To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
P. F. Rasmussen, Institute of Hydrodynamics and Hydraulic Engineering, Technical University of Denmark, Lyngby, Denmark,
D. Rosbjerg, Institute of Hydrodynamics and Hydraulic Engineering, Technical University of Denmark, Lyngby, Denmark
ABSTRACT In order to obtain a good description of the exceedances in a partial duration series it is often necessary to divide the year into a number (2–4) of seasons. Hereby a stationary exceedance distribution can be maintained within each season. This type of seasonal model may, however, not be suitable for prediction purposes due to the large number of parameters required. In the particular case with exponentially distributed exceedances and Poissonian occurrence times the precision of the T-year event estimator has been thoroughly examined considering both seasonal and non-seasonal models. The two-seasonal probability density function of the T-year event estimator has been deduced and used in the assessment of the precision of approximate moments. The non-seasonal approach covered both a total omission of seasonality by pooling data from different flood seasons and a discarding of nonsignificant season(s) before the analysis of extremes. Mean square error approximations (bias second order, variance first and second order) were employed as measures for prediction uncertainty. It was found that optimal estimates can usually be obtained with a non-seasonal approach.
Since its introduction into flood frequency analysis, the partial duration series (PDS) method has gained increased acceptance as an appealing alternative to the annual maximum series (AMS) method. PDS models were introduced in hydrology by Shane & Lynn (1964), and Todorovic & Zelenhasic (1970). They assumed independent and identically distributed exceedances occurring according to a Poisson process with time-dependent intensity.
Email your librarian or administrator to recommend adding this to your organisation's collection.