Year: 2022 | Month: December | Volume 67 | Issue 5
Assessment of Future Pattern of Rainfall in Different Zones of Kerala Using Incorporation of SARIMA, ANN and Hybrid SARIMA-ANN Models
Gokul Krishnan
K.B.
Vishal Mehta
Rama Shankar Yadav
DOI:10.46852/0424-2513.5.2022.17
Abstract:
Agriculture production all over the world is directly influenced by rainfall which is an important weather parameter. The changes in rainfall can cause the failure of crops and even lead to starvation and ruin the economy of a country. The economy of a country becomes inferior due to catastrophic circumstances like floods, drought, and landslides. Thus the prediction of future values with the highest accuracy is very crucial to regulate and avoiding the undesirable influences of instabilities in rainfall. Under current research work, SARIMA, ANN, and hybrid SARIMA-ANN models are applied to identify the future pattern and for availing essential proposals for scheduling agriculture procedures such that variations in rainfall may not affect the economy. The data of monthly rainfall was collected from RARS, Pilicode for the northern zone, RARS, Pattambi for the central zone, and RARS, Vellayani for the southern zone. The results revealed that ANN model predicted future values of rainfall with the highest precision for the northern and central zone, whereas for the southern zone, SARIMA (1,0,1) (2,0,0)12 gave anticipated values with more accuracy. The comparison of projected rainfall among different zones indicated that the northern part might receive the highest amount of rainfall, the central zone indicated moderate rainfall, and the southern part of Kerala with the least amount of rainfall. The study also recommended the farmers take necessary safeguards to regulate the adverse influences of fluctuations in rainfall such that it might not affect agricultural production and the economy of the country.
Highlights
- Fluctuations in rainfall affect agricultural production and the economy of the country
- SARIMA, ANN, and hybrid SARIMA-ANN models are applied to identify the future pattern of rainfall.
- ANN model gave an accurate projection of rainfall in the northern and central zone, whereas SARIMA (1,0,1) (2,0,0)12 model gave anticipated values with higher precision in the southern zone.
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