A master’s thesis was discussed in Department of Dams  and Water Resources Engineering / College of Engineering at University of Mosul entitled "Non-Stationarity Removing in Flow Time Series using Wavelets Transform Technique of al-Khabor River" on Tuseday, Oct. 12, 2021 submitted by postgraduate student (Reyan Hussein Saleh) and Supervised By Prof. Dr. Kamel Ali Abd Al-Mohseen.

The study explored the possibility of using Discrete Wavelets Transform technique (DWT) in diagnosing the usually imbedded non-stationarity in hydrologic time series, which typically masks the real characteristics of those series. The difficulties accompanied the presence of the non-stationarity arise when one is trying to fit linear traditional stochastic stationary models such as AR, AM and ARMA for the purpose of prediction and/or forecasting the outcomes of the process in hand. This is in fact considered an important task in the contest of planning and management of water resources systems.

Basically, this manuscript divided into two phases: in the first phase, a defined stochastic linear model parameter, i.e. (ARMA (1,1)) was developed with known parameters and of (0.8 and 0.4) respectively. The ACF and PACF analyses before and after intentionally adding some defined deterministic components (such as trend, periodicity, etc.) confirm the capability of (DWT) in diagnosing those non-stationarity sources. After removing such sources of non-stationarity, the parameters of the model have been restored to approximately their original values. While phase two makes use of (DWT) technique in diagnozing the non-statioarity in an observed flow time series of al-Khabor River, Kurdistan region-Iraq, where 24 years of flow time series is available. After removing the source of the non-stainarity diagnozed by the proposed method in the data, a stationary model (ARMA (2,1)) has been fitted.

Also Read