Frequency analysis of a sequence of dependent and/or non-stationary hydro-meteorological observations: a review

By M. N. Khaliq, Taha B. M. J. Ouarda, Jean-Cléophas Ondo, Philippe Gachon, Bernard Bobée. 2006

454 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/5be0035d5f1dffbf0541b8a23fa46db4df9f893f

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In Environmental Engineering

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Citations in the corpus

Evaluating the Three Methods of Goodness of Fit Test for Frequency Analysis (2015, methodology): “There are three steps in frequency analysis (Khaliq et al., 2006): (i) selecting a suitable probability distribution function (PDF); (ii) estimating the parameters of PDF based on samples; (iii) assessing the uncertainty of objective of interest in prescribed confidence level.”
Non‐stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil (2009, methodology): “POT approach and GPD model The POT approach is described as follows (Smith, 2001; Khaliq et al., 2006): Consider a sequence of M iid random variables X1,X2, . . . , XM conditioned on X > u, where u is a given high threshold.”
Modelling nonlinear trend for developing non‐stationary rainfall intensity–duration–frequency curve (2017, methodology): “Therefore, as recommended by previous researchers (Kharin and Zwiers, 2004; Khaliq et al., 2006; Cannon, 2010), the residual bootstrap technique can be used to estimate the confidence intervals for non-stationary GEV distribution parameters.”
Quantile regression neural networks: Implementation in R and application to precipitation downscaling (2011, methodology): “As pointed out by Khaliq et al. (2006), however, quantile regression is well suited for nonparametric, nonstationary extreme value analysis of annual series of ﬂood or precipitation extremes.”
Non-Stationary Frequency Analysis of Extreme Water Level: Application of Annual Maximum Series and Peak-over Threshold Approaches (2017, methodology): “Although the assumption of independency for the extreme water levels can be justified by temporal resolution, the likelihood of stationarity, resulted from the existing trends in the mean and/or the variability of the observations, is often suspected (Khaliq et al. 2006).”
Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach (2017, methodology): “The first metric (xp) is more appropriate in a nonstationary case according to the meaning of the Treturn period (Khaliq et al. 2006; Salas and Obeysekera 2014).”
A framework of change‐point detection for multivariate hydrological series (2015, background): “The assumption of stationarity, a basic premise behind conventional hydrological frequency analysis, is often necessary in hydrologic practice such as hydrologic design but may be invalid for nonstationary hydrological series [Khaliq et al., 2006].”
Historical changes and future projection of extreme precipitation in China (2015, background): “The generalized extreme value (GEV) distribution is widely applied for modeling extreme events in meteorology and many other fields (Coles et al. 2003; Khaliq et al. 2006).”