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Öğe Application of Signal Processing in Tracking Meteorological Drought in a Mountainous Region(Birkhauser, 2021) Vaheddoost, Babak; Safari M.J.S.This study addresses the application of signal processing in the evaluation of meteorological drought associated with monthly precipitation time series. Several drought indices and a Haar wavelet decomposition (WD) with ten components are implemented in the evaluation of the monthly precipitation of a mountainous region called Mount Uludag in Turkey. Monthly precipitation time series in three meteorological stations at the summit and foothills are used. The Standardized Precipitation Index (SPI) is used at monthly, annual, and 12- and 48-month moving average time frames as the benchmark to investigate the drought patterns. The results obtained by the WD and SPI are then confirmed using the Z-score index (ZSI) at monthly and annual scales, together with the modified China Z-index (MCZI) and rainfall anomaly index (RAI) at a monthly scale. Changes in the moments of the distribution, correlation analysis, mutual information, and power spectrum are applied to investigate the nature of the relationship between the sequences of precipitation events in time and space. The temporal correlation analysis, together with the mutual information, showed that the system has a short-term memory with strong seasonality. Similarly, the power spectra depicted major seasonality at 1, 3, 5, 6, 12, 22, and 60 months in the precipitation time series. It is concluded that the recent drought events have an infrequent nature, which altered the sinusoidal patterns of the large-scale events. The SPI-48 and the WD showed that declines are strongly related to the large-scale cycles, but the decline patterns are more related to the station located at the mountain summit.Öğe Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients(Elsevier Ltd, 2021) Vaheddoost, Babak; Safari M.J.S.; Ilkhanipour Zeynali R.A novel method is suggested for the determination of flow discharge in vertical sluice gates with considerably small bias. First, in order to derive an equation for the discharge coefficient, energy-momentum equations are implemented to define the physical realization of the phenomenon. Afterward, the discharge coefficient is presented in terms of contraction and energy loss coefficients. Subsequently, discharge coefficient, contraction, and energy loss coefficients were determined through an implicit optimization technique on the data. Data analysis illustrated that there is a meaningful power relationship between the contraction and energy loss coefficients. Thereafter, dimensional analysis is performed and an explicit best-fit regression equation is developed for defining the energy loss coefficient. The obtained equations for contraction and energy loss coefficients were then used in the computation of the discharge coefficient and determination of the flow discharge in the vertical sluice gate. The performance of the developed approach is validated against the selected benchmarks existing in the literature.