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Adaptive measurements of urban runoff quality

dc.contributor.authorWong, Brandon P.
dc.contributor.authorKerkez, Branko
dc.date.accessioned2017-01-10T19:08:32Z
dc.date.available2018-01-08T19:47:53Zen
dc.date.issued2016-11
dc.identifier.citationWong, Brandon P.; Kerkez, Branko (2016). "Adaptive measurements of urban runoff quality." Water Resources Research 52(11): 8986-9000.
dc.identifier.issn0043-1397
dc.identifier.issn1944-7973
dc.identifier.urihttps://hdl.handle.net/2027.42/135503
dc.description.abstractAn approach to adaptively measure runoff water quality dynamics is introduced, focusing specifically on characterizing the timing and magnitude of urban pollutographs. Rather than relying on a static schedule or flow‐weighted sampling, which can miss important water quality dynamics if parameterized inadequately, novel Internet‐enabled sensor nodes are used to autonomously adapt their measurement frequency to real‐time weather forecasts and hydrologic conditions. This dynamic approach has the potential to significantly improve the use of constrained experimental resources, such as automated grab samplers, which continue to provide a strong alternative to sampling water quality dynamics when in situ sensors are not available. Compared to conventional flow‐weighted or time‐weighted sampling schemes, which rely on preset thresholds, a major benefit of the approach is the ability to dynamically adapt to features of an underlying hydrologic signal. A 28 km2 urban watershed was studied to characterize concentrations of total suspended solids (TSS) and total phosphorus. Water quality samples were autonomously triggered in response to features in the underlying hydrograph and real‐time weather forecasts. The study watershed did not exhibit a strong first flush and intraevent concentration variability was driven by flow acceleration, wherein the largest loadings of TSS and total phosphorus corresponded with the steepest rising limbs of the storm hydrograph. The scalability of the proposed method is discussed in the context of larger sensor network deployments, as well the potential to improving control of urban water quality.Key PointsAn Internet‐enabled sensor node autonomously adapts to weather forecasts and hydrograph features to collect water quality samplesFirst flush was not observed and peak loadings were primarily driven by erosion and flashinessCompared to present methods, our framework significantly reduces manpower and resource requirements in the study of water quality dynamics
dc.publisherWiley Periodicals, Inc.
dc.publisherIsl. Press
dc.subject.otherautomated sampling
dc.subject.otherurban stream
dc.subject.otherstorm water
dc.subject.othersensors
dc.subject.otherreal‐time measurements
dc.subject.otheradaptive sampling
dc.subject.otherfirst flush
dc.subject.othernutrients
dc.titleAdaptive measurements of urban runoff quality
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelNatural Resources and Environment
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/135503/1/wrcr22370.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/135503/2/wrcr22370_am.pdf
dc.identifier.doi10.1002/2015WR018013
dc.identifier.sourceWater Resources Research
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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