Rainfall time series forecasting using ARIMA model

Swagatam Bora, Abhilash Hazarika
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Abstract

The Northeastern region of India, especially Assam and Meghalaya receive very heavy rainfall in the months of monsoon, which results in repeated loss of property, life and resources every year. This study aims to predict the rainfall distribution pattern over Assam and Meghalaya for the next five years. From the data available at Indian Meteorological Department’s website of the daily rainfall distribution pattern of the two regions, a time series has been created. This time series has been used to forecast the rainfall distribution pattern using an ‘Auto Regressive Integrated Moving Average’ (ARIMA) model. ARIMA (0,0,1)(2,1,2) was selected by comparing AICc values to forecast the data. This forecasting algorithm uses the past values of the series in predicting the future trend. The R programming language has been used for the entire study for precise statistical analysis. Thus, an accurate forecast of the rainfall pattern for the future 5 years can be extremely beneficial for the people of the region in planning their resources, crop patterns and managing disasters.
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基于ARIMA模型的降雨时间序列预测
印度东北部地区,特别是阿萨姆邦和梅加拉亚邦在季风月份降雨量非常大,每年都造成财产、生命和资源的反复损失。这项研究旨在预测未来五年阿萨姆邦和梅加拉亚邦的降雨分布模式。根据印度气象部门网站上提供的这两个地区的日降雨量分布模式数据,创建了一个时间序列。该时间序列已用于使用“自动回归综合移动平均”(ARIMA)模型预测降雨分布模式。通过比较AICc值,选择ARIMA(0,0,1)(2,1,2)进行数据预测。这种预测算法使用序列的过去值来预测未来的趋势。整个研究使用R编程语言进行精确的统计分析。因此,对未来5年降雨模式的准确预测对该地区人民规划资源、作物模式和管理灾害极为有益。
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