Results of model fitting showed that three models Based on the test results, logarithmic transformation andįirst order differencing were performed to bring the original series to a (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests were among the Normality tests conducted whereas, Augmented Dickey-Fuller (ADF), Phillips-Perron Shapiro-Wilk (SW),Īnderson-Darling (AD) and Kolmogorov-Smirnov (KS) tests were among the Was from a normally distributed and stationary process. Series, normality and stationarity tests were conducted to check if the time series (over the period 1954-2015) of Debre Markos town, Ethiopia. Identify and examine a capable stochastic model for annual rainfall series Moving average (ARMA) and autoregressive integrated moving average (ARIMA) Autoregressive (AR), moving average (MA), autoregressive Many statistics-based methods are available to simulate and Which calls for time series analysis to better understand interesting featuresĬontained in it. Rainfall process is one of such hydrologic events Simulation of temporally sequenced and stochastic hydrologic events. Many years planning and management of water resources involved modeling and
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