Sampling frequency for water quality variables in streams: Systems analysis to quantify minimum monitoring rates. (15th October 2017)
- Record Type:
- Journal Article
- Title:
- Sampling frequency for water quality variables in streams: Systems analysis to quantify minimum monitoring rates. (15th October 2017)
- Main Title:
- Sampling frequency for water quality variables in streams: Systems analysis to quantify minimum monitoring rates
- Authors:
- Chappell, Nick A.
Jones, Timothy D.
Tych, Wlodek - Abstract:
- Abstract: Insufficient temporal monitoring of water quality in streams or engineered drains alters the apparent shape of storm chemographs, resulting in shifted model parameterisations and changed interpretations of solute sources that have produced episodes of poor water quality. This so-called 'aliasing' phenomenon is poorly recognised in water research. Using advances in in-situ sensor technology it is now possible to monitor sufficiently frequently to avoid the onset of aliasing. A systems modelling procedure is presented allowing objective identification of sampling rates needed to avoid aliasing within strongly rainfall-driven chemical dynamics. In this study aliasing of storm chemograph shapes was quantified by changes in the time constant parameter ( TC ) of transfer functions. As a proportion of the original TC, the onset of aliasing varied between watersheds, ranging from 3.9–7.7 to 54–79 % TC (or 110–160 to 300–600 min). However, a minimum monitoring rate could be identified for all datasets if the modelling results were presented in the form of a new statistic, Δ TC. For the eight H +, DOC and NO3 -N datasets examined from a range of watershed settings, an empirically-derived threshold of 1.3(Δ TC ) could be used to quantify minimum monitoring rates within sampling protocols to avoid artefacts in subsequent data analysis. Graphical abstract: Image 1 Highlights: Systems analysis tool to help define monitoring strategies for stream water quality. Inadequate waterAbstract: Insufficient temporal monitoring of water quality in streams or engineered drains alters the apparent shape of storm chemographs, resulting in shifted model parameterisations and changed interpretations of solute sources that have produced episodes of poor water quality. This so-called 'aliasing' phenomenon is poorly recognised in water research. Using advances in in-situ sensor technology it is now possible to monitor sufficiently frequently to avoid the onset of aliasing. A systems modelling procedure is presented allowing objective identification of sampling rates needed to avoid aliasing within strongly rainfall-driven chemical dynamics. In this study aliasing of storm chemograph shapes was quantified by changes in the time constant parameter ( TC ) of transfer functions. As a proportion of the original TC, the onset of aliasing varied between watersheds, ranging from 3.9–7.7 to 54–79 % TC (or 110–160 to 300–600 min). However, a minimum monitoring rate could be identified for all datasets if the modelling results were presented in the form of a new statistic, Δ TC. For the eight H +, DOC and NO3 -N datasets examined from a range of watershed settings, an empirically-derived threshold of 1.3(Δ TC ) could be used to quantify minimum monitoring rates within sampling protocols to avoid artefacts in subsequent data analysis. Graphical abstract: Image 1 Highlights: Systems analysis tool to help define monitoring strategies for stream water quality. Inadequate water quality sampling introduces artefacts into process interpretations. Approach makes better use of high-frequency water quality sampling. Potential applicability to any rainfall-driven system (sewers, drains, groundwater). … (more)
- Is Part Of:
- Water research. Volume 123(2017)
- Journal:
- Water research
- Issue:
- Volume 123(2017)
- Issue Display:
- Volume 123, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 123
- Issue:
- 2017
- Issue Sort Value:
- 2017-0123-2017-0000
- Page Start:
- 49
- Page End:
- 57
- Publication Date:
- 2017-10-15
- Subjects:
- Monitoring -- Water quality -- In-situ measurement -- Aliasing -- System analysis
Water -- Pollution -- Research -- Periodicals
363.7394 - Journal URLs:
- http://catalog.hathitrust.org/api/volumes/oclc/1769499.html ↗
http://www.sciencedirect.com/science/journal/00431354 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.watres.2017.06.047 ↗
- Languages:
- English
- ISSNs:
- 0043-1354
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9273.400000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25118.xml