Potential and Application of Flood Frequency Determinations

Beard, Leo R.

doi:10.1007/978-94-009-3955-4_16

Cited by 6 publications

(16 citation statements)

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“…This is because the accretion sets that formed the bar mimic the contemporary channel bottom and the bedforms that generated the structures would also have also parallelled the channel bottom. floods between or as part of larger principal flood events in modern dryland settings (Patterson, 1963(Patterson, , 1965Gupta & Fox, 1974;Beard, 1975;Baker, 1977;Zawada, 1994Zawada, , 2000Macklin et al, 2010;Tooth & Nanson, 2011;Tooth, 2013;Milan et al, 2018). The UCHs channel fills could thus represent small floods, or alternatively smaller flows locally within larger floods that may have generated deeper channels elsewhere.…”

Section: Channel-scale Architectural Elementsmentioning

confidence: 99%

Structures, architecture, vertical profiles, palaeohydrology and taphonomy of an upper‐flow‐regime‐dominated fluvial system, the Triassic Dockum Group of the Palo Duro Canyon, Texas

Walker

Holbrook

2022

Sedimentology

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Triassic strata of the Tecovas and Trujillo formations in the Palo Duro Canyon of West Texas record deposition dominated throughout by upper‐flow‐regime channel flow. These strata provide an opportunity for new insights into the architecture, floodplain/channel processes, vertical profiles, palaeohydrology and taphonomy typical of broader upper‐flow‐regime‐dominated fluvial systems. Thicker channel‐fills (ca 2 m, aspect ratio ca 24) host upper‐plane‐bed, symmetrical antidune, breaking‐antidune, chute‐and‐pool, and cyclic‐step structures. The thinner channel‐fill population (<1 m, aspect ratio ca 35) comprises upper‐plane‐bed and some antidune structures. Some of the larger channel fills developed low‐angle downstream‐accreting bars, with rare examples of laterally accreting side‐attached bars. This appears to be the first documentation of an ancient upper‐flow‐regime side‐attached bar. Lamina orientation of structures parallel accretion surfaces because these followed the original bed surface, and structures drop in flow regime down the bar surfaces as formative Froude numbers also declined. A generalized vertical sequence for large upper‐flow‐regime channel storeys has upper‐plane‐bed structures above the basal scour, transitioning upward into higher flow regime structures (for example, antidunes, cyclic steps, etc.), then back to a mix of upper‐plane‐bed and antidunes or lower‐flow‐regime structures towards the top. The Tecovas Formation and overlying Trujillo Sandstone both bear layers of cross‐cutting laterally amalgamated valley fills, multivalleys, and are separated by a regional sequence boundary. Calculated palaeodischarges for Tecovas (ca 90 m3/s) and Trujillo (ca 76 m3/s) rivers record flow at the stage where symmetrical antidunes were deposited. These discharges occurred at some point on the falling limb of a flood hydrograph of currently unknown shape. Slopes for the rivers were on the order of 10−4 to 10−5, consistent with typical continental‐interior rivers. Large and flashy discharge was, thus, the likely cause for supercritical‐flow conditions instead of excessive slopes. Rivers in both the Tecovas and Trujillo formations record a fluvial system developed in a tropical to subtropical megamonsoonal environment. The tendency for preservation of metre‐scale channel‐fills and catastrophic inundations of floodplains and lakes in single floods has also made the Dockum Group a prolific preserver of large Triassic vertebrates.

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Section: Channel-scale Architectural Elementsmentioning

confidence: 99%

Structures, architecture, vertical profiles, palaeohydrology and taphonomy of an upper‐flow‐regime‐dominated fluvial system, the Triassic Dockum Group of the Palo Duro Canyon, Texas

Walker

Holbrook

2022

Sedimentology

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“…The Beard flash flood index (F; Beard, 1975) was utilized to quantify flashiness, with a greater difference between the magnitude of large floods and more typical annual floods resulting in more hazardous conditions. The index was computed for each streamgaged watershed (Figure S11) and averaged for each zone, with these averages varying from 1.30 to 0.49 (Table 1).…”

Section: Flood Indicesmentioning

confidence: 99%

“…Six regions where flash floods have been more frequent were identified, including the eastern slopes of the Southern Rocky Mountains and adjacent Great Plains (Saharia, Kirstetter, Vergara, Gourley, Hong, & Giroud, 2017). There have been a number of flashiness indices proposed, with computations based on the variability of peak flows (Baker et al, 2004;Beard, 1975;Smith & Smith, 2015), characteristics of the flood hydrographs (Gourley et al, 2013;Saharia, Kirstetter, Vergara, Gourley, Hong, & Giroud, 2017), as well as predictions based on watershed characteristics (Smith, 2010;Zogg & Deitsch, 2013). Additionally, Patton and Baker (1976) utilized a flood potential index based on the Beard flash flood magnitude index (Beard, 1975) and related this to watershed characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…From a hazard perspective, flood flashiness is an additional consideration to the expected flood magnitude. Flood flashiness refers to both how large a flood is compared to typical annual floods (Beard, 1975;Enzel et al, 1993), as well as the rate of short-term change in streamflow (Poff et al, 1997;Saharia, Kirstetter, Vergara, Gourley, Hong, & Giroud, 2017). A greater difference between the magnitude of large floods and more normal (and typically expected) annual peak streamflow, as well as rapid rises in hydrographs, results in more hazardous conditions-when large floods occur, they can be unexpectedly large and rapid rising, compared to more typical events.…”

Section: Introductionmentioning

confidence: 99%

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Methods for Assessing Expected Flood Potential and Variability: Southern Rocky Mountains Region

Yochum

Scott

Levinson

2019

Water Resources Research

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Enhanced understanding of flood hazards, and how they vary across regions and continents, is needed to help protect lives and develop more resilient communities. Using the greater Southern Rocky Mountains region as a study area, a novel methodology was developed to predict, rank, and communicate expected flood magnitudes across similar responding areas (zones). Using 463 streamgages, up to 93% of the variance was explained by regression models developed for 11 derived zones. These regressions define the expected flood potential of each zone, a term introduced to assist practitioners, policy makers, and the public in understanding what flood magnitudes can be expected given the maximum recorded streamgage floods in nearby watersheds. Discharges above the 90% prediction limit, the maximum likely flood potential, are considered extreme; departure above this limit denotes the degree of extremity. The seasonality of the largest 5% floods varied substantially between zones, with the greatest frequency in July, August, and September in some zones (due to the North American monsoon) and May and June in other zones (due to snowmelt and rainfall). Using the lowest flood potential zone as an index area, flood potential and hazard indices were developed for comparing flood hazards across broad regions. The largest floods occur in the southern portion of the eastern slopes of the Southern Rocky Mountains and the adjacent Great Plains, with these events being 15 times larger than floods experienced in central Colorado and New Mexico mountain valleys, on average for a given watershed area.

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“…A variety of probability distributions and parameter estimation methods have been tested as alternatives to the logarithm-Pearson Type 3 (LP3) method-of-moments and the B17B approach to flood-frequency analysis. Probability distribution types include normal, log-normal, Gumbel, log-Gumbel, and two-and three-parameter gamma distribution types (Beard, 1974; Interagency Advisory Committee on Water Data, 1982). The Extreme Value and Wakeby distributions are also commonly used in flood frequency analysis (Houghton, 1978;Rao and Hamed, 2000).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the expected moments algorithm and a multiple low-outlier test for flood frequency analysis at streamgaging stations in Arizona

Paretti¹,

Kennedy²,

Cohn³

2014

Scientific Investigations Report

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Potential and Application of Flood Frequency Determinations

Cited by 6 publications

References 0 publications

Structures, architecture, vertical profiles, palaeohydrology and taphonomy of an upper‐flow‐regime‐dominated fluvial system, the Triassic Dockum Group of the Palo Duro Canyon, Texas

Structures, architecture, vertical profiles, palaeohydrology and taphonomy of an upper‐flow‐regime‐dominated fluvial system, the Triassic Dockum Group of the Palo Duro Canyon, Texas

Methods for Assessing Expected Flood Potential and Variability: Southern Rocky Mountains Region

Evaluation of the expected moments algorithm and a multiple low-outlier test for flood frequency analysis at streamgaging stations in Arizona

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