Physiographic characteristics of bridge‐stream intersections

Johnson, Peggy A.

doi:10.1002/rra.924

Cited by 14 publications

(14 citation statements)

References 24 publications

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“…All of the study reaches are located within Eastern U.S (Appalachian Highland and Coastal Plain). Across Eastern USA there exist distinct regional conditions that can induce channel instability (Johnson, 2006). In Appalachian Plateau, the removal of vegetation tends to produce high instability (Johnson, 2006).…”

Section: Intrinsic Channel Instability At Regional Scalementioning

confidence: 99%

“…Across Eastern USA there exist distinct regional conditions that can induce channel instability (Johnson, 2006). In Appalachian Plateau, the removal of vegetation tends to produce high instability (Johnson, 2006). In Piedmont, the potential of debris jam and bedrock outcropping is high (Johnson, 2006).…”

Section: Intrinsic Channel Instability At Regional Scalementioning

confidence: 99%

“…The high variability of the exponents is attributed to the system instability (Phillips, 1990) and myriad factors controlling AHG (Shen, Wang, & Liu, 2016). Nonetheless, recent activities in stream restoration have motivated the development of regional equations that provide stream width and depth as a function of bankfull discharge (Johnson, 2006). These equations have been developed within specific physiographic regions for channels that are likely to be stable (Johnson, 2006).…”

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confidence: 99%

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At‐a‐station hydraulic geometry for reaches with bridge collapse events

Ashraf

Spaunhorst

2022

River Research & Apps

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This study explores the at‐a‐station hydraulic geometry (AHG) for reaches with bridge collapse events. Eighteen reaches in Eastern United States, thirteen reaches in Appalachian Highland, and five reaches in Coastal Plain are examined. The methodology applied for retrieving AHG uses LiDAR (Light detection and ranging) data, and the study results are checked for both hydraulic and geomorphic consistency. The resulting data set is composed of five to thirty‐five measurements of water surface width, mean depth, and mean velocity at each of the 181 cross‐sections. The exponents of the AHG relationships vary considerably. Nonetheless, for most of the cross‐sections, width responds more rapidly to changing discharge, and velocity exponents are less than the width and depth exponents combined. Wide shallow channels with highly erodible beds and/or banks, the ability to transport large bed materials, and the ability to attain a super‐critical condition—are the common profile extracted for most of the cross‐sections across all sites. A definitive AHG configuration is found for the sites with the least human interference. Comparatively low variation of bank‐full geometry is also found for the sites with the least human interference. The prevalence of low flows and/or lower return periods of heavy‐tail flows are also exhibited for most of the sites. The study results suggest that the stream channel instability can be reasonably understood and predicted from AHG particularly if human interference is limited within the watershed. These findings have implications not only for the study of the risk of bridge collapse and bridge design but also to characterize instability in a more rigorous and practical way.

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Section: Intrinsic Channel Instability At Regional Scalementioning

confidence: 99%

Section: Intrinsic Channel Instability At Regional Scalementioning

confidence: 99%

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confidence: 99%

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At‐a‐station hydraulic geometry for reaches with bridge collapse events

Ashraf

Spaunhorst

2022

River Research & Apps

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“…It is possible that other hydraulic events may induce scour, accumulating over a long period of time even at low flows, resulting in total/partial bridge collapse. In fact, in the Appalachian Highland (a) debris jam causing increased flooding, (b) high erodible soil causing accelerated rate of channel widening, lateral migration and vertical degradation, and (c) high channel modification resulting in destabilized channels, led to accelerated scour even at low flows [54][55][56]. b.…”

Section: Collapse Causementioning

confidence: 99%

Analysis of Peak Flow Distribution for Bridge Collapse Sites

Ashraf

Flint

2019

Water

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Bridge collapse risk can be evaluated more rigorously if the hydrologic characteristics of bridge collapse sites are demystified, particularly for peak flows. In this study, forty-two bridge collapse sites were analyzed to find any trend in the peak flows. Flood frequency and other statistical analyses were used to derive peak flow distribution parameters, identify trends linked to flood magnitude and flood behavior (how extreme), quantify the return periods of peak flows, and compare different approaches of flood frequency in deriving the return periods. The results indicate that most of the bridge collapse sites exhibit heavy tail distribution and flood magnitudes that are well consistent when regressed over the drainage area. A comparison of different flood frequency analyses reveals that there is no single approach that is best generally for the dataset studied. These results indicate a commonality in flood behavior (outliers are expected, not random; heavy-tail property) for the collapse dataset studied and provides some basis for extending the findings obtained for the 42 collapsed bridges to other sites to assess the risk of future collapses.Water 2020, 12, 52 2 of 25 are used to directly define an extreme value distribution; and peaks over-threshold (POT), in which distributions are fit to both the frequency of floods above a threshold and their magnitudes. The U.S. Water Resources Council requires the use of log-Pearson type 3 (LP3) distributions for the annual maxima approach, although the generalized extreme value distribution (GEV) seems to be the most widely used model for extreme events [7]. The major benefit of the GEV model is its ability to fit highly skewed data [7]. Therefore, recent hydrologic research has focused on explaining the parameters of the GEV distribution of streamflow extremes [8][9][10][11][12][13][14].If annual maximum exceedances are assumed to be GEV-distributed, the POT exceedances are assumed to be generalized Pareto (GP)-distributed [15], following recommendations in the field of statistics [16,17]. Fitting the GP distribution to exceedances over a high threshold and also estimating the frequency of exceeding the threshold by fitting a Poisson distribution allows for the simultaneous fitting of parameters concerning both the frequency and intensity of extreme events. Compared to the annual maxima approach, therefore, the main advantage of POT modeling is that it allows for a more rational selection of events to be considered as "floods" and is not confined to only one event per year. The POT approach considers a wide range of events and provides the possibility of controlling the number of flood occurrences to be included in the analysis by appropriate selection of the threshold. However, the POT approach remains under-employed mainly because of the complexities associated with the choice of threshold and the selection of criteria for retaining flood peaks (Lang et al. (1999)). Nonetheless, threshold selection is tightly linked to the choice of the process distribution, to t...

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“…Erosion increases on the disturbed land surface due to recontouring and leveling during construction (Wohl 2006). Alteration of natural stream channels by channel realignment, placement of culverts, and construction of bridges also can occur (Johnson 2006).…”

Section: Aquatic Systemsmentioning

confidence: 99%

Evaluating the Effects of the Blennerhassett Island Bridge Crossing (Ohio River) on Soil, Vegetation, and Wildlife

Vance¹

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, I researched the impacts of the Blennerhassett Island Bridge upon vegetation, soil, and the following wildlife groups: waterbirds, songbirds, anurans, turtles, small mammals, and furbearers. Comparisons were made to two other islands (Buckley Island [bridge crossing present for about 45 years] and Muskingum Island [no bridge crossing]), to three distances from the bridge (0 [under], 100, and 300 m), and to pre-construction data collected during the 1985-1987 and 1998-2000 time periods. Over the course of this study, 170 plant, 19 waterbird, 60 songbird, 7 anuran, 5 turtle, 9 small mammal, and 4 furbearer species were detected among the three islands. Also, 19 soil variables were analyzed. Vegetative communities were different under the bridge compared to other sampling distances and pre-construction data. Vegetative communities were composed of species from the seed mixture used for reclamation, exotic and invasive species, and disturbance tolerant species with low herbaceous cover and minimal woody plants. Thirteen soil variables (phosphorus, bray II phosphorus, potassium, sodium, calcium, manganese, soluble sulfur, zinc, aluminum, copper, total exchange capacity, organic matter, and estimated nitrogen released) had altered levels under the Blennerhassett Island Bridge and/or Buckley Island Bridge. Great blue heron (Ardea herodias) abundances were lower at islands with bridges. Songbird abundances were lower under the bridge and species composition differed compared to other distances with generalist species present under the bridge. Carolina chickadee (Poecile carolinensis), Carolina wren (Thryothorus ludovicianus), and common yellowthroat (Geothlypis trichas) abundances were lower under the bridge and rock pigeon (Columba livia), cliff swallow (Petrochelidon pyrrhonota), and European starling (Sturnus vulgaris) abundances were highest under bridges. Overall small mammal abundance, richness, and diversity were lower under the new bridge compared to other distances and abundances of Peromyscus spp. were lower under the new bridge. Raccoon (Procyon lotor) occurrences were lower under the new bridge compared to other sites and distances. Anurans and turtles showed no differences among islands and distances. The Blennerhassett Island Bridge was found to have some impacts to vegetation, soil, and wildlife. These impacts, however, are minor in scale and are mostly limited to the area directly under the bridge and did not impact large portions of Blennerhassett Island or the adjacent mainlands. Some of these impacts under the bridge include: altered soil chemistry, altered amount and type of vegetation, attraction of exotic and non-native vegetation, lower abundances and different composition of songbirds, attraction of urbanized songbird species, lower abundance, richness, and diversity of small mammals, and changes and alteration in habitat. I recommend that all possible care should be taken during future bridge construction to minimize environmental impacts to vegetation, soil, and wildlife and to restore the imp...

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Physiographic characteristics of bridge‐stream intersections

Cited by 14 publications

References 24 publications

At‐a‐station hydraulic geometry for reaches with bridge collapse events

At‐a‐station hydraulic geometry for reaches with bridge collapse events

Analysis of Peak Flow Distribution for Bridge Collapse Sites

Evaluating the Effects of the Blennerhassett Island Bridge Crossing (Ohio River) on Soil, Vegetation, and Wildlife

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