Regional flood frequency analysis for<scp>Ç</scp>oruh<scp>B</scp>asin of<scp>T</scp>urkey with<scp>L</scp>‐moments approach

Aydogan, D.; Kankal, Murat; Önsoy, Hızır

doi:10.1111/jfr3.12116

Cited by 24 publications

(28 citation statements)

References 53 publications

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“…The generalized normal extreme value distribution has been identified as the bestfit distribution for the upper-and lower-Menderes subregions. Aydogan et al (2014) conduct a simulation study to compare parametric L-moments and n frequency analysis. Saf (2009) The significance or meaning of this would be that: M100 is the z second, and M130 is the third probability weighted moments.…”

Section: L-moments Methodsmentioning

confidence: 99%

Drought analysis of the Seyhan Basin by using standardized precipitation ındex (spı) and l-moments

SEÇKİN¹

2016

Tarım Bilimleri Dergisi

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The aim of this study is to monitor drought in the Seyhan Basin by using Standardized Precipitation Index (SPI) based on a long term monthly precipitation of 11 meteorological stations and secondly, to also carry out regional frequency analysis using the index flood procedure coupled with the L-moments method based on recorded precipitation data of the most drought month for each year acquired from Standardized Precipitation Index method for each station. The SPI values of each station for 3, 6, 9 and 12-month time scales were calculated. According to the results, all stations are on the boundary of drought. Research results show that the wettest station is Ulukışla and the most drought station is Karaisalı with respect to the average SPI values. According to the drought frequency values, however, the station having the highest drought occurrence frequency is the Karaisalı station, whereas the station having the lowest drought frequency is the Tufanbeyli station. Results show that the Seyhan Basin is on the boundary of drought and mildly wet. Drought occurrence frequency is 47.7%. L-moments method was used to define homogenous regions. Homogenous regions for 3 and 6-month time scales minimum precipitation series couldn't be obtained while homogenous regions for 9-month time scale minimum precipitation series were obtained only by dividing the whole basin into two parts. The whole basin is homogenous for the 12-month time scale minimum precipitation series. The Pearson Type 3 distribution is found to be most suitable for two homogenous sub-basins regarding 9-month time scale minimum precipitation series, whereas the Generalized Normal distribution is found to be most suitable for the whole basin with respect to 12-month time scale minimum precipitation series.

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Section: L-moments Methodsmentioning

confidence: 99%

Drought analysis of the Seyhan Basin by using standardized precipitation ındex (spı) and l-moments

SEÇKİN¹

2016

Tarım Bilimleri Dergisi

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“…The calculated values for all sites are less than the critical value of 3. The same methodology has been adopted by many studies around the world [30][31][32][34][35][36]. In the present study we declared no one site to be discordant (Table 3).…”

Section: Study Area and Datamentioning

confidence: 55%

“…The number of clusters is normally a subjective choice. Cluster analysis is an effective method if we have a large number of sites in each cluster while the range of drainage area of these sites in homogenous regions should not be too large, as reported in [30][31][32][33][34][35][36]. The tests to check the homogeneity of the regions suggested by [4], are based on L-moments and Kappa distribution in its simulation study for the reason that Kappa distribution is less restrictive than Gumbel or GEV.…”

Section: ) Identification Of Homogeneous Regionsmentioning

confidence: 99%

Regional Frequency Analysis of Annual Peak Flows in Pakistan Using Linear Combination of Order Statistics

Ahmad¹,

Fawad²,

Akbar³

et al. 2016

Pol. J. Environ. Stud.

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For this paper we conducted a regional analysis (RA) of annual peak flows using linear combination of order statistics, i.e., linear-moments (LM) and trimmed linear moments (TLM). Design flood estimates are calculated and compared at different return periods, which are useful for water resources management, including hydrological structures and basin management. The main objective of our study was to compare regional design flood estimates for untrimmed and trimmed samples. LM is the special case of TLM, when we have no trimming from either side. First, regional flood frequency analysis is performed for LM and then for TLM. After initial screening of the annual peak flow series, a discordancy measure was used to diagnose the discordant sites. No site was found to be discordant. For homogeneity of the region, the homogeneity measure "H" was employed using simulation study based on Kappa distribution, and found that the nine sites on the Indus Basin included in the study constitute a single homogeneous region. In this study we used TLM with trimming values (γ, 0), where γ = 1, 2, 3, 4. In order to determine the most appropriate probability distribution for regional quantile estimates, different probability distributions are used, namely: generalized extreme value (GEV), generalized pareto (GPA), generalized logistic (GLO), Pearson type three (PE3), and generalized normal (GNO). L-moments ratio diagram and Z-test as goodness of fit are engaged to identify the most suitable probability distribution. A comparison revealed that GNO is the best distribution for first three cases as (0, 0), (1, 0), and (2, 0), while for the last two cases of (3, 0) and (4, 0) the most appropriate choice is GEV. A simulation study was also carried out to evaluate the performance and robustness of the best fit probability distribution using relative bias (RB) and relative root mean square error (RRMSE).

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“…The H measure has been extensively used in the identification of hydrological homogeneous regions (Aydoğan et al, ; Beskow et al, ; Seckin et al, ; Smith et al, ). Given a group of sites, which can be generated using a clustering algorithm, H compares the sample L‐moments variation between sites that would be expected from a simulated homogeneous region (Hosking & Wallis, ).…”

Section: Methodsmentioning

confidence: 99%

Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis

Cassalho

Beskow

Mello

et al. 2019

Hydrological Processes

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Due to the severity related to extreme flood events, recent efforts have focused on the development of reliable methods for design flood estimation. Historical streamflow series correspond to the most reliable information source for such estimation; however, they have temporal and spatial limitations that may be minimized by means of regional flood frequency analysis (RFFA). Several studies have emphasized that the identification of hydrologically homogeneous regions is the most important and challenging step in an RFFA. This study aims to identify state‐of‐the‐art clustering techniques (e.g., K‐means, partition around medoids, fuzzy C‐means, K‐harmonic means, and genetic K‐means) with potential to form hydrologically homogeneous regions for flood regionalization in Southern Brazil. The applicability of some probability density function, such as generalized extreme value, generalized logistic, generalized normal, and Pearson type 3, was evaluated based on the regions formed. Among all the 15 possible combinations of the aforementioned clustering techniques and the Euclidian, Mahalanobis, and Manhattan distance measures, the five best were selected. Several watersheds' physiographic and climatological attributes were chosen to derive multiple regression equations for all the combinations. The accuracy of the equations was quantified with respect to adjusted coefficient of determination, root mean square error, and Nash–Sutcliffe coefficient, whereas, a cross‐validation procedure was applied to check their reliability. It was concluded that reliable results were obtained when using robust clustering techniques based on fuzzy logic (e.g., K‐harmonic means), which have not been commonly used in RFFA. Furthermore, the probability density functions were capable of representing the regional annual maximum streamflows. Drainage area, main river length, and mean altitude of the watershed were the most recurrent attributes for modelling of mean annual maximum streamflow. Finally, an integration of all the five best combinations stands out as a robust, reliable, and simple tool for estimation of design floods.

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Regional flood frequency analysis forÇoruhBasin ofTurkey withL‐moments approach

Cited by 24 publications

References 53 publications

Drought analysis of the Seyhan Basin by using standardized precipitation ındex (spı) and l-moments

Drought analysis of the Seyhan Basin by using standardized precipitation ındex (spı) and l-moments

Regional Frequency Analysis of Annual Peak Flows in Pakistan Using Linear Combination of Order Statistics

Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis

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