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Sharing perceptual models of uncertainty: On the use of soft information about discharge data
IVL Swedish Environmental Research Institute Stockholm Sweden.ORCID iD: 0000-0002-9382-0782
IVL Swedish Environmental Research Institute Stockholm Sweden.ORCID iD: 0000-0002-3367-5077
2024 (English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 38, no 5Article in journal (Refereed) Published
Abstract [en]

There is often very limited information available about uncertainty in discharge data as it is rarely communicated by data providers. However, ‘soft’ information about station characteristics, climate and flow regime, and catchment characteristics can be used to understand the likelihood that discharge data in a particular location are uncertain. For example, if high flows are of short duration (i.e., a few hours) it is practically quite difficult to manage to gauge high flows, leading to likely extrapolation of stage–discharge rating curves and large high flow uncertainty.

The aim of this commentary is to share – and to encourage sharing – of soft information about data uncertainty sources, to promote more informed decisions on data uncertainty in hydrological studies. We summarize the soft information about discharge data uncertainty as a perceptual model of uncertainty. We find that soft information can inform us about three main types of uncertainty sources: uncertainty related to the hydraulic control, uncertainty related to incomplete gauging of the full flow range, and uncertainty due to measurement error. We believe that a key benefit of the type of generalized perceptual model of uncertainty we present is to facilitate dialogue on, and understanding of, possible sources of observational uncertainties and their impacts.  

Place, publisher, year, edition, pages
Stockholm: IVL Svenska Miljöinstitutet, 2024. Vol. 38, no 5
Keywords [en]
Discharge data; Data uncertainty; Rating curves; Perceptual model; Soft information
Keywords [sv]
Vattenföringsdata; Dataosäkerhet; Avbördningskurva; Perceptuell modell
National Category
Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:ivl:diva-4413DOI: 10.1002/hyp.15145Local ID: A2709OAI: oai:DiVA.org:ivl-4413DiVA, id: diva2:1894469
Funder
Swedish Research Council Formas, 2019‐01094
Note

A-rapport, A2709.

Available from: 2024-09-03 Created: 2024-09-03 Last updated: 2024-09-03

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Westerberg, Ida K.Karlsen, Reinert Huseby
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  • apa
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