Turbidity and suspended sediment relationship based on sediment composition and particle size distribution.

Jongmin Kim, Siyoon Kwon, Sewoong Chung, Young Do Kim

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jongmin KimDepartment of Civil and Environmental Engineering, Myongji University, 116 Myeongji-ro, Cheoin-gu, Yongin, Gyeonggi, South Korea.

Siyoon KwonDepartment of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, South Korea.

Sewoong ChungDepartment of Environmental Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju, Chungcheongbuk, South Korea.

Young Do KimDepartment of Civil and Environmental Engineering, Myongji University, 116 Myeongji-ro, Cheoin-gu, Yongin, Gyeonggi, South Korea. ydkim@mju.ac.kr.

Funding

Korea Environmental Industry and Technology Institute 2021003030004

6 · The paper itself

Abstract

High turbidity in rivers, intensified by extreme rainfall associated with climate change, poses a great challenge to water resource management globally. To manage and control turbidity events, prediction models have been developed utilizing suspended sediment (SS) data. However, traditional methods for measuring SS data, such as water sampling and laboratory analysis, are time-consuming and impractical for real-time applications. Although the turbidity-SS relationship is widely used, its accuracy depends on sediment particle size distribution. To address this limitation, we developed turbidity-SS equations adaptive to various SS fractions, using data from controlled circulating flume experiments designed to reflect sediment characteristics of a natural river. The results showed significant improvements in the linear turbidity-SS relationship, with R

Indexed as

Particle size distributionSediment fractionsSuspended sedimentTurbidityTurbidity–SS relationship

Identifiers

PMID40348788

DOI10.1016/j.advwatres.2021.104076

PMCPMC12065833

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

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.