Regional Estimation of Floods for Ungauged Sites Using Partial Duration Series and Scaling Approach

Gado, Tamer A.; Nguyen, Van‐Thanh‐Van

doi:10.1061/(asce)he.1943-5584.0001439

Cited by 7 publications

(4 citation statements)

References 42 publications

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“…The study concluded that the city's storm drainage design criteria were underestimated. In general, RRFA consists of two main steps: the identification of groups of hydrologically homogeneous regions, and the application of a regional estimation method within each delineated homogeneous group (Gado and Nguyen, 2016).…”

Section: Introductionmentioning

confidence: 99%

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Gado

Hsu

Sorooshian

2017

Journal of Hydrology

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a b s t r a c tThe occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

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Section: Introductionmentioning

confidence: 99%

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Gado

Hsu

Sorooshian

2017

Journal of Hydrology

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“…The selected peak flows need to be independent, for this reason, it is recommended to use a time window equal to the concentration time of the basin. In addition, literature recommends using the minimum annual peak flow in the observed record as peak flow threshold (Gado & Nguyen, 2016;Malamud & Turcotte, 2006;Mohssen, 2009). In this study, we estimate the peak flow quantiles based on Partial Duration Series because a large sample of peak flows can be related to rainfall and soil moisture observations.…”

Section: Extraction Of Peak Flow Quantiles (Q P )mentioning

confidence: 99%

Examining Observed Rainfall, Soil Moisture, and River Network Variabilities on Peak Flow Scaling of Rainfall‐Runoff Events with Implications on Regionalization of Peak Flow Quantiles

Pérez

Mantilla

Krajewski

et al. 2019

Water Resources Research

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The scaling of peak flows associated with a probability of exceedance (Q p ) or a specific rainfall-runoff event (Q R ) with respect to drainage area (A) is known as flood scaling and it has been widely used in peak flow regionalization. The attenuation and aggregation processes within the hillslopes and river network in a rainfall-runoff event, provide a framework to test the scaling of Q R . Although scaling of Q p has been reported in empirical studies, its physical interpretation is compromised, since Q p at each site could come from different rainfall-runoff events. To address this problem, the authors explored the effect of actual variabilities of rainfall and soil moisture fields, and the effect of the river network structure, in the scaling of peak flows of 85 rainfall-runoff events and peak flow quantiles that were observed in the Iowa River Basin at 43 streamflow gauges. The authors established empirical evidence that addresses two questions: (1) What does control the performance of the scaling of observed Q R ? (2) What is the interplay between sampling errors and the selection of explanatory variables in the construction of regional regression models for Q R and Q p ? For the first question, the authors found that the slope magnitude in the scaling of the rainfall intensity fields with respect to A controls the scaling' performance of Q R . Regarding the second question, the authors demonstrate that the inclusion of river network descriptors should improve the regional equations to estimate peak flow quantiles unless stream gauging sampling errors affect the analysis.

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“…RFFA methods or partial duration series can be used (Gado and Nguyen, 2016). In the context of non-12 stationarity, methods can also be employed to take into account this non-stationarity while estimating the 13 associated uncertainties (Sraj et al, 2016).…”

mentioning

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Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

Arnaud

Cantet

Odry

2017

Journal of Hydrology

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Regional Estimation of Floods for Ungauged Sites Using Partial Duration Series and Scaling Approach

Cited by 7 publications

References 42 publications

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Examining Observed Rainfall, Soil Moisture, and River Network Variabilities on Peak Flow Scaling of Rainfall‐Runoff Events with Implications on Regionalization of Peak Flow Quantiles

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

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