Statistics of extremes in hydrology

By R. Katz, Marc B. Parlange, Philippe Naveau. 2002

1,641 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/799d5b0a3f01e860d77d68ce7f6ec381820151af

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

In Water Science and Technology

Citations in the corpus

Extremes on river networks (2015, result): “National studies conclude that there are no significant trends in the extremes of stream flows in our area of interest (Katz et al., 2002; Kundzewicz et al., 2005), in agreement with our exploratory analysis, so henceforth we treat our data as temporally stationary.”
Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach (2017, methodology): “Indeed, the POT approach generally allows considering a larger number of extreme events than the BM approach (Begueria et al. 2011; Bezak et al. 2014; Coles 2001; Davison and Smith 1990; Katz 2013; Katz et al. 2002; Osman et al. 2013; Roth et al. 2012; Zoglat et al. 2014).”
Comprehensive evaluation of regional flood frequency analysis by L- and LH-moments. II. Development of LH-moments parameters for the generalized Pareto and generalized logistic distributions (2009, background): “Some of the more relevant research in this case include, and are not limited to GREHYS (1996), Madsen et al. (1997a, b), Lang et al. (1999) and Katz et al. (2002) .”
A Review of Extreme Value Threshold Estimation and Uncertainty Quantification (2012, background): “The threshold of u = 0.395 inches suggested by Katz et al. (2002) gives over 1000 exceedances, and is justified by the empirical MRL becoming close to linear above this level, and below this level a curved MRL is observed indicating a bias due to the GPD asymptotics breaking down.”
A Bayesian hierarchical approach to regional frequency analysis (2011, methodology): “X - 18 RENARD: HIERARCHICAL REGIONAL ESTIMATION 2009]. However, the possible underestimation of predictive uncertainty in the absence of 326 regression errors still holds. 327 Lastly, the Bayesian hierarchical framework shares several similarities with the GLS 328 approach proposed by Stedinger and ”
Comparison of methods for non-stationary hydrologic frequency analysis: Case study using annual maximum daily precipitation in Taiwan (2017, methodology): “Besides, incorporating teleconnection indices into frequency models as covariates also has been shown improve the statistical modeling of extreme events (Villarini et al., 2009; Cox et al., 2002; Katz et al., 2002; Vasiliades et al., 2015; Li et al., 2015).”
A review of statistical methods to analyze extreme precipitation and temperature events in the Mediterranean region (2019, methodology): “The GEV commonly fits the block maxima series (Kotz and Nadarajah 1999; Kharin and Zwiers 2000; Katz et al. 2002; García et al. 2002), while the GPD distribution fits data series produced by the peaks over threshold (POT) method (Katz et al. 2002).”
Use of a Gaussian copula for multivariate extreme value analysis: Some case studies in hydrology (2007, background): “More generally, we believe that multivariate extreme events analysis is likely to improve hydrological risks assessment, as emphasized by Katz et al. [31].”
Monte Carlo experiments on the detection of trends in extreme values (2004, methodology): “For example, days with precipitation tend to occur in clusters (Katz et al. 2002).”
Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database (2016, background): “…block-maxima over different years [see e.g., Bernard, 1932; Demar ee, 1985; Cunnane, 1973; Madsen et al., 1997a,1997b; Koutsoyiannis et al., 1998; Katz et al., 2002; Papalexiou and Koutsoyiannis, 2013; Serinaldi and Kilsby, 2014], while PDS are constructed by retaining all excesses above a…”
Extreme rainfall in West Africa: A regional modeling (2012, background): “[3] The extreme value theory (EVT) [see, e.g., Coles, 2001; Katz et al., 2002] is the most widely used statistical framework to study the extremes.”
Downscaling extremes: A comparison of extreme value distributions in point-source and gridded precipitation data (2010, background): “Katz, Parlange and Naveau (2002) gave an excellent overview of the application of extreme value methods in hydrology.”
Climate-change effects on extreme precipitation in central Europe: uncertainties of scenarios based on regional climate models (2009, background): “The POT approach also adapts better to heavytailed distributions (Madsen et al. 1997; May 2004) which are typical for extreme daily precipitation totals ( Katz et al. 2002; Koutsoyiannis 2004; Kyselý and Picek 2007).”
INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles (2018, methodology): “However, its tail decays exponentially fast, and is therefore often found to be too light and to underestimate probabilities associated with extreme events (Katz et al. , 2002); by contrast, the GP model used in Stage 3 is motivated by asymptotic theory, and can capture heavy tails.”