Mahsa Mirdashtvan; Ali Najafinejad; Amir Sadoddin
Abstract
Trend and stationarity analyses of hydrological variables are useful tools for understanding climate change and may provide useful information about likely changes in the future. As non-stationary of time series can occur due to various reasons such as trend existence in data; therefor, in current study ...
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Trend and stationarity analyses of hydrological variables are useful tools for understanding climate change and may provide useful information about likely changes in the future. As non-stationary of time series can occur due to various reasons such as trend existence in data; therefor, in current study the non-parametric Mann-Kendall trend test was used to detect the trend of the data. A corrector approach, namely “TFPW” was utilized to modify the effects of serial dependence of the time series on the trend detection results. The stationarity of time series was tested by unit root and stationarity tests to evaluate the relationship between trend and stationarity of the time series. The results showed that the surface flows of all of the studied rivers have a decreasing trend; although the significant trends changed to insignificant ones after applying TFPW approach. The results of the stationarity tests showed non-stationary time series for all of the sites after removing the serial dependence of the series, which is a sign of the lack of trend existence in the time series; however, Latian station (Lar river) reveals non-stationarity after applying TFPW which may be originated from the existence of abrupt changes in the series. The findings of current study can help the planners and policy-makers and water resources managers to cope with climate change in the future.
