A rainfall-runoff simulation model for estimation of flood peaks for small drainage basins

Dawdy, David R.; Lichty, Robert W.; Bergmann, James M.

doi:10.3133/pp506b

Cited by 103 publications

(50 citation statements)

References 13 publications

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“…Researchers have long used United States Geologic Survey (USGS) streamflow data for hydrologic modeling, but traditionally, the emphasis was on model calibrations (James, 1972;Dawdy et al, 1972;Magette et al, 1976). Basin streamflow data are useful in broad-scale modeling, calibration, and validation because measurements integrate ecosystem water input, movement, and usage.…”

Section: Wateruse Validationmentioning

confidence: 99%

Predictions and Projections of Pine Productivity and Hydrology in Response to Climate Change Across the Southern United States

McNulty¹,

Vose²,

Swank³

1998

Ecological Studies

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Section: Wateruse Validationmentioning

confidence: 99%

Predictions and Projections of Pine Productivity and Hydrology in Response to Climate Change Across the Southern United States

McNulty¹,

Vose²,

Swank³

1998

Ecological Studies

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“…Table 1 (page 35) summarizes the model parameters and their application in the modeling process; (all tables are at end of report). For a more complete description of the model see Dawdy, Lichty, and Bergmann (1972).…”

Section: Rainfall-runoff Modelmentioning

confidence: 99%

“…Rainfall-runoff modeling is undertaken because relatively long records (60 to 70 years) of rainfall are available at many locations throughout the country. Basically, the concept is that the information contained in the long-term rainfall records can be transformed to streamflow information by synthesizing a long record of annual floods using a calibrated rainfall-runoff model, such as that developed by Dawdy, Lichty, and Bergmann (1972). That is, a short record of observed floods can be effectively lengthened, and the time-sampling error inherent in small samples can be reduced, by the rainfall-runoff modeling process.…”

Section: Introductionmentioning

confidence: 99%

A rainfall-runoff modeling procedure for improving estimates of T-year (annual) floods for small drainage basins

Lichty¹,

Liscum²

1978

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16. Abstracts Maps depicting the influence of a climatic factor, C, on the magnitude of synthetic T-year (annual) floods were prepared for a large portion of the eastern United States. The climatic factors were developed by regression analysis of flood data generated using a parametric rainfall-runoff model and long-term rainfall records. Map estimates of C values and calibrated values of rainfall-runoff model parameters were used as variables in a synthetic T-year flood relation to compute "map-model" flood estimates for 98 small drainage basins in a six-state study area. Improved estima,tes of T-year floods were computed as a weighted average of the map-model estimate and an observed estimate, with the weights proportional to the relative accuracies of the two estimates. The accuracy of the map-model estimates was appraised by decomposing components of variance into average time-sampling error associated with the observed estimates and average map-model error. Map-model estimates have an accuracy, in terms of equivalent length of observed record, that ranges from 6 years for the 1.25-year flood up to 30 years for the 50-and 100-year flood._____________________ ABSTRACTThe U.S. Geological Survey rainfall-runoff model is used to synthesize a sample of 550 annual-flood series, that are representative of both rural-and impervious-area model applications, using data from each of 36 long-term recording rainfall sites. A flood-frequency curve is developed for each annual-flood series, and a single-coefficient, regression relation for the 2-, 25-, and 100-year floods is developed for each one of the rainfall sites a generalized definition of the model output as a function of the model parameters for each rainfall site. The site-to-site variability in the magnitude of the coefficient that characterizes the synthetic T-year (annual) flood relation is interpreted as reflecting the spatially varying influence of local climatic factors, C{, 9 on the results of synthesis. Three contour maps that depict the geographic variability of the climatic factor were prepared. Estimates of the C^ values taken from these maps were used in conjunction with fitted rainfall-runoff model parameters and the synthetic T-year flood relation to develop map-model, T-year flood estimates for 98 rural-area streamflow stations located in Missouri, Illinois, Tennessee, Mississippi, Alabama, and Georgia. Comparisons of these flood estimates with those based on observed annual floods show that the map-model estimates are generally lower than the observed estimates for return periods greater than the 2-year recurrence interval. This tendency to underestimate the higher recurrence interval floods was removed by use of an average adjustment factor, B£, and the average accuracy of "unbiased", map-model flood estimates was appraised for the test sample of 98 streamflow stations. The accuracy of the map-model estimates increases rapidly with increasing recurrence interval up to the 10-year interval, and then reverses its trend and decreases slowly. The ma...

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“…The rainfall-runoff model was developed by the Geological Survey (Dawdy, Lichty, and Bergmann, 1972) specifically for the purpose of modeling flood-runoff hydrographs from small watersheds.…”

Section: Synthesized Flood Datamentioning

confidence: 99%

Techniques for estimating magnitude and frequency of floods in South Carolina

Whetstone¹

1982

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A rainfall-runoff simulation model for estimation of flood peaks for small drainage basins

Cited by 103 publications

References 13 publications

Predictions and Projections of Pine Productivity and Hydrology in Response to Climate Change Across the Southern United States

Predictions and Projections of Pine Productivity and Hydrology in Response to Climate Change Across the Southern United States

A rainfall-runoff modeling procedure for improving estimates of T-year (annual) floods for small drainage basins

Techniques for estimating magnitude and frequency of floods in South Carolina

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