Open AccessPredictive Modelling of Rainfall Data for Aurangabad Region by using ARIMA Method
Author(s) -
Rupali D. Patil,
Omprakash S. Jadhav
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.10.27924
Subject(s) - autoregressive integrated moving average , autoregressive model , time series , water resources , set (abstract data type) , data set , computer science , series (stratigraphy) , meteorology , moving average , environmental science , statistics , econometrics , mathematics , geography , geology , ecology , paleontology , biology , programming language
In day to day life prediction of weather parameters play important role for planning in environment management fields. Predictive modelling of rainfall is very necessary criterion for water management resources. In time series analysis most effective autoregressive integrated moving average model (ARIMA) are used. In this paper, we set up various ARIMA models for prediction of rainfall from which ARIMA (1, 0, 0) (2, 0, 0)12 are best fitted models for future forecasting purpose. Forecasting the next three years has been described to decide water demand management priorities.