Time Series Analysis of Trend and Variability of Monthly Total Rainfall
R. Ramakrishna1, R.Gautham Goud2, Alemayehu Sbhat3
1R. Ramakrishna*, Professor, Vidya Jyothi Institute of Technology, CB Post, Aziznagar, Hyderabad, India.
2R.Gautham Goud, Asst Professor, CVR College of Engineering, Mangalapally, Ibrahimpatan, Hydearabad, India.
3Alemayehu Sbhat, Department of Statistics, CNCS, Mekelle University, Mekelle, Tigray, Ethiopia.
Manuscript received on June 28, 2021. | Revised Manuscript received on July 07, 2021. | Manuscript published on July 30, 2021. | PP: 104-114 | Volume-10 Issue-2, July 2021. | Retrieval Number: 100.1/ijrte.B61900710221| DOI: 10.35940/ijrte.B6190.0710221
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The long-term variation in rainfall, one of the most important conditions for the climate in a particular region. The purpose of this study was to analysis the total monthly rainfall in the Maychew, which is located in the Tigray region of Ethiopia. The monthly rainfall is on the Maychew meteorological station has been calculated for the period from 2007-2018. The data were analyzed with the help of Minitab-14, R-3.3.1 an Overview of the descriptive statistics and unvaried, Box-Jenkins method, The seasonal ARIMA model was built to analyze the observed data and forecast the total rainfall, after the detection of non stationarity using the Augmented Dickey-Fuller Test is a Test, and time plot. Some of the main findings of the study indicated that the monthly total rainfall tends to increase. In addition, it was found that, on the basis of the data contained in the history of the last twelve years of age. In addition, the descriptive statistics show that the average amount of rainfall in the Maychew is 58.82. After non-seasonal the first-order differentiation and once seasonal series, differentiation, they will be moved. A time series model for the Maychew Station and was adapted to be processed, diagnostically tested, and ultimately, to be obtained by SARIMA (3, 2, 2)*(0, 2, 2)12 a model has been created, and this model was used to Forecast the two years monthly values of the total rainfall. The forecasted accumulated rainfall values showed a similar pattern to the previous reports.
Keywords: Box-Jenkins methodology, Variability of rainfall, Non-stationary, SARIMA