Vol. 8, Special Issue 4 (2020)
Time series ARIMA model to forecast monthly precipitation for Balodabazar, Bemetara and Raipur (Chhattisgarh)
Author(s): Avinash Yadu, Anosh Graham and Anurag Sanadya
Abstract: Weather forecasting is an important issue in meteorology and scientific research in this research, the Seasonal Auto Regressive Integrated Moving Average (ARIMA) model, which is based on Box-Jenkins method, was adopted to build the forecasting model. The Monthly Rainfall data for Balodabazar, Bemetara, Raipur city for the period (Jan. 1968 to Dec. 2018) was used. The autocorrelation and partial autocorrelation functions for time series data from years 1968 to 2018 were used to identify the most appropriate orders of the ARIMA models. To calculate the model's accuracy and compare among them, statistical criteria such as RMSE and R2 were used. The model Balodabazar (1,0,1) (1,1,1), Bemetara (0,0,2) (0,1,1), Raipur (1,0,1) (0,1,1) gave the most accurate results and used to forecast the monthly rainfall for the period (2019 to 2025) for study regions. This long term prediction will help decision makers in efficient scheduling of urban planning, and rainwater harvesting and crop management.
DOI: 10.22271/chemi.2020.v8.i4c.9900
Pages: 180-185 | 739 Views 109 Downloads
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How to cite this article:
Avinash Yadu, Anosh Graham and Anurag Sanadya. Time series ARIMA model to forecast monthly precipitation for Balodabazar, Bemetara and Raipur (Chhattisgarh). International Journal of Chemical Studies. 2020; 8(4): 180-185. DOI: 10.22271/chemi.2020.v8.i4c.9900
