Development of an Integrated Observation Data and Global Numerical Weather Prediction System-Based Rainfall-Runoff Forecasting Model as PJT-I’s Effort in Water Resources Disaster Mitigation

Abstract

Abstract Given the vital role of water resources and their vulnerability to climate-driven disasters, especially floods and droughts, the need for effective disaster mitigation strategies in water resource management is evident. PJT-I, a key player in the industry, grapples with this challenge. To address it, PJT-I has embraced the Smart Water Management System (SWMS) platform and innovative enhancements in rainfall-runoff modeling, showcasing their dedication to bolstering real-time monitoring and predictive capabilities. These advances hold the promise of strengthening operational water resource management, spanning allocation and infrastructure operations, and are particularly relevant in the face of escalating extreme weather events. The study’s focus on the Sengguruh reservoir catchment area serves as an illustration, highlighting the creation of two hydrometric-based models: the AWLR Gadang model and the Sengguruh reservoir model. Their effectiveness is validated through data calibration and integration of GFS forecast data, enabling 120-hour forecasting. Rigorous assessment involving correlation, efficiency, determination, and error metrics provides insights into the models’ predictive capacities and limitations amid the dynamic interplay of rainfall-runoff dynamics.