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CALIBRATION OF A TRANSPORT MODEL USING DRIFTING BUOYS DEPLOYED DURING THE PRESTIGE ACCIDENT S. CASTANEDO, A.J. ABASCAL, R. MEDINA and I.J. LOSADA

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1. Introduction 2.Data 3.Methodology 4. Conclusions OUTLINE

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1. Introduction 2.Data 3.Methodology 4. Conclusions OUTLINE

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1. INTRODUCTION Along the Spanish coast several emergency spill response systems were built during the Prestige crisis (UC, AZTI, MeteoGalicia, IMEDEA,...). In these response systems one important task was to establish operational forecasting systems for developing proper response strategies

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1. INTRODUCTION Generally, the structure of these predictions systems was composed by collection of observations including oil slicks, numerical modelling to provide forecasts of wind, waves, currents and oil trajectories and finally, data management and dissemination. The emergency spill response systems were considered to be important tools in addressing the Prestige crisis.

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1. INTRODUCTION - Daily cleaning-up of the beaches - Mechanical recovery from the water surface - Protection of estuaries by means of booms Delegación del Gobierno en Cantabria Consejería de Medio Ambiente de Cantabria

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1. INTRODUCTION Now, we can take advantage of the experience acquired during the Prestige accident and develop a Spanish operational oceanographic system (Project ESEOO:www.eseoo.org). One of the main objective of the ESEOO transport model is to be used by SASEMAR in sea rescue and response to pollution of marine water. The success of the system will be based on the accuracy of the different numerical models involved in trajectory forecasting.

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1. INTRODUCTION The aim of this study is to calibrate a Lagrangian particle- tracking trajectory algorithm and, at the same time, investigate about the relative importance that the different forcing (wind, wave, currents) have on the oil spill fate. C D =0.02 C D =0.03

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1. Introduction 2.Data 3.Methodology 4. Conclusions OUTLINE

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2. DATA WHAT DO WE NEED? Trajectory Analysis handbook (NOAA)

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WHAT DO WE NEED? 2. DATA FORCINGS : Wind Currents Waves BUOYS NUMERICAL MODEL

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2. DATA 2.1. Buoys Among the decisions made during the management of the Prestige accident, it was proposed to release lagrangian floats to both track the biggest oil slicks position and trajectory and to provide some feedback and/or validation for the numerical models of currents and oil dispersion forecast. The deployment of drifting floats was organised by the National Spanish Research Council (CSIC) and AZTI Foundation using available ARGOS buoys used for oceanographic studies ( García-Ladona et al., 2005 ).

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Buoy number Type Initial longitude Initial latitude Initial dateLast dateOwner 16291 PTR-5.86845.31115/01/200309/02/2003AZTI 16651 PTR -3.51844.27827/12/200203/02/2003AZTI 16735 PTR -6.59345.17529/12/200216/02/2003AZTI 16751 SC40 -9.44742.91519/12/200231/01/2003CSIC 16752 SC40 -9.35643.15519/12/200219/01/2003CSIC 16753 SC40 -9.58142.96919/12/200230/01/2003CSIC 16754 SC40 -9.60442.68819/12/200201/02/2003CSIC 23249 SC40 -12.04642.20716/01/200319/02/2003CSIC 23258 SC40 -9.5842.66211/01/200319/02/2003CSIC 23259 SC40 -12.05442.17427/01/200319/02/2003CSIC 23282 SC40 -3.35045.24902/01/200318/02/2003CSIC 23289 SC40 -4.00745.57502/01/200318/02/2003CSIC 23348 SC40 -9.41642.86111/01/200325/01/2003CSIC 2. DATA 2.1. Buoys

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December 2002 - February 2003 2. DATA 2.1. Buoys

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WIND: HIRLAM model (INM) ( www.inm.es) 2.2. Wind and wave conditions 2. DATA Wind at 10 meters above the MSL x 0.2º x 0.2º ( z 22 km) t 6 hours Data from re-analysis corresponding to the period November 2002-November 2003

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x 0.25 x 0.25º ( z 28km) t 3 hours WAVE: WAM model (PE) (www.puertos.es) 2.2. Wind and wave conditions 2. DATA

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2.3. Currents 2. DATA CURRENTS 1: NRLPOM model (USA) (http://www.aos.princeton.edu) CURRENTS 2: MERCATOR model (FR) (http://www.mercator-ocean.fr/) x z 7 km, t 3 hours x z 7 km, t 24 hours

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FORCINGPeríodoFUENTE WIND Re-analysis data Nov. 2002 -Nov. 2003 HIRLAM (INM) WAVE Dic. 2002 – Dic. 2003WAM (PE) CURRENTS 1 Dic. 2002 - Dic. 2003 NRLPOM (USA) CURRENTS 2 Nov. 2002 -Mar. 2003MERCATOR (FR) 2. DATA BUOYS Dic. 02 – Feb. 03 2.4. Summary

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1. Introduction 2.Data 3.Methodology 4. Conclusions OUTLINE

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We want to simulate the buoy trajectory by means of a numerical model: Lagrangian transport model X i (t+ t) = X i (t) + u(t) t + diffusion u(t) = u currents + C D * u wind + C W * u wave C D : wind drag coefficient C W : wave coefficient Difussion : (García-Martínez y Flores-Tovar, 1999; Lonin, 1999) k : diffusion coefficient 3. METHODOLOGY

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U S,V C D * U V U wind : Wind-induced current C D : 3% (Sobey, 1992) 2.5%-4.4% (ASCE, 1996) U wave : Wave-induced Stokes drift (Sobey y Barker, 1997) C W : 0.01- 0.1 (FLTQ, 2003)

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3. METHODOLOGY We need to determine the coefficients C D and C w in order to obtain the best fit between the numerical result and the observed buoy trajectory Owing to the great quantity of variables involved in the problem, aa optimization algorithm is used in this study as a preliminary tool

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3. METHODOLOGY 1. Coefficients that minimize the error between numerical and actual buoy trajectory: optimization algorithm PROCEDURE: 2. Introduction of these coefficients in the Lagrangian transport model 3. Analysis of the results/conclusions

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3. METHODOLOGY SCE-UA (shuffled complex evolution method – University of Arizona) (Duan et al, 1994) Global optimization algorithm: SCE-UA (shuffled complex evolution method – University of Arizona) (Duan et al, 1994) 3.1. Automatic calibration N: number of buoys U B : actual buoy velocity U M : numerical buoy velocity (wind, wave and currents) Objective function: The goal of calibration is to find those values for the coefficients that minimize J

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a H : wave coefficient ( Cw ) a W : wind coefficient (C D ) a C : current coefficient (indication of the error in the numerical current field) Actual buoy velocity Numerical buoy velocity 3. METHODOLOGY 3.1. Automatic calibration

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3.2. Experiment with all buoys 3. METHODOLOGY Numero Boya Fecha inicial Fecha final Número de horas 16291 15/01/200309/02/2003107 16651 27/12/200203/02/2003215 16735 29/12/200216/02/2003240 16751 19/12/200231/01/2003234 16752 19/12/200219/01/2003143 16753 19/12/200230/01/2003234 16754 19/12/200201/02/2003235 23249 16/01/200319/02/200380 23258 11/01/200319/02/2003155 23259 27/01/200319/02/200333 23282 02/01/200318/02/2003301 23289 02/01/200318/02/2003157 23348 11/01/200325/01/200345 Hipothesis: 1.- Linear expression of the wind coefficient a W = w + w | u wind | 2.- Swell ( )

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3.2. Experiment with all buoys 3. METHODOLOGY Correlation coefficient < 50%

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Next step: We need to delimitate the problem Calibration for each buoy 3.2. Experiment with all buoys 3. METHODOLOGY

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BoyaaHaH ww ww acac RxRx RyRy 162910.100850.0224260.0004780.104440.58180.6521 16651-0.130770.0264480.0003840.011230.68540.5972 167350.031620.0203490.0008450.063690.59190.4331 232490.053410.0311100.0007690.164350.48120.5012 232580.057970.024382-0.0001860.383090.54870.4948 23259-0.169320.024124-0.000371-0.023910.76450.4155 232820.037020.0212860.0002260.040800.50840.2750 232890.033980.029249-0.000489-0.272400.42120.2726 167510.090230.025523-0.0006760.474680.21930.1955 167520.394330.0153690.0005130.540860.38560.2220 167530.210310.0124070.0009020.171930.40220.4244 167540.040530.029186-0.0005660.469130.43920.3780 23348-0.040040.018670-0.0006270.194330.00020.1553 3.3. Experiment with each buoy 3. METHODOLOGY

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BoyaaHaH ww ww acac RxRx RyRy 162910.100850.0224260.0004780.104440.58180.6521 16651-0.130770.0264480.0003840.011230.68540.5972 167350.031620.0203490.0008450.063690.59190.4331 232490.053410.0311100.0007690.164350.48120.5012 232580.057970.024382-0.0001860.383090.54870.4948 23259-0.169320.024124-0.000371-0.023910.76450.4155 232820.037020.0212860.0002260.040800.50840.2750 232890.033980.029249-0.000489-0.272400.42120.2726 167510.090230.025523-0.0006760.474680.21930.1955 167520.394330.0153690.0005130.540860.38560.2220 167530.210310.0124070.0009020.171930.40220.4244 167540.040530.029186-0.0005660.469130.43920.3780 23348-0.040040.018670-0.0006270.194330.00020.1553 3.3. Experiment with each buoy 3. METHODOLOGY

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Boyaacac RxRx RyRy 162910.104440.58180.6521 166510.011230.68540.5972 167350.063690.59190.4331 232490.164350.48120.5012 232580.383090.54870.4948 23259-0.023910.76450.4155 Best fit buoys Small current coefficient Dominant forcing : wind 3.3. Experiment with each buoy 3. METHODOLOGY

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Boyaacac RxRx RyRy 232820.040800.50840.2750 23289-0.272400.42120.2726 167510.474680.21930.1955 167520.540860.38560.2220 167530.171930.40220.4244 167540.469130.43920.3780 233480.194330.00020.1553 Worse fit buoys Dominant forcing : wind and current 3.3. Experiment with each buoy 3. METHODOLOGY

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We obtain the best fit when wind is the dominant forcing When currents are important (continental slope and near the coast) the agreement between observed and numerical trajectories is worse The numerical current field must be improved 3.3. Experiment with each buoy 3. METHODOLOGY

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PROCEDURE: 1. We select the buoys located outside of the continental slope (mainly affected by wind) Hipothesis: In these buoys the effect of the currents is negligible 2. We obtain C D and C W with these outer buoys 3. With all buoys and with C D and C W obtained in 2., the current coefficient is carried out

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Numero Boya Fecha inicial Fecha final Número de horas 1629115/01/200320/01/200337 1665114/01/200221/01/200359 1673529/12/200218/01/2003100 2328214/01/200318/02/200337 2328901/02/200316/01/200351 2325928/01/200303/02/200331 2328901/02/200316/01/200351 3.4. Outer buoys 3. METHODOLOGY 1. We select the buoys located outside of the continental slope (mainly affected by wind) Hipothesis: In these buoys the effect of the currents is negligible

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2. We obtain C D and C W with these outer buoys 3.4. Outer buoys 3. METHODOLOGY a W = w + w | u wind |

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3.4. Outer buoys 3. METHODOLOGY

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Current fields POM MERCATOR 3.5. Current coefficient 3. METHODOLOGY 3. With all buoys and with C D and C W obtained in 2., the current coefficient is carried out

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POM 3.5. Current coefficient 3. METHODOLOGY

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MERCATOR 3.5. Current coefficient 3. METHODOLOGY

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X i (t+ t) = X i (t) + u(t) t + diffusion Introduction of the calculated coefficients (C D, C w, a c ) in the Lagrangian transport model 3.6. Lagrangian model 3. METHODOLOGY u(t) =0.10312* u current +(0.0178+0.000798*| u wind |)* u wind + 0.0526* u wave x=7.27 km, y=6.77 km, t=60 s

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RMSE: C D, C w and a c coefficients calculated by the SCE_UA method Numerical simulation with all buoys 3.6. Lagrangian model 3. METHODOLOGY

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3.6. Lagrangian model 3. METHODOLOGY RMSE: C D and C w coefficients calculated by the SCA_UA method and a c =1 Numerical simulation with all buoys

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Period: 15-01-2003 al 23-01-2003 3.6. Lagrangian model 3. METHODOLOGY Numerical simulation with 5 buoys (3 outside of continental slope)

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2 1 3 4 5 8 days 1 2 3 4 5 48 hour steps 3.6. Lagrangian model 3. METHODOLOGY

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Fecha RMSE m (km) Boya 1 RMSE m (km) Boya 2 RMSE m (km) Boya 3 RMSE m (km) Boya 4 RMSE m (km) Boya 5 15/01/2003 17/01/2003 30.2915.494.574.678.20 17/01/2003 19/01/2003 25.6216.025.475.942.78 19/01/2003 21/01/2003 21.7355.3812.753.17 21/01/2003 23/01/2003 43.9449.9215.27 Fecha RMSE m (km) Boya 1 RMSE m (km) Boya 2 RMSE m (km) Boya 3 RMSE m (km) Boya 4 RMSE m (km) Boya 5 15/01/2003 23/01/2003 95.5183.1926.3122.7719.37 RMSE (48 HOUR STEPS) RMSE (8 DAYS SIMULATION) 3.6. Lagrangian model 3. METHODOLOGY

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Fecha RMSE m (km) Boya 1 RMSE m (km) Boya 2 RMSE m (km) Boya 3 RMSE m (km) Boya 4 RMSE m (km) Boya 5 15/01/2003 17/01/2003 30.2915.494.574.678.20 17/01/2003 19/01/2003 25.6216.025.475.942.78 19/01/2003 21/01/2003 21.7355.3812.753.17 21/01/2003 23/01/2003 43.9449.9215.27 Fecha RMSE m (km) Boya 1 RMSE m (km) Boya 2 RMSE m (km) Boya 3 RMSE m (km) Boya 4 RMSE m (km) Boya 5 15/01/2003 23/01/2003 95.5183.1926.3122.7719.37 3.6. Lagrangian model 3. METHODOLOGY RMSE (48 HOUR STEPS) RMSE (8 DAYS SIMULATION)

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Fecha RMSE m (km) Boya 1 RMSE m (km) Boya 2 RMSE m (km) Boya 3 RMSE m (km) Boya 4 RMSE m (km) Boya 5 15/01/2003 17/01/2003 30.2915.494.574.678.20 17/01/2003 19/01/2003 25.6216.025.475.942.78 19/01/2003 21/01/2003 21.7355.3812.753.17 21/01/2003 23/01/2003 43.9449.9215.27 Fecha RMSE m (km) Boya 1 RMSE m (km) Boya 2 RMSE m (km) Boya 3 RMSE m (km) Boya 4 RMSE m (km) Boya 5 15/01/2003 23/01/2003 95.5183.1926.3122.7719.37 3.6. Lagrangian model 3. METHODOLOGY RMSE (8 DAYS SIMULATION) RMSE (48 HOUR STEPS)

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1. Introduction 2.Data 3.Methodology 4. Conclusions OUTLINE

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A global optimization method (SCE-UA), developed for calibrating watershed models, has been used in this study. The goal of this method was to find the optimal forcing coefficients to be applied in a numerical transport model. The forcing coefficients that minimize the error between the numerical and the observed buoy trayectories were obtained. A linear relation between wind velocity and wind drag coefficient was found. 4. CONCLUSIONS

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Regarding the wave action, the separation of the sea and swell effect on the buoy trajectory provided the best result. We obtained the best solution when the wind was the dominant forcing. When it is not possible to neglect the currents (continental slope and near the coast) the agreement between actual and numerical trajectories was worse The numerical current fields were no correct to simulate the buoy trajectories. Further research in this area is needed. 4. CONCLUSIONS

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CALIBRATION OF A TRANSPORT MODEL USING DRIFTING BUOYS DEPLOYED DURING THE PRESTIGE ACCIDENT S. CASTANEDO, A.J. ABASCAL, R. MEDINA and I.J. LOSADA

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