Evidence map›Paper›PMID 39247256›Full record

ReviewHeliyon2024

Blockage at cross-drainage hydraulic structures - Advances, challenges and opportunities.

Umair Iqbal, Muhammad Zain Bin Riaz

Abstract readReview
In one paragraph

Review in Heliyon, 2024. 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

2 authors.

Umair IqbalSMART Infrastructure Facility, University of Wollongong, Wollongong, Australia.
Muhammad Zain Bin RiazSchool of Civil, Mining, Environmental and Architectural Engineering (SCMEA), University of Wollongong, Wollongong, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blockage of cross-drainage hydraulic structures is a significant concern in water resources and civil engineering projects, particularly in urban areas experiencing increased debris supply. During storms or floods, debris can accumulate and restrict the flow capacity of these structures, leading to potential failures and adverse impacts on flood levels. While some argue that blockage at culverts is a non-issue, scientific research supports its significance in specific regions. However, in context of rivers and dams, blockage by Large Wood (LW) is an established issue with plenty of research in terms of its hydraulic impacts, dynamics, modeling and scouring impacts. Specifically in Australasia the Australian Rainfall and Runoff (ARR) initiative recognized the importance of studying blockage at culverts and introduced guidelines incorporating it into design and modeling. These guidelines also included post flood visual inspections of structures to understand blockage, however, this approach has been criticized by hydraulic engineers arguing that post flood visuals can not be considered as the representation of the peak floods blockage. Recently, an approach of using visual information to interpret the blockage has been adopted as a new dimension to the problem. This paper, therefore, highlights the advances, challenges, and opportunities in studying blockage, emphasizing the need for data-driven approaches and interdisciplinary collaboration. Understanding and addressing blockage are crucial for ensuring the efficient operation and longevity of hydraulic structures and promoting the resilience of infrastructure systems in the face of evolving environmental conditions.

Indexed as

BlockageBridgesCulvertsFloodsLarge wood (LW)Pier scouring

Identifiers

PMID39247256
PMCPMC11379570

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.