ARIMA模型的概率分析与降雨预报

IF 0.7 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

MAUSAM Pub Date : 2023-10-01 DOI:10.54302/mausam.v74i4.805

CHANDRAN S., SELVAN P., NAMITHA M. R., PRADEEP MISHRA, KUMAR V.

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引用次数: 0

摘要

本文收集了泰米尔纳德邦Vaigai河10个子流域1976 - 2009年34年的降水资料，并利用各种概率分布函数进行了统计分析。使用两次拟合优度检验找到了研究区域年、月和季节降雨量的最佳拟合概率分布。采用Box-Jenkins自回归综合移动平均(ARIMA)方法进行模型识别、诊断检查和预测研究区年降雨量。选取了各子流域的最佳ARIMA模型，对2010、2015、2020和2025年的年平均降水量进行了预测。预测结果与2020年实测数据吻合较好，表明了模型的适用性。

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Probability analysis and rainfall forecasting using ARIMA model

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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来源期刊

MAUSAM 地学-气象与大气科学

CiteScore

1.20

自引率

0.00%

发文量

1298

审稿时长

6-12 weeks

期刊介绍： MAUSAM (Formerly Indian Journal of Meteorology, Hydrology & Geophysics), established in January 1950, is the quarterly research journal brought out by the India Meteorological Department (IMD). MAUSAM is a medium for publication of original scientific research work. MAUSAM is a premier scientific research journal published in this part of the world in the fields of Meteorology, Hydrology & Geophysics. The four issues appear in January, April, July & October.