Theoretical derivation of the index flood

Gioia, Andrea; Fiorentino, Mauro; Iacobellis, Vito; Margiotta, Maria Rosaria

doi:10.5194/adgeo-2-249-2005

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…A comparison of some of those methods has been carried out by Grover et al (2002), who analyzed the use of method OLS (Ordinary Least Squares), and the WLS method (Weighted Least Squares). A geomorphological approach has been used by Gioia et al (2005) introducing a simple hypothesis regarding the probability distribution of flood discharges and rainfalls in the estimation of the index flood.…”

Section: Introductionmentioning

confidence: 99%

Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy

Noto

Loggia

2008

Water Resour Manage

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Extremely great floods are among environmental events with the most disastrous consequences for the entire world. Estimates of their return periods and design values are of great importance in hydrologic modeling, engineering practice for water resources and reservoirs design and management, planning for weatherrelated emergencies, etc. Regional flood frequency analysis resolves the problem of estimating the extreme flood events for catchments having short data records or ungauged catchments. This paper analyzes annual maximum peak flood discharge data recorded from more than 50 stream flow gauging sites in Sicily, Italy, in order to derive regional flood frequency curves. First these data are analyzed to point out some problems concerning the homogeneity of the single time series. On the basis of the L-moments and using cluster analysis techniques, the entire region is subdivided in five subregions whose homogeneity is tested using the L-moments based heterogeneity measure. Comparative regional flood frequency analysis studies are carried out employing the L-moments based commonly used frequency distributions. Based on the L-moment ratio diagram and other statistic criteria, generalized extreme value (GEV) distribution is identified as the robust distribution for the study area. Regional flood frequency relationships are developed to estimate floods at 2208 L.V. Noto, G. La Loggia various return periods for gauged and ungauged catchments in different subregions of the Sicily. These relationships have been implemented using the L-moment based GEV distribution and a regional relation between mean annual peak flood and some geomorphologic and climatic parameters of catchments.

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Section: Introductionmentioning

confidence: 99%

Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy

Noto

Loggia

2008

Water Resour Manage

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“…To estimate flood frequency at ungauged drainage basins, flood frequency analysis using regression analysis is performed (9). In regional methods for flood prediction, the estimation of the index flood is a crucial point in order to attain reliable predictions in ungauged basins (10). In recent years, the regression methods have been successfully employed and demonstrated satisfactory results (11)(12)(13).…”

Section: Introductionmentioning

confidence: 99%

Comparison of hybrid regression and multivariate regression in the regional flood frequency analysis: A case study in Khorasan Razavi province

Hosseini

Khaleghi

Jami

et al. 2018

Environ Health Eng Manag

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Background: Magnitude, rate and frequency of the stochastic and unexpected events are of great significance and importance in hydrology. Nowadays, for economic planning of the projects, the use of analytical methods of unexpected events in hydrology is unavoidable. The aim of this study was to compare hybrid regression and multivariate regression to estimate flood peak discharge in the province of Khorasan Razavi and in the selected water measured stations. Methods: For this purpose, 19 hydrometric stations were selected and analyzed. In the first step, the rate of peak discharge was estimated with different return periods and by selecting the best regional distribution (lognormal distribution type ΠΙ). In the next step, independent and important variables including area, mean annual rainfall, the average height of the watershed and its slope were determined using functional analysis and using SPSS software version 22. Then, two hydrologically homogeneous regions were determined by homogeneity test using cluster analysis, and accordingly, two models were presented for the whole area and also for homogeneous areas. To compare and evaluate the accuracy and efficiency of the estimated models, the rates of discharges were estimated and compared with observational rates using three control watersheds. To compare models, it was used from the average absolute values of the relative error index. Results: It was revealed that the hybrid method was more accurate than the multivariate regression method in the return period of 50 years and provides better results of flood discharges for the area. Homogenous areas had a higher coefficient of determination (R 2) and lower relative standard error (RSE) compared to the whole area. It was also revealed that with increase of return period, the rates of R 2 decreased but the rates of relative standard error increased. Conclusion: The accuracy of multivariate regression and hybrid methods was the same in the 25-year return period. In the present study, the importance and necessity of homogenous areas compared with the model of the whole area are completely evident.

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“…There is no doubting about the novelty of the model proposed by Iacobellis and Fiorentino [2000] and Fiorentino et al [2006]. However, in spite of providing an analytical expression for the mean annual flood (see Iacobellis et al [2002] and Gioia et al [2005] for some other known properties), these papers did not provide a complete description of the theoretical probability distribution of Q . In this note, we derive various probabilistic properties of Q .…”

Section: Introductionmentioning

confidence: 99%

Exact distribution of the peak streamflow

Nadarajah

2007

Water Resources Research

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[1] Iacobellis and Fiorentino (2000) and Fiorentino et al. (2006) proposed modeling the peak of direct streamflow as a product of two independent random variables: one gamma distributed and the other Weibull distributed. However, the papers did not provide any results on the theoretical probability distribution of the peak streamflow. In this note, we derive explicit expressions for the probability density function, cumulative distribution function, and the moment measures of the peak streamflow. We also show how one could determine the percentiles of the peak streamflow. The results of this note could be applied more widely than just for the modeling of peak streamflow.

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Theoretical derivation of the index flood

Cited by 3 publications

References 6 publications

Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy

Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy

Comparison of hybrid regression and multivariate regression in the regional flood frequency analysis: A case study in Khorasan Razavi province

Exact distribution of the peak streamflow

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