Prediction of Daily Maximum Streamflow Based on Stochastic Approaches

Authors

Publication Date

2004

Keywords

Daily maximum streamflow, stochastic model, ARIMA, Thomas-Fiering

Abstract

This study analyzed daily maximum streamflow data of each month from three gauge stations on Cekerek Stream for simulation using stochastic approaches. Initially non-parametric test (Mann-Kendall) was used to identify the trend during study period. The two approaches of stochastic modeling, ARIMA and Thomas-Fiering models, were used to simulate monthly maximum data. The error estimates (RMSE and MAE) of predictions from both approaches were compared to identify the most suitable approach for reliable simulation. The two error estimates calculated for two approaches indicate that ARIMA model appear to be slightly better than Thomas-Fiering. However, both approaches were identified as appropriate method for simulating daily maximum streamflow data of each month from three gauge stations on Cekerek Stream.

BYU ScholarsArchive Citation

(2004) "Prediction of Daily Maximum Streamflow Based on Stochastic Approaches," Journal of Spatial Hydrology: Vol. 4: No. 2, Article 7.
Available at: https://scholarsarchive.byu.edu/josh/vol4/iss2/7