Stochastic Time Series Analysis, Modeling, and Forecasting of Weekly Rainfall Using Sarima Model

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dc.contributor.authorDamor, PAen_US
dc.contributor.authorRam, Ben_US
dc.contributor.authorKunapara, AN.en_US
dc.date.accessioned2024-09-24T08:02:30Z
dc.date.available2024-09-24T08:02:30Z
dc.date.issued2023-12
dc.description.abstractRainfall holds critical significance for water resource applications, particularly in rainfed agricultural systems. This study employs the Autoregressive Integrated Moving Average (ARIMA) technique, a data mining approach commonly used for time series analysis and future forecasting. Given the increasing importance of climate change forecasting in averting unexpected natural hazards such as floods, frost, forest fires, and droughts, accurate weather data forecasting becomes imperative. The objective of this study was to develop a Seasonal Auto-Regressive Integrative Moving Average (SARIMA) model for forecasting weekly rainfall in Junagadh Station, Gujarat. Utilizing 53 years of historical data (1963 to 2016), the SARIMA model predicts weekly rainfall for the subsequent five years (2018 to 2022). Through comprehensive evaluation using ACF and PACF plots, AIC, SBC, MAPE, and MAE values, the study identifies SARIMA (0,0,4)(0,1,1)52 as the optimal model, offering the most accurate prediction. The robust results affirm that the SARIMA model provides reliable and satisfactory weekly rainfall predictions. This research contributes valuable insights into the precision and efficacy of SARIMA models for rainfall forecasting, aiding in strategic water resource management in the Junagadh region.en_US
dc.identifier.affiliationsJunagadh Agricultural University, Junagadh-362001, Indiaen_US
dc.identifier.affiliationsAnand Agricultural University, Anand, Gujarat-388110, Indiaen_US
dc.identifier.affiliationsAnand Agricultural University, Anand, Gujarat-388110, Indiaen_US
dc.identifier.citationDamor PA, Ram B, Kunapara AN.. Stochastic Time Series Analysis, Modeling, and Forecasting of Weekly Rainfall Using Sarima Model . International Journal of Environment and Climate Change. 2023 Dec; 13(6): 773-782en_US
dc.identifier.issn2581-8627
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/230901
dc.languageenen_US
dc.publisherMs. M. B. Mondalen_US
dc.relation.issuenumber6en_US
dc.relation.volume13en_US
dc.source.urihttps://doi.org/10.9734/ijecc/2023/v13i123740en_US
dc.subjectSARIMAen_US
dc.subjectAICen_US
dc.subjectBICen_US
dc.subjectMAPEen_US
dc.subjectSICen_US
dc.titleStochastic Time Series Analysis, Modeling, and Forecasting of Weekly Rainfall Using Sarima Modelen_US
dc.typeJournal Articleen_US
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