Estimation of Flow-Duration Curves at Ungaged Sites in Southern New England

Archfield, Stacey A.; Vogel, Richard M.; Brandt, Sara L.

doi:10.1061/40927(243)407

Cited by 10 publications

(4 citation statements)

References 4 publications

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“…The pattern does not indicate a clearly preferred distribution, especially considering that the large sample sizes associated with these series result in negligible sampling variability. Archfield et al (2007, Figure 3) used L-moment diagrams for complete series of daily streamflow observations to demonstrate that the sampling variability in Lmoment ratios is negligible for the sample sizes considered in this study. Thus, the scatter shown in Figure 1 is likely due to real distributional differences rather than due to sampling variability as is often the case when one constructs L-moment diagrams for short AMS rainfall records.…”

Section: Probability Plot Correlation Coefficient Goodness-of-fit Evamentioning

confidence: 99%

The Probability Distribution of Daily Rainfall in the United States

Hanson

Vogel

2008

World Environmental and Water Resources Congress 2008

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Choosing a probability distribution to represent the precipitation depth at various durations has long been a topic of interest in hydrology. Early study into the distribution of wet-day daily rainfall has identified the 2-parameter Gamma (G2) distribution as the most likely candidate distribution based on traditional goodness of fit tests. This paper uses probability plot correlation coefficient test statistics and Lmoment diagrams to examine the complete series and wet-day series of daily precipitation records at 237 U.S. stations. The analysis indicates that the Pearson Type-III (P3) distribution fits the full record of daily precipitation data remarkably well, while the Kappa (KAP) distribution best describes the observed distribution of wet-day daily rainfall. We also show that the G2 distribution performs poorly in comparison to either the P3 or KAP distributions.

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Section: Probability Plot Correlation Coefficient Goodness-of-fit Evamentioning

confidence: 99%

The Probability Distribution of Daily Rainfall in the United States

Hanson

Vogel

2008

World Environmental and Water Resources Congress 2008

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“… Vogel and Fennessey [1995] note that daily streamflows originate from highly skewed populations, and sample estimates of distribution parameters may contain large bias even for sites with very long records. A number of different statistical functions have been used to model daily flow distributions, including the lognormal, exponential, γ , and pareto [ Fennessey and Vogel , 1990; Vogel and Fennessey , 1993; Nash , 1994; Potter , 2001; Vogel et al , 2003; Castellarin et al , 2004; Goodwin , 2004; Doyle et al , 2005; Mueller and Pitlick , 2005; Archfield et al , 2007; Doyle and Shields , 2008]. The procedure for fitting these distributions is straightforward, and any one of them might offer a reasonably good fit to a series of observations.…”

Section: Characterization Of the Distribution Of Daily Flowsmentioning

confidence: 99%

Scaling frequency of channel‐forming flows in snowmelt‐dominated streams

Segura

Pitlick

2010

Water Resources Research

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1] The scaling properties of channel-forming flows are investigated using a regional flow frequency model developed for snowmelt-dominated streams in Colorado. The model is derived from analyses of daily flow records at 32 gauging stations where we have independent measurements of the bankfull discharge. The study sites are located in alpine/subalpine basins with drainage areas ranging from 4 to 3700 km 2 . The frequency distribution of daily flows at these locations can be reproduced with a broken power law (BPL) function described by two free parameters. Both parameters are strongly correlated with drainage area, and based on these correlations, a regional model capable of predicting the frequency of daily flows above the mean annual flow was formulated.The applicability of the model was tested using daily flow records from 32 similar-size basins in Idaho. The frequency distributions of daily flows in snowmelt-dominated streams in Colorado and Idaho with highly predictable hydrographs (i.e., 1 year autocorrelation above 0.7) are well fitted by the BPL function. According to the model, the frequency of flows greater than bankfull decreases downstream from about 15 d/yr in headwater reaches to about 6 d/yr in downstream reaches. These results imply that the basin response to precipitation and runoff is nonlinear. This multiscaling behavior can be physically interpreted as the result of scale-dependent variations in runoff and sediment supply, which influence downstream trends in the bankfull channel geometry and intensity of sediment transport.Citation: Segura, C., and J. Pitlick (2010), Scaling frequency of channel-forming flows in snowmelt-dominated streams, Water Resour. Res., 46, W06524,

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“…Many continuous probability distribution functions have been used to represent daily stream flow, which are generally highly positively skewed, including the two‐parameter lognormal, gamma, Generalized Pareto, exponential, as well as broken power law functions [e.g., Vogel et al ., ; Goodwin , ; Archfield et al ., ; Quader and Guo ; Segura and Pitlick , ]. In general, continuous PDFs fit natural flow records with mixed results, especially in the right tail of the distribution and in multimodal cases [ Nash , ; Segura and Pitlick , ].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Physical context for theoretical approaches to sediment transport magnitude‐frequency analysis in alluvial channels

Sholtes

Werbylo

Bledsoe

2014

Water Resources Research

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Theoretical approaches to magnitude-frequency analysis (MFA) of sediment transport in channels couple continuous flow probability density functions (PDFs) with power law flow-sediment transport relations (rating curves) to produce closed-form equations relating MFA metrics such as the effective discharge, Q eff , and fraction of sediment transported by discharges greater than Q eff , f1, to statistical moments of the flow PDF and rating curve parameters. These approaches have proven useful in understanding the theoretical drivers behind the magnitude and frequency of sediment transport. However, some of their basic assumptions and findings may not apply to natural rivers and streams with more complex flowsediment transport relationships or management and design scenarios, which have finite time horizons. We use simple numerical experiments to test the validity of theoretical MFA approaches in predicting the magnitude and frequency of sediment transport. Median values of Q eff and f1 generated from repeated, synthetic, finite flow series diverge from those produced with theoretical approaches using the same underlying flow PDF. The closed-form relation for f1 is a monotonically increasing function of flow variance. However, using finite flow series, we find that f1 increases with flow variance to a threshold that increases with flow record length. By introducing a sediment entrainment threshold, we present a physical mechanism for the observed diverging relationship between Q eff and flow variance in fine and coarse-bed channels. Our work shows that through complex and threshold-driven relationships sediment transport mode, channel morphology, flow variance, and flow record length all interact to influence estimates of what flow frequencies are most responsible for transporting sediment in alluvial channels.

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Estimation of Flow-Duration Curves at Ungaged Sites in Southern New England

Cited by 10 publications

References 4 publications

The Probability Distribution of Daily Rainfall in the United States

The Probability Distribution of Daily Rainfall in the United States

Scaling frequency of channel‐forming flows in snowmelt‐dominated streams

Physical context for theoretical approaches to sediment transport magnitude‐frequency analysis in alluvial channels

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