Evidence map›Paper›PMID 41820544›Full record

ArticleScientific reports2026

High-frequency turbidity by sensors as a proxy for total phosphorus: implications of sampling strategies on the water framework directive classification.

Eva Skarbøvik, Anastasija Isidorova, Maria Kämäri, Pasi Valkama, Sofie G M Van't Veen, Emma E Lannergård, Jens Fölster, Brian Kronvang

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Eva SkarbøvikDivision of Environment and Natural Resources, Norwegian Institute of Bioeconomy Research (NIBIO), P.O. Box 115, Ås, 1431, Norway. eva.skarbovik@nibio.no.
Anastasija IsidorovaDivision of Environment and Natural Resources, Norwegian Institute of Bioeconomy Research (NIBIO), P.O. Box 115, Ås, 1431, Norway.
Maria KämäriFinnish Environment Institute (Syke), Marine and freshwater solutions, Latokartanonkaari, 11, Helsinki, 00790, Finland.
Pasi ValkamaFinnish Environment Institute (Syke), Marine and freshwater solutions, Latokartanonkaari, 11, Helsinki, 00790, Finland.
Sofie G M Van't VeenDepartment of Ecoscience, Aarhus University, C.F. Møllers Allé, Aarhus C, Denmark and Envidan A/S, Vejlsøvej, 23, Silkeborg, 8600, Denmark.
Emma E LannergårdDepartment of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, PO Box 7050, Uppsala, 750 07, Sweden.
Jens FölsterDepartment of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, PO Box 7050, Uppsala, 750 07, Sweden.
Brian KronvangDepartment of Ecoscience, Aarhus University, C.F. Møllers Allé 3, Aarhus C, 8000, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mean concentrations of pollutants and nutrients are frequently used in the classification of water bodies under the European Commission Water Framework Directive. Turbidity can be used as a proxy for several particle-associated substances. We used three years of sensor turbidity data in each of 10 Nordic streams to assess the uncertainty in the annual arithmetic mean concentration of turbidity when sampling weekly, fortnightly, or monthly. On average, weekly sampling produced an uncertainty of 17±9% for all streams, whereas monthly sampling increased this to 40±19%. We then developed a multiple linear model that shows how the uncertainty in annual mean turbidity increases with decreasing sampling frequency, decreasing catchment size, and increasing proportion of agricultural land in the catchment. As an example, a river of 800 km2 catchment area and 20% agricultural land will need 29 samples a year to give a mean annual turbidity within 10% uncertainty, but a stream of 10 km2 catchment area and 80% agricultural land will need 95 samples to achieve the same uncertainty. Turbidity was a suitable proxy for total phosphorus in seven of the 10 streams. The range of the annual mean total phosphorus concentration was compared with the environmental objective (good water quality) in each river. The results highlight that when the estimated mean total phosphorus concentration is close to the concentration of the environmental objective, an infrequent sampling strategy can lead to false water quality classification. .

Indexed as

PhosphorusSampling frequencyStreamTurbidityUncertainty

Identifiers

PMID41820544
PMCPMC13106753

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.