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DSD-SEA 2018 Development of an operational storm surge forecasting system for the Gulf of Thailand - Sisomphon

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Presentation by Mrs. Piyamarn Sisomphon, PhD., (the Hydro Agro Informatics Institute, Thailand) at the Seminar Cutting Edge Hydro Software for South-East Asia, during the Deltares Software Days South-East Asia 2018. Thursday, 6 September 2018, Yogyakarta.

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DSD-SEA 2018 Development of an operational storm surge forecasting system for the Gulf of Thailand - Sisomphon

  1. 1. 1 Hydro and Agro Informatics Institute Ministry of Science and Technology Thailand Development of an operational storm surge forecasting system for the Gulf of Thailand Watin Thanathanphon, Narongrit Luangdilok, Piyamarn Sisomphon
  2. 2. 2 Introduction  The Gulf of Thailand receives a direct impact from the monsoon winds and normally receives the effect of tropical storm which can produce a larger wave propagating into the inner gulf.  Storm surge is the serious hazards to coastal regions, such as flooding, coastal erosion and devastating the properties of people who live in the coastal areas.
  3. 3. 3 Objective  To develop and implement a fully automated storm surge and wave forecasting and early warning system for the Gulf of Thailand  To support decision making for better management of inland & coastal flooding
  4. 4. 4 Gulf of Thailand The disastrous tropical cyclones crossed over Thailand  Semi-enclosed sea located in the western part of South China Sea.  The average depth is 44 m and the maximum depth is 86 m.  Southwest monsoon (May - October) Northeast monsoon October - February)  The previously 6 disastrous tropical cyclones crossed over Thailand • typhoon “VAE” (Oct, 1952) • typhoon “HARRIET” (Oct, 1962) • tropical storm “RUTH” (Nov, 1970) • tropical storm Forrest (Nov, 1992) • typhoon “GAY” (Nov, 1989) • typhoon “LINDA” (Nov, 1997)
  5. 5. 5 Modelling System  Hydrodynamic Model Delft3D Flexible Mesh (Delft3D FM)  Wave Model Simulating WAves Nearshore (SWAN)  Numerical Weather Prediction Model Coupled atmosphere and ocean modeling system (WRF- ROMS)  Early Warning System Delft-FEWS operational forecasting platform The components of storm surge modelling system
  6. 6. 6 Model Extent Hydrodynamic Model Wave Model Grid: Unstructured grid Resolution: 250 m along Thai coast, 1,000 m along other coasts, 8,000 m over deep waters. Boundary conditions: TPXO 7.2 Global Inverse Tide model (14 constituents: M2, S2, N2, K2, K1, O1, P1, Q1, MF, MM, M4, MS4, MN4, SA) Grid: Rectangular grid Resolution: 1,500 m for regional model, 300 m for local model Boundary conditions: WAVEWATCH III (wave height, wave period, wave direction)
  7. 7. 7 Bathymetry Data  Local survey data Department of Mineral Resources  Nautical charts Royal Thai Navy  GEBCO 30 arc-seconds British Oceanographic Data Center The bathymetry data used for hydrodynamic and wave models Bathymetry Surveying Nautical charts GEBCO 30 arc-seconds
  8. 8. 8 System Architecture  Automatic import of real time data feeds provided to the system  Pre-processing of meteo-data (forecasts) before using it in the hydrodynamic and wave models  Execution of the hydrodynamic and wave modelling framework  Visualization of measurement data and forecasts  Exporting of forecasts in various format  Dissemination of forecasts (e.g. internet, intranet) An overview of the early warning system workflow
  9. 9. 9 Model Validation – Hydrodynamic model Ko Lak water level tide only surge only Station R2 (total) R2 (tide) R2 (surge) RMSE, m (total) RMSE, m (tide) RMSE, m (surge) Ao Udom 0.96 0.97 0.40 0.15 0.12 0.10 Ban Lam 0.94 0.96 0.33 0.18 0.15 0.11 Klong Wan 0.95 0.98 0.54 0.11 0.07 0.09 Laem Ngop 0.95 0.97 0.55 0.10 0.08 0.07 Narathiwat 0.84 0.89 0.63 0.12 0.09 0.08 Prasae 0.94 0.96 0.50 0.12 0.09 0.08 Pattani 0.75 0.77 0.65 0.14 0.12 0.07 Sichon 0.90 0.96 0.62 0.12 0.07 0.09 Samutsakorn 0.95 0.97 0.42 0.16 0.13 0.09 Thachalaep 0.85 0.86 0.55 0.17 0.16 0.07 Bang Pakong 0.93 0.95 0.29 0.19 0.16 0.11 Samutsongkhram 0.92 0.94 0.23 0.21 0.18 0.11 Pak Phanang 0.74 0.80 0.43 0.19 0.15 0.13 Rayong 0.96 0.97 0.58 0.11 0.08 0.07 Ko Samui 0.83 0.90 0.26 0.21 0.15 0.15 Ko Lak 0.93 0.97 0.40 0.13 0.08 0.11 Average 0.90 0.93 0.46 0.15 0.12 0.10 Statistics of the comparison of observed data and hydrodynamic model results
  10. 10. 10 Model Validation – Wave model Coordinates Significant wave height Longitude Latitude R RMSE (m) 99.75 9.75 0.72 0.67 99.75 10.50 0.75 0.26 100.50 9.00 0.53 0.29 100.50 9.75 0.65 0.31 100.50 12.75 0.62 0.18 101.25 7.50 0.63 0.53 101.25 8.25 0.55 0.45 101.25 11.25 0.53 0.43 102.00 9.75 0.46 0.41 102.00 12.00 0.45 0.27 103.50 7.50 0.71 0.34 103.50 9.75 0.62 0.36 Average 0.60 0.37 Lat: 10.5°N Long: 99.75°E Statistics of the comparison of ERA-interim data and wave model results wave height wave period wave direction
  11. 11. 11 Visualization WRF-ROMS meteorological forecast Observed and simulated time series Water level map from hydrodynamic model Significant wave height map from wave model
  12. 12. 12 Conclusions  The overall Delft3D FM hydrodynamic model and SWAN wave model performance is sufficient to forecast the state of the Gulf of Thailand  Delft-FEWS system also provides flexibility to adjust data format, connect the models and present the real time data and model output  This system is among the first fully automated storm surge forecasting system that combine all relevant phenomena. After few years in operation it is proved its performance to provide sufficient information to support decision making for coastal management and early warning procedures to protect and reduce the losses in the Gulf of Thailand.  Capacity building & Research foundation
  13. 13. 13 Acknowledgements  Thank you to Royal Thai Navy, Marine Department and Department of Mineral Resources for providing data during the development of this project  Special thanks to Deltares, The Netherlands for being a good partner, sharing knowledge and hands-on experiences
  14. 14. 14 www.haii.or.th ● www.thaiwater.net Hydro and Agro Informatics Institute Ministry of Science and

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