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 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 a...

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Bibliographic Details
Published inIOP conference series. Earth and environmental science Vol. 1343; no. 1; pp. 12013 - 12024
Main Authors Muttaqin, R M A, Nugrahany, A
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.05.2024
Subjects
Catchment areas
Disaster management
Disasters
Drought
Emergency preparedness
Extreme weather
Global weather
Hydrologic models
Mitigation
Numerical weather forecasting
Rain
Rainfall
Rainfall-runoff relationships
Reservoirs
Resource management
Runoff
Runoff forecasting
Water management
Water resources
Water resources management
Weather
Weather forecasting
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Summary: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.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/1343/1/012013