A new threshold selection method for peak over for nonstationary time series

International Conference on Water Resource and Environment 2016

地球科学;生态环境科学

Zhou, C.R.^1 ; Chen, Y.F.^1 ; Gu, S.H.^2 ; Huang, Q.^1 ; Yuan, J.C.^1 ; Yu, S.N.^1

Hohai University, College of Hydrology and Water Resources, Nanjing

210000, China^1

Shanghai Hydrological General Station, Shanghai

200000, China^2

关键词: Annual maximum series;    Global climate changes;    Hydrological time-series;    Non-stationarities;    Non-stationary time series;    Peak over threshold;    Stationary stochastic process;    Threshold selection;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/39/1/012071/pdf
DOI  :  10.1088/1755-1315/39/1/012071

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In the context of global climate change, human activities dramatically damage the consistency of hydrological time series. Peak Over Threshold (POT) series have become an alternative to the traditional Annual Maximum series, but it is still underutilized due to its complexity. Most literature about POT tended to employ only one threshold regardless of the non-stationarity of the whole series. Obviously, it is unwise to ignore the fact that our hydrological time series may no longer be a stationary stochastic process. Hence, in this paper, we take the daily runoff time series of the Yichang gauge station on the Yangtze River in China as an example, and try to shed light on the selection of the threshold provided non- stationarity of our time series. The Mann-Kendall test is applied to detect the change points; then, we gave different thresholds according to the change points to the sub-series. Comparing the goodness-of-fit of the series with one and several thresholds, it clearly investigates the series that employs different thresholds performs much better than that just fixes one threshold during the selection of the peak events.