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.

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
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
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
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
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
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)

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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
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
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
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
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
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
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

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www.haii.or.th ●
www.thaiwater.net
Hydro and Agro
Informatics Institute
Ministry of Science and