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Quality and timing of crowd-based water level class observations
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  • Simon Etter,
  • Barbara Strobl,
  • Ilja van Meerveld,
  • Jan Seibert
Simon Etter
University of Zurich Faculty of Science

Corresponding Author:simon.etter@outlook.com

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Barbara Strobl
University of Zurich Faculty of Science
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Ilja van Meerveld
University of Zurich Faculty of Science
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Jan Seibert
University of Zurich Faculty of Science
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Abstract

Crowd-based hydrological observations can supplement existing monitoring networks and allow data collection in regions where otherwise no data would be available. In the citizen science project CrowdWater, repeated water level observations using a virtual staff gauge approach result in time series of water level classes. To investigate the quality of these observations, we compared the water level class data for a number of locations where water levels were also measured and assessed when these observations were submitted. We analysed data for nine locations where citizen scientists reported multiple observations using a smartphone app and stream level data were also available. At twelve other locations, signposts were set up to ask citizens to record observations on a form that could be left in a letterbox. The results indicate that the quality of the data collected with the app was higher than for the forms. A possible explanation is that for each app location, most contributions were made by a single person, whereas at the locations of the forms almost every observation was made by a new contributor. On average, more contributions were made between May and September than during the other months. Observations were submitted for a range of flow conditions, with a higher fraction of high flow observations for the data collected with the app. Overall, the results are encouraging for citizen science approaches in hydrology and demonstrate that the smartphone application with its virtual staff gauge is a promising approach for crowd-based water level class observations.
20 Feb 2020Submitted to Hydrological Processes
21 Feb 2020Submission Checks Completed
21 Feb 2020Assigned to Editor
21 Feb 2020Reviewer(s) Assigned
16 Apr 2020Review(s) Completed, Editorial Evaluation Pending
16 Apr 2020Editorial Decision: Revise Major
29 May 20201st Revision Received
30 May 2020Submission Checks Completed
30 May 2020Assigned to Editor
30 May 2020Reviewer(s) Assigned
02 Jul 2020Review(s) Completed, Editorial Evaluation Pending
03 Jul 2020Editorial Decision: Accept