Trivariate Flood Frequency Analysis Using Discharge Time Series with Possible Different Lengths: Cuyahoga River Case Study

AbstractA common approach to multivariate flood frequency analysis is to apply discharge time series records with the same length (i.e., one upstream and one downstream discharge gauge in the same river for bivariate flood frequency analysis, and multivariate flood frequency analysis at the confluence of river systems). However, in reality the gauged discharge time series records may have different lengths due to different activation times of the gauges. In addition, there exists one common assumption for flood frequency analysis, that is, the discharge time series may be considered as a stationary signal. However, due to land-use and land-cover (LULC) and climate changes, the stationary assumption may need to be justified. To answer the above questions, this paper investigates (1) the full-length discharge record at each discharge gauge; (2) the dependence structure of bivariate and multivariate discharge time series with different lengths using the copula theory; (3) employment of the vine copula for mu...

[1]  Rao S. Govindaraju,et al.  Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas , 2008 .

[2]  V. Singh,et al.  Application of Archimedean copulas in the analysis of the precipitation extremes: effects of precipitation changes , 2011, Theoretical and Applied Climatology.

[3]  Hongxing Zheng,et al.  Responses of streamflow to climate and land surface change in the headwaters of the Yellow River Basin , 2009 .

[4]  Luis Samaniego,et al.  Streamflow prediction in ungauged catchments using copula‐based dissimilarity measures , 2010 .

[5]  D. Widder,et al.  The Laplace Transform , 1943, The Mathematical Gazette.

[6]  Miguel A. Losada,et al.  Non-stationary wave height climate modeling and simulation , 2011 .

[7]  Glenn E. Moglen,et al.  Trend Assessment in Rainfall-Runoff Behavior in Urbanizing Watersheds , 2002 .

[8]  Claudia Czado,et al.  Pair-Copula Constructions of Multivariate Copulas , 2010 .

[9]  C. Genest,et al.  The Joy of Copulas: Bivariate Distributions with Uniform Marginals , 1986 .

[10]  A. Bárdossy Copula‐based geostatistical models for groundwater quality parameters , 2006 .

[11]  M. Rosenblatt Remarks on a Multivariate Transformation , 1952 .

[12]  Francesco Serinaldi,et al.  Fully Nested 3-Copula: Procedure and Application on Hydrological Data , 2007 .

[13]  Andrew J. Patton Estimation of multivariate models for time series of possibly different lengths , 2006 .

[14]  A. Favre,et al.  Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data , 2007 .

[15]  G. Evin,et al.  A new rainfall model based on the Neyman‐Scott process using cubic copulas , 2008 .

[16]  Vijay P. Singh,et al.  Evaluation of risk of hydrological droughts by the trivariate Plackett copula in the East River basin (China) , 2013, Natural Hazards.

[17]  B. Bobée,et al.  Multivariate hydrological frequency analysis using copulas , 2004 .

[18]  A. Bárdossy,et al.  Geostatistical interpolation using copulas , 2008 .

[19]  Conleth Cunnane,et al.  Review of Statistical Models for Flood Frequency Estimation , 1987 .

[20]  Renzo Rosso,et al.  Bivariate Statistical Approach to Check Adequacy of Dam Spillway , 2005 .

[21]  A. Robson,et al.  A study of national trend and variation in UK floods , 1998 .

[22]  Gianfausto Salvadori,et al.  Frequency analysis via copulas: Theoretical aspects and applications to hydrological events , 2004 .

[23]  Vijay P. Singh,et al.  Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm , 2010 .

[24]  F. Serinaldi A multisite daily rainfall generator driven by bivariate copula-based mixed distributions , 2009 .

[25]  C. Genest,et al.  Statistical Inference Procedures for Bivariate Archimedean Copulas , 1993 .

[26]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[27]  R. Bartels The Rank Version of von Neumann's Ratio Test for Randomness , 1982 .

[28]  M. Sklar Fonctions de repartition a n dimensions et leurs marges , 1959 .

[29]  A. Frigessi,et al.  Pair-copula constructions of multiple dependence , 2009 .

[30]  A. Sankarasubramanian,et al.  Climate elasticity of streamflow in the United States , 2001 .

[31]  Ni-Bin Chang,et al.  Copula‐based flood frequency (COFF) analysis at the confluences of river systems , 2009 .

[32]  Harald Kunstmann,et al.  Copula-based statistical refinement of precipitation in RCM simulations over complex terrain , 2011 .

[33]  Vijay P. Singh,et al.  Trivariate Flood Frequency Analysis Using the Gumbel–Hougaard Copula , 2007 .

[34]  Niko E. C. Verhoest,et al.  A comparative copula‐based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett‐Lewis modeled rainfall , 2011 .

[35]  V. Singh,et al.  Bivariate Flood Frequency Analysis Using the Copula Method , 2006 .

[36]  G. Moglen,et al.  Adjusting measured peak discharges from an urbanizing watershed to reflect a stationary land use signal , 2003 .

[37]  V. Singh,et al.  Spatio-temporal variations of precipitation extremes in Xinjiang, China , 2012 .

[38]  George E. P. Box,et al.  Time Series Analysis: Box/Time Series Analysis , 2008 .

[39]  G. Moglen,et al.  Methods for Adjusting U.S. Geological Survey Rural Regression Peak Discharges in an Urban Setting , 2006 .

[40]  Vijay P. Singh,et al.  Bivariate rainfall frequency distributions using Archimedean copulas , 2007 .

[41]  Wen Wang,et al.  Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes , 2005 .

[42]  J. Wolfowitz,et al.  On a Test Whether Two Samples are from the Same Population , 1940 .

[43]  Roger M. Cooke,et al.  Uncertainty Analysis with High Dimensional Dependence Modelling: Kurowicka/Uncertainty Analysis with High Dimensional Dependence Modelling , 2006 .

[44]  Bruno Rémillard,et al.  Goodness‐of‐fit Procedures for Copula Models Based on the Probability Integral Transformation , 2006 .

[45]  Use of observed scaled daily storm profiles in a copula based rainfall disaggregation model , 2012 .

[46]  Vijay P. Singh,et al.  Gumbel–Hougaard Copula for Trivariate Rainfall Frequency Analysis , 2007 .

[47]  B. Rémillard,et al.  Goodness-of-fit tests for copulas: A review and a power study , 2006 .

[48]  Yongqiang Zhang,et al.  Relative merits of different methods for runoff predictions in ungauged catchments , 2009 .

[49]  R. Govindaraju,et al.  A bivariate frequency analysis of extreme rainfall with implications for design , 2007 .