Non-stationary approach to at-site flood frequency modelling I. Maximum likelihood estimation
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 iden...
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| Veröffentlicht in: | Journal of hydrology (Amsterdam) 2001-07, Vol.248 (1), p.123-142 |
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| container_title | Journal of hydrology (Amsterdam) |
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| creator | Strupczewski, W.G. Singh, V.P. Feluch, W. |
| description | 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. |
| doi_str_mv | 10.1016/S0022-1694(01)00397-3 |
| format | Article |
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| subjects | computer software Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Exact sciences and technology Flood Frequency Hydrology Hydrology. Hydrogeology Natural hazards: prediction, damages, etc Partial duration series probability distribution Time series Trend |
| title | Non-stationary approach to at-site flood frequency modelling I. Maximum likelihood estimation |
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