An online tomographic sediment trap for high-resolution environmental monitoring.
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| Title: | An online tomographic sediment trap for high-resolution environmental monitoring. |
|---|---|
| Authors: | Johansson, Markus1 (AUTHOR) johansso@student.uef.fi, Saarni, Saija2 (AUTHOR) saija.saarni@utu.fi, Sorvari, Jouni3 (AUTHOR) jouni.sorvari@luke.fi |
| Source: | Environmental Monitoring & Assessment. Jun2026, Vol. 198 Issue 6, p1-17. 17p. |
| Subject Terms: | *Environmental monitoring, *Sediment transport, *Aquatic habitats, Optical tomography, Sediment sampling, Sediment analysis, Autonomous robots, Optical signal detection |
| Abstract: | Sediment trapping is a well-established method for obtaining information on sedimentation flux and composition in aquatic environments. Passive sediment traps typically have a collection period of several months to a year, while autonomous traps with revolving wheels can achieve a daily time resolution. However, these devices are often costly, require laborious maintenance, and have high power consumption, which limits their use in remote field locations. This study presents a novel, ultra-high-resolution (hourly temporal resolution) sediment trap based on optical tomography that enables continuous online monitoring of sediment flux. Laboratory validation demonstrated a high volumetric calibration accuracy, with a mean measurement error of ± 0.6 mL (R2 = 0.99). We deployed a prototype in Savilahti Bay, Kuopio, to evaluate its ability to detect short-term sediment pulses caused by onshore construction work. The field results confirmed the method's effectiveness and reliability in tracking highly dynamic flux variations, although image processing techniques require further development for extreme sedimentation rates. The autonomous, solar-powered system transmits data wirelessly, significantly reducing fieldwork requirements. This methodology provides a crucial tool for monitoring high-resolution sediment dynamics and remote study sites. [ABSTRACT FROM AUTHOR] |
| Copyright of Environmental Monitoring & Assessment is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 194723325 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An online tomographic sediment trap for high-resolution environmental monitoring. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Johansson%2C+Markus%22">Johansson, Markus</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> johansso@student.uef.fi</i><br /><searchLink fieldCode="AR" term="%22Saarni%2C+Saija%22">Saarni, Saija</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> saija.saarni@utu.fi</i><br /><searchLink fieldCode="AR" term="%22Sorvari%2C+Jouni%22">Sorvari, Jouni</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> jouni.sorvari@luke.fi</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Environmental+Monitoring+%26+Assessment%22">Environmental Monitoring & Assessment</searchLink>. Jun2026, Vol. 198 Issue 6, p1-17. 17p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Environmental+monitoring%22">Environmental monitoring</searchLink><br />*<searchLink fieldCode="DE" term="%22Sediment+transport%22">Sediment transport</searchLink><br />*<searchLink fieldCode="DE" term="%22Aquatic+habitats%22">Aquatic habitats</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+tomography%22">Optical tomography</searchLink><br /><searchLink fieldCode="DE" term="%22Sediment+sampling%22">Sediment sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Sediment+analysis%22">Sediment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Autonomous+robots%22">Autonomous robots</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+signal+detection%22">Optical signal detection</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Sediment trapping is a well-established method for obtaining information on sedimentation flux and composition in aquatic environments. Passive sediment traps typically have a collection period of several months to a year, while autonomous traps with revolving wheels can achieve a daily time resolution. However, these devices are often costly, require laborious maintenance, and have high power consumption, which limits their use in remote field locations. This study presents a novel, ultra-high-resolution (hourly temporal resolution) sediment trap based on optical tomography that enables continuous online monitoring of sediment flux. Laboratory validation demonstrated a high volumetric calibration accuracy, with a mean measurement error of ± 0.6 mL (R2 = 0.99). We deployed a prototype in Savilahti Bay, Kuopio, to evaluate its ability to detect short-term sediment pulses caused by onshore construction work. The field results confirmed the method's effectiveness and reliability in tracking highly dynamic flux variations, although image processing techniques require further development for extreme sedimentation rates. The autonomous, solar-powered system transmits data wirelessly, significantly reducing fieldwork requirements. This methodology provides a crucial tool for monitoring high-resolution sediment dynamics and remote study sites. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Environmental Monitoring & Assessment is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10661-026-15469-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 1 Subjects: – SubjectFull: Environmental monitoring Type: general – SubjectFull: Sediment transport Type: general – SubjectFull: Aquatic habitats Type: general – SubjectFull: Optical tomography Type: general – SubjectFull: Sediment sampling Type: general – SubjectFull: Sediment analysis Type: general – SubjectFull: Autonomous robots Type: general – SubjectFull: Optical signal detection Type: general Titles: – TitleFull: An online tomographic sediment trap for high-resolution environmental monitoring. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Johansson, Markus – PersonEntity: Name: NameFull: Saarni, Saija – PersonEntity: Name: NameFull: Sorvari, Jouni IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 01676369 Numbering: – Type: volume Value: 198 – Type: issue Value: 6 Titles: – TitleFull: Environmental Monitoring & Assessment Type: main |
| ResultId | 1 |
