
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)11817-8
10.1016/j.heliyon.2024.e35786
e35786
Review Article
Blockage at cross-drainage hydraulic structures – Advances, challenges and opportunities
Iqbal Umair umair@uow.edu.au
a⁎
Riaz Muhammad Zain Bin b
a SMART Infrastructure Facility, University of Wollongong, Wollongong, Australia
b School of Civil, Mining, Environmental and Architectural Engineering (SCMEA), University of Wollongong, Wollongong, Australia
⁎ Corresponding author. umair@uow.edu.au
08 8 2024
30 8 2024
08 8 2024
10 16 e3578612 6 2023
9 7 2024
2 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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.

Keywords

Blockage
Large wood (LW)
Bridges
Culverts
Floods
Pier scouring
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pmc1 Introduction

Cross-drainage hydraulic structures serve as critical components in water resources and civil engineering projects, facilitating the flow of water across natural or artificial drainage channels while maintaining the integrity of the hydraulic system [1]. However, these structures often encounter blockage,1 which refers to the accumulation of debris2 that hinders the flow capacity of the structure, potentially leading to structural failure, flow diversion and downstream scouring (Fig. 1(a) and Fig. 1(b) show examples of flow diversion and structural failure, respectively) [3], [4], [5], [6], [7], [8], [9]. The impacts and consequences of blocked hydraulic structures during urban flooding events include increased damage to adjacent infrastructure due to overtopping and flow diversions, safety risks during post-flood culvert maintenance procedures, and elevated costs associated with post-flood debris removal [10].Figure 1 Examples of blockage Impacts [3], [4].

Figure 1

The presence of easily transportable debris within the stormwater network [4], [11] exacerbates the issue, resulting in heightened peak flood levels by obstructing drainage structures [5], [12]. This condition can have adverse effects on flood outcomes, both in straightforward ways, such as increased water levels upstream of the blockage (known as afflux), and in more complex ways, including the premature loss of storage in floodplains or basins, diversion of flows away from flood mitigation infrastructure, or redirection towards more vulnerable areas [6], [10], [13], [14]. Blockage is a dynamic process that can vary depending on local conditions and the severity of the event [4], [15]. Typical instances of blocked cross-drainage hydraulic structures are shown in Fig. 2(a)-(f).Figure 2 Typical examples of blockage at cross-drainage hydraulic structures [4], [13], [15].

Figure 2

There are two primary types of debris, namely floating and non-floating, that can lead to blockage in cross-drainage hydraulic structures. Floating debris can be categorized as small, medium, or large based on size. Small floating debris includes items like small trees, leaves, and small branches, typically measuring up to 150 mm. It is commonly found in both urban and rural catchments. Medium floating debris consists of larger tree limbs and twigs, ranging in size from greater than 150 mm to less than 3 m. Large floating debris comprises items such as tree logs, cars, and other urban debris exceeding 3 m in size. Non-floating debris mainly consists of sediment and gravel, further classified into fine sediment (0.004 mm to 8 mm), gravel/cobbles (4.75 mm to 300 mm), and boulders (larger than 300 mm) [4], [11], [14], [15].

The issue of blockage in cross-drainage hydraulic structures, specifically at culverts, is often considered insignificant by hydraulic design engineers worldwide. This perception stems from the belief that blockage at culverts does not have a significant or frequent impact on flooding. However, it is important to note that blockage of bridges by Large Wood (LW) in rivers is an established problem and well studied in terms of hydraulic impacts, transient motions, transportation and pier scouring [8], [9]. Further, for culverts, in specific geographic locations like certain sites in the United Kingdom and Australia, where there is a high availability of debris upstream, blockage has been identified as a significant factor in causing floods. In Australasian context, flood events in Wollongong [5], [10], [16], [17] and Newcastle [5], [18], have highlighted the role of culvert blockage as a major contributing factor. Blockage of cross-drainage hydraulic structures is regarded as a complex phenomenon due to its non-linear and uncertain nature in terms of debris accumulation at the structures and dependence on various local factors. This makes it a challenging problem for numerical modeling and forces to make various assumptions. Factors such as upstream water level, downstream water level, debris supply, channel characteristics, debris transport mechanisms, upstream channel slope, upstream discharge, flow velocity, and rainfall intensity are believed to play significant roles in understanding blockage behavior at cross-drainage hydraulic structures [4], [6], [10], [12], [14], [15].

In the context of studying blockage in cross-drainage hydraulic structures, there exist multiple interpretations in literature based on how the problem is addressed. One perspective emphasizes the hydraulic implications of blockage and its incorporation into design guidelines. Blockage is tagged as a local problem specific to certain regions where topographic factors and debris supply make it a significant issue. The contention here is that blockage becomes a significant concern when it leads to flooding beyond the capacity of the watercourse (i.e., non-existence of blockage problem). To assess the additional damage and incorporate blockage into design considerations, the hydraulic effects of blockage need to be quantified. In context to blockage by LW, many lab-scale studies, field investigations and numerical modeling studies have been performed in literature to study the blockage at bridges in rivers in terms of accumulation, transport, transient motions, pier scouring and upstream water rise [3], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33]. However, in the context of culverts, fewer studies were identified where researchers performed in-lab hydraulic experiments to study the blockage by vegetation, sediment and urban debris [1], [7], [25], [34]. Another viewpoint highlights the tangible obstruction caused by debris accumulation, contending that it diminishes the hydraulic capacity of the structure. This perspective is primarily based on post-flood visual examinations of hydraulic infrastructure with the presence of a significant amount of debris. It is argued that the regular maintenance and cleaning of structures based on visual inspections can reduce the likelihood of floods. However, apart from post-flood visual data, there is no recorded data or inquiry in the literature to support the argument. The evaluation of blockage through post-flood visual inspections is deemed inadequate for representing blockage during peak floods by many hydraulic engineers. A structure with the presence of a significant amount of debris post flood may have experienced the least hydraulic blockage during the peak floods because debris may have been floating on the surface. However, the settled-down debris after one flood session will result in a high blockage for the upcoming flood if not removed. Currently, no quantifiable relationship between visual interpretation and hydraulic impacts of blockage has been reported other than Iqbal et al. [35] where hydraulic blockage at culverts is predicted using the images.

The occurrence of blockage in cross-drainage hydraulic structures depends on several factors: the availability of debris within the catchment area, the processes by which debris is mobilized (e.g., storms, winds), the transportation of debris, and its interaction with the hydraulic structure. The combination of these factors determines the actual blockage condition of the hydraulic structure. For instance, the presence of abundant vegetation in the catchment does not necessarily guarantee blockage unless specific triggering events mobilize that vegetation [10], [15]. Understanding how debris interacts with cross-drainage hydraulic structures is crucial for estimating blockage. In terms of mobility, the lower density debris (e.g., small vegetation, medium tree branches) is likely to be moved easily in comparison to the higher density debris (e.g., urban debris, large tree logs) [22], [23], [36]. The lower density debris is prone to be moved even at lower flows and quickly arrive at the structure, however, is not considered as critical from blockage perspective as it either flushes away or overtops during peak flow. On the other hand, higher density debris is likely to mobilize only during the peak floods, however, blocks/damages the structure quickly with high impact. Post-flood images are likely to provide inaccurate information regarding blockage during low-energy flood flows, as most of the debris causing the blockage would have been flushed away by the receding floodwaters. Similarly, sediment blockage may result in high bed levels after the flooding event, but during peak floods, the sediment would have been flushed away [15]. Although there are studies in context to blockage by debris accumulation and their use for flood risk assessments [29], [30], [31], [33], [37], [38], [39], however, the lack of data collected from actual floods with blockage at cross-drainage hydraulic structures is a major obstacle to quantitatively estimate real flood risks associated with blockage. Ideally, blockage data should be collected during flood events by observing the hydraulic structures, but this practice is rarely feasible due to practical limitations such as low visibility, safety concerns, and the urgency of flood events.

Despite these challenges, numerous opportunities exist for further advancements. Research and development efforts should focus on exploring innovative solutions related to design and modeling of blockage phenomena. Data-driven approaches, utilizing analytics, machine learning, and artificial intelligence, hold promise in predicting and detecting blockage with greater accuracy, enabling proactive interventions. Embracing multi-disciplinary collaboration among civil engineers, hydrologists, ecologists, and environmental scientists is crucial to develop holistic solutions that consider both hydraulic performance and ecological considerations. Understanding and addressing blockage at cross-drainage hydraulic structures are vital for ensuring their efficient operation and longevity. By reviewing the advances, challenges, and opportunities associated with this topic, this paper aims to provide a comprehensive understanding of the current state-of-the-art, stimulate further research and innovation in this field.

2 Existing blockage policies in Australasia

Australia is among the countries adversely impacted by the floods originated from blockage of culverts and presents a unique use-case. This section summarises the culvert blockage related policies in Australia. In this context, many city councils and disaster management agencies have established codes to address blockage issues. However, there is a lack of mechanisms to deal with the broader impact of blockage on flooding and flow conditions.

The 1986 New South Wales (NSW) Flood Development Manual did not consider blockage a major concern in flood modeling and assumed that all cross-drainage hydraulic structures were clear. However, the 2005 iteration of the NSW Flood Management Manual introduced blockage as a factor in flood modeling. Similarly, the Queensland Urban Drainage Manual emphasized the inclusion of hydraulic blockage in modeling and design but did not provide specific guidelines in this regard. The Wollongong City Council (WCC) stands out for introducing the “Conduit Blockage Policy” in 2002 following the 1998 flood event under the Australian Rainfall and Runoff (ARR) initiative “Project 11: Blockage of Hydraulic Structures,” [4]. According to this policy, all cross-drainage hydraulic structures with an opening of less than 6 meters are considered 100% blocked, while structures with an opening larger than 6 meters are considered 25% bottom-up blocked. Additionally, if handrails over the structures are covered during overtopping, it is considered 100% blockage [4], [5], [12].

Jones et al. [15] reviewed the existing WCC Conduit Blockage Policy and conducted a probabilistic analysis using historical records to revise the policy. They performed stochastic modeling for 20 selected locations in the Wollongong area of NSW, Australia, and investigated the joint probability of rainfall Annual Exceedance Probability (AEP) and the likelihood of blockage. From their analysis, Jones et al. [15] observed that blockage was overestimated for some locations. They also emphasized that for smaller AEP events, there is likely to be no blockage since debris material is not mobilized. However, they were unable to establish a concrete relationship between hydraulic blockage and other relevant factors such as location, debris type, debris mobility, land use, and debris availability due to limited data availability. Nevertheless, they found instances where blockage was highly probable due to factors such as smaller openings, the availability of vegetation debris upstream, and steeper upstream flow. Table 1 provides classification data of culverts based on their opening size.Table 1 Classification of cross-drainage hydraulic structures (i.e., culverts) based on opening sizes [15].

Table 1	Pipe Culvert	Boxed Culvert	
(Internal Diameter)	(Diagonal Opening)	
Class 1	≤1.2 Image 1	<1.5 Image 1	
Class 2	>1.2 Image 1	>1.5 Image 1 and <3 Image 1	
Class 3	–	>3 Image 1 and <6 Image 1	
Class 4	–	≥6 Image 1	

Although these analyses have improved the blockage policy, limitations are still evident due to the lack of concrete relationships to understand blockage behavior. The revised blockage policy, based on probabilistic results, is presented in Table 2. The current blockage guidelines provided by ARR are not adaptive and are based on a constant opening size for hydraulic structures. However, considering the highly complex and non-linear nature of hydraulic blockage, it is anticipated that blockage management guidelines should be adaptive. This aspect requires detailed exploration through laboratory-scale investigations and monitoring of structures during real-world flood events. By conducting such studies, a better understanding of blockage behavior can be achieved, leading to the development of more effective and adaptive blockage management guidelines.Table 2 Revised blockage policy proposed by Jones et al. [15].

Table 2Design AEP	Percentage Blockage	
Class 1	Class 2	Class 3	Class 4	
20% or more frequent	35%	25%	15%	0%	
Rarer than 20% and frequent than 2%	50%	40%	30%	5%	
2% or greater	70%	50%	40%	10%	

3 Current blockage management practices

Efficient management of debris is crucial for the proper operation of cross-drainage hydraulic structures. Two approaches are commonly followed: reactive measures and proactive measures. The reactive approach involves cleaning the hydraulic structures before and after potential flooding events to prevent blockage. A register is maintained, categorizing sites based on their perceived risk or vulnerability to blockage. High-risk sites are regularly cleaned, usually monthly, as well as before and after potential flooding events. However, this approach is criticized by the local community due to its limited effectiveness and the increasing awareness of the importance of blockage [3]. Usually, following activities are performed under this approach• Visual Inspections: Conducting routine visual inspections of hydraulic structures to identify any signs of blockage, including accumulation of debris or vegetation growth.

• Remote Monitoring: Using remote monitoring systems, such as sensors or cameras, to continuously monitor the condition of hydraulic structures and detect any blockage issues.

• Debris Removal: Regularly removing accumulated debris from hydraulic structures to ensure their unobstructed flow capacity. This may involve manual cleaning or the use of equipment, such as debris removal vehicles or water jets.

• Vegetation Management: Controlling vegetation growth near hydraulic structures to prevent blockage caused by overhanging branches or root systems.

• Sediment Removal: Periodically removing sediment that may accumulate in the hydraulic structures, as it can contribute to blockage issues.

In a proactive approach, debris control structures are constructed based on available data and established best practices. Various structures can be used for culverts, including debris deflectors, debris risers, debris fins, and debris racks [3].• Debris deflectors are V-shaped structures installed at the culvert opening to redirect incoming debris away from the opening (see Fig. 3(a) for steel rail debris deflector and Fig. 3(b) for steel rail and cable debris deflector). The apex angle of the deflector should typically be between 15 and 25 degrees, and the area on both sides of the culvert should be at least ten times the area of the culvert opening. Horizontal and vertical members can be added to allow smaller debris to pass through while deflecting larger debris that has a higher potential for blocking the opening.Figure 3 Examples of debris deflectors [3].

Figure 3

• Debris racks are vertical structures placed across the stream channel to collect debris before it reaches the culvert opening. They can also be installed at the entrance of a culvert to trap debris (see Fig. 4(a) for hinged steel debris rack and Fig. 4(b) for steel grill debris rack at slope). The spacing between the racks can be customized based on the culvert opening size, as it serves as a filter to allow only debris smaller than the specified size to pass through. The spacing is typically set at 6 inches to prevent children from entering the culvert.Figure 4 Examples of debris racks [3].

Figure 4

• Debris risers serve as enclosed structures positioned directly above the culvert inlet to induce the accumulation of debris and fine particles, preventing them from reaching the culvert inlet (see Fig. 5(a) for metal pipe debris riser and Fig. 5(b) for combined concrete fin with metal pipe debris riser). Typically constructed using metal pipes, these risers can also function as emergency outlets in situations where the entrance is entirely obstructed by debris.Figure 5 Examples of debris risers [3].

Figure 5

• Debris fins are extended walls inside the culvert that aim to realign incoming debris, allowing it to pass through the culvert opening (see Fig. 6(a) for concrete debris fin with slopping and Fig. 6(b) for timber debris fin with slopping). These walls are sloped and are recommended for larger culverts with openings greater than 4 feet. Implementing these proactive measures can help manage debris effectively and reduce the risk of blockage in hydraulic structures.Figure 6 Examples of debris fins [3].

Figure 6

In addition, emergency response and public awareness activities are also commonly practiced across few countries. In emergency response, aim is to quickly assess the situation, and remove the blocking debris to avoid to drastic situation [3]. Emergency response usually involves following activities:• Rapid Assessment: Having protocols in place to quickly assess blockage during flood events or extreme weather conditions.

• Mitigation Measures: Implementing temporary measures, such as bypass channels or pumps, to redirect water flow and alleviate blockage impacts.

• Debris Removal Teams: Mobilizing trained personnel and equipment for prompt debris removal in case of blockage emergencies.

On the other hand, public awareness and education involves following activities:• Public Outreach: Conducting awareness campaigns to educate the public about the importance of proper waste disposal and the potential consequences of blockage on the hydraulic system.

• Reporting Systems: Establishing mechanisms for the public to report blockage incidents or potential hazards, enabling timely response and intervention.

4 Advances in blockage management research

The literature on innovative solutions for addressing the blockage of cross-drainage hydraulic structures and its impact on floods is limited due to the scarcity of data available for interpreting debris behavior during flooding events. However, a few notable studies have made efforts to scientifically investigate the issue of hydraulic blockage. Here, I present a chronological systematic review of the most relevant studies, highlighting the advancements made in studying blockage at cross-drainage hydraulic structures.

4.1 Review methodology

The reported systematic review is carried using the standard PRISMA guidelines as used by Kitchenham et al. [40], [41] and Kankanamge et al. [42]. As a review protocol, followings steps were used: (a) research questions formulation (b) definition of keywords (c) identification of research databases (d) formulation of exclusion/inclusion criteria (e) review of selected literature. The main research question explored in this manuscript was “What are the different ways by which blockage at cross-drainage hydraulic structures is addressed in literature?” A list of keywords relevant to research question was formulated including “blockage”, “debris”, “cross-drainage hydraulic structures”, “culvert”, “bridges”, “gravel debris”, “vegetation”, “urban debris”, “large wood”, “stream wood”, “drift wood”, “clogging”, “woody material”, “sediment”. Different combinations of these keywords were searched on IEEEXplore, ScienceDirect and Web of Science (WoS) to extract the relevant literature in regards to blockage at cross-drainage hydraulic structures. As a result, total of 1637 literature entries were found with 523 from IEEEXplore, 394 from ScienceDirect and 720 from WoS. An inclusion/exclusion criteria was defined as follows to filter and refine the extracted literature:• Only English language literature entries were included.

• Only journal articles, conference articles, theses and technical reports were considered.

• Only literature entries published between 1990 - 2023 were considered.

• Duplicate entries across the databases were removed.

In addition to the defined criteria, remaining literature was screen through multiple stages of title screening, abstract screening and full text assessment. In the end, only 51 unique literature entries were included in the review and were subjectively discussed in detail. The PRISMA flow diagram for the presented systematic review is given in Fig. 7.Figure 7 PRISMA flow diagram for the presented systematic review.

Figure 7

4.2 Review of identified literature

This section presents the summary of literature in context to blockage at cross-drainage hydraulic studies. The literature includes the works related blockage by LW/vegetation, urban debris, sediment and hybrid debris. The literature is organized in chronological order to better understand the advancements over time.

Bruce et al. [19] in 1992 investigated pier scour with debris accumulation, highlighting that rivers often carry substantial floating debris during floods, leading to the formation of debris rafts around bridge piers. The accumulated debris obstructs flow, causing scour depths exceeding those without debris. While prior research extensively studied local scour at bridge piers, the quantitative impact of debris rafting was largely unexplored. To address the challenge of estimating scour depth with floating debris, the study proposed a method to determine the effective pier diameter for computing local scour depth. Despite the difficulty in predicting debris raft size, the paper emphasized the importance of measuring and documenting debris characteristics on bridges. The study recommended the use of the effective pier diameter in the local scour equation for conservative predictions, contributing valuable insights into the comprehension and management of pier scour with debris accumulation. In 1995, Shields et al. [27] introduced a straightforward method to predict the impact of woody debris removal on flow resistance in river channels. The technique involves determining the density of debris through measurements or visual estimations of cross-sectional debris formations perpendicular to flow. The Darcy-Weisbach friction factor, a vital parameter for assessing flow resistance, is then computed using the determined debris density, channel geometry, and the debris drag coefficient, which can be obtained from a power function with experimentally derived coefficients. To validate the proposed approach, the researchers measured debris density and friction factors in river reaches in western Tennessee and southeastern NSW, Australia. The computed friction factors closely approximated the measured values, within 30% for straight, sand-bed reaches, and within 38% for sinuous, gravel-bed reaches, effectively explaining 84% of the observed variance. While the method provides a valuable first-order approximation, it simplifies the intricate non-uniform flow often associated with woody debris structures. Notably, the procedure allows for the estimation of the effects of debris removal, leading to a notable decrease in the Darcy-Weisbach friction factor for near-bank-top conditions and an increase in bank-top flow capacity. The developed technique facilitated the estimation of friction factors for both straight, sand-bed, and sinuous, gravel-bed channels, with the estimates closely aligning with measured values, within 15% and 38% respectively. However, the authors highlighted the need for site-specific adaptations to account for resistance components not considered in the model, such as bridges.

Braudrick et al. [20] in 2001 investigated the dynamics of LW debris transport and deposition in streams, focusing on the interactions among hydraulics, channel geometry, transport distance, and wood deposition. Their experiments in a gravel bed flume revealed that floating wood pieces tend to align themselves parallel to the flow and are deposited primarily where the channel depth is less than the buoyant depth. The researchers proposed a debris roughness model, considering the ratios of piece length and diameter to channel width, depth, and sinuosity, to predict wood transport efficiency under various channel geometries. They found that the transport distance of logs is influenced by the ratio of piece length to both channel width and radius of curvature, but this relationship varied with different channel planforms. Interestingly, the proportion of the channel area where flow depth exceeds buoyant depth appeared to be more critical than the average depth in determining the distance traveled and retention of wood pieces. The study also highlighted the significance of considering the frequency of potential deposition sites in understanding the movement of large wood debris. While recognizing the complexity of wood transport, their research emphasized the development of simplified physical models to describe the movement of individual pieces and their deposition patterns. In their 2002 study, Gurnell et al. [28] delved into the significance of LW in woodland river ecosystems, highlighting the complex relationship between LW and the physical attributes of river systems, which are heavily influenced by factors such as tree species, climatic and hydrological conditions, and river and woodland management practices. Over the past 25 years, research on LW and its interaction with fluvial processes has concentrated on its impact on flow hydraulics, sediment transfer, and river channel geomorphology. The authors introduced a conceptual framework that categorizes rivers into “Small,” “Medium,” and “Large” based on their width relative to the dimensions of the wood pieces, thereby establishing how hydrological characteristics, wood characteristics, and geomorphological features play differing roles in these distinct river categories. They emphasized the critical role of wood properties like length, diameter, buoyancy, and ability to sprout, along with the influence of wood supply, in determining wood dynamics and storage within river systems. Furthermore, they underscored the substantial impact of fluvial processes, such as flow regime, slope, sediment availability, and water depth, on the dynamics and storage of wood in rivers of various sizes.

Rigby et al. [10] in 2002 found that the size of the structure's clear opening is the primary factor in determining the degree of blockage. Culverts or bridge openings larger than approximately 6 meters are unlikely to block, and if blockage occurs, it is likely to be partial. On the other hand, culverts with openings less than 6 meters are prone to blockage, with the data collected during the storm indicating a full range of blockage scenarios, from unblocked to complete blockage. The consequences of culvert blockage on catchment flooding are discussed, including increased flood levels, diversion of flow out of streams, the formation of unexpected overland flood flowpaths, and scouring of overtopped embankments. These considerations are crucial in conducting flood studies and evaluating the potential impacts of culvert blockage on flood events. Abbe et al. [43] in 2003 conducted an extensive study in the Queets river basin, exploring the accumulation patterns and processes of wood debris in forested mountain river networks. Through field surveys and historical data, they identified ten distinctive wood debris accumulation types categorized based on recruitment modes and the orientation of key, racked, and loose debris in relation to the channel axis. These accumulations, including stable in-stream structures, were found to significantly impact alluvial morphology and the development of the riparian ecosystem. The research presented a classification system for wood debris accumulations that can potentially be applied to other forested mountain regions, emphasizing the influence of local forest conditions, physical processes, and valley-bottom physiography on the development and subsequent effects of these accumulations. They highlighted the importance of understanding the processes governing the recruitment, transport, and deposition of wood debris, which are contingent on various factors such as wood size and shape, channel morphology, and their locations within the channel network. Notably, the study underscored the significant geomorphic consequences of altering the supply of large and stable wood debris, offering insights into how landscape disturbances and changes might impact wood debris jams and forested river systems.

In 2003, Lyn et al. [44] conducted an extensive study focusing on the accumulation of LW debris at bridge piers, a recurring and often severe issue at various bridge crossings in Indiana. The research encompassed both laboratory experiments and field studies, examining the underlying factors contributing to the initiation and development of such debris accumulations. The laboratory component, conducted in a rectangular channel with a model pier, demonstrated a notable influence of local depth on debris accumulation, indicating a higher likelihood of accumulation in shallower flow regions. The field study, involving video monitoring at two sites, provided qualitative insights into debris movement during flow events and the effectiveness of debris deflectors. Findings suggested that stable debris piles tend to form at lower flow velocities and are more likely to develop in shallower flow regions. Additionally, the study explored the impact of potential countermeasures, such as debris deflectors and groin-like structures, observing mixed results in their performance. While the laboratory experiments indicated the development of debris piles at the model deflector, the field observations pointed to the instability of debris piles at the deflectors, potentially due to the complex channel geometry and flow dynamics. The research highlighted the intermittent nature of debris transport during flow events, with debris accumulation often initiated early and reaching a substantial size before the hydrograph peak. The study concluded that the currently installed deflectors were more likely to trap rather than deflect debris, emphasizing the limitations of these measures in managing debris accumulation at bridge crossings. In 2004, Moulin et al. [45] conducted a comprehensive study focusing on the characteristics and temporal variability of LW debris trapped in a reservoir. Highlighting the significance of woody debris as a structural element in river systems, the study emphasized its role in providing habitats for aquatic communities and the potential risks it poses to infrastructure and flooding. In an effort to strike a balance between preserving and reintroducing woody debris for ecological benefits, and the necessity for channel clearance for risk management, the research aimed to understand the residence time and transport dynamics of woody debris in regulated rivers. Utilizing reservoirs as a key analytical context, the study aimed to determine the geographical origin and temporal variations of the trapped woody debris concerning the flow regime. The investigation focused on the Genissiat dam on the upper Rhone river in France, where the findings revealed that wood input escalated with flood frequency, contingent upon the position of the flood event in the hydrological series. The study also provided a qualitative description of the extracted wood, indicating its origin and characteristic alterations, including the impact of physical breakage in high-energy rivers. Overall, the research underscored the significance of examining dead wood dynamics from a drainage basin perspective, offering insights valuable for both scientific inquiry and effective river management strategies. The study outlined the potential for leveraging the concept of an ‘observation window’ in assessing wood transit volumes, leading to a better understanding of the complex interplay between flood characteristics and the quality and quantity of exported wood. The findings presented important questions concerning the effectiveness of riverbank clearance, the influence of different flood origins and meteorological factors on wood morphology, and the necessity for more frequent and precise extraction intervals to establish clearer associations between extracted wood and the responsible flood events.

In their 2007 flume experiment, Bocchiola et al. [21] investigated the dynamics of LW debris jams in complex stream environments, simulating scenarios where non-rooted, defoliated LW interacted with obstacles in the channel. By inserting numerous wood dowels into the flume, they mapped the final positions of the dowels and classified resulting jams based on size and position. The study revealed that longer dowels and shallower water led to shorter travel distances, while congested transport allowed wood pieces to travel farther. Statistical analyses indicated that the traveled distance of wood pieces followed a Gamma distribution, while jams displayed a Uniform pattern. The study underscored the complexity of wood jam formation, suggesting a combination of deterministic mechanisms and random factors, and highlighted the need for further research to incorporate more complex LW geometry, sediment load presence, and the study of accumulation processes in streams with varying configurations. In 2007, Lyn et al. [46] conducted a comprehensive investigation into the factors contributing to debris accumulation at bridge piers, a persistent issue affecting numerous bridge sites in Indiana. By employing a multifaceted approach, including the analysis of underwater bridge inspection reports, regular site visits, and video monitoring, the study aimed to identify key factors influencing debris accumulation and subsequently develop design guidelines for mitigating its impact. The research revealed that approximately 20% of the surveyed sites experienced significant debris accumulation, with the most severe cases concentrated in the southwestern region of the state, typically occurring at single piers. The persistence of accumulation at specific piers, the lack of strong correlation between the thalweg location and accumulation points, and the impact of nearby bank proximity, islands, and lateral channel expansions all suggested that the accumulation process is influenced by localized factors rather than random occurrences. Additionally, the study noted that longer bridge spans were associated with less frequent and more substantial debris accumulations compared to shorter spans. Furthermore, the research highlighted the temporal aspects of debris transport, with the heaviest transport occurring during the initial rising phase of the hydrograph and often well before the flow peak in long-duration events. The study also revealed the limited effectiveness of cylindrical pile debris deflectors as countermeasures, with some evidence suggesting that they may have exacerbated the accumulation problem.

Ali et al. [47] in 2009 proposed a video analysis framework for the automated counting of fallen trees, bushes, and debris carried by rivers during floods. Their novel approach involved the development of an unsupervised segmentation method for identifying wooden objects in the river, along with a technique to distinguish wood from water waves. By tracking the identified wooden objects across consecutive frames, the algorithm successfully counted the number of fallen trees in the river during flood events. The study emphasized the challenges posed by the highly dynamic river environment, where the absence of a reliable background model necessitated the use of distinct image features for wood detection. Incorporating both spectral and spatial features, the segmentation process effectively separated wooden materials and water waves from the rest of the water. However, the study acknowledged certain limitations, such as the difficulty in detecting submerged wooden objects and the potential confusion caused by the resemblance of water waves to wood, especially in adverse weather conditions. Despite these challenges, the experimental results demonstrated the algorithm's ability to detect and count wood with a reasonable level of accuracy. MacVicar et al. [48] in 2009 focused on quantifying the temporal dynamics of wood in large rivers, emphasizing the role of wood in stream ecology and geomorphology. They identified the lack of documented temporal data, particularly in large rivers, as a key challenge. To address this gap, the study field-tested various techniques for assessing temporal wood dynamics. These techniques included repeated high-resolution aerial surveys, measurement of wood physical characteristics as proxies for 14C dating, Radio Frequency Identification (RFID) tags (both passive and active), radio transmitters, and video monitoring. The paper highlighted the utility and limitations of each technique, emphasizing their roles in improving the understanding of wood transfer processes and the calibration of wood budgets in rivers. By outlining the methodologies and presenting preliminary results from field trials, the study aimed to encourage further investigation into the temporal aspects of wood in rivers. The research underscored that while no single technique could capture all aspects of wood transport, these methods could be effectively employed to address specific components of wood budgets, providing valuable insights into the dynamics of wood in river systems.

Mazzorana et al. [29] in 2009 introduced a methodology for creating hazard index maps focusing on the recruitment and transport of woody material in alpine catchments. This procedure, established on empirical indicators, facilitated the determination of the relative susceptibility of mountain streams to the entrainment and delivery of recruited woody debris. The study produced hazard index maps for all torrent catchments in the Autonomous Province of Bolzano/Bozen, emphasizing the importance of considering the implications of woody material transport during the development of hazard zone maps. The credibility of the findings was rigorously validated through a comprehensive retrospective analysis of natural hazard events documented since 1998. The research addressed key questions related to hazard assessment, aiming to identify torrents requiring consideration for woody material-related phenomena in hazard mapping, pinpoint sensitive reaction-prone torrents, propose relevant scenarios for system loading and response, and rationalize protection forest management policies from a woody material transport hazard perspective. The generated hazard index maps, complementing existing maps for debris flow and sediment transport and deposition processes, served as a reference for detecting pertinent hazard processes within each assessment unit. The authors advocated for in-depth analysis of critical configurations in catchments with high woody material transport indicator values, emphasizing the utility of knowledge derived from the hazard index maps for the strategic planning of effective protection systems. Leveraging high-resolution digital models, hydrological computations, and detailed forest cover datasets, the approach facilitated detailed catchment-scale insights and enhanced parameter estimates for woody material recruitment and transport, laying the groundwork for more informed and foresighted planning processes. In 2010, Balkham et al. [49] comprehensively addressed the blockage of culverts and bridges in the United Kingdom using a risk-based approach. They provided design guidance and procedures to deal with the blockage problem, focusing primarily on local hydraulic structures. In 2010, Lagasse et al. [50] conducted a comprehensive investigation focusing on the impacts of waterborne debris on bridge pier scour during flood events. The research aimed to address the varying effects of debris accumulation on bridge foundations, ranging from minor flow constrictions to severe flow contraction leading to significant scour. The study made significant strides in predicting debris scour by considering the diverse geometry of debris clusters observed at bridge piers in the field. Notably, the research sought to achieve two main objectives: firstly, to predict the accumulation characteristics of debris from different source areas, taking into account the varying geomorphic characteristics of rivers and the substructure geometries of bridges, and secondly, to develop improved methods for quantifying the depth and extent of scour at bridge piers, considering both the accumulation variables and a wide range of hydraulic factors.

In 2010, Mazzorana and Fuchs [30] employed fuzzy formative scenario analysis to assess risks associated with woody material transport in mountainous regions. Their study utilized Formative Scenario Analysis to establish well-defined sets of assumptions about potential system dynamics at critical stream configurations, facilitating a systematic reconstruction of the underlying loading mechanisms and system responses. This approach served as a robust modeling framework for integrating qualitative and quantitative knowledge and managing the inherent uncertainties crucial for natural hazard risk assessment. The researchers emphasized the need to apply this scenario development technique within flood risk management planning, highlighting its capacity to ensure quality throughout the hazard assessment process and provide a coherent problem setting for risk evaluation. By adopting a level-based scenario approach, they explored the consequences arising from hazards triggered by woody material transport during extreme flood events at critical channel cross-sections. Their use of Formative Scenario Analysis, in conjunction with Fuzzy set theory, enhanced the representation of knowledge, and the application of Rough Set Data Analysis validated the predictive accuracy of the generated scenarios. This work demonstrated the significance of developing practical and effective solutions from both the system loading and system response perspectives, aiming to bridge existing gaps and enhance the reliability and robustness of natural hazard risk management. The study by Mazzorana et al. [31] in 2011 focused on modeling the transport and accumulation of woody material in alpine rivers and its implications for hazard mapping. The research highlighted the significant damages caused to protection measures and bridges as a result of woody material transport, leading to unexpected floodplain inundations and subsequent damage to elements at risk. To address the inaccuracies in hazard prediction arising from the insufficient consideration of woody material transport, the study proposed a modeling approach that facilitates the estimation of woody material recruitment, evaluation of its disposition for entrainment and transport, and delineation of hazard process patterns at critical configurations along the stream. The research emphasized the importance of considering wood stand productivity, dead wood production, and the intensity of wood-flood interaction in flood hazard assessments. Additionally, the study stressed the critical role of the intensity of flood processes, such as flow depths and velocities, in the entrainment and transport of woody material. It also highlighted the significance of interaction phenomena at critical channel geometry configurations, particularly in relation to woody material entrapment and the associated consequences, such as bridge failures. The developed modeling concept aimed to provide detailed insights into hazard assessment, enabling the identification of potential risk factors and the formulation of effective risk mitigation strategies, including the removal of critical configurations inducing woody material accumulation, reconfiguration of weak points, and implementation of silvicultural measures in recruitment areas to reduce the hazard source. By incorporating these elements into emergency planning and preparations, the study aimed to enhance the resilience of elements at risk and improve overall risk management.

Pagliara et al. [51] in 2011 delved into the impact of LW debris on sediment scour at bridge piers, highlighting its influence on flow patterns and scour depth enhancement. Their investigation analyzed the planimetry of drift accumulation and its effects on bridge pier scour. The study considered various factors, including relative longitudinal lengths, flow area occlusions, and downstream planimetrical positions in relation to the pier center. Through a series of clear-water flume experiments encompassing diverse hydraulic and geometric conditions, they proposed new relationships to predict the impact of drift accumulation on maximum scour hole depths at bridge piers, both in terms of relative maximum scour and temporal scour evolution. The findings underscored the significant influence of both the longitudinal length and downstream extension of drift accumulation on bridge pier scour, with variations in the debris accumulation length and position significantly affecting the debris effect factor. The study also revealed the role of accumulation position and planimetrical shape in determining the shape of self-similar longitudinal scour holes, providing insights crucial for countermeasure design. While their proposed design equation improved the assessment capability of maximum scour hole depth in the presence of LW, the study emphasized the need for further analysis of the interaction between the debris boundary layer and the downflow to better understand its role in scour development and morphological features. In 2011, Schmocker et al. [32] conducted an experimental investigation to assess the probability of drift blockage at bridge decks, focusing on the impacts of drift dimensions, freeboard, flow characteristics, and bridge properties. The study encompassed systematic model tests involving the accumulation of single logs and rootstocks, aiming to simulate major flood scenarios where the freeboard approaches zero, enabling interaction between the drift and the bridge deck. The research highlighted the significant influence of factors such as the freeboard, approach flow Froude number, and bridge characteristics on drift accumulation, allowing for the estimation of the blocking probability. The tests provided insights into the randomness of the blocking process, exhibiting varying results and emphasizing the need to accept a certain level of unpredictability in drift blocking tests. Notably, the blocking probability was observed to increase with decreasing freeboard and increasing drift dimensions, while it decreased with higher Froude numbers, as increased stream power and wave action aided in freeing accumulated drift. The research emphasized the significance of bridge design, with truss and railing bridges posing a higher risk of blockage compared to baffle bridges, which facilitated drift passage without damage. Additionally, the study highlighted the importance of considering river geometry and sediment load in future research to provide a comprehensive understanding of drift accumulations and blockages in various flow conditions and bridge configurations.

Bocchiola [52] in 2011 conducted a comprehensive flume experiment to investigate the altered hydraulic properties and habitat conditions resulting from the presence of LW debris in streams. Simulated feeding of LW was accomplished by introducing wood dowels of varying dimensions, mimicking both lumped and distributed load processes. The study proposed a methodology to predict flow properties in the presence of LW, demonstrating that distributed wood inputs led to uniformly increased bed roughness, consequently influencing flow depth and velocity. On the other hand, localized wood introductions caused clustered wood formations, affecting flow conditions locally but with limited influence on the overall hydraulic properties. The study emphasized the critical ecological role of wood in streams, underscoring the need for understanding flow patterns and habitat availability in the presence of LW, particularly in the context of stream restoration initiatives. By introducing a simple empirical estimation method based on the wetter usable area concept, the study highlighted the significant changes in habitat availability resulting from the introduction of LW. The findings suggested that the homogeneous restoration of streams may be more effectively achieved by introducing LW along the stream or fostering riparian feeding. Additionally, the study proposed an approach to estimate flow depth and velocity based on the spacing of wood pieces, facilitating the assessment of habitat availability in relation to flow variables. However, the study acknowledged certain limitations, including uncertainties associated with the choice of drag coefficients for LW and the potential complexities arising from real-world bed load movements and channel dynamics. In 2012, Lassettre et al. [53] delved into the impacts of LW debris in urban stream channels, emphasizing its significance as a crucial ecological element in rivers and streams. They addressed the common practice of removing LW from urban stream channels for flood control and road maintenance, which incurs substantial economic and ecological costs and is often ineffective. To counter this, the researchers proposed a novel strategy to conserve LW in channels by modifying infrastructure such as culverts and bridges to facilitate LW passage, ultimately preserving aquatic habitats and mitigating flooding and road maintenance expenses. Focusing on Soquel Creek in California, which had experienced LW-related flooding, the study conducted a comparative analysis of long-term LW management costs under historical, current, and the proposed LW-passage approach, which involved enlarging infrastructure to accommodate downstream LW passage. The study estimated various costs, including infrastructure replacement, programmatic flood control (LW removal), LW-related flood damage, and the loss of aquatic habitat. The findings indicated that while the costs associated with infrastructure modifications for LW passage were nearly double that of historical costs, they were comparable to current costs. The LW-passage approach showed parity with removal approaches in the short term, but proved to be significantly less expensive in the long term due to the reduction in flooding costs and habitat loss resulting from the investments in infrastructure modifications. Highlighting the pressing need to preserve and restore aquatic habitats, the study suggested the broader applicability of the proposed approach.

MacVicar et al. [54] in 2012 conducted a comprehensive study on wood budgeting in rivers, utilizing video monitoring techniques. The research aimed to quantify wood transport rates and their relation to water discharge in the Ain River, France, during flood events. The study verified the effectiveness of streamside video cameras in measuring wood transport, including tests related to detection frequency, wood velocity, and piece size. A log base two transformation was proposed for wood classification by piece length. Findings indicated a positive linear correlation between wood transport and discharge, with an observed wood transport threshold at approximately two-thirds of the bankfull discharge. Notably, wood transport rates were found to be about four times higher on the rising limb of the hydrograph compared to the falling limb. The study also constructed and validated a wood budget for the upstream reach using data from field observations and aerial photography. However, the research emphasized the need to address uncertainties related to wood diameter measurements, sampling length and frequency, and antecedent floods to enhance the accuracy of wood budget estimates. The analysis presented a three-stage relation with hysteresis between discharge and volumetric wood transport, highlighting the complexity of wood dynamics influenced by various factors including floodplain interactions and wood sources. While the wood estimates from video monitoring and the rating curve model were higher than the wood budget estimates, they were lower than the removal records from regional reservoirs. The study recommended reducing uncertainties and accounting for the scale differences between the local monitoring site and the contributing reach for improved wood budget estimates. In 2013, Blanc [7] conducted lab-scale experiments using a Froude-scaled physical model of a culvert to study the impact of trash screen design on culvert inlet blockage. The experiments demonstrated that while trash screens are intended to prevent blockage and reduce flood risk, they can actually increase flood risk when trapped by debris. The study highlighted factors such as debris length, trash screen position relative to the flow zone, and the relationship between debris and screen spacing. However, the investigation did not explore the impact of blockage on upstream water levels and peak flood levels, and it focused on a single circular culvert configuration, neglecting the study of different culvert configurations.

Ruiz-Villanueva et al. [37] in 2013 conducted a comprehensive investigation into the impacts of LW transport during flash flooding in a mountain basin, aiming to analyze the associated flood hazard patterns. The study highlighted the need for accurate estimation of peak flows in the presence of backwater effects caused by bridge clogging, emphasizing the limitations of traditional methods such as high water mark or palaeostage indicators. Through a combination of indirect estimation techniques and one-dimensional hydraulic simulation, the researchers validated the estimated peak discharge, revealing a blockage ratio of approximately 48% during the 1997 event. Rainfall-runoff modeling utilizing stochastic simulation further confirmed the consistency of the estimated discharge range with the observed rainfall amount. Notably, the study identified a significant backwater effect attributed to wood obstruction, equating the 1997 flood to a 50-year event, despite its original 35-year return period. This finding led to the introduction of the concept of the equivalent return period, representing the recurrence interval of an obstructed event that yields a comparable water depth and flooded area to a more extreme unobstructed event. The research emphasized the crucial role of obstruction phenomena in flood hazard analysis, underscoring the need to account for the influence of large wood transport during flood events. By reconstructing the complex interaction processes and establishing the clogging curves, the study provided valuable insights into the catchment response and enhanced the understanding of flood risk analysis, emphasizing the importance of considering wood transport in comprehensive flood hazard assessments. The findings shed light on the significance of incorporating obstruction-related concepts in flood hazard and risk analysis. Streftaris et al. [55] in 2013 addressed the lack of tools for making informed decisions about the inspection requirements of trash screens installed at culvert entrances. The study developed a stochastic predictive model using inspection records from 140 screens in Belfast, Northern Ireland, to determine the probability of screen blockage. The model related blockage probabilities to seven potential drivers, including channel, land-use, meteorological, temporal, and social deprivation factors, using a logistic regression approach. A Bayesian framework was adopted to account for data randomness and report uncertainty in predictions through credible intervals. The predictive accuracy of the model was assessed and found to be within acceptable limits, despite inherent uncertainties. This research provides valuable insights for decision-making processes related to screen inspections, offering a tool to assess potential site-specific blockage risks and support effective maintenance strategies for trash screens at culvert entrances.

Kramer et al. [56] in 2014 conducted a study that focused on estimating fluvial wood discharge using time-lapse images with varied sampling intervals. The research emphasized the importance of monitoring LW during river transport to better comprehend the patterns and controls of LW flux and loads in river basins. By employing time-lapse photography with coarse interval sampling, the study aimed to construct fluvial wood flux curves, analyze the effects of sample interval lengths on transport estimates, and estimate total wood loads within a specified time period. The research was conducted in the Slave River, a significant subarctic river in Canada, and revealed a threshold relationship for wood mobility around 4500 mete cube per second. Notably, wood flux was observed to be higher on the rising limb of the hydrograph, with a rapid decline on the falling limb. The study suggested that five- and ten-minute sampling intervals provided unbiased equal variance estimates comparable to one-minute sampling. However, 15-minute intervals exhibited a bias towards underestimation by approximately 5-6%. While the research presented several strengths of using time-lapse photography for wood monitoring, such as cost-effectiveness and the ability to extrapolate data gaps, it also highlighted limitations such as imprecise estimates and assumptions about sampling and log characteristics. The study recommended future research focusing on improving precision, analyzing data gaps, estimating rootwad volumes, and comparing time-lapse methods to video monitoring, among other areas of exploration. The study conducted by Ruiz-Villanueva et al. [38] in 2014 delved into the transportation of LW and its influence on flood risk in mountainous regions. Recognizing the pivotal role of LW in river ecosystems, the research emphasized the necessity of comprehending wood transport and deposition in streams, thus advocating against its removal. Employing scenario-based 2D hydrodynamic flood modeling, the study incorporated probabilistic and possibilistic approaches to ascertain the potential impact of LW on flood risk assessment. By generating a probabilistic flood map for a 500-year return period and constructing various scenarios based on wood budgets to simulate wood transport and deposition, the study successfully pinpointed critical stream configurations, particularly bridges, susceptible to the effects of LW passage and blockage. Through this analysis, the study estimated potential damages and assessed the preliminary social vulnerability associated with different LW transport scenarios. Findings indicated that wood transport and deposition during flooding could elevate potential damage at critical stream locations, leading to increased inundation in nearby areas by up to 35%. The study acknowledged the challenges posed by the lack of direct observations, underscoring the significance of models as tools for generating and evaluating scenarios.

Ruiz-Villanueva et al. [57] in 2014 conducted a study focusing on the dynamics of wood transport in rivers and developed a numerical model that simulates wood transport coupled with a two-dimensional (2D) hydrodynamic model. This new computational module was integrated into ‘Iber’, a 2D hydraulic simulation software, where wood drag forces were incorporated as additional source terms in the shallow water equations. The model considered the initial motion threshold of wood, calculating the position and velocity of logs of different shapes using a kinematic approach. It also accounted for interactions between the logs themselves and between the logs and the channel boundaries. The researchers validated the model's capabilities using flume experiments in a straight channel with obstructions, demonstrating its accuracy in replicating the movement of floating logs under various hydraulic conditions over relatively short time scales. While acknowledging the simplifications made in the model's development, the study emphasized the need for further research to capture the complexity of wood transport in natural watercourses. The authors indicated that the model could serve as a valuable tool in the field of fluvial geomorphology and related areas, and they expressed the intention to continue refining and testing the model in different settings and for various purposes. In 2014, study by Putri [58] focused on investigating the influence of expansion section width on culvert performance in steep terrains, conducting laboratory experiments using a scaled model. The experiments, which simulated both clear water and sediment transport conditions, highlighted that the culvert's performance was notably affected by the width of the expansion section and the chosen inlet setup. Narrower expansion section widths generally resulted in improved culvert performance, with the sediment deposition pattern directly related to the flow phenomena influenced by the expansion section width. Additionally, the study emphasized the connection between expansion channel width, water depth, and the occurrence of hydraulic jumps, noting that wider widths were exposed to higher energy resulting from hydraulic jumps, leading to increased sediment transport towards the inlet. Despite the presence of sediment reducing the culvert's hydraulic capacity, the study found that factors such as sediment size, amount, and feeding methods had minimal impacts on the culvert's overall performance.

Sorourian et al. [59] in 2014 emphasized the significant influence of culvert blockage on the scouring patterns downstream. The study conducted experimental tests in a laboratory flume at the Hydraulics Laboratory of the University of Technology Sydney, comparing partially blocked and non-blocked conditions to examine the effect of blockage on scour patterns. The results indicated that a substantial portion of the maximum scour depth, ranging from 88% to 98%, occurs during the rising limb of the hydrograph. This research contributes valuable insights into the understanding of scour behavior in partially blocked box culverts under unsteady flow conditions. In 2015, Kramer et al. [25] conducted a scaled laboratory investigation to study the impact of debris blockage on the hydraulic flow of culverts. The experiments showed that debris tends to align itself parallel to the flow, and the results varied significantly for different debris alignments and test case scenarios. However, the study did not establish a concrete relationship between visual interpretations and hydraulic impacts of blockage for the given scenarios. Scaling issues were also encountered in physical models used to study blockage behavior, particularly regarding sediment and flow behaviors. In 2015, Manning-Dickfos [34] investigated the validity of current blockage design guidelines in the Sunshine Coast region of Queensland, Australia. They used a Froude-scaled physical model of a real-world culvert site designed as an open channel, allowing for more realistic implementation of channel characteristics, debris availability, and flow directions. The study simulated different flooding scenarios based on historical data, controlling culvert flow capacity to determine the percentage of blocked culverts using a gate-type mechanism. The experiments showed that a higher percentage of debris reached the culvert at lower flow rates compared to higher flow rates. Based on the observations, the study proposed design blockage factors of 40% for typical events and 20% for extreme events. However, the research focused more on the volume of debris reaching the culvert rather than the impact of accumulated debris on flood levels and the accumulation behavior of debris at the culvert. Additionally, the study was limited to a rectangular culvert configuration in a specific channel. In 2016, Sullivan et al. [60] proposed the use of remotely collected data using Unmanned Aerial Vehicles (UAVs) to identify culverts and bridges susceptible to blockage during flooding events. They suggested automating the detection and classification of debris piles using different types of information. However, the study did not develop a vision-based algorithm for automatic feature extraction and relied on manual review-based approaches. The research emphasized the importance of remote sensing data in detecting debris material but did not provide evidence of developing a computer vision-based algorithm for automatic detection and classification of debris piles.

Benacchio et al. [61] in 2017 introduced a novel methodology for monitoring wood fluxes in rivers using ground imagery, emphasizing the increasing application of ground imagery in understanding fluvial processes. Their study focused on automating the image analysis process to monitor wood delivery from the upstream Rhône River, with the Génissiat dam serving as the observation point. By employing a random forest classification method, they achieved a high classification rate for detecting the wood raft surface, establishing a strong correlation between wood weight and wood raft area. However, they encountered significant challenges in continuously monitoring wood flux due to substantial changes in raft density and form, leading to difficulties in accurately converting wood raft area into wood weight or flux. Factors such as weather conditions, variations in pixel resolution, and raft dynamics, including dam operations and wind effects, posed additional complexities. While the study successfully detected the extent of the wood raft, limitations were highlighted concerning the misclassification rate and inaccuracies in estimating wood raft area, primarily during significant flow events. Recommendations were made to optimize the monitoring process, considering aspects such as the resolution of images, camera angle and position, and the incorporation of water level variations. In 2017, Gscgbitzer et al. [33] conducted a series of lab experiments to assess the blockage of bridges by LW debris. Through logistic regression analysis, they processed the influence of geometric, hydraulic, and wood-related parameters on LW clogging probabilities, leading to the development of a practical guideline for assessing flood risk induced by LW blockage. The study suggested two specific local structural protection measures for bridges: a deflecting baffle installed on the upstream face of the bridge and a channel constriction to alter flow state, increase flow velocities, and enhance freeboard at the bridge cross-section. However, the study acknowledged limitations due to the simplified nature of the flume-based experiments, which couldn't capture the complexities of open-channel variations, particularly significant in the case of blockages. The research proposed a three-step approach, including estimation of LW potential, entrainment, and transport; assessment of the clogging scenario at the bridge; and the evaluation of impacts on channel and floodplain hydraulics. Additionally, the study emphasized the need for an optimized river management approach, tailored to specific river basins and local conditions, to effectively mitigate flood risks associated with LW blockage. The authors suggested an extension of physical model tests, focusing on parameters related to sediment transport and morphological changes, to enhance the accuracy and applicability of the proposed approach.

In 2018, Persi et al. [62] introduced a novel model that simulates the transport of LW by employing a coupled Eulerian-Lagrangian approach. The model, tailored to predict the trajectory of floating rigid bodies, particularly woody debris mobilized during floods, seamlessly integrates a Discrete Element (DE) Lagrangian approach with the Eulerian solution of the Shallow Water Equations (SWE). Distinguishing itself from existing models, it incorporates a dynamic approach, adapting the Basset-Boussinesq-Oseen equation to account for the motion of rigid bodies, which, in this case, were represented as cylinders capable of altering their orientation in response to the flow. To ensure accuracy, the researchers conducted laboratory tests on partially submerged cylinders to determine the drag and side coefficients, crucial parameters affecting the model's precision. They validated the coupled model against existing laboratory data, focusing on the transport of spheres and wooden cylinders. The model, which represents a significant advancement in the prediction of the effects of large floating debris on flood flow evolution, enables the computation of the displacement and rotation of submerged, floating, and buoyant spheres and cylinders. Notably, the model accounts for hydrodynamic forces on each rigid body, integrating a dynamic coupling between the Lagrangian and Eulerian solvers, and incorporates elastic collision modeling for body-to-body and body-to-wall interactions. Despite the need for further refinements, including the enhancement of the collision model and the validation of rotational dynamics, the proposed dynamic approach demonstrates its adaptability in accommodating diverse components required for accurate numerical simulations. It allows for the automatic integration of various factors, such as the variability of hydrodynamic coefficients and friction forces, thereby establishing its potential as an effective instrument for simulating the transport of floating logs during flood events. Ghaffarian et al. [63] in 2018 conducted experimental investigations focusing on the transient motion of floating wood in rivers, addressing the challenges posed by the movement of large wood among hydraulic structures, especially in urban areas. Despite previous studies on the statistical, morphological, and hydrodynamical aspects of this phenomenon, limited information exists regarding the transient behavior of floating wood pieces. The study employed both theoretical and experimental analyses to examine the transient motion of floating particles under simple acceleration. From a standard advection model, the authors identified a crucial parameter, the particle characteristic response distance, which serves as a key indicator of the probability of impact on hydraulic structures based on the characteristics of the floating wood. The experiments revealed that this parameter is approximately two to three times the streamwise body length and is independent of the flow velocity for floating particles such as wood in rivers. The study also determined that the presence of roots primarily affects the frontal area of the particles and not the root pattern. Although the results were obtained using simplified symmetric geometries, the researchers suggested that the findings remain applicable to real wood pieces in natural conditions. The comparison between the characteristic response distance of the objects and typical flow scales, such as the size of bridge piers, offers valuable insights into the likelihood of impact with river infrastructure and the associated risk of flooding and damage from wood trapping.

Furlan et al. [64] in 2019 conducted repeated experiments to investigate the blockage of large stems at spillways and piers, which is often observed when rivers carry substantial amounts of LW into reservoirs during heavy rainfall events. The study aimed to provide systematic and reliable estimations for the blocking probabilities of ogee crested spillways equipped with piers, using physical models. Two statistical methods were applied to calculate confidence intervals, and the study recommended a minimum number of repetitions for achieving a maximum acceptable error in blocking probabilities. The research highlighted the significance of accuracy in probabilistic estimations, which had often been overlooked in previous works. The paper emphasized the importance of defining the number of repetitions based on statistical accuracy and proposed a maximum acceptable error of 0.09 for rigorous assessments of large wood blockage risk. Furthermore, the study suggested that a minimum of 30 repetitions per experiment is necessary to achieve estimations with errors smaller than 0.09, with a confidence level of 90%. Additionally, the paper recommended using confidence intervals, specifically the Wald or Clopper-Pearson methods with a confidence level of 90%, to estimate the accuracy of observations when reporting estimated probabilities. The findings stressed the value of these statistical tools in enhancing the understanding of large wood behavior and risk assessment associated with blockage probabilities at hydraulic structures. The study conducted by Schalko et al. [23] in 2019 focused on the analysis of local scour resulting from natural spanwise LW accumulations using hydraulic model tests in a laboratory flume. The experiments were designed to simulate spanwise accumulations resembling a vertical barrier, akin to a LW retention rack in real-world scenarios. The tests were conducted at a 1:30 scale, ensuring Froude similitude, and included various approach flow conditions and different uniform bed materials. The results provided valuable insights into the estimation of local scour depth due to spanwise LW accumulations, with the scour depth and length found to be influenced by unit discharge, sediment diameter, and wood volume. The study revealed that higher unit discharge, finer bed material, and increased wood volume contributed to greater local scour depths. The longitudinal shape of the cross-sectional scour depth was described using a Gaussian normal distribution, demonstrating symmetry around the position of the maximum scour depth at the rack. A design equation was derived based on dimensional analysis to estimate the maximum local scour depth, incorporating the relative characteristic LW volume, unit discharge, and mean grain size diameter. The study recommended the application of this equation for both spanwise LW accumulations and the design of LW retention racks, emphasizing its utility for efficient planning and design. The results contributed to an improved understanding of the formation of LW accumulations and the interactions between flow, LW, and sediment, offering practical implications for the planning of LW retention structures. The authors suggested the need for complementary experiments involving nonuniform bed material and varying initial sediment transport conditions to further investigate these interactions. Additionally, they emphasized the importance of considering sediment feeding to evaluate sediment continuity at rack structures, as well as the potential impact of log remobilization, log stiffness, and varying log densities on LW accumulation formation during floods. The study acknowledged the simplified nature of the model tests compared to natural LW accumulations during floods and recommended further research to incorporate these additional factors for a more comprehensive understanding of the processes involved.

The research conducted by Schalko et al. [22] in 2019 involved laboratory flume experiments to investigate the impact of LW accumulation on backwater rise in rivers. The study aimed to enhance the understanding and predictability of the formation and influence of spanwise LW accumulations at natural or artificial obstructions, such as LW retention racks. By performing hydraulic model tests with both fixed and movable beds under various flow conditions, LW dimensions, and organic fine materials, the researchers identified the effects of spanwise LW accumulations on backwater rise. The experiments revealed that natural LW accumulations reduced backwater rise to approximately 3/5, and resulting local scour further decreased it to around 1/3 compared to predefined worst-case scenarios. The study extended the design equation proposed in a previous work to estimate backwater rise, incorporating the accumulation type factor to account for the effects of natural accumulations and movable beds. A characteristic LW volume was defined as the volume generating the primary backwater rise, which was expressed as a function of the approach flow Froude number for a fixed bed and additionally of flow depth and mean grain size diameter for a movable bed. The study's results provided valuable insights for the efficient design of LW retention racks, with the proposed design equations offering a ±30% uncertainty range deemed adequate from an engineering perspective. The authors emphasized the necessity of sensitivity analyses for robust and sustainable design and recommended further experiments exploring log density variations, unsteady flow conditions, and suspended sediment to improve the understanding of wood accumulations. Additionally, the study underscored the need for enhanced process comprehension regarding wood accumulation formation, backwater rise, and scour in various accumulation types and river infrastructures, including weirs, bridge piers, and check dams. In 2020, Brooks [1] investigated culvert blockage by boulders through a lab-scale study integrated with field research. They developed a scaled physical model (Froude scale of 1:16) of a rectangular culvert in a mountainous stream in South Africa. The study identified the culvert inlet as the major location for boulder deposition and proposed multiple culvert inlet designs (T-model, CT-model) to mitigate boulder blockage. The CT-model proved to be the most efficient in mitigating blockage by either settling boulders far upstream or transporting them through the culvert. The study provided detailed guidelines for culvert design to avoid boulder deposition near or inside the culvert. However, the investigation did not explore the impact of boulders on blockage itself, such as the influence on peak flood levels and the hydraulic performance of the structure. The study had a localized scope, and the proposed guidelines may not be applicable globally.

Ghaffarian et al. [65] in 2020 introduced the use of video cameras for monitoring and quantifying wood discharge in rivers. This study emphasized the importance of understanding wood flux and discharge in rivers, particularly with regard to the exacerbated flooding hazards and infrastructure damage caused by wood obstruction and jamming. Employing the streamside videography technique, they demonstrated the effectiveness of this method in providing high temporal and spatial resolution. Through comparative analysis of two sites on the Ain River and the Isère River in France, they established that the maximum wood discharge typically occurs at bankfull discharge, confirming the three-stage model proposed by previous researchers. Furthermore, they observed similarities in transverse distributions of wood pieces and wood lengths for various flood magnitudes at each site. The study highlighted the critical factors influencing measurement accuracy, including camera resolution, installation specifics, and best practices for streamside video monitoring. The findings underscored the potential of the videography technique in monitoring wood flux, facilitating comparisons between river reaches and basins, and determining wood regimes and geographical controls. This work serves as a valuable resource for decision-makers involved in wood hazard management and those seeking to implement effective monitoring techniques for wood discharge in river systems. Taha et al. [66] in 2020 utilized numerical simulations with the sediment transport model in FLOW 3D to investigate different ratios of blockage through the box culvert. The accuracy of the FLOW 3D program in simulating scour downstream of the box culvert was validated through comparison with experimental data. The results demonstrated that a blockage ratio of 70% of the culvert height significantly increases the water depth upstream by 2.3 times the culvert height and the mean velocity by 3 times compared to the base case. Additionally, an equation was developed to estimate the relative maximum scour depth based on the blockage ratio. This research provides valuable insights into the behavior of blockage in box culverts and its implications for water surface characteristics and scour, contributing to the understanding and design considerations of crossing structures.

Piton et al. [36] in 2020 delved into the impact of LW on open check dams, specifically focusing on head losses and release conditions. The study aimed to clarify the extent to which the presence of LW modifies the stage-discharge relationships of open check dams. It highlighted the crucial need to understand this modification in order to estimate the potential trapping of bedload transport and the resulting overflow depth atop the structure. The research emphasized the potential hazards associated with high overflow depths triggering sudden releases of trapped LW downstream. Through experimental quantification, the study provided insights into LW-related energy dissipation and presented simple methodologies to compute the related increase in water depth at various dam shapes. The study observed that LW often gets released over the structure when the overflowing depth is about 3-5 times the mean log diameter. The paper introduced two observed regimes of LW accumulation, indicating different behavior based on the dam's permeability. A new dimensionless number, the ratio of buoyancy to drag force, was proposed to predict the flow regime in the presence of LW. The study demonstrated the need for comprehensive understanding and consideration of LW effects in the design of open check dams to avoid potential downstream damages caused by sudden releases of trapped LW. Schalko [67] in 2020 investigated the impact of wood retention at inclined racks on flow and local bedload processes. The study hypothesized that inclined racks could potentially mitigate backwater rise and local scour by obstructing the upper part of the rack with wood, thus creating an increased open flow cross-section below the accumulation. Experimentation was conducted under both clear water and live bed scour conditions to analyze the effects of rack inclination, hydraulic inflow conditions, uniform bed material, and LW volume on backwater rise and local scour. The results indicated that both backwater rise and local scour decreased as the rack angle to the horizontal decreased, with LW predominantly accumulating at the upper part of the rack, thereby creating a larger open flow cross-section below the accumulation. The study proposed modifications to existing design equations for backwater rise and local scour depth, considering the effect of the rack angle. Additionally, initial experiments incorporating bedload transport revealed reduced backwater rise and local scour depth. The findings emphasized the necessity of innovative rack designs to facilitate wood retention and bedload transport, providing valuable insights for the development of more efficient rack structures. This work marked the first exploration of the interaction between bedload transport and wood retention at rack structures, contributing to a more comprehensive understanding of the dynamics of wood accumulation and its influence on flow and local bedload processes.

In 2021, Iqbal et al. [24] proposed lab-scale simulations using scaled physical models of culverts to study the behavior and effects of urban and vegetative debris. The investigations focused on the interaction between specific debris types and culvert inlet geometries, as well as the complex relationships between blockage-related influential factors and the observed visual and hydraulic interpretations of blockage. The results revealed that urban debris is the main contributor to increasing hydraulic blockage, with the orientation of debris playing a significant role. Furthermore, the experiments highlighted the temporally variable nature of blockage, suggesting the need to revise existing constant blockage guidelines based on ARR. Understanding the temporal variability of blockage is critical for structural design, flood modeling, and maintenance policies. It ensures resilient structure designs that accommodate changing flow conditions, aids accurate flood predictions for effective management strategies, and facilitates timely maintenance interventions to prevent severe blockages and associated risks. By acknowledging the temporal variability of blockage and accounting for it in various aspects of structural design, flood modeling, and maintenance policies, authorities can better prepare for and mitigate the potential impacts of blockages on infrastructure and the surrounding environment. In 2021, Iqbal et al. [68] explored the utility of deep learning image classification models for the first time towards automating the process of visual identification of blockage at culverts. Given a camera system pointing at the culvert, the ideas was to capture the image of culvert and the Convolutional Neural Network (CNN) model will predict if the culvert is in visually blocked state or visually clear state. Authors developed real (i.e., Images of Culvert Opening and Blockage (ICOB)) and simulated datasets (i.e., Visual Hydraulics-Lab Dataset (VHD), Synthetic Images of Culvert (SIC)) for the training of deep learning models containing images of culverts with blockage and no blockage. Results show that NASNet achieves the highest accuracy (85%) in accurately classifying a culvert as visually blocked or visually clear, while MobileNet is recommended for hardware implementation due to its improved response time and comparable accuracy (78%). The study highlights the challenges posed by background noise and oversimplified labeling criteria in CNN models and proposes a framework for partial automation of blockage classification. It suggests a detection-classification pipeline (i.e., first detect the openings of culverts from image, crop the openings and classify the cropped images as visually clear or visually blocked) for achieving higher blockage classification accuracy (94%). This research provides valuable insights for improving the maintenance perspective of culverts and contributes to the automation of manual visual blockage classification processes.

Zhang et al. [69] in 2021 delved into the video monitoring of wood, aiming to characterize and predict wood fluxes for a comprehensive understanding of wood dynamics and efficient management of flood risk in river basins. By utilizing the streamside videography technique, the study focused on detecting wood passage and measuring instantaneous rates of wood transport during various flood and wind events on the Ain River, France. Notably, approximately 24,000 wood pieces were visually identified, offering valuable insights into wood behavior under different hydrological conditions. The findings confirmed the presence of a general threshold for wood motion in the river, corresponding to 60% of bankfull discharge, highlighting the role of antecedent conditions in wood transport. Particularly, the study observed the significant influence of wind in preparing wood for transportation between floods, emphasizing the importance of considering wind events in wood flux analysis. Additionally, the study revealed the empirical relationship between wood frequency and wood discharge, facilitating the estimation of total wood production during each flood event. Leveraging the dataset, a random forest regression model was developed to predict wood frequency based on three input variables derived from the flow hydrograph, enabling the calculation of total wood volume during both day and night. This novel application of the video monitoring technique not only expanded its utility for wood budgeting in watersheds but also established a fundamental connection between the fraction of detected wood pieces and the dimensionless parameter “passing time × frame rate,” thereby offering valuable guidance for the design of monitoring stations. The study thus significantly advanced the understanding of wood flux dynamics and provided a robust framework for the efficient prediction of wood transport in rivers. In 2022, Iqbal et al. [70] explored data-driven solutions and implemented four models (k-Nearest Neighbor (k-NN), Artificial Neural Network (ANN), Support Vector Regressor (SVR), 1D-CNN) to predict hydraulic blockage at culverts. Idea floated was to record the hydraulic data such as water levels, inlet discharge, input velocity, bed slope and debris type, and train a machine learning regression model to predict the percentage of hydraulic blockage based on the input data. A new dataset, the Hydraulics-Lab Blockage Dataset (HBD), was established from lab-scale hydraulic experiments. The results indicated that the ANN model performs the best, achieving a high R2 score of 0.95. The article also discussed the potential real-world application of this research, demonstrating its practical feasibility. In 2022, Iqbal et al. [71] proposed the use of computer vision technologies, specifically object detection models (Faster R-CNN, YOLOv4), for automated floodborne object type identification from vision sensor images. Given an image of culvert, the model would be able to detect the debris in image as bounding box and will also classify if it is a tree, rock or a bin. The Floodborne Objects Recognition Dataset (FORD) was utilized, consisting of real and simulated images of floodborne objects blocking hydraulic structures. The results demonstrated that the Faster R-CNN model with MobileNet backbone achieved the highest Mean Average Precision (mAP) of 84% on the test dataset. Two potential use cases for floodborne object type recognition were discussed, emphasizing the practical feasibility of the proposed approach. The findings indicated the potential of computer vision models for automated identification of floodborne object types, addressing a critical aspect in assessing their impact on flooding.

In 2022, Iqbal et al. [35] addressed the blockage issue by leveraging Artificial Intelligence (AI) and proposed a deep learning pipeline to predict hydraulic blockage from a culvert image. A unique concept has been floated where given the image of a culvert, the model would be able to predict the hydraulic blockage at the culvert. This approach is also referred to as regression on deep visual features in literature. Two experiments were conducted, comparing a conventional pipeline approach (CNN for feature extraction and ANN for regression) with end-to-end deep learning models (E2E_MobileNet, E2E_BlockageNet). The datasets used in this research include the HBD and the VHD, obtained from laboratory experiments using scaled physical models of culverts. The E2E_BlockageNet model demonstrates the best performance in predicting hydraulic blockage with an R2 score of 0.91, indicating the interrelation between visual features and hydraulic blockage at the culvert. This research contributes to the understanding of blockage management and highlights the potential of AI in addressing the challenges associated with visual and hydraulic blockage in hydraulic structures. In 2022, Miranzadeh et al. [26] examined an experimental study investigating the temporal variations of blockage caused by woody debris upstream of culverts under unsteady flow conditions. The research focused on two culvert shapes, namely box and circular pipe culverts, and utilizes synthetic flow hydrographs to simulate flood conditions in the laboratory. Cylindrical wooden dowels representing woody debris of varying diameters were used in the experiments. The results indicated that the highest percentage of blockage occurs during the falling limb of the hydrograph. The feeding rate of smaller diameter woody debris significantly affects the culvert blockage, while the feeding rate of larger woody debris has no impact on the blockage percentage. Additionally, the study revealed that pipe culverts are more prone to blockage compared to box-shaped culverts. Regression analysis were employed to propose predictive equations for estimating the percentage of culvert blockage during flood events. These findings contribute valuable insights into understanding the dynamics of culvert blockage and can aid in developing effective strategies for managing debris accumulation in culverts during floods. In 2022, Iqbal et al. [72] proposed an intelligent video analytics (IVA) approach using deep learning models for the extraction of blockage information. The proposed pipeline involved segmenting visible culvert openings and classifying them into four percentage visual blockage categories (i.e., 0-10%, 10-50%, 50-75%, >75%). The models were trained using the ICOB and VHD. Mask R-CNN with ResNet50 backbone achieved the best segmentation performance (mAP@75 of 77.2%), while NASNet achieved the highest classification performance (81.2% test accuracy). The practical implication of the research was demonstrated through a proposed visual blockage monitoring use-case. This study highlighted the potential of deep learning-based approaches for timely maintenance decisions and improved flash flood prevention by prioritizing highly blocked culvert sites.

4.3 Discussions

Over the years, a diverse array of studies has been conducted to address the challenges associated with blockage management in culverts and bridges, each employing distinct methodologies and technologies. Initially, traditional flume-based experiments served as the foundation for understanding the complex hydraulic behavior of various types of debris, including LW debris, woody material, boulders, and urban and vegetative debris (see [19], [20], [21], [22], [23], [24], [25], [26]). These experiments involved controlled simulations of flow conditions and debris interaction, providing crucial insights into the dynamics of debris movement and their effects on the hydraulic performance of structures during flood events. Additionally, these flume-based studies helped in the development of empirical relationships between flow conditions and debris blockage, contributing to the formulation of basic blockage prediction models.

The availability and transport of upstream debris has been identified as one of the significant factors in context to blockage and is studied in detail [10], [15], [20], [22], [23], [28], [29], [34], [36], [43], [44], [45], [46]. The presence of debris upstream serves as a foundational element influencing the blockage dynamics within river systems and hydraulic infrastructures. The origins of this debris can be multifaceted, encompassing natural events like tree falls, erosion processes, and sediment accumulation, as well as human activities including deforestation and improper waste disposal. Once established, the mobility and transport of this debris are intricately tied to a range of hydraulic and environmental factors. Flow velocity plays a critical role, with higher velocities capable of mobilizing larger debris. Additionally, the size, shape, and buoyancy of the debris itself, from sizable tree trunks to smaller branches and detritus, further determine its transportability. Channel morphology, including the presence of obstructions and bends, can either facilitate the movement or trap debris, leading to localized accumulation points and potential blockages. Moreover, the influence of episodic events, such as intense storms or rapid snowmelt, cannot be understated, as these can dramatically alter flow regimes and sediment transport capacities, further complicating the dynamics of debris transport. In sum, a nuanced understanding of the upstream debris availability and its interaction with various influencing factors is paramount for developing comprehensive strategies to mitigate blockage risks in river systems.

As research progressed, there was a notable emergence of modeling-based approaches, where sophisticated numerical models were developed to integrate the complexities of debris transport, culvert hydraulics, and river morphology (see [27], [28], [29], [30], [31], [32], [73]). These advanced models, often based on computational fluid dynamics (CFD) principles, facilitated the comprehensive analysis of debris behavior under varying flow conditions and allowed for the prediction of blockage probabilities and the assessment of associated flood risks. These modeling-based approaches enabled researchers to simulate complex scenarios and evaluate the effectiveness of different mitigation strategies, such as debris traps, in reducing the impact of blockage on hydraulic infrastructure.

Concurrently, there was a significant shift towards the utilization of advanced video monitoring technology for real-time detection and quantification of debris blockage (see [47], [48], [54], [60], [65], [69]). Streamside videography, coupled with UAVs and remote sensing techniques, enabled researchers to automate the identification, classification, and quantification of debris accumulation in culverts and bridges. This transition to advanced video monitoring provided a more comprehensive understanding of the spatial and temporal dynamics of blockage occurrences, allowing for the development of predictive models for the assessment of potential blockage risks during extreme flow events.

Furthermore, the integration of AI techniques has revolutionized the field of blockage management, allowing for the development of intelligent systems capable of automated analysis and prediction (see [35], [68], [70], [71], [72]). AI-based solutions, such as deep learning algorithms and computer vision models, have facilitated the real-time monitoring and assessment of blockage occurrences, enabling the timely implementation of preventive measures and effective decision-making in response to evolving hydraulic conditions. These AI-based studies have enhanced the accuracy and efficiency of blockage management strategies, providing valuable insights into the identification of different types of debris and their potential impacts on hydraulic infrastructure during flood events.

In summary, the reviewed literature provided valuable insights into the understanding and management of culvert blockage, emphasizing the importance of considering various factors and employing innovative approaches. Studies have highlighted the significance of LW accumulation, LW transport, bridge pier scouring, hazard risk mapping, culvert opening size, and the consequences of blockage on flood events, such as increased flood levels, diversion of flow, and scouring. Risk-based approaches, physical modeling, field investigations and numerical simulations have been utilized to propose design guidelines, evaluate debris behavior, and assess the impact on water levels and hydraulic performance. Furthermore, research has explored the use of remote sensing data, deep learning, and computer vision technologies to automate blockage identification and classification processes, enabling timely maintenance decisions. However, further research is needed to address the blockage by other debris types (e.g., urban, sediment, hybrid), and its impact on flood levels, as well as to develop innovative and comprehensive solutions that can be applied globally. Fig. 8 shows the advancement in blockage related research over the years.Figure 8 Advancement in blockage-related research over time.

Figure 8

5 Challenges

The presented research in the field of blockage at cross-drainage hydraulic structures identified several challenges which are important in understanding, assessing and managing blockage problem. A summary of challenges is identified as follows:• Complex and Nonlinear Nature: Blockage as a phenomena and accumulation of debris at cross-drainage hydraulic structures are highly complex and nonlinear, influenced by a range of factors such as debris characteristics, flow conditions, structural features, and local topography. Therefore, it is a challenging task to model and understand the complex interactions towards assessing the blockage. Several aspects of blockage remain poorly understood such as the dynamics of debris transport, deposition patterns, and the influence of vegetation on blockage formation, which will require further investigation.

• Limited Field Data: To understand the blockage and its hydraulic impacts, engineers argue that hydraulic data from during the peak flooding events impacted by blockage is required, which is often a challenging task and therefore, considered a major lacking. The lack of extensive and detailed field data hampers the development and validation of blockage models and limits the understanding of the factors influencing blockage formation and its hydraulic impacts.

• Data Variability: Blockage events can vary significantly in terms of debris characteristics, flow conditions, and structural configurations. Developing models that can capture this variability is a challenge and will require a diverse training datasets for data-driven modeling.

• Integration of Visual and Hydraulic Assessments: Assessing blockage typically involves a combination of visual inspections and hydraulic measurements. However, integrating these two assessments and establishing a quantifiable relationship between visual observations and hydraulic impacts of blockage is challenging. The development of robust methodologies that can bridge the gap between visual and hydraulic assessments is necessary to improve the accuracy and reliability of blockage evaluation.

• Computational and Technical Limitations: The computational complexity of modeling blockage, particularly in large-scale hydraulic systems, can be computationally demanding. It requires efficient algorithms, computational resources, and specialized software tools. Overcoming these computational and technical limitations is necessary to enable the practical implementation of blockage assessment models.

6 Opportunities

Although, there were several challenges identified by the reviewed literature related to addressing blockage issues, however, this also presented opportunities for future research in this domain. Followings are a few of the research opportunities to explore in the field of blockage assessment at cross-drainage hydraulic structures:• Data-Driven Modeling: Given the success of AI and Machine Learning approaches in efficiently managing the complex real-world problems, it is of high interest to subject the blockage problem to this field. Although, there are a few research articles reported in this context, however, still there is a lot of scope. For example:– The blockage assessment methods consider a fundamental assumption that blockage is an instantaneous entity, and assessed blockage for a given instance without taking contextual information into account. However, field observations and gradual accumulation of debris to form the blockage suggest that exploring blockage as a time-series or sequential problem may provide better insight into the problem. In this context, the latest AI models, including Transformer [74], Long Short Term Memory (LSTM) [75], Recurrent Neural Network (RNN) [76] and Gated Recurrent Unit (GRU) [77] can be implemented to assess blockage.

– Given that, from a practical perspective, collecting hydraulic data is expensive and difficult compared to visuals, it is desired to use hydraulic data during training only. One such framework of training machine learning models is referred to as Learning using Privileged Information (LUPI) [78]. In this context, hydraulic data can be used during the training process only as privileged information and models can be trained with the capability to assess blockage using visual data only.

– The ray-tracing approach can be implemented to improve photo-realism and multiple background scenes can be added to enhance diversity of simulated data for computer vision based assessments. For the generation of simulated representatives of real-world data, Generative Adversial Networks (GAN) [79] can be explored and are anticipated to generate encouraging results.

– Given that video-based solutions already proposed by researchers for continuous monitoring of hydraulic structures [47], [48], [54], [60], [65], [69], [71], there exists a potential gap to link the video-based velocimetry techniques [80], [81] for hydraulic discharge measurements. This could also lead towards use of same camera towards measuring hydraulic parameters such as water levels and surface velocities.

• Improved Modeling Techniques: Advances in modeling techniques, such as CFD, can contribute to better understanding and predicting blockage behavior. CFD simulations using latest tools such as FLOW 3D can simulate blockage formation, deposition patterns, and hydraulic impacts, enabling the design of hydraulic structures with improved resilience to blockage. Incorporating realistic debris transport and deposition models into hydraulic simulations can provide valuable insights into blockage dynamics.

• Integration of Multi-Disciplinary Expertise: Blockage research can benefit from collaboration among different disciplines such as civil engineering, hydrology, ecology, and environmental science. Integrating knowledge and expertise from multiple fields can lead to holistic solutions that consider both hydraulic performance and ecological considerations. Collaborative efforts can enhance the understanding of blockage processes and support the development of effective blockage management strategies. The same concept was coined by Iqbal et al. [82] to demonstrate the importance of considering the opinions of the experts from the target application domain while developing a technology-oriented solution.

• Realistic Simulation and Testing: The use of realistic simulation and testing methods can enhance blockage research. Physical and numerical modeling techniques can be employed to replicate real-world scenarios and investigate blockage processes. Physical models can help understand the fundamental aspects of blockage, while numerical models can simulate various scenarios and assess the effectiveness of mitigation measures. These simulation and testing methods can inform the development of design guidelines and improve the resilience of hydraulic structures.

• Proactive Blockage Management: The development of proactive blockage management strategies is an opportunity to minimize the impacts of blockage events. Early warning systems, remote sensing technologies, and real-time monitoring can help identify potential blockage risks and enable timely interventions. By implementing proactive measures, such as debris traps, regular maintenance, and vegetation management, the occurrence and severity of blockage events can be reduced.

• Resilient Infrastructure Design: Designing hydraulic structures with resilience to blockage is an important opportunity. Innovative design approaches, such as self-cleaning culverts or culverts with adjustable openings, can minimize the likelihood of blockage and improve system performance during extreme events. Integrating resilience concepts into the design process can enhance the overall performance and longevity of hydraulic structures.

• Policy Development and Guidelines: Advancements in blockage research can inform the development of policies and guidelines for blockage management. Incorporating scientific findings into design codes and regulations can promote standardized practices and ensure the resilience of hydraulic systems. The collaboration between researchers, practitioners, and policymakers can facilitate the translation of research outcomes into practical guidelines and regulations.

7 Conclusion

Blockage of cross-drainage hydraulic structures is reported as a highly non-linear and complex phenomenon, mainly because of the uncertain behavior of debris interaction and accumulation at hydraulic structures. Different perspectives have emerged from the literature regarding the interpretation of blockage in cross-drainage hydraulic structures. One perspective prioritizes hydraulic analyses during peak floods, aiming to understand blockage's influence on upstream water levels and subsequent flood dynamics. Conversely, the other viewpoint advocates for leveraging visual data as a means to evaluate blockage. However, this visual approach faces skepticism from hydraulic design engineers, primarily due to its conflicting assumptions and potential inaccuracies. The approach of using scaled physical models of cross-drainage hydraulic structures is adopted in the literature to investigate different aspects of blockage, however, these are limited by numbers and comprehensiveness. In addition to that, field investigations and 2D modeling approaches have been identified to investigate the impact of LW blockage in rivers. Video-based monitoring of structures for debris budgeting is another approach reported in literature. The impacts of the urban debris and sediment are not as comprehensively addressed as the LW. Several challenges were identified from the reviewed literature including limited field data, data variability, complexity, integration of visual and hydraulic information, and computational/practical limitations. Furthermore, review also highlighted the potential future research opportunities including data-driven modeling using computer vision and artificial intelligence approaches, improved modeling using CFD tools (e.g., FLOW 3D), collaboration with multi-disciplinary experts, realistic physical representation/modeling, resilient designs and development of efficient policy/guidelines.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used ChatGPT in order to get assistance with improving the language and readability of manuscript. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

CRediT authorship contribution statement

Umair Iqbal: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Muhammad Zain Bin Riaz: Writing – review & editing, Methodology, Formal analysis.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

1 Restriction of the inlet to a stormwater conveyance like pipe, culvert or channel degrading its flow capacity (ARR Manual 2019 [2]).

2 Floating or submerged material, such as logs, vegetation or trash, transported by a stream (FHWA-IF-04-016 HEC-09 [3], ARR-Project 11 [2], [4]).
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