Year: 2025
Type: article
Abstract: This study focuses on forecasting monthly mean rainfall in District Dir (Lower) using various ARMA models to identify the most suitable approach for accurate rainfall prediction. Rainfall forecasting is a critical and intriguing area of study, and the Box-Jenkins methodology, which employs ARMA models, is highly effective for analyzing and forecasting time series with diverse patterns of variation. The ARMA modeling process involves defining, estimating, diagnosing, and forecasting stages, making it well-suited for this application. Based on the analysis, the ARMA (4,4) model emerged as the best fit for the dataset, evaluated using SIGMASQ, AIC, and SC criteria, which yielded the smallest values and confirmed through the Ljung-Box Q-test. Using the ARMA (4,4) model, the study successfully forecasted monthly mean rainfall in District Dir (lower) from June 2022 to May 2028.
Authors: Aimal Khan, Habib Ullah Khan, Muhammad Ismail
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: diamond
OpenAlex ID: W4408447901