Non-stationary approach to at-site flood frequency modelling I. Maximum likelihood estimation

By W. Strupczewski, Vijay P. Singh, W. Feluch. 2001

265 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/7c581d09fdb78c51cd2ca619454f1ce084678fc9

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

1. Chong-yu Xu
2. Shenglian Guo
3. R. Palmer
4. Kuk‐Hyun Ahn
5. Lihua Xiong
6. Saeed Golian
7. Z. Zahmatkesh
8. A. Razmi

In Water Science and Technology

1. R. Palmer
2. Kuk‐Hyun Ahn
3. Shenglian Guo
4. Chong-yu Xu
5. S. E. Debele
6. E. Bogdanowicz
7. Lihua Xiong
8. Cong Jiang

Citations in the corpus

• Modelling nonlinear trend for developing non‐stationary rainfall intensity–duration–frequency curve (2017, methodology): “The best model The Akaike information criterion (AIC), which penalizes the minimized −L(𝛽/X) for the number of parameters estimated, can be used to select the best model (Strupczewski et al., 2001; Katz, 2013).”
• Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice (2018, methodology): “…moments model The time-varying moments model expresses the distribution parameters or moments as functions of time or some other explanatory variable(s), and has been widely employed to capture the nonstationarity of univariate flood series (Strupczewski et al., 2001; Villarini et al., 2009).”
• Comparison of methods for non-stationary hydrologic frequency analysis: Case study using annual maximum daily precipitation in Taiwan (2017, methodology): “AOGCM predictions of precipitation are even less certain than those of temperature, rendering them largely inapplicable for engineering purpose (Miller and Russell, 1992; Strupczewski et al., 2001).”
• A framework of change‐point detection for multivariate hydrological series (2015, background): “…series [Kendall, 1975; Chiew and McMahon, 1993; Moraes et al., 1998; Perreault et al., 1999; Rasmussen, 2001; Strupczewski and Kaczmarek, 2001; Strupczewski et al., 2001a,b; Yue et al., 2002; Wong et al., 2006; El Adlouni et al., 2007; Villarini et al., 2009; Villarini and Serinaldi, 2012;…”
• Use of a nonstationary copula to predict future bivariate low flow frequency in the Connecticut river basin (2016, background): “Most nonstationary frequency analysis has directed to the investigation floods (high flow): annual daily maximum flood (Strupczewski et al., 2001; Delgado et al., 2010; López and Francés, 2013), frequency of floods (Silva et al.”
• A comparison of three approaches to non-stationary flood frequency analysis (2017, background): “As has been proved in Strupczewski and Feluch (1998); Strupczewski et al. (2001b), ML provides efficient estimators of time-dependent moments only in the case of long time series and the functional forms of distribution and trend approximating well the true forms.”
• Non‐stationary intensity‐duration‐frequency curves integrating information concerning teleconnections and climate change (2018, background): “Strupczewski et al. (2001) incorporated hydrological non-stationarity into at-site flood frequency analysis (FFA).”
• Non-Stationary Frequency Analysis of Extreme Water Level: Application of Annual Maximum Series and Peak-over Threshold Approaches (2017, background): “Methods of time-varying moments can be employed for non-stationary flood FA (Strupczewski et al. 2001a, b; Strupczewski and Kaczmarek 2001; Coles 2001; Katz et al. 2002; Khaliq et al. 2006; Villarini et al. 2009; Salas and Obeysekera 2014).”