Probability analysis and rainfall forecasting using ARIMA model

Authors

  • CHANDRAN S. Thiagarajar College of Engineering
  • SELVAN P. Thiagarajar College of Engineering, Madurai – 625 015, India
  • NAMITHA M. R. KCAET, Tavanur-Malapuram (Kerala) – 679 573, India
  • PRADEEP MISHRA College of Agriculture, Rewa, J. N. K. V. V. – 486 001 (M.P.), India
  • KUMAR V. ACRI-TNAU-Madurai Campus – 625 104, Tamil Nadu, India

DOI:

https://doi.org/10.54302/mausam.v74i4.805

Keywords:

ARIMA; Rainfall, Probability analysis; Forecasting.

Abstract

A 34-year rainfall data from 1976 to 2009 of ten sub-basins of the Vaigai River in Tamil Nadu were collected and analysed statistically using various probability distribution functions. The best-fit probability distributions for the annual, monthly and seasonal rainfall for the study area were found using two goodness-of-fit tests. The Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting the study area's annual rainfall. The best ARIMA models were selected for each sub-basin and the average annual precipitation for 2010, 2015, 2020 and 2025 has been forecasted. The forecasted result compared well with observed dataup to 2020, which indicates the appropriateness of the model.

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Published

01-10-2023

How to Cite

[1]
C. S., S. P., N. M. R., P. MISHRA, and K. V., “Probability analysis and rainfall forecasting using ARIMA model”, MAUSAM, vol. 74, no. 4, pp. 1081–1092, Oct. 2023.

Issue

Vol. 74 No. 4 (2023): MAUSAM

Section

Research Papers

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