Nonstationary analysis of annual flow indices in western Taiwan

Abstract

Flow indices are important and robust indicators to support the decisions for water resources management and flood control Due to the climate change and rapid urbanization the assumption of stationary condition used in water resources planning and hydraulic design may not be applicable In this study the generalized additive model for location scale and shape (GAMLSS) is used to model the nonstationarity of 10 annual flow indices of three main river basins in western Taiwan (Dan-Shui Zhuo-Shui Kao-Ping) which include total runoff maximum 1-day streamflow minimum 1- 7- 30-day streamflow Q5 Q25 Q50 Q75 and Q95 The results indicate that (1) the best probability model for fitting flow indices (180 models in total) are the gamma distribution (54 models) log-normal distribution (53 models) and Weibull distribution (41 models) Among these models 145 models show nonstationarity (2) The minimum 1-day streamflow of all stations exhibits nonstationarity On the other hand only half stations show nonstationarity in the maximum 1-day streamflow (3) The model incorporating the reservoir index as the covariate shows better performance than the model using the time as covariate for the maximum 1-day streamflow and Q5 indices (4) The GAMLSS framework provides not only the trend of hydro-climate series but also point out the information of distributional changes

Date of Award	2020
Original language	English
Supervisor	Jenq-Tzong Shiau (Supervisor)