scholarly journals Review of recent advances in index flood estimation

2003 ◽  
Vol 7 (3) ◽  
pp. 283-296 ◽  
Author(s):  
D. Bocchiola ◽  
C. De Michele ◽  
R. Rosso

Abstract. Index flood estimation for regional flood frequency analysis needs to be based on the information available. The most appropriate method depends on the specific application and its choice requires a problem-oriented analysis. This paper presents a simple theoretical framework to deal with index flood estimation for a specific river site. The methodological approaches available for the purpose are reviewed. For each, the information required is specified and the reliability of the estimate, particularly desirable in risk analysis and management, is discussed. Where flood observations are lacking, indirect estimation must be undertaken using scenarios including those commonly met in hydrological practice; generally, these depend on the amount and type of information available. For each scenario, the methodologies are outlined, in order of the expected degree of complexity. After a guided analysis, an investigator can adopt the method providing the best tradeoff between effort in collecting and handling data and the resultant reliability which can be expected. Keywords: direct and indirect methods, index flood estimation, reliability, scenarios.

2020 ◽  
Author(s):  
Gang Zhao ◽  
Paul Bates ◽  
Jeff Neal ◽  
Bo Pang

<p>Design flood estimation in data-poor regions is a fundamental task in hydrology. In this paper, we propose a regional flood frequency analysis approach to estimate design floods anywhere on the global river network. This approach involves two stages: (i) clustering global gauging stations into subareas by a K-means model based on twelve globally available catchment descriptors and (ii) developing a regression model in each subarea for design flood estimation using the same descriptors. Nearly 12,000 discharge stations globally were selected for model development and a benchmark global index-flood method was adopted for comparison. The results showed that: (1) the proposed approach achieved the highest accuracy for design flood estimation when using all catchment descriptors for clustering; and the regression model accuracy improved by considering more descriptors in model development; (2) a support vector machine regression showed the highest accuracy among all regression models tested, with relative root mean squared error of 0.67 for mean flood and 0.83 for 100-year return period flood estimations; (3) 100-year return period flood magnitude in tropical, arid, temperate, continental and polar climate zones could be reliably estimated with relative mean biases of -0.18, -0.23, -0.18, 0.17 and -0.11 respectively by adopting a 5-fold cross-validation procedure; (4) the proposed approach outperformed the benchmark index-flood method for 10, 50 and 100 year return period estimates; We conclude that the proposed RFFA is a valid approach to generate design floods globally, improving our understanding of the flood hazard, especially in ungauged areas.</p>


2016 ◽  
Vol 20 (12) ◽  
pp. 4717-4729 ◽  
Author(s):  
Martin Durocher ◽  
Fateh Chebana ◽  
Taha B. M. J. Ouarda

Abstract. This study investigates the utilization of hydrological information in regional flood frequency analysis (RFFA) to enforce desired properties for a group of gauged stations. Neighbourhoods are particular types of regions that are centred on target locations. A challenge for using neighbourhoods in RFFA is that hydrological information is not available at target locations and cannot be completely replaced by the available physiographical information. Instead of using the available physiographic characteristics to define the centre of a target location, this study proposes to introduce estimates of reference hydrological variables to ensure a better homogeneity. These reference variables represent nonlinear relations with the site characteristics obtained by projection pursuit regression, a nonparametric regression method. The resulting neighbourhoods are investigated in combination with commonly used regional models: the index-flood model and regression-based models. The complete approach is illustrated in a real-world case study with gauged sites from the southern part of the province of Québec, Canada, and is compared with the traditional approaches such as region of influence and canonical correlation analysis. The evaluation focuses on the neighbourhood properties as well as prediction performances, with special attention devoted to problematic stations. Results show clear improvements in neighbourhood definitions and quantile estimates.


2020 ◽  
Vol 6 (12) ◽  
pp. 2425-2436
Author(s):  
Andy Obinna Ibeje ◽  
Ben N. Ekwueme

Hydrologic designs require accurate estimation of quartiles of extreme floods. But in many developing regions, records of flood data are seldom available. A model framework using the dimensionless index flood for the transfer of Flood Frequency Curve (FFC) among stream gauging sites in a hydrologically homogeneous region is proposed.  Key elements of the model framework include: (1) confirmation of the homogeneity of the region; (2) estimation of index flood-basin area relation; (3) derivation of the regional flood frequency curve (RFFC) and deduction of FFC of an ungauged catchment as a product of index flood and dimensionless RFFC. As an application, 1983 to 2004 annual extreme flood from six selected gauging sites located in Anambra-Imo River basin of southeast Nigeria, were used to demonstrate that the developed index flood model: , overestimated flood quartiles in an ungauged site of the basin.  It is recommended that, for wider application, the model results can be improved by the availability and use of over 100 years length of flood data spatially distributed at critical locations of the watershed. Doi: 10.28991/cej-2020-03091627 Full Text: PDF


2020 ◽  
Vol 15 (2) ◽  
pp. 130-141
Author(s):  
Zuzana Németová ◽  
Silvia Kohnová ◽  
Romana Marková

AbstractRegional flood frequency analysis is considered to be an important and popular method for estimating different hydrological variables at ungauged sites. The estimation of the index flood is the essential problem when this method is applied. The objective of the study is a comparison of the estimation of the mean annual flood (or index flood) by using two approaches based on the ‘so-called’ index flood method and top-kriging. The concept behind these methods permits estimating the mean annual flood at ungauged locations using information taken from gauged sites located within the same homogeneous pooling groups. The study area comprises 104 gauging stations on the whole territory of Slovakia. The observation period of the annual maximum discharges of the selected stations was from 1961-2010. The identification of the homogeneous pooling group was performed using a non-hierarchical k-means clustering algorithm. The optimal number of clusters is determined by the Silhouette method. As a result, eight homogeneous pooling group clusters were identified. Finally, the results of the estimated mean annual floods using the index flood method and top-kriging were compared with the observed data. Top-kriging provided better results than the classical index flood method for estimating the mean annual flood at ungauged sites.


Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1717 ◽  
Author(s):  
Do-Hun Lee ◽  
Nam Won Kim

The design of hydraulic structures and the assessment of flood control measures require the estimation of flood quantiles. Since observed flood data are rarely available at the specific location, flood estimation in un-gauged or poorly gauged basins is a common problem in engineering hydrology. We investigated the flood estimation method in a poorly gauged basin. The flood estimation method applied the combination of rainfall-runoff model simulation and regional flood frequency analysis (RFFA). The L-moment based index flood method was performed using the annual maximum flood (AMF) data simulated by the rainfall-runoff model. The regional flood frequency distribution with 90% error bounds was derived in the Chungju dam basin of Korea, which has a drainage area of 6648 km2. The flood quantile estimates based on the simulated AMF data were consistent with the flood quantile estimates based on the observed AMF data. The widths of error bounds of regional flood frequency distribution increased sharply as the return period increased. The results suggest that the flood estimation approach applied in this study has the potential to estimate flood quantiles when the hourly rainfall measurements during major storms are widely available and the observed flood data are limited.


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.


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