Regional Flood Frequency Relationships Research Articles

Development of Regional Flood Frequency Relationship for Narmada Basin using Index Flood Procedure

Water Resources decision making problems such as flood plain zoning, design of hydraulic structures etc. are based on design flood estimate, defined as discharge for a specified probability of exceedance. Flood Frequency Analysis helps to estimate the flood value for a specific return period. This procedure requires sufficient length of observed data of floods on river gauging sites which many a time is not available. In India major rivers have very few gauging sites and their tributaries are mostly ungauged. When quantiles have to be estimated for ungauged sites, Flood Frequency Analysis is neither possible nor reliable. Regional Flood Frequency Analysis is the means to overcome such problems, reasonably quantifying flood estimates at desired frequencies for sites within a more or less hydrological homogeneous region. Narmada Basin located in central India covers an area about 98,976 sq. km, drained by a large number of tributaries, most of which are ungauged, has been considered as the case. Index Flood method utilizing Gumbel’s EV-1 distribution have been used in the present study to develop the Regional flood frequency relationship. The Annual Peak Flood data of 16 gauging sites of Narmada Basin, having record length of 12 to 17 years, is utilized for flood estimation. Flood frequency curves for the considered gauging stations are generated. Development of regional flood frequency relationship leads to the estimation of different return period flood.

Connecting Event-Based Scaling of Flood Peaks to Regional Flood Frequency Relationships

AbstractRegional flood frequency (RFF) equations are statistical characterizations that, in their simplest form, show how peak discharge quantiles scale with drainage area. They remain separated from the physical processes that occur during flood-generating rainfall-runoff events. A physical understanding of RFF equations is a long-standing unsolved problem in hydrology. This study addresses this problem using a scaling framework. Two hypotheses are introduced that collectively state that scaling slopes of event peak discharges are on average equivalent to the mean scaling slope of annual peak quantiles; the later quantity refers to an average taken over a set of exceedance probabilities under consideration. To test these hypotheses, a nested mixed-effects linear (NMEL) model was developed that characterizes event-to-event variability in scaling relationships between stream discharge peaks and drainage area. The model leads to scaling relationships for event peak discharge quantiles and annual peak quanti...

Regional Flood Frequency Analysis using Soft Computing Techniques

For design of various types of hydraulic structures as well as for taking different flood management measures flood frequency estimates are required. Regional flood frequency analysis is carried out employing L-moments and soft computing techniques viz. artificial neural network (ANN) and fuzzy inference system (FIS) for the lower Godavari subzone 3(f) of India. The study area covers an areal extent of 174,201 km2 and annual maximum peak flood data of 17 catchments ranging in size from 35 to 824 km2 are used. The data screening is carried out employing L-moments based Discordancy measure (Di) and regional homogeneity is examined based on the heterogeneity measure (H). On the basis of the L-moment ratio diagram and Zidist –statistic criteria, Pearson Type III (PE3) distribution is chosen as the suitable frequency distribution for the region. For the region under study, a relationship is developed between mean annual maximum peak flood and area of the catchment using the Levenberg-Marquardt (LM) iteration and the same is coupled with the PE3 based regional flood frequency relationship developed for estimation of floods of various frequencies for the ungauged catchments of the region. The regional flood frequency relationships developed based on L-moments and soft computing techniques are compared.

LQ-Moments for Regional Flood Frequency Analysis: A Case Study for the North-Bank Region of the Brahmaputra River, India

The LQ-moment proposed by Mudholkar, et al. (1998) is used for regional flood frequency analysis of the North-Bank region of the river Brahmaputra, India. Five probability distributions are used for the LQmoment: generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA), lognormal (LN3) and Pearson Type III (PE3). The same regional frequency analysis procedure proposed by Hosking (1990) for the L-moment is used for the LQ-moment. Based on the LQ-moment ratio diagram and |Zidist| -statistic criteria, the PE3 distribution is identified as the robust distribution for the study area. For estimation of floods of various return periods for both gauged and ungauged catchments of the study area, regional flood frequency relationships are developed using the LQ-moment based PE3 distribution.

Flood frequency analysis of Turkey using L-moments method

The index flood procedure coupled with the L-moments method is applied to the annual flood peaks data taken at all stream-gauging stations in Turkey having at least 15-year-long records. First, screening of the data is done based on the discordancy measure (Di) in terms of the L-moments. Homogeneity of the total geographical area of Turkey is tested using the L-moments based heterogeneity measure, H, computed on 500 simulations generated using the four parameter Kappa distribution. The L-moments analysis of the recorded annual flood peaks data at 543 gauged sites indicates that Turkey as a whole is hydrologically heterogeneous, and 45 of 543 gauged sites are discordant which are discarded from further analyses. The catchment areas of these 543 sites vary from 9·9 to 75121 km2 and their mean annual peak floods vary from 1·72 to 3739·5 m3 s−1. The probability distributions used in the analyses, whose parameters are computed by the L-moments method are the general extreme values (GEV), generalized logistic (GLO), generalized normal (GNO), Pearson type III (PE3), generalized Pareto (GPA), and five-parameter Wakeby (WAK). Based on the L-moment ratio diagrams and the |Zdist|-statistic criteria, the GEV distribution is identified as the robust distribution for the study area (498 gauged sites). Hence, for estimation of flood magnitudes of various return periods in Turkey, a regional flood frequency relationship is developed using the GEV distribution. Next, the quantiles computed at all of 543 gauged sites by the GEV and the Wakeby distributions are compared with the observed values of the same probability based on two criteria, mean absolute relative error and determination coefficient. Results of these comparisons indicate that both distributions of GEV and Wakeby, whose parameters are computed by the L-moments method, are adequate in predicting quantile estimates. Copyright © 2011 John Wiley & Sons, Ltd.

Hydrologic simulation‐aided regional flood frequency analysis of Nepalese river basins

AbstractIn Nepal, there are only two hydrometric stations in two of the five recognized hydrologic regions. Thus, data are available at fewer hydrometric stations than usually accepted as adequate for reliable estimation of regional frequency distributions and index flood relationships, which are two major elements of index flood‐based regional flood frequency analysis. This study deals with estimation of regional frequency distributions and index flood relationships in the five hydrologic regions of Nepal, with emphasis on the regions that have inadequate hydrometric stations. Synthetic flood data have been used for supplementing the hydrometric data in the two hydrologic regions. A rainfall‐runoff model SimHyd was used for synthetic flood data generation. Return period flood estimates of the derived regional flood–frequency relationships were compared with that of at‐site and Water and Energy Commission Secretariat of Nepal (WECS) (a frequently used method in Nepal) methods. The regional relationships were found to have far better estimation capabilities than the WECS method.

Regional Flood Frequency Analysis of North-Bank of the River Brahmaputra by Using LH-Moments

In this study LH-moment proposed by Wang (Water Resour Res 33(12):2841–2848, 1997) has been used for regional flood frequency analysis of the North-Bank region of the river Brahmaputra, India. Three probability distributions i.e. generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA) has been used for each level of LH-moments i.e. L, L1, L2, L3 and L4. The regional frequency analysis procedure proposed by Hosking and Wallis (Water Resour Res 29(2):271–281, 1993) for L-moments i.e. discordancy measure for screening the data, heterogeneity measure for formation of homogeneous region and goodness-of-fit test have been used for each level of LH-moments. Based on the LH-moment ratio diagram and ∣Z∣-statistic criteria, GEV distribution for level one LH-moment is identified as the robust distribution for the study area. For estimation of floods of various return periods for both gauged and ungauged catchments of the study area, regional flood frequency relationships have been developed by using the level one LH-moment based on GEV distribution. A comparative study has been performed between L-moments and LH-moments for the study area. It is observed from comparative study that the regional flood frequency analysis based on the GEV distribution by using level one LH-moment (L1) is superior to the use of L-moments.

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

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 weather-related 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 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.

Closure to “Regional Flood Frequency Analysis Using L-Moments for North Brahmaputra Region of India” by Rakesh Kumar and Chandranath Chatterjee

Closure to “Regional Flood Frequency Analysis Using L-Moments for North Brahmaputra Region of India” by Rakesh Kumar and Chandranath Chatterjee

Regional Flood Frequency Analysis Using L-Moments for North Brahmaputra Region of India

Data of 13 stream flow gauging sites of the North Brahmaputra region of India are screened using the discordancy measure ( Di ) and homogeneity of the region is then tested employing the L-moments based heterogeneity measure (H) . For computing heterogeneity measure H , 500 simulations are performed using the Kappa distribution. Based on this test, it is observed that the data of 10 out of 13 gauging sites constitute a homogeneous region. Comparative regional flood frequency analysis studies are conducted employing the L-moments based commonly used frequency distributions. Based on the L-moment ratio diagram and ∣ Zidist ∣ -statistic criteria, general extreme value (GEV) distribution is identified as the robust distribution for the study area. Regional flood frequency relationships are developed for estimation of floods of various return periods for gauged and ungauged catchments using the L-moment based GEV distribution and a regional relationship between mean annual peak flood and catchment area. Flood ...

Development of Regional Flood Frequency Relationships Using L-moments for Middle Ganga Plains Subzone 1(f) of India

In this study, screening of the data has been carried out basedon the discordancy measure (Di) in terms of the L-moments. Homogeneity of the region has been tested using the L-moments based heterogeneity measure, H. For computing the heterogeneity measure H, 500 simulations were carried out using the four parameter Kappa distribution. Based on this test, it has been observed that the data of 8 out of 11 bridge sites constitute ahomogeneous region. Hence, the data of these 8 sites have been used in this study. Catchment areas of these 8 sites vary from 32.89 to 447.76 km2 and their mean annual peak floods varyfrom 24.29 to 555.21 m3 s-1. Comparative regional floodfrequency analysis studies have been carried out using the various L-moments based frequency distributions viz. Extreme value (EV1), General extreme value (GEV), Logistic (LOS), Generalized logistic (GLO), Normal (NOR), Generalized normal (GNO), Uniform (UNF), Pearson Type-III (PE3), Exponential (EXP),Generalized Pareto (GPA), Kappa (KAP), and five parameter Wakeby(WAK). Based on the L-moment ratio diagram and ∣ Zidist ∣–statistic criteria, GEV distribution has been identified as the robust distribution for the study area. For estimation of floods of various return periods for gauged catchments of the study area, regional flood frequency relationship has been developed using the L-moments based GEV distribution. Also, for estimation of floods of desiredreturn periods for ungauged catchments, regional flood frequencyrelationship has been developed by coupling the regional flood frequency relationship with the regional relationship between mean annual maximum peak flood and catchment area.

Classification of drainage basins according to their physical characteristics; an application for flood frequency analysis in Scotland

If the standardised floods at all sites within a given region are assumed to be samples from the same distribution, all data may be combined to yield an estimate of a regional dimensionless flood frequency relationship. The identification of these hydrologically homogeneous regions can be achieved on the basis of the physical characteristics of the basin which control the hydrological processes. Classification of the basins independent of the discharge data avoids the problems of regionalisation based on the highly variable, individual site estimates of flood frequency. Classification of the basins can be performed using the NORMIX multivariate clustering algorithm. The homogeneity of the basins can be tested using a likelihood ratio test of whether standardised data for all basins within a region may be adequately represented by a single regional flood frequency relationship. The method was applied to 168 basins in Scotland and five regions were identified, corresponding to physically reasonable basin types and all but one of which yield homogeneous distributions of flood frequency.