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FORECASTING WEEKLY RAINFALL USING SARIMA MODEL FOR RAINFED AGRICULTURE
ISSN: 2277 - 7601
Publisher: author
FORECASTING WEEKLY RAINFALL USING SARIMA MODEL FOR RAINFED AGRICULTURE
Indexed in
Agriculture and Food Sciences
ARTICLE-FACTOR
1.3
Article Basics Score: 3
Article Transparency Score: 3
Article Operation Score: 2
Article Articles Score: 3
Article Accessibility Score: 3
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-0202
Publisher: Kiran Abasaheb More
International Journal Address (IAA):
IAA.ZONE/2277388267601
eISSN
:
2277 - 7601
VALID
ISSN Validator
Abstract
Background: Rainfed crops occupy partial portion of net sown area and production of agriculture in the tropics. In view of the importance ofrainfed crop, there is a need to increase the productivity of rainfed areas. Crop production under rainfed condition requires climatemeasures such as rainfall prediction. Maximum work of rainfall forecasting mainly depends on monthly rainfall. But distribution of rainfallfrom week to week is very important for crop planning under rainfed condition.Method: In present study, weekly rainfall data was collected for 2000 to 2019. The rainfall during 2000 to 2018 was used to train the modeland remaining part of data was used for validation process. The model selection was made using AIC, BIC, MAE and RMSE, andSARIMA(1,0,2)(1,0,1)52 was identified to be the appropriate one.Results: The validation process confirmed that SARIMA(1,0,2)(1,0,1)52 was the best model for forecasting weekly rainfall. It is benef...
