Research Details
Predictive Ability of Delft3D-Based Storm Surge Forecasts Using Historical and Forecasted Typhoon Tracks
Christine B. Mata, Clein Winslee Duquez, Olivia C. Cabrera, Tristan Janryll A. Mata, Nathaniel R. Alibuyog
Category
Study
Status
Completed
Duration
Jan 2, 2025 -
Jul 1, 2025
Parent Project
→ Assessment, Monitoring, and Prediction of Coastal Flooding of Selected Municipalities in Region IRelated Studies
- • Storm Surge Modeling with DELFT-3D: The influence of Tide and Wind During Typhoon Ineng in the Laoag River Coastal Zone
- • Integrated Assessment of Tidal and Flood Control Scenarios on Inundation Using HECRAS
- • Integrated Assessment of Tidal and Flood Control Scenarios on Inundation Using HEC-HMS-RAS
- • Development of a Web-Based Platform for Integrated Coastal Monitoring and Flood Preparedness
- • Evaluating the Suitability of GSMaP Satellite-Based Precipitation Data for Runoff Estimation in the Abra River Basin
- • Integrated assessment of tidal and flood control scenarios on inundation using HEC-RAS and HEC-HMS
Brief Description
The DELFT3D Flexible Mesh (D3D FM) model with an unstructured grid extending up to 10 m elevation above mean sea level inland was developed to simulate storm surge in coastal areas of Northwestern Luzon (NWL), Philippines. The objective of this research is to examine the forecasting ability of the model at different lead time during extreme events by using historical versus forecasted data. Three events were selected: Super Typhoon Mangkhut (2018), Tropical Storm Pankhar (2017), and Typhoon Hato (2017). Two sea level stations were used to validate the model: Currimao (CM) and San Fernando (SF) stations. Model’s performance revealed an average NSE = 0.834, RMSE = 7.8 cm, and MAE = 6.2 cm indicating very good agreement between observed and simulated water levels at both CM and SF stations. Using forecasted tracks of the same events by Japan Meteorological Agency (JMA), the average RMSE at 72-, 48-, and 24-hr lead times are 5.6 cm, 7.5 cm, and 10.6 cm, respectively while average MAE are 4.3 cm, 6.9 cm and 8.9 cm, respectively. Forecasting ability of the model performs very high and indicates suitable for operational surge forecasting although becomes less reliable closer to landfall, especially for intense typhoons with rapid structural changes. Model performance is generally better for moderate typhoons with simpler wind and pressure fields. Overall, the model can be readily used to support disaster preparedness and early warning systems in coastal communities.
Expected Output
1. Calibrated and validated DELFT3D-based storm surge model in Northwestern Luzon
2. Validated forecasting ability of storm surge model at different lead time
2. Validated forecasting ability of storm surge model at different lead time