Back to Search Start Over

A hybrid SARIMA-Prophet model for predicting historical streamflow time-series of the Sobat River in South Sudan.

Authors :
Kenyi, Manzu Gerald Simon
Yamamoto, Kayoko
Source :
Discover Applied Sciences; Sep2024, Vol. 6 Issue 9, p1-20, 20p
Publication Year :
2024

Abstract

Accurate river streamflow forecasting is pivotal for effective water resource planning, infrastructure design, utilization, optimization, and flood planning and warning. Streamflow prediction remains a difficult task due to several factors such as climate change, topography, and lack of observed data in some cases. This paper investigates and evaluates the individual performances of the seasonal auto-regressive integrated moving average (SARIMA) and Prophet models in forecasting the streamflow of the Sobat River and proposes a hybrid SARIMA-Prophet model to leverage the strengths of both approaches. Using the augmented Dickey-Fuller (ADF) and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests, the flow of the Sobat River was found to be stationary. The performance of the models was then assessed based on their residual errors and predictive accuracy using the mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination (R<superscript>2</superscript>). Residual analysis and prediction capabilities revealed that Prophet slightly edged SARIMA in terms of prediction efficacy; however, both models struggled to effectively capture extreme values, resulting in significant overestimations and slight underestimations. The hybrid SARIMA-Prophet model significantly reduced residual variability, achieving a lower MAE of 4.047 m<superscript>3</superscript>/s, RMSE of 6.17 m<superscript>3</superscript>/s, and a higher R<superscript>2</superscript> of 0.92 than did the SARIMA (MAE: 5.39 m<superscript>3</superscript>/s, RMSE: 8.70 m<superscript>3</superscript>/s, R<superscript>2</superscript>: 0.85) and Prophet (MAE: 5.35 m<superscript>3</superscript>/s, RMSE: 8.32 m<superscript>3</superscript>/s, and R<superscript>2</superscript>: 0.86) models. This indicates that the hybrid model handles both long-term patterns and short-term fluctuations more effectively than the individual models. The findings of the present study highlight the potential of hybrid SARIMA-Prophet models for streamflow forecasting in terms of accuracy and reliability, thus contributing to more effective water resource management and planning, particularly in the Sobat River.Article Highlights: The Sobat River’s flow patterns remained statistically consistent, affirming stationarity. Both the SARIMA and Prophet models showed good performance but with limitations in handling extreme values The hybrid SARIMA-Prophet model effectively minimized residual variability and extreme prediction errors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
30049261
Volume :
6
Issue :
9
Database :
Complementary Index
Journal :
Discover Applied Sciences
Publication Type :
Academic Journal
Accession number :
179180726
Full Text :
https://doi.org/10.1007/s42452-024-06083-x