Application of Time Series Models for Streamflow Forecasting

Abstract

Precise prediction of the streamflow has a significantly importance in water resources management. In this study, two time series models, Autoregressive Moving Average model (ARMA) Autoregressive Integrated Moving Average model (ARIMA) are used for predicting streamflow. In this research, monthly streamflow from 1974 to 2010 were used. The statistics related to first 28 years were used to train the models and last 7 years were used to forecast. The prediction accuracy of both time series models is examined by comparing root mean square error (RMSE), the mean absolute percentage error (MAPE) and the Nash efficiency (NE). According to the results, ARIMA model performs better than the ARMA time series models.

Keywords: Streamflow forecasting, Time series models, ARIMA, ARMA