DSD-SEA 2019 Recent coupled field observation and modeling works in Thai Seas-Pokavanich
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This document summarizes recent coupled field observation and modeling work in Thai seas conducted by Dr. Tanuspong Pokavanich. It describes the setup and validation of a 3D hydrodynamic model of the Gulf of Thailand, including modeling of currents, water properties, and larval transport. Field observations of water level, temperature, salinity and currents were used to validate model results. The modeling aims to improve understanding of hydrodynamic processes and inform management of issues like water quality and fisheries in the Gulf of Thailand.
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DSD-SEA 2019 Recent coupled field observation and modeling works in Thai Seas-Pokavanich
- 1. Recent coupled field observation and modeling works in Thai Seas Dr. Tanuspong Pokavanich Estuarine and Coastal Dynamics Modeling Laboratory (ECDM) Department of Marine Science, Faculty of Fisheries, Kasetsart University Email: ffistop@ku.ac.th 27 November 2019
- 2. ดร. ธนัสพงษ์ โภควนิช (วศ.ด.) Dr. Tanuspong Pokavanich (D.Eng.) อาจารย์ - ภาควิชาวิทยาศาสตร์ทางทะเล คณะประมง มหาวิทยาลัยเกษตรศาสตร์ Lecturer - Department of Marine Science, Faculty of Fisheries, Kasetsart University Former career 2010-2016 Associate Research Scientist (KISR-Kuwait) 2009-2010 Post- doc research (Tokyo Institute of Technology-Japan) 2003 -2004 Coastal Engineer (SEATEC-Thailand) Education o Bachelor of Engineering 1998 – Civil Engineering, Sirindhon International Institute of Technology-Thammasat University o Master of Engineering 2003 -Water Engineering and Management, Asian Institute of Technology -Thailand o Doctoral of Engineering 2009 – Environmental informatics, Tokyo Institute of Technology - Japan Expertise Coastal oceanography, Field instrument and measurement, Hydrodynamics and water quality modeling
- 3. No resting water and continuous changing properties!!
- 4. Complex current → Complex water movement
- 6. How to understand it/them?
- 7. Problem is that we can not measure everywhere and everytime !!! We measure!!!
- 8. Modeling is much better and cheaper and safer and …..etc. Problem is that how to know that modeling results are correct?Tidal current pattern at the Gulf of Thailand
- 9. The answer greatly depends on problems (processes) that you are looking at !! Water level validation Water Temperature validation Salinity validation Ok sure, we compare the measurements and modeling results. Acceptable? Measured Simulated
- 10. Pokavanich T. (unpublished) Jan2017 Simulated near-surface monthly mean currents Apr2017 Jul2017
- 11. Jan-Feb2017 Apr-May2017 Jul-Aug2017 Simulated trajectory of floating objects Pokavanich T. (unpublished) How much can we believe in the results?
- 12. Yes!! Now we do Coupled Field survey & Numerical Modeling !! So we have to do both in parallel !!
- 13. Gulf of Thailand
- 14. Tanuspong Pokavanich, Kittipong Pattananurat Department of Marine Science Faculty of Fisheries, Kasetsart University Progress on Developing 3D-Hydrodynamic Model of the Gulf of Thailand 23 September 2019 Tracer trajectory Water circulation pattern Special Seminar on 23 September 2019, Department of Marine Science, Faculty of Fisheries, Kasetsart University, Thailand
- 15. The Gulf of Thailand (GoT) is a big shallow estuary extended from the South China Sea (part of Pacific Ocean). Water depth (m)
- 16. *Bathymetric data 10 time exaggerated compared to land elevations.
- 17. Gulf of Thailand Inner-Gulf of Thailand • Shallow (average 45 m, maximum 80 m) • Diurnal and mixed tide range 2.5-3.0 m • Dominate by SW and NE monsoonal wind • Recipient of wastewater discharged from big cities and 4 Thailand’s major rivers. • Source of natural gas and oil
- 18. Now, the Inner-Gulf of Thailand having Serious problems on Fisheries, Water Quality especially during the SW monsoon (Flooding season). Depth (m)
- 20. Existing Problems at the GoT Marine debris Landed marine debris Pore sediment quality Eutrophication and plankton bloom More frequent massive fish-kill Microplastics Oil spilled Eastern Economic Corridor (EEC)
- 21. 3+1 major factors that move water in the GoT 1. Wind driven currents 2. Tidal driven currents 3. Thermohaline (or density driven) currents + 4. Interactions between the GoT and SCS
- 22. What is a level of interactions between the GoT and South- China Sea ??? Another big question to be investigated… To study the current and circulation patterns and their seasonal changes using 3D hydrodynamic model which calibrate and validate with field observed data Objectives
- 23. Numerical model setup Setup lists 3D Gulf of Thailand model Simulation period 1/1/2018-31/5/2019 Validation period 26/1/2018-24/5/2019, 22/1/2019-31/5/2019, 16/3/2019-31/5/2019 Type of grid Curvilinear grid in Spherical coordinate Vertical layer 10 layers Initial conditions 0 m water level and 0 velocity Bottom roughness chezy 70 m1/2/s Time step 3 minutes Discharge data Monthly average discharge data from Hydro and Agro Informatics Institute Off-shore boundaries condition TPXO 9.0: Global Inverse Tide Model –Tidal components, Salinity and Temperature Monthly average data from JAMSTEC *** Salinity -5 ppt 10 m Wind direction and velocity, air pressure, 2 m air temperature, total cloud cover, total precipitation, relative humidity Hourly data form ERA5 reanalysis dataset
- 24. x coordinate (m) → ycoordinate(m)→ 100 100.2 100.4 100.6 100.8 101 101.2 12.4 12.6 12.8 13 13.2 13.4 13.6 distance along cross-section n=78 (km) → elevation(m)→ hydrodynamic grid 01-Sep-2018 00:00:00 0 100 200 300 400 500 600 700 800 900 1000 -80 -70 -60 -50 -40 -30 -20 -10 0 10 distance along cross-section m=40 (km) → elevation(m)→ hydrodynamic grid 01-Sep-2018 00:00:00 0 10 20 30 40 50 60 70 80 90 -25 -20 -15 -10 -5 0 5 distance along cross-section n=81 (km) → elevation(m)→ hydrodynamic grid 01-Sep-2018 00:00:00 0 20 40 60 80 100 120 140 -25 -20 -15 -10 -5 0 5 distance along cross-section n=78 (km) → elevation(m)→ hydrodynamic grid 01-Sep-2018 00:00:00 0 100 200 300 400 500 600 700 800 900 1000 -80 -70 -60 -50 -40 -30 -20 -10 0 10
- 25. Examples of simulated weather data from the ECMWF* *ECMWF = European Centre for Medium-Range Weather Forecasts
- 26. KU Long-term marine monitoring station (since Feb2018-now) Location of the platform
- 27. KU Long-term continuous measurement (since Feb2018-now)Water level Water temperature Salinity
- 31. Model validation – Near-surface water temperature observationsimulation Celsius **Field observation from Dr. Shettapong Meksumpan’s project, KU Apr 2017 Jul 2017 Dec 2017 Apr 2018
- 32. Model validation – Near-surface salinity observationsimulation ppt Apr 2017 Jul 2017 Dec 2017 Near-surface Apr 2018 **Field observation from Dr. Shettapong Meksumpan’s project, KU
- 33. 33 0.3 m/s Ebb tide 0.3 m/s Low tide Tidal Currents
- 34. 0.3 m/s0.3 m/s 34 Tidal CurrentsFlood tide High tide
- 35. Jan 0.1 m/s 0.1 m/sApr Wind & Thermohaline Currents (Monthly residual currents)
- 36. 0.1 m/s Sep e 0.1 m/s0.1 m/s Dec Wind & Thermohaline Currents (Monthly residual currents)
- 37. Simulated water temperature (Near-surface) Jan-Dec 2017 -Preliminary results- Dr. Tanuspong Pokavanich Dept. of Marine Science Faculty of Fisheries, Kasetsart University 18/12/2018
- 38. Simulated salinity (Near-surface) Jan-Dec 2017 -Preliminary results- Dr. Tanuspong Pokavanich Dept. of Marine Science Faculty of Fisheries, Kasetsart University 18/12/2018
- 39. Simulated surface larval transport -Unpublished materials- Dr. Tanuspong Pokavanich Dept. of Marine Science Faculty of Fisheries, Kasetsart University 18/12/2018 January August
- 40. January 2018 Dr. Tanuspong Pokavanich Dept. of Marine Science Faculty of Fisheries, Kasetsart University 18/12/2018 Simulated surface larval transport -Preliminary results-April 2018
- 41. August 2018 Dr. Tanuspong Pokavanich Dept. of Marine Science Faculty of Fisheries, Kasetsart University 18/12/2018 Simulated surface larval transport -unpublished materials-October 2017
- 42. Development of Satellite Drifter The drifter aims to provide 1 hour interval self- position for minimum 1 month. Prototype design
- 43. Location of marine station
- 44. Marine Monitoring Station at Sriracha Area Maximet JFE-CTWJFE-Rinko WJFE-CLW AWAC Datalogger
- 45. Ao Kung Krabean
- 46. Seasonal Water Residence Time Investigation at Ao Kung Krabaen Lagoon, Chantaburi Province Tanuspong Pokavanicha* Anukul Buranaprathepratb a Department of Marine Science, Faculty of Fisheries, Kasetsart University 2 Department of Aquatic Science, Faculty of Science, Burapha University *Email: ffistop@ku.ac.th 27/11/2018
- 47. Characteristics of the Ao Kung Krabaen Lagoon 0 1 2 km N •6.7 km2 lagoon •Low-inflow estuary •Avg. depth of 0.8 m •Tidal range 1.6 m (spring tide) and 0.6 m (neap tide) •Dominated by NE and SW monsoonal wind •Seagrass, mangrove, resorts, local fishing villages and intensive shrimp farming complex
- 48. Intensive shrimp farming at the AKBL • AKBL* has started in 1986 with black tiger shrimp farming. • Disease outbreaks in 1990 (YHV), 1994-1995 (SEMBV) • Opened-system to closed-system • Seawater irrigation (max. 10 m3/s) • Deteriorated water quality *AKBL = Ao Kung Krabaen Lagoon Therefore, insight knowledge about oceanography (such as currents, circulation and water residence time) is needed and essential for better water management.
- 49. Objective To study in circulation, water residence time and seasonal variation at Ao Kung Krabaen Lagoon Scope of the Research •Using numerical model and hydrodynamic model to simulate current, circulation controlled by tidal wind and water density •Simulate water residence time by analyze residence time of conservative tracer
- 50. 50 Intensive Field Observations at the AKKL
- 51. Bathymetry survey at the AKKL Depth (m) Lawrance HDS9 (USA) echo- sounder *Echo-sounder provided by SEAFDEC Survey track
- 52. Measured Water temperature (oC) SW Monsoon SW Monsoon NE Monsoon NE Monsoon
- 53. Measured Salinity (ppt) SW Monsoon SW Monsoon NE Monsoon NE Monsoon
- 54. Plastic PVC pipe Rubble ban Plastic mesh Known length nylon rope WLL Data logger HOBO-WLL (Onset, USA) pressured logger was deployed btw 24 April to 13 May 2017 Water level (tide) variation data collection inside the AKKL WLL Data logger Rubber ban Plastic mesh -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 24-Apr-17 25-Apr-17 26-Apr-17 27-Apr-17 28-Apr-17 29-Apr-17 30-Apr-17 01-May-17 02-May-17 03-May-17 04-May-17 05-May-17 06-May-17 07-May-17 08-May-17 09-May-17 10-May-17 11-May-17 12-May-17 13-May-17 14-May-17 m Date Measured water level
- 55. 20 cm/s 20 cm/s 20 cm/s 20 cm/s Flood tide High tide Ebb tide Flood tide Current Measurement using ADCP
- 56. Numerical model setup Offshore boundaries Item GoT (2D) Chanthaburi (3D) Sim. Period 1 Jan to 31 Dec 2015 Mesh Curvilinear grid in spherical coordinate No. vertical layer 1 6 Time step 5 minute 1 minute Initial condition Uniformly rested water Bottom roughness Chezy 65 Hor. eddy viscosity 10.0 m2/s 1 m2/s Hor. diffusivity - 10 m2/s Offshore boundary condition TPXO8.0: Global Inverse Tide Model GoT Model Wind & Air pressure data 6 hourly ECMWF-ERA Interim –spatial and temporal varying data Air tem, Relative humidity, Cloud cover data 6 hourly ECMWF-ERA Interim –spatial and temporal varying data Delft3D-FLOW 249*416 GoT model GoT model
- 57. Modelled Results Validation: GoT scale Water level values between simulated and measured water level at different locations at the GoT show comparable results.
- 58. -1.000 -0.800 -0.600 -0.400 -0.200 0.000 0.200 0.400 0.600 0.800 1.000 23-Apr-17 24-Apr-17 25-Apr-17 26-Apr-17 27-Apr-17 28-Apr-17 29-Apr-17 30-Apr-17 1-May-17 2-May-17 3-May-17 4-May-17 5-May-17 6-May-17 7-May-17 8-May-17 9-May-17 10-May-17 11-May-17 12-May-17 13-May-17 14-May-17 15-May-17 meter Time Water Level and Fish Cage Measured Simulated Hydrodynamics model reproduce tidal behaviors well inside the lagoon. Water level comparison Water level values between simulated and measured water level at inside the lagoon show good agreement. Modelled Results Validation: AKBL scale
- 59. At Chanthaburi coast Waterdepth(m) Waterdepth(m) At the AKBL Simulated Tidal Current Pattern of the GoT
- 60. 22 24 26 28 30 32 34 36 1-Jan-15 1-Feb-15 4-Mar-15 4-Apr-15 5-May-15 5-Jun-15 6-Jul-15 6-Aug-15 6-Sep-15 7-Oct-15 7-Nov-15 8-Dec-15 Celcius SimulatedWaterTemperature Sta.1AKKL Outersea 25 26 27 28 29 30 31 1-Jan-15 1-Feb-15 4-Mar-15 4-Apr-15 5-May-15 5-Jun-15 6-Jul-15 6-Aug-15 6-Sep-15 7-Oct-15 7-Nov-15 8-Dec-15 ppt SimulatedSalinity Sta.1AKKL Outersea 1014 1015 1016 1017 1018 1019 1020 1-Jan-15 1-Feb-15 4-Mar-15 4-Apr-15 5-May-15 5-Jun-15 6-Jul-15 6-Aug-15 6-Sep-15 7-Oct-15 7-Nov-15 8-Dec-15 kg/m3 SimulatedDensity Sta.1AKKL Outersea Outer sea Sta.1 Simulated Different Water Properties btw inside and outside
- 61. Water temperature Salinity Flow velocity Apr Aug Oct DecMonthly Avg Values
- 62. Residence time analysis using conservative tracer Neap – April 2015 Neap – August 2015
- 63. After 25hr 50hr 75hrInitial April August October December Residence Time Analysis using Conservative Numerical Tracer Shortest residence time
- 64. With wind stress in August Without wind stress August Averaged Flow Velocity
- 65. Ao Ban Don
- 66. AO Bando Bay is one of the most (maybe the most) productive water body in Thailand.
- 67. Prediction of Blue Swimming Crab Laval Dispersion at Ao Bandon Bay, Surat Thani Province Dr. Tanuspong Pokavanich Department of Marine Science, Faculty of Fisheries Kasetsart University Asst. Prof. Dr. Amornsak Sawasdee Faculty of Science, Walailuk University Dr. Piyamarn Srisomporn Numerical modelling section Hydro Informatics Institute 03/07/2561
- 68. Objectives 1. To examine current, circulation and oceanographic properties of the water bodies. 2. To examine the larval transport of the BSC and changes in seasons. Life cycle of the BSC 10 days plankton !
- 70. Synoptic Survey around the bay
- 71. Results of the synoptic survey Temperature (oC) Salinity (ppt) Dissolved oxygen (mg/l)Chlorophyll-a (mg/m3)
- 72. Measured sectional salinity (ppt) 28 Jan 2019 A B C
- 73. Cross-sectional flow velocity measurement 10 km long transact!!
- 74. Data loggers deployment for continuous measurement Water level, temperature, salinity Flow velocity Meteorology
- 75. Long-term flow velocity measured at Ao Bandon Bay
- 76. Continuous measured at Ao Bandon Bay
- 77. Model Validation
- 78. 3 May 2019 Comparison between simulated and measured density (kg/m3) Simulated Measured 28 Jan 2019 15 Aug 2019
- 79. 0.5 ม./วินาที 0.5 ม./วินาที 28 Jan 2019 28 Jan 2019 Tidal Current
- 80. 3 May 2019 28 Jan 2019 15 Aug 2019 Ao Ban Don Water is not always well mixed. Neap tide Spring tide
- 81. Different circulation and movement of river plumes
- 82. Preliminary simulated results of BSC larval transport April May
- 83. BSC larval is transported differently in each season!!!
- 84. Final Concluding Remarks •Numerical modelling can not represent everything in the real-world. •Field observation although can provide best information of the real-world but has many limitations. •Coupled field observation and numerical modelling therefore can be feasible and provide realistic information for many application. ☺
- 85. “ No one can whistle a symphony. It takes a whole orchestra to play it.” Hallford Loccok Thank you.
- 90. SW monsoon NE monsoon Averaged monthly wind vector over the Gulf of Thailand (Source: http://www.remss.com/) Wind rose between 2008- 2018 at BKK
- 92. Mixed tide with tidal range between 1.5 to 3.0 m at the Inner-GoT.
- 93. Tidal current amplitudes (source: Yanagi and Takao, 1998a)
- 94. Average monthly river discharge into the GoT (source: Royal Irrigation Dept, Thailand) From Buranapratheprat et al. (2016)
- 95. Average monthly atmospheric freshwater flux (source: oaflux.whoi.edu/) From Buranapratheprat et al. (2016)
- 96. Average monthly surface heat fluxes over GoT (source: dtsv.scc.u-tokai.ac.jp/j-ofuro/) From Buranapratheprat et a. (2016)
- 97. 97 Monthly averaged temperature at surface a) January b) April c) September d) December a b c d °C
- 98. 98 Monthly average salinity at surface a) January b) April c) September d) December ppta b c d
- 99. Concluding Remarks ✓ We successfully developed a 3D hydrodynamic model of the GoT with acceptable weekly and seasonally accuracy at the Inner-GoT. ✓ This 3D model can be used to investigate hydrodynamic characteristics of the Inner-Gulf of Thailand. ✓ The Inner-GoT circulation is highly influenced by river-runoff and monsoonal wind direction and the tropical storm event. ✓ Operational prediction system of the hydrodynamics of the Inner-GoT is possible through integration of the 3D model with atmospheric model and river run-off prediction and real-time field observation at HII.
- 100. Concluding remarks •The AKBL is a smaller water body that has short water residence time. •The residence time of the lagoon is 2-3 days and varies seasonally. •Numerical model shows significant variation of the oceanographic condition inside the lagoon which can affect the lagoon ecosystem. •More field data and model calibration is needed. •Future works should include the seawater irrigation system, shrimp farming activities into the model and evaluate influences of them to the lagoon system.