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Information content of stream level class data for hydrological model calibration
Univ Zurich, Dept Geog, Zurich, Switzerland..
Univ Zurich, Dept Geog, Zurich, Switzerland..
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Zurich, Dept Geog, Zurich, Switzerland..ORCID iD: 0000-0002-6314-2124
2017 (English)In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 21, no 9, p. 4895-4905Article in journal (Refereed) Published
Abstract [en]

Citizen science can provide spatially distributed data over large areas, including hydrological data. Stream levels are easier to measure than streamflow and are likely also observed more easily by citizen scientists than streamflow. However, the challenge with crowd based stream level data is that observations are taken at irregular time intervals and with a limited vertical resolution. The latter is especially the case at sites where no staff gauge is available and relative stream levels are observed based on (in) visible features in the stream, such as rocks. In order to assess the potential value of crowd based stream level observations for model calibration, we pretended that stream level observations were available at a limited vertical resolution by transferring streamflow data to stream level classes. A bucket-type hydrological model was calibrated with these hypothetical stream level class data and subsequently evaluated on the observed streamflow records. Our results indicate that stream level data can result in good streamflow simulations, even with a reduced vertical resolution of the observations. Time series of only two stream level classes, e.g. above or below a rock in the stream, were already informative, especially when the class boundary was chosen towards the highest stream levels. There was some added value in using up to five stream level classes, but there was hardly any improvement in model performance when using more level classes. These results are encouraging for citizen science projects and provide a basis for designing observation systems that collect data that are as informative as possible for deriving model based streamflow time series for previously ungauged basins.

Place, publisher, year, edition, pages
COPERNICUS GESELLSCHAFT MBH , 2017. Vol. 21, no 9, p. 4895-4905
National Category
Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-336473DOI: 10.5194/hess-21-4895-2017ISI: 000411889800005OAI: oai:DiVA.org:uu-336473DiVA, id: diva2:1168337
Available from: 2017-12-20 Created: 2017-12-20 Last updated: 2018-01-13Bibliographically approved

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