Asymmetric copula in multivariate flood frequency analysis

The univariate flood frequency analysis is widely used in hydrological studies. Often only flood peak or flood volume is statistically analyzed. For a more complete analysis the three main characteristics of a flood event i.e. peak, volume and duration are required. To fully understand these variables and their relationships, a multivariate statistical approach is necessary. The main aim of this paper is to define the trivariate probability density and cumulative distribution functions. When the joint distribution is known, it is possible to define the bivariate distribution of volume and duration conditioned on the peak discharge. Consequently volume–duration pairs, statistically linked to peak values, become available. The authors build trivariate joint distribution of flood event variables using the fully nested or asymmetric Archimedean copula functions. They describe properties of this copula class and perform extensive simulations to highlight differences with the well-known symmetric Archimedean copulas. They apply asymmetric distributions to observed flood data and compare the results those obtained using distributions built with symmetric copula and the standard Gumbel Logistic model.     

Hydrological risk analysis of dam overtopping using bivariate statistical approach: a case study from Geheyan Reservoir,China

Hydrological risk analysis is essential and provides useful information for dam safety management and decision-making. This study presents the application of bivariate flood frequency analysis to risk analysis of dam overtopping for Geheyan Reservoir in China. The dependence between the flood peak and volume is modelled with the copula function. A Monte Carlo procedure is conducted to generate 100,000 random flood peak-volume pairs, which are subsequently transformed to corresponding design flood hydrographs (DFHs) by amplifying the selected annual maximum flood hydrographs (AMFHs). These synthetic DFHs are routed through the reservoir to obtain the frequency curve of maximum water level and assess the risk of dam overtopping. Sensitive analysis is performed to investigate the influence of different AMFH shapes and correlation coefficients of flood peak and volume on estimated overtopping risks. The results show that synthetic DFH with AMFH shape characterized by a delayed time to peak results in higher risk, and therefore highlight the importance of including a range of possible AMFH shapes in the dam risk analysis. It is also demonstrated that the overtopping risk is increased as the correlation coefficient of flood peak and volume increases and underestimated in the independence case (i.e. traditional univariate approach), while overestimated in the full dependence case. The bivariate statistical approach based on copulas can effectively capture the actual dependence between flood peak and volume, which should be preferred in the dam risk analysis practice.     

Probabilistic modelling of flood events using the entropy copula

The estimation of flood frequency is vital for the flood control strategies and hydraulic structure design. Generating synthetic flood events according to statistical properties of observations is one of plausible methods to analyze the flood frequency. Due to the statistical dependence among the flood event variables (i.e. the flood peak, volume and duration), a multidimensional joint probability estimation is required. Recently, the copula method is widely used for multivariable dependent structure construction, however, the copula family should be chosen before application and the choice process is sometimes rather subjective. The entropy copula, a new copula family, employed in this research proposed a way to avoid the relatively subjective process by combining the theories of copula and entropy. The analysis shows the effectiveness of the entropy copula for probabilistic modelling the flood events of two hydrological gauges, and a comparison of accuracy with the popular copulas was made. The Gibbs sampling technique was applied for trivariate flood events simulation in order to mitigate the calculation difficulties of extending to three dimension directly. The simulation results indicate that the entropy copula is a simple and effective copula family for trivariate flood simulation.     

Development of design flood hydrographs using probability density functions

Probability density functions (PDFs) are used to fit the shape of hydrographs and have been popularly used for the development of synthetic unit hydrographs by many hydrologists. Nevertheless, modelling the shapes of continuous stream flow hydrographs, which are probabilistic in nature, is rare. In the present study, a novel approach was followed to model the shape of stream flow hydrographs using PDF and subsequently to develop design flood hydrographs for various return periods. Four continuous PDFs, namely, two parameter Beta, Weibull, Gamma and Lognormal, were employed to fit the shape of the hydrographs of 22 years at a site of Brahmani River in eastern India. The shapes of the observed and PDF fitted hydrographs were compared and root mean square errors, error of peak discharge (EQ_P) and error of time to peak (ET_P) were computed. The best‐fitted shape and scale parameters of all PDFs were subjected to frequency analysis and the quartiles corresponding to 20‐, 50‐, 100‐ and 200‐year were estimated. The estimated parameters of each return period were used to develop the flood hydrographs for 20‐, 50‐, 100‐ and 200‐year return periods. The peak discharges of the developed design flood hydrographs were compared with the design discharges estimated from the frequency analysis of 22 years of annual peak discharges at that site. Lognormal‐produced peak discharge was very close to the estimated design discharge in case of 20‐year flood hydrograph. On the other hand, peak discharge obtained using the Weibull PDF had close agreement with the estimated design discharge obtained from frequency analysis in case of 50‐, 100‐ and 200‐year return periods. The ranking of the PDFs based on estimation of peak of design flood hydrograph for 50‐, 100‐ and 200‐year return periods was found to have the following order: Weibull > Beta > Lognormal > Gamma. Copyright © 2009 John Wiley & Sons, Ltd.     

INTERNATIONAL HYDROLOGICAL DECADE / WORKING GROUP ON “THE INFLUENCE OF MAN ON THE HYDROLOGICAL CYCLE”

Abstract

Floods, as extreme hydrological phenomena, can be described by more than one correlated characteristic, such as peak, volume and duration. These characteristics should be jointly considered since they are generally not independent. For an ungauged site, univariate regional flood frequency analysis (FA) provides a limited assessment of flood events. A recent study proposed a procedure for regional FA in a multivariate framework. This procedure represents a multivariate version of the index-flood model and is based on copulas and multivariate quantiles. The performance of the proposed procedure was evaluated by simulation. However, the model was not tested on a real-world case study data. In the present paper, practical aspects are investigated jointly for flood peak (Q) and volume (V) of a dataset from the Côte-Nord region in the province of Quebec, Canada. The application of the proposed procedure requires the identification of the appropriate marginal distribution, the estimation of the index flood and the selection of an appropriate copula. The results of the case study show that the regional bivariate FA procedure performed well. This performance depends strongly on the performance of the two univariate models and, more specifically, the univariate model of Q. The results show also the impact of the homogeneity of the region on the performance of the univariate and bivariate models.

Editor D. Koutsoyiannis     

Projection of extreme flood inundation in the Mekong River basin under 4K increasing scenario using large ensemble climate data

Projecting changes in the frequency and intensity of future precipitation and flooding is critical for the development of social infrastructure under climate change. The Mekong River is among the world's large-scale rivers severely affected by climate change. This study aims to define the duration of precipitation contributing to peak floods based on its correlation with peak discharge and inundation volume in the Lower Mekong Basin (LMB). We assessed the changes in precipitation and flood frequency using a large ensemble Database for Policy Decision-Making for Future Climate Change (d4PDF). River discharge in the Mekong River Basin (MRB) and flood inundation in the LMB were simulated by a coupled rainfall-runoff and inundation (RRI) model. Results indicated that 90-day precipitation counting backward from the day of peak flooding had the highest correlation with peak discharge (R² = .81) and inundation volume (R² = .81). The ensemble mean of present simulation of d4PDF (1951–2010) showed good agreement with observed extreme flood events in the LMB. The probability density of 90-day precipitation shifted from the present to future climate experiments with a large variation of mean (from 777 to 900 mm) and SD (from 57 to 96 mm). Different patterns of sea surface temperature significantly influence the variation of precipitation and flood inundation in the LMB in the future (2051–2110). Extreme flood events (50-year, 100-year, and 1,000-year return periods) showed increases in discharge, inundation area, and inundation volume by 25%–40%, 19%–36%, and 23%–37%, respectively.     

A simulation experiment for optimal design hyetograph selection

The aim of this work is to assess the accuracy of literature design hyetographs for the evaluation of peak discharges during flood events. Five design hyetographs are examined in a set of simulations, based upon the following steps: (i) an ideal river basin is defined, characterized by a Beta distribution shaped unit hydrograph (UH); (ii) 1000 years of synthetic rainfall are artificially generated; (iii) a discharge time‐series is obtained from the convolution of the rainfall time‐series and the UH, and the reference T‐years flood is computed from this series; (iv) for the same return period T, the parameters of the intensity–duration–frequency (IDF) curve are estimated from the 1000 years of synthetic rainfall; (v) five design hyetographs are determined from the IDF curves and are convolved with the discrete UH to find the corresponding design hydrographs; (vi) the hydrograph peaks are compared with the reference T‐years flood and the advantages and drawbacks of each of the five approaches are evaluated. The rainfall and UH parameters are varied, and the whole procedure is repeated to assess the sensitivity of results to the system configuration. We found that all design hyetographs produce flood peak estimates that are consistently biased in most of the climatic and hydrologic conditions considered. In particular, significant underestimation of the design flood results from the adoption of any rectangular hyetograph used in the context of the rational formula. In contrast, the Chicago hyetograph tends to overestimate peak flows. In two cases it is sufficient to multiply the result by a constant scaling factor to obtain robust and nearly unbiased estimates of the design floods. Copyright © 2007 John Wiley & Sons, Ltd.     

基于SWAT模型的淮河上游流域设计洪水修订

变化环境下洪水序列的一致性遭到破坏,引发基于统计原理计算的设计洪水可靠性下降,亟需开展非一致性条件下的设计洪水修订研究.以淮河上游流域为研究区域,运用Pettitt检验法和滑动t检验法综合检测年最大洪峰流量序列突变点,在此基础上,采用SWAT分布式水文模型对变异前的洪峰与洪量序列进行还现,利用径流深的模拟结果修订设计洪...     

Assessment of flooding in urbanized ungauged basins: a case study in the Upper Tiber area,Italy

The reliability of a procedure for investigation of flooding into an ungauged river reach close to an urban area is investigated. The approach is based on the application of a semi‐distributed rainfall–runoff model for a gauged basin, including the flood‐prone area, and that furnishes the inlet flow conditions for a two‐dimensional hydraulic model, whose computational domain is the urban area. The flood event, which occurred in October 1998 in the Upper Tiber river basin and caused significant damage in the town of Pieve S. Stefano, was used to test the approach. The built‐up area, often inundated, is included in the gauged basin of the Montedoglio dam (275 km²), for which the rainfall–runoff model was adapted and calibrated through three flood events without over‐bank flow. With the selected set of parameters, the hydrological model was found reasonably accurate in simulating the discharge hydrograph of the three events, whereas the flood event of October 1998 was simulated poorly, with an error in peak discharge and time to peak of −58% and 20%, respectively. This discrepancy was ascribed to the combined effect of the rainfall spatial variability and a partial obstruction of the bridge located in Pieve S. Stefano. In fact, taking account of the last hypothesis, the hydraulic model reproduced with a fair accuracy the observed flooded urban area. Moreover, incorporating into the hydrological model the flow resulting from a sudden cleaning of the obstruction, which was simulated by a ‘shock‐capturing’ one‐dimensional hydraulic model, the discharge hydrograph at the basin outlet was well represented if the rainfall was supposed to have occurred in the region near the main channel. This was simulated by reducing considerably the dynamic parameter, the lag time, of the instantaneous unit hydrograph for each homogeneous element into which the basin is divided. The error in peak discharge and time to peak decreased by a few percent. A sensitivity analysis of both the flooding volume involved in the shock wave and the lag time showed that this latter parameter requires a careful evaluation. Moreover, the analysis of the hydrograph peak prediction due to error in rainfall input showed that the error in peak discharge was lower than that of the same input error quantity. Therefore, the obtained results allowed us to support the hypothesis on the causes which triggered the complex event occurring in October 1998, and pointed out that the proposed procedure can be conveniently adopted for flood risk evaluation in ungauged river basins where a built‐up area is located. The need for a more detailed analysis regarding the processes of runoff generation and flood routing is also highlighted. Copyright © 2005 John Wiley & Sons, Ltd.     

Hydrological model for urban catchments – analytical development using copulas and numerical solution

Abstract

A model based on analytical development and numerical solution is presented for estimating the cumulative distribution function (cdf) of the runoff volume and peak discharge rate of urban floods using the joint probability density function (pdf) of rainfall volume and duration together with information about the catchment's physical characteristics. The joint pdf of rainfall event volume and duration is derived using the theory of copulas. Four families of Archimedean copulas are tested in order to select the most appropriate to reproduce the dependence structure of those variables. Frequency distributions of runoff event volume and peak discharge rate are obtained following the derived probability distribution theory, using the functional relationship given by the rainfall–runoff process. The model is tested in two urban catchments located in the cities of Chillán and Santiago, Chile. The results are compared with the outcomes of continuous simulation in the Storm Water Management Model (SWMM) and with those from another analytical model that assumes storm event duration and volume to be statistically independent exponentially distributed variables.

Citation Zegpi, M. & Fernández, B. (2010) Hydrological model for urban catchments – analytical development using copulas and numerical solution. Hydrol. Sci. J. 55(7), 1123–1136.     

Assessment of river flow with significant lateral inflow through reverse routing modeling

The discharge hydrograph estimation in rivers based on reverse routing modeling and using only water level data at two gauged sections is here extended to the most general case of significant lateral flow contribution, without needing to deploy rainfall–runoff procedures. The proposed methodology solves the Saint‐Venant equations in diffusive form also involving the lateral contribution using a “head‐driven” modeling approach where lateral inflow is assumed to be function of the water level at the tributary junction. The procedure allows to assess the discharge hydrograph at ends of a selected river reach with significant lateral inflow, starting from the stage recorded there and without needing rainfall data. Specifically, the MAST 1D hydraulic model is applied to solve the diffusive wave equation using the observed stage hydrograph at the upstream section as upstream boundary condition. The other required data are (a) the observed stage hydrograph at the downstream section, as benchmark for the parameter calibration, and (b) the bathymetry of the river reach, from the upstream section to a short distance after the downstream gauged section. The method is validated with different flood events observed in two river reaches with a significant intermediate basin, where reliable rating curves were available, selected along the Tiber River, in central Italy, and the Alzette River, in Luxembourg. Very good performance indices are found for the computed discharge hydrographs at both the channel ends and along the tributaries. The mean Nash‐Sutcliffe value (NS_q) at the channel ends of two rivers is found equal to 0.99 and 0.86 for the upstream and downstream sites, respectively. The procedure is also validated on a longer stretch of the Tiber River including three tributaries for which appreciable results are obtained in terms of NS_q for the computed discharge hydrographs at both the channel ends for three investigated flood events.     

Multivariate modeling of droughts using copulas and meta-heuristic methods

This study investigated the utility of two meta-heuristic algorithms to estimate parameters of copula models and for derivation of drought severity–duration–frequency (S–D–F) curves. Drought is a natural event, which has huge impact on both the society and the natural environment. Drought events are mainly characterized by their severity, duration and intensity. The study adopts standardized precipitation index for drought characterization, and copula method for multivariate risk analysis of droughts. For accurate estimation of copula model parameters, two meta-heuristic methods namely genetic algorithm and particle swarm optimization are applied. The proposed methodology is applied to a case study in Trans Pecos, an arid region in Texas, USA. First, drought severity and duration are separately modeled by various probability distribution functions and then the best fitted models are selected for copula modeling. For modeling the joint dependence of drought variables, different classes of copulas, namely, extreme value copulas, Plackett and Student’s t copulas are employed and their performance is evaluated using standard performance measures. It is found that for the study region, the Gumbel–Hougaard copula is the best fitted copula model as compared to the others and is used for the development of drought S–D–F curves. Results of the study suggest that the meta-heuristic methods have greater utility in copula-based multivariate risk assessment of droughts.     

Direct estimation of catchment response time parameters in medium to large catchments using observed streamflow data

In single‐event deterministic design flood estimation methods, estimates of the peak discharge are based on a single and representative catchment response time parameter. In small catchments, a simplified convolution process between a single‐observed hyetograph and hydrograph is generally used to estimate time parameters such as the time to peak (T_P), time of concentration (T_C), and lag time (T_L) to reflect the “observed” catchment response time. However, such simplification is neither practical nor applicable in medium to large heterogeneous catchments, where antecedent moisture from previous rainfall events and spatially non‐uniform rainfall hyetographs can result in multi‐peaked hydrographs. In addition, the paucity of rainfall data at sub‐daily timescales further limits the reliable estimation of catchment responses using observed hyetographs and hydrographs at these catchment scales. This paper presents the development of a new and consistent approach to estimate catchment response times, expressed as the time to peak (T_Px) obtained directly from observed streamflow data. The relationships between catchment response time parameters and conceptualised triangular‐shaped hydrograph approximations and linear catchment response functions are investigated in four climatologically regions of South Africa. Flood event characteristics using primary streamflow data from 74 flow‐gauging stations were extracted and analysed to derive unique relationships between peak discharge, baseflow, direct runoff, and catchment response time in terms of T_Px. The T_Px parameters are estimated from observed streamflow data using three different methods: (a) duration of total net rise of a multipeaked hydrograph, (b) triangular‐shaped direct runoff hydrograph approximations, and (c) linear catchment response functions. The results show that for design hydrology and for the derivation of empirical equations to estimate catchment response times in ungauged catchments, the catchment T_Px should be estimated from both the use of an average catchment T_Px value computed using either Methods (a) or (b) and a linear catchment response function as used in Method (c). The use of the different methods in combination is not only practical but is also objective and has consistent results.     

洪泽湖历史洪水分析(1736-1992年)

根据１７３６－１９１１年文献记载的洪泽湖年最高水位及１９１４－１９９２年湖区水文测站的水位,流量资料,进行了长,短序列的入湖洪峰流量及不同时段洪量的频主分析,进而推求出不同重现期的设计入湖洪量和洪水年份相当的重现期,并分析洪水的灾害特征,结果：１）洪泽湖历史上洪水发生频繁,１７８６,１８５１,１９０６年均发生过特大洪水,高堰志桩分别至１６．３,２３．４,１６．１尺。２）１９５３年建库后,湖水位上升     

Flood hydrograph reconstruction from the peak flow value in ephemeral streams using a simplified robust single‐parameter model

Flood hydrographs from ephemeral streams in arid areas provide valuable information for assessing run‐off and groundwater recharge. However, such data are often scarce or incomplete, especially in hyper‐arid regions. The hypothesis of this study was that it is possible to reconstruct a hydrograph of a specific point along an ephemeral stream with the knowledge of only the peak flow rate of a flood event at that point and that this can be done at almost every point along the stream. The feasibility of this approach lies in the shape of the recession stage of the flood hydrograph, which is known to be a repeating phenomenon. The recession stage comes immediately after the peak flow rate, when it begins its decline, and lasts until the flood is extinguished. A general shape of the flood recession stage can be provided. Because the recession stage represents ~80% of the duration of a flood event, it can provide a general idea of the flood hydrograph's shape. A simple model based on geometric progression is suggested to describe the repeating recession stage of a flood. The advantage of the proposed model is that it requires only one parameter: the recession characteristic at a fixed point along the ephemeral stream, termed recession coefficient q. By knowing the recession coefficient of a fixed point and the peak flow rate of a flood event at that point, one can plot the flood hydrograph. A good agreement is shown between the observed and computed values of the recession stage. Copyright © 2016 John Wiley & Sons, Ltd.     

Copula models for frequency analysis what can be learned from a Bayesian perspective?

Large spring floods in the Québec region exhibit correlated peakflow, duration and volume. Consequently, traditional univariate hydrological frequency analyses must be complemented by multivariate probabilistic assessment to provide a meaningful design flood level as requested in hydrological engineering (based on return period evaluation of a single quantity of interest). In this paper we study 47 years of a peak/volume dataset for the Romaine River with a parametric copula model. The margins are modeled with a normal or gamma distribution and the dependence is depicted through a parametric family of copulas (Arch 12 or Arch 14). Parameter joint inference and model selection are performed under the Bayesian paradigm. This approach enlightens specific features of interest for hydrological engineering: (i) cross correlation between margin parameters are stronger than expected , (ii) marginal distributions cannot be forgotten in the model selection process and (iii) special attention must be addressed to model validation as far as extreme values are of concern.     

A steepness index unit volume flood hydrograph approach for sub‐daily flow disaggregation

The estimation of sub‐daily flows from daily flood flows is important for many hydrological and hydraulic applications. Flows during flood events often vary significantly within sub‐daily time‐scales, and failure to capture the sub‐daily flood characteristic can result in an underestimation of the instantaneous flood peaks, with possible risk of design failure. It is more common to find a longer record of daily flow series (observed or modelled using daily rainfall series) than sub‐daily flow data. This paper describes a novel approach, known as the steepness index unit volume flood hydrograph approach, for disaggregating daily flood flows into sub‐daily flows that takes advantage of the strong relationship between the standardized instantaneous flood peak and the standardized daily flood hydrograph rising‐limb steepness index. The strength of this relationship, which is considerably stronger than the relationship between the standardized flood peak and the event flood volume, is shown using data from six rivers flowing into the Gippsland Lakes in southeast Australia. The results indicate that the steepness index unit volume flood hydrograph approach can be used to disaggregate modelled daily flood flows satisfactorily, but its reliability is dependent on a model's ability to simulate the standardized daily flood hydrograph rising‐limb steepness index and the event flood volume. Copyright © 2007 John Wiley & Sons, Ltd.     

Application of copulas for derivation of drought severity–duration–frequency curves

This study presents copula‐based multivariate probabilistic approach to model severity–duration–frequency (S‐D‐F) relationship of drought events in western Rajasthan, India. Drought occurrences are analysed using standardized precipitation index computed on monthly mean areal precipitation, aggregated at a time scale of 6 months. After testing with a series of probability density functions, the drought variable severity is found to be better represented with log‐normal distribution, whereas duration is well fitted with exponential distribution. Four different classes of bivariate copulas – Archimedean, extreme value, Plackett, and elliptical families are evaluated for modelling joint distribution of drought characteristics. It is observed that the extreme value copula – Gumbel–Hougaard copula – performed better as compared with other classes of copulas, based on results of various statistical tests and upper tail dependence coefficient. The joint distribution obtained from best performing copula is then employed to determine conditional return period and to derive drought severity‐duration‐frequency (S‐D‐F) curves for the study region. The results of the study suggests that the copula method can be used effectively to derive the drought S‐D‐F curves, which can be helpful in planning and adopting suitable drought mitigation strategies in drought‐prone areas. Copyright © 2011 John Wiley & Sons, Ltd.     

Data‐based analysis of bivariate copula tail dependence for drought duration and severity

In recent decades, copula functions have been applied in bivariate drought duration and severity frequency analysis. Among several potential copulas, Clayton has been mostly used in drought analysis. In this research, we studied the influence of the tail shape of various copula functions (i.e. Gumbel, Frank, Clayton and Gaussian) on drought bivariate frequency analysis. The appropriateness of Clayton copula for the characterization of drought characteristics is also investigated. Drought data are extracted from standardized precipitation index time series for four stations in Canada (La Tuque and Grande Prairie) and Iran (Anzali and Zahedan). Both duration and severity data sets are positively skewed. Different marginal distributions were first fitted to drought duration and severity data. The gamma and exponential distributions were selected for drought duration and severity, respectively, according to the positive skewness and Kolmogorov–Smirnov test. The results of copula modelling show that the Clayton copula function is not an appropriate choice for the used data sets in the current study and does not give more drought risk information than an independent model for which the duration and severity dependence is not significant. The reason is that the dependence of two variables in the upper tail of Clayton copula is very weak and similar to the independent case, whereas the observed data in the transformed domain of cumulative density function show high association in the upper tail. Instead, the Frank and Gumbel copula functions show better performance than Clayton function for drought bivariate frequency analysis. Copyright © 2012 John Wiley & Sons, Ltd.     

Flooding duration and volume more important than peak discharge in explaining 18 years of gravel–cobble river change

Floods play a critical role in geomorphic change, but whether peak magnitude, duration, volume, or frequency determines the resulting magnitude of erosion and deposition is a question often proposed in geomorphic effectiveness studies. This study investigated that question using digital elevation model differencing to compare and contrast three hydrologically distinct epochs of topographic change spanning 18 years in the 37-km gravel–cobble lower Yuba River in northern California, USA. Scour and fill were analysed by volume at segment and geomorphic reach scales. Each epoch's hydrology was characterized using 15-min and daily averaged flow to obtain distinct peak and recurrence, duration, and volume metrics. Epochs 1 (1999–2008) and 3 (2014–2017) were wetter than average with large floods reaching 3206 and 2466 m³/s, respectively, though of different flood durations. Epoch 2 (2008–2014) was a drought period with only four brief moderate floods (peak of 1245 m³/s). Total volumetric changes showed that major geomorphic response occurred primarily during large flood events; however, total scour and net export of sediment varied greatly, with 20 times more export in epoch 3 compared to epoch 1. The key finding was that greater peak discharge was not correlated with greater net and total erosion; differences were better explained by duration and volume above floodway-filling stage. This finding highlights the importance of considering flood duration and volume, along with peak, to assess flood magnitude in the context of flood management, frequency analysis, and resulting geomorphic changes.