Discharge Forecasting in Monsoonal Gung Watershed: A Comparative Analysis of F. J. Mock, Markov, and ARIMA Models

Environmental Engineering, Faculty of Civil and Environmental Engineering, 40132 Institut Teknologi Bandung, Indonesia

^* Corresponding author: ahyaaulia99@gmail.com

Abstract

Water resources are crucial for human needs along with their increasing demand due to rapid population growth. Nevertheless, water availability is readily limited, and disaster might also occur due to unplanned water infrastructure management. Gung watershed, as a primary water resource, is vulnerable in water availability and flood, primarily influenced by land cover degradation. Moreover, no prior research has been conducted to obtain accurate discharge forecasting in this area. In reinforcing disaster mitigation and infrastructure planning, our recent work utilizes a 10-year dataset of hydrometeorological data (2013-2022) in the monsoonal Gung watershed. A comparative study of F. J. Mock, Markov, and ARIMA models shows that all three models are excellent in forecasting discharge with more than 80% correlation to its observed value. Markov model performs best (r=0.91; NSE=0.82), followed by ARIMA and F. J. Mock models. Aside from discharge forecasting, this study offers a reference for strategic planning in water resources infrastructure and disaster mitigation efforts.