Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstation-arity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold) data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.
|Number of pages||4|
|Journal||IAHS-AISH Proceedings and Reports|
|Publication status||Published - 2015|
|Event||HS02 � Hydrologic Non-Stationarity and Extrapolating Models to Predict the Future in the 2015 IUGG General Assembly - Prague, Czech Republic|
Duration: 2015 Jun 22 → 2015 Jul 2
Bibliographical notePublisher Copyright:
© Author(s) 2015.
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)