater than baseflow measurements, with greater concentrations at the downstream monitoring site, revealing high contributions from stormwater outfalls between the two locations. Observations from custom, in situ fluorometers resembled results obtained using laboratory methods for identifying DOM source material and indicated that DOM transitioned to a more microbially derived composition as the summer season progressed, while stormwater contributions contributed DOM from terrestrial sources. Deployment of a mobile sensing platform during varying flow conditions captured spatial changes in DOM concentration and composition and revealed contributions of DOM from outfalls during stormflows that would have otherwise been unobserved.
KeywordsDissolved organic matter Urban Stormwater In situ Fluorescence Water quality
This work was supported by funding from the Utah Water Research Laboratory at Utah State University and from the US National Science Foundation under EPSCoR grant IIA-1208732 awarded to Utah State University as part of the State of Utah EPSCoR Research Infrastructure Improvement Award. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
- Carpenter, K. D., Kraus, T. E. C., Goldman, J. H., Saraceno, J. F., Downing, B. D., Bergamaschi, B. A., McGhee, G., & Triplett, T. (2013). Sources and characteristics of organic matter in the Clackamas River, Oregon, related to the gormation of disinfection by-products in treated drinking water. U.S. Geological Survey Scientific Investigations Report, 2013-5001, 78.Google Scholar
- Casper, A. F., Dixon, B., Steimle, E. T., Hall, M. L., & Conmy, R. N. (2012). Scales of heterogeneity of water quality in rivers: insights from high resolution maps based on integrated geospatial, sensor and ROV technologies. Applied Geography, 32, 455–464. https://doi.org/10.1016/j.apgeog.2011.01.023.CrossRefGoogle Scholar
- City of Grand Junction. (2016). Grand junction municipal code volume II: Development regulations; Title 28: stormwater management manual; Chapter 28.52: Irrigation/drainage structures. Grand Junction, Colorado. http://www.codepublishing.com/CO/GrandJunction/html2/GrandJunction28/GrandJunction2852.html#28.52. Accessed 8 February 2017.
- City of Logan. (2016). Storm water management plan. Logan, Utah. http://www.loganutah.org/SWMP%20Document%20Less%20Appendices_Final.pdf. Accessed 8 February 2017.
- City of Sequim. (2016). Storm and surface water master plan. Sequim, Washington. http://www.sequimwa.gov/DocumentCenter/View/7735. Accessed 8 Februrary 2017.
- Creed, I. F., McKnight, D. M., Pellerin, B. A., Green, M. B., Bergamaschi, B. A., Aiken, G. R., Burns, D. A., Findlay, S. E. G., Shanley, J. B., Striegl, R. G., Aulenbach, B. T., Clow, D. W., Laudon, H., Mcglynn, B. L., Mcguire, K. J., Smith, R. A., & Stackpoole, S. M. (2015). The river as a chemostat : fresh perspectives on dissolved organic matter flowing down the river continuum. Canadian Journal of Fisheries and Aquatic Sciences, 14, 1–14. https://doi.org/10.1139/cjfas-2014-0400.Google Scholar
- Downing, B. D., Pellerin, B. A., Bergamaschi, B. A., Saraceno, J. F., & Kraus, T. E. C. (2012). Seeing the light: the effects of particles, dissolved materials, and temperature on in situ measurements of DOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10, 767–775. https://doi.org/10.4319/lom.2012.10.767.CrossRefGoogle Scholar
- Dunbabin, M., & Grinham, A. (2010). Experimental evaluation of an autonomous surface vehicle for water quality and greenhouse gas emission monitoring. Paper presented at: IEEE International Conference on Robotics and Automation (ICRA). 5268–5274, May 3-8, Anchorage, AK, doi: https://doi.org/10.1109/ROBOT.2010.5509187.
- Fellman, J. B., Hood, E., Edwards, R. T., & D’Amore, D. V. (2009). Changes in the concentration, biodegradability, and fluorescent properties of dissolved organic matter during stormflows in coastal temperate watersheds. Journal of Geophysical Research, 114, G01021. https://doi.org/10.1029/2008JG000790.CrossRefGoogle Scholar
- Gabor, R. S., Baker, A., McKnight, D. M., & Miller, M. P. (2014). Fluorescence indices and their interpretation. In P. G. Coble, J. Lead, A. Baker, D. M. Reynolds, & R. G. M. Spencer (Eds.), Aquatic organic matter fluorescence, Cambridge environmental chemistry series (pp. 303–338). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139045452.015.CrossRefGoogle Scholar
- Kaiser, K., Guggenberger, G., & Haumaier, L. (2004). Changes in dissolved lignin-derived phenols, neutral sugars, uronic acids, and amino sugars with depth in forested Haplic Arenosols and Rendzic Leptosols. Biogeochemistry, 70, 135–151. https://doi.org/10.1023/B:BIOG.0000049340.77963.18.CrossRefGoogle Scholar
- Keith, M. K., Sobieszczyk, S., Goldman, J. H., & Rounds, S. A. (2014). Investigating organic matter in Fanno Creek, Oregon, part 2 of 3: identifying and quantifying sources of organic matter to an urban stream. Journal of Hydrology, 519, 3010–3027. https://doi.org/10.1016/j.jhydrol.2014.07.027.CrossRefGoogle Scholar
- Low, K. H., Podnar, G., Stancliff, S., Dolan, J. M., & Elfes, A. (2009). Robot boats as a mobile aquatic sensor network. Paper presented at: Workshop on Sensor Networks for Earth and Space Science Applications (ESSA), Apr. 16, San Francisco, CA.Google Scholar
- Lundquist, J. D., & Cayan, D. R. (2002). Seasonal and spatial patterns in diurnal cycles in streamflow in the Western United States. Journal of Hydrometeorology, 3, 591–603. https://doi.org/10.1175/1525-7541(2002)003<0591:SASPID>2.0.CO;2.CrossRefGoogle Scholar
- McKnight, D. M., Boyer, E. W., Westerhoff, P. K., Doran, P. T., Kulbe, T., & Andersen, D. T. (2001). Spectrofluorometric characterization of dissolved organic matter for indication of precursor organic material and aromaticity. Limnology and Oceanography, 46, 38–48. https://doi.org/10.4319/lo.2001.46.1.0038.CrossRefGoogle Scholar
- Mihalevich, B. A., & Horsburgh, J. S. (2017a). Grab sample data for dissolved organic matter study in the northwest field canal. Logan: HydroShare. https://doi.org/10.4211/hs.a3a9ba772aac4cba9533b35bb6b5fe42
- Mihalevich, B. A., & Horsburgh, J. S. (2017b). Mobile sensing platform data for dissolved organic matter study in the northwest field canal. Logan: HydroShare. https://doi.org/10.4211/hs.6711ca843bcc4834b51288a3ddc3aa08
- Mihalevich, B. A., Horsburgh, J. S., & Melcher, A. A. (2017). Time series data for dissolved organic matter study in the northwest field canal. Logan: HydroShare. https://doi.org/10.4211/hs.c1be74eeea614d65a29a185a66a7552f
- Paul, M. J., & Meyer, J. L. (2001). Streams in the urban landscape. Annual Review of Ecology and Systematics, 32, 333–365. https://doi.org/10.1146/annurev.ecolsys.32.081501.114040.CrossRefGoogle Scholar
- Pellerin, B. A., Saraceno, J. F., Shanley, J. B., Sebestyen, S. D., Aiken, G. R., Wollheim, W. M., & Bergamaschi, B. A. (2012). Taking the pulse of snowmelt: In situ sensors reveal seasonal, event and diurnal patterns of nitrate and dissolved organic matter variability in an upland forest stream. Biogeochemistry, 108, 183–198. https://doi.org/10.1007/s10533-011-9589-8.CrossRefGoogle Scholar
- Podnar, G., Dolan, J. M., Low, K. H., & Elfes, A. (2010). Telesupervised remote surface water quality sensing, paper presented at: IEEE Aerospace Conference, 1–9. Mar. 6-13, Big Sky, MT, doi: https://doi.org/10.1109/AERO.2010.5446668.
- Saraceno, J. F., Pellerin, B. A., Downing, B. D., Boss, E., Bachand, P. A. M., & Bergamaschi, B. A. (2009). High-frequency in situ optical measurements during a storm event: assessing relationships between dissolved organic matter, sediment concentrations, and hydrologic processes. Journal of Geophysical Research, 114, G00F09. https://doi.org/10.1029/2009JG000989.CrossRefGoogle Scholar
- Saraceno, J. F., Shanley, J. B., & Aulenbach, B. (2016). Multi-site field verification of laboratory derived FDOM sensor corrections: the good, the bad and the ugly. Abstract H11B-087 presented at: 49th Annual AGU Fall Meeting, Dec. 12-16, San Francisco, CA.Google Scholar
- Saraceno, J. F., Shanley, J. B., Downing, B. D., & Pellerin, B. A. (2017). Clearing the waters: evaluating the need for site-specific field fluorescence corrections based on turbidity measurements. Limnology and Oceanography: Methods, 15, 408–416. https://doi.org/10.1002/lom3.10175.CrossRefGoogle Scholar
- Spencer, R. G. M., Pellerin, B. A., Bergamaschi, B. A., Downing, B. D., Kraus, T. E. C., Smart, D. R., Dahlgren, R. A., & Hernes, P. J. (2007). Diurnal variability in riverine dissolved organic matter composition determined by in situ optical measurement in the San Joaquin River (California, USA). Hydrological Processes, 21, 3181–3189. https://doi.org/10.1002/hyp.6887.CrossRefGoogle Scholar
- U.S. Census Bureau, Population Division (2016). Annual estimates of the resident population: April 1, 2010 to July 1, 2015. https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk. Accessed 26 April 2017.
- Utah Depatment of Environmental Quality, Division of Water Quality (2004). Utah’s 2004 303(d) list of impaired waters, Salt Lake City, UT.Google Scholar
- Utah Depatment of Environmental Quality, Division of Water Quality (2010). Middle Bear River and cutler reservoir total maximum daily load (TMDL), Salt Lake City, UT.Google Scholar
- iUTAH GAMUT Working Group (2017a). iUTAH GAMUT Network Quality Control Level 1 Data at Climate Station at Logan River Golf Course (LR_GC_C), HydroShare, http://www.hydroshare.org/resource/86a27290e1b443a488f0b84cb9e2af91.
- iUTAH GAMUT Working Group (2017b). iUTAH GAMUT Network Quality Control Level 1 Data at Logan River at the Utah Water Research Laboratory west bridge (LR_WaterLab_AA), HydroShare, http://www.hydroshare.org/resource/1b87fe7452624e82a54fa57432b17583.
- Utah Office of Administrative Rules (2017). R317–2. Standards of quality for waters of the state. Salt Lake City, UT.Google Scholar