Flood Frequency Analysis Methods Research Articles

A methodology for extreme groundwater surge predetermination in carbonate aquifers: Groundwater flood frequency analysis

Summary The present paper introduces a methodology devoted to groundwater flooding hazard assessment. It focuses on groundwater floodings due to water table rises that are induced by heavy rainfall events. This special kind of flooding can cause devastating damages, particularly in fractured and karstified carbonate aquifers. Indeed, hydrodynamic conditions prevailing in these heterogeneous formations can involve strong groundwater surges. The developed methodology shows how flood frequency analysis methods can be applied in groundwater flood frequency analysis. Actually, it consists in estimating the T-year hydraulic head that characterizes the T-year groundwater surge, given a return period T. It also aims at defining the rainfall events likely to cause such extreme groundwater surges. This methodology was applied within the framework of a building construction project in a karstic Mediterranean aquifer located in Southern France. The present paper is designated to be a first contribution to groundwater flood frequency analysis. This new field of research has to be further developed in order to put forward consensus guidelines for hydrogeologists and decision-makers as in flood frequency analysis.

Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.

Flash flooding in Spain: geomorphological approaches supporting flood frequency analysis, and the implications for the design of structures

AbstractConventional methods for the estimation of flood frequency are generally based on the statistical analysis of data series resulting from the measurement of water levels at specific locations, which are translated into discharges (m3/s) using standard stage/discharge relationships. Subsequently, these gauged flows are used to identify the largest flood event experienced by a river or catchment, and to produce growth curves used in the estimation of the return periods of specific flood events, as well as in the calculation of discharges for specific required design events (e.g. return period 1 in 100 year). In areas where gauging data records are scarce, and/or the data series are short or interrupted, geomorphological interpretation of the physical environment, dating of fluvial deposits and flooding episodes and hydraulic reconstruction of past flood events can be used as complementary tools aiding conventional hydrological and flood frequency analysis methods. This paper will discuss the undertaking of this approach in the Guadalope Catchment in northeast Spain. It will examine the findings in relation to the inadequate design of existing structures such as dams, spillways, canals and reservoirs, and will also look at the potential risks associated with flooding at present.

우리나라의 빈도홍수량의 추정

빈도홍수량은 중ㆍ소 수공구조물의 설계에 중요한 지표로서 매우 중요하나, 자료의 부족과 설계 관습으로 인하여 홍수량을 직접해석하여 사용하지 못하고 있는 실정으로 설계호우-단위도법과 같은 간접적인 홍수량추정방법이 이용되고 있다. 따라서 본 연구에서는 수집가능한 일제시대부터 1999년까지 망라한 국내 첨두홍수량 자료를 수집하여 연 최대치 계열을 작성하고 지수홍수법에 의해서 지역홍수빈도분석을 수행하였다. 지역홍수빈도분석을 위해서 사용된 분포는 WMO(1989)가 권장한 Wakeby 분포였으며, 매개변수 추정은 Hosking(1990)의 L-모멘트를 이용하였다. 지역의 수문학적인 동질성을 위해서 Hosking과 Wallis(1993)의 불일치성, 이산성의 검정을 따랐다. 지수홍수와 상관시킨 물리적인 독립 변수는 유역면적이고, 이는 비유량이 유역면적이 커짐에 따라 작아지는 소위 멱함수 형태를 잘 따르고 있었다. 우리나라 주요유역을 4개의 유역 즉, 한강, 낙동강, 금강, 영산/섬진강으로 나누어 유역별 재현기간별 홍수량을 이러한 형태로 제시하였다. 또한 비교를 위해서 점빈도분석에 의한 지역화를 수행하여 지역빈도 분석의 결과와 비교하였다. 댐 개발전과의 비교에서는 댐의 역할이 첨두홍수량의 변화에 큰 영향이 없는 것으로 나타났다. 이 결과를 기존의 타 연구와 비교함으로써 본 연구의 타당성을 구체화할 수 있었다. Flood frequency estimate is an essential index for determining the scale of small and middle hydraulic structure. However, this flood quantity could not be estimated directly for practical design purpose due to the lack of available flood data, and indirect method like design rainfall-runoff method have been used for the estimation of design flood. To give the good explain for design flood estimates, regional flood frequency analysis was performed by flood index method in this study. First, annual maximum series were constructed by using the collected data which covers from Japanese imperialism period to 1999. Wakeby distribution recommended by WMO(1989) was used for regional flood frequency analysis and L-moment method by Hosking (1990) was used for parameter estimation. For the homogeneity of region, the discordance and heterogeneity test by Hosking and Wallis(1993) was carried for 4 major watersheds in Korea. Physical independent variable correlated with index flood was watershed area. The relationship between specific discharge and watershed area showed a type of power function, i.e. the specific discharge decreases as watershed area increases. So flood quantity according to watershed area and return period was presented for each watershed(Han rivet, Nakdong river, Geum river and Youngsan/Seomjin river) by using this relation type. This result was also compared with the result of point frequency analysis and its regionalization. It was shown that the dam construction couldn't largely affect the variation of peak flood. The property of this study was also examined by comparison with previous studies.

A reliability‐based selective index for regional flood frequency analysis methods

AbstractIn this paper, a new index is proposed for the selection of the best regional frequency analysis method. First, based on the theory of reliability, the new selective index is developed. The variances of three regional T‐year event estimators are then derived. The proposed methodology is applied to an actual watershed. For each regional method, the reliability of various T‐year regional estimates is computed. Finally, the reliability‐based selective index graph is constructed from which the best regional method can be determined. In addition, the selection result is compared with that based on the traditional index, root mean square error. The proposed new index is recommended as an alternative to the existing indices such as root mean square error, because the influence of uncertainty and the accuracy of estimates are considered. Copyright © 2003 John Wiley & Sons, Ltd.

Homogeneity tests based upon Gumbel distribution and a critical appraisal of Dalrymple's test

Homogeneity tests are an important component of many regional flood frequency analysis methods, particularly index flood methods. The index flood method was first suggested by Dalrymple, who also proposed a homogeneity test. Dalrymple's test has been widely used in hydrologic practice for more than 30 years. This paper analyzes the relative performance of Dalrymple's test, a normalized quantile test based upon L-moment parameter estimation ( X-10 test), and a method of moment Cν test (MoM- Cν test). Dalrymple's original test is shown to be in error and a corrected version is developed. A Monte Carlo study compares the power of these three tests, after applying correction factors to the test statistics to achieve a 5% Type I error. The L-moment X-10 test was always more powerful then Dalrymple's test or the MoM- Cν test. Moreover, the X-10 test needs much less correction to achieve the specified Type I error. An analytical analysis of the power of the tests is consistent with the Monte Carlo results. The superior performance of the X-10 test is due to its L-moment estimation procedure, which yields a smaller sampling variance and a sampling distribution closer to normality than classical product moments. The relationship of the X-10 test with other L-moment based tests proposed by other workers is discussed. The original version of Dalrymple's test should not be used.