New idea and two new methods for identifying periodicities of hydrological time series

In this thesis,a new idea for estimating the periodicities of hydrological time series is put forward. Two new methods,series simulating and prolonging method(SSAP)and main frequency series reconstructing method(MFSR),are developed. The former is to build a suitable model to prolong the length of the original series,and the latter is to reconstruct the main frequency series of the original series. Maximum Entropy Spectral Analysis(MESA)is used to analyze the periods of new series. Various period-estimating methods(including traditional ones and newly developed ones)are used to identify which is better for same time series. Results show that the traditional methods(Fast Fourier Transform,MESA and Wavelet Analysis) are not as good as expected because of the influences of short length of series,complex random series and skew distribution, etc. However,using new methods(SSAP,MFSR)are not so strongly affected. It can be concluded that the new methods would greatly improve the estimation of results and,to some extent,eliminate disturbance.