TITLE:
Stochastic Modelling of Great Letaba River Flow Process
AUTHORS:
Gislar E. Kifanyi, Julius M. Ndambuki, Samuel N. Odai, Charles Gyamfi
KEYWORDS:
Modelling, Great Letaba River, South Africa, Stochastic Flow Process
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.7 No.6,
June
24,
2019
ABSTRACT: A stochastic approach is presented in view that a
time series modelling is achieved through an Autoregressive Moving Average
(ARMA) model. The applicability of the ARMA model is then further presented
using the Great Letaba River as a case study. River flow discharge for 25 years
(1989-2014) for the Great Letaba River was obtained from the Department of
Water and Sanitation, South Africa and analysed by Autoregressive (AR),
Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving
Average (ARIMA) models. Monte Carlo simulation approach was used to generate
forecasts of the ARIMA error model for the next 25 years. Initial model
identification was done using the Autocorrelation function (ACF) and Partial
Autocorrelation function (PACF). The model analysis and evaluations provided
proper predictions of the river system. The models revealed some degree of
correlation and seasonality behaviour with decreasing river flow. Hence, in
conclusion, the Great Letaba River flow has shown a decreasing trend and
therefore, should be effectively used for sustainable future development.