Non-stationary approach to at-site flood frequency modelling I. Maximum likelihood estimation Academic Article uri icon

abstract

  • For dealing with hydrological non-stationarity in flood frequency modelling (FFM) and hydrological design, it is necessary to account for trends. Taking the case of at-site FFM, statistical parametric techniques are discussed for investigation of the time-trend. The investigation entails (1) an identification of a probability distribution, and (2) development of a trend software. The Akaike Information Criterion (AIC) was used to identify the optimum distribution, i.e. the distribution and trend function, which enabled an identification of the optimum non-stationary FFM in a class of 56 competing models. The maximum likelihood (ML) method was used to estimate the parameters of the identified model using annual peak discharge series. A trend can be assumed in the first two moments of a probability distribution function and it can be of either linear or parabolic form. Both the annual maximum series (AMS) and partial duration series (PDS) approach were considered in the at-site frequency modeling. 2001 Elsevier Science B.V.

published proceedings

  • Journal of Hydrology

author list (cited authors)

  • Strupczewski, W. G., Singh, V. P., & Feluch, W.

citation count

  • 201

complete list of authors

  • Strupczewski, WG||Singh, VP||Feluch, W

publication date

  • July 2001