Application of ARIMA Model for River Discharges Analysis

Authors

  • Bhola NS Ghimire Department of Civil Engineering, Pulchowk Campus, Institute of Engineering, T. U., Lalitpur

DOI:

https://doi.org/10.3126/jnphyssoc.v4i1.17333

Keywords:

Time Series Analysis, ARIMA Model, Hydrological Process, Autocorrelation, Seasonal Variation

Abstract

Time series data often arise when monitoring hydrological processes. Most of the hydrological data are time related and directly or indirectly their analysis related with time component. Time series analysis accounts for the fact that data points taken over time may have an internal structure (such as autocorrelation, trend or seasonal variation) that should be accounted for. Many methods and approaches for formulating time series forecasting models are available in literature. This study will give a brief overview of auto-regressive integrated moving average (ARIMA) process and its application to forecast the river discharges for a river. The developed ARIMA model is tested successfully for two hydrological stations for a river in US.

Journal of Nepal Physical Society
Volume 4, Issue 1, February 2017, Page: 27-32

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Published

2017-05-22

How to Cite

Ghimire, B. N. (2017). Application of ARIMA Model for River Discharges Analysis. Journal of Nepal Physical Society, 4(1), 27–32. https://doi.org/10.3126/jnphyssoc.v4i1.17333

Issue

Vol. 4 No. 1 (2017)

Section

Articles

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