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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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Presentation on theme: "CALIBRATION OF A TRANSPORT MODEL USING DRIFTING BUOYS DEPLOYED DURING THE PRESTIGE ACCIDENT S. CASTANEDO, A.J. ABASCAL, R. MEDINA and I.J. LOSADA."— Presentation transcript:

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

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

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

4 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

5 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.

6 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

7 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.

8 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

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

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

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

12 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 ).

13 Buoy number Type Initial longitude Initial latitude Initial dateLast dateOwner PTR /01/200309/02/2003AZTI PTR /12/200203/02/2003AZTI PTR /12/200216/02/2003AZTI SC /12/200231/01/2003CSIC SC /12/200219/01/2003CSIC SC /12/200230/01/2003CSIC SC /12/200201/02/2003CSIC SC /01/200319/02/2003CSIC SC /01/200319/02/2003CSIC SC /01/200319/02/2003CSIC SC /01/200318/02/2003CSIC SC /01/200318/02/2003CSIC SC /01/200325/01/2003CSIC 2. DATA 2.1. Buoys

14 December February DATA 2.1. Buoys

15 WIND: HIRLAM model (INM) ( 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

16  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

17 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

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

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

20 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

21 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 : (FLTQ, 2003)

22 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

23 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

24 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

25 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

26 3.2. Experiment with all buoys 3. METHODOLOGY Numero Boya Fecha inicial Fecha final Número de horas /01/200309/02/ /12/200203/02/ /12/200216/02/ /12/200231/01/ /12/200219/01/ /12/200230/01/ /12/200201/02/ /01/200319/02/ /01/200319/02/ /01/200319/02/ /01/200318/02/ /01/200318/02/ /01/200325/01/ Hipothesis: 1.- Linear expression of the wind coefficient a W =  w +  w | u wind | 2.- Swell ( )

27 3.2. Experiment with all buoys 3. METHODOLOGY Correlation coefficient < 50%

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

29 BoyaaHaH ww ww acac RxRx RyRy Experiment with each buoy 3. METHODOLOGY

30 BoyaaHaH ww ww acac RxRx RyRy Experiment with each buoy 3. METHODOLOGY

31 Boyaacac RxRx RyRy Best fit buoys Small current coefficient Dominant forcing : wind 3.3. Experiment with each buoy 3. METHODOLOGY

32 Boyaacac RxRx RyRy Worse fit buoys Dominant forcing : wind and current 3.3. Experiment with each buoy 3. METHODOLOGY

33 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

34 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

35 Numero Boya Fecha inicial Fecha final Número de horas /01/200320/01/ /01/200221/01/ /12/200218/01/ /01/200318/02/ /02/200316/01/ /01/200303/02/ /02/200316/01/ 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

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

37 3.4. Outer buoys 3. METHODOLOGY

38 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

39 POM 3.5. Current coefficient 3. METHODOLOGY

40 MERCATOR 3.5. Current coefficient 3. METHODOLOGY

41 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) = * u current +( *| u wind |)* u wind * u wave  x=7.27 km,  y=6.77 km,  t=60 s

42 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

43 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

44 Period: al Lagrangian model 3. METHODOLOGY Numerical simulation with 5 buoys (3 outside of continental slope)

45 days hour steps 3.6. Lagrangian model 3. METHODOLOGY

46 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/ /01/ /01/ /01/ /01/ /01/ /01/ /01/ 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/ /01/ RMSE (48 HOUR STEPS) RMSE (8 DAYS SIMULATION) 3.6. Lagrangian model 3. METHODOLOGY

47 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/ /01/ /01/ /01/ /01/ /01/ /01/ /01/ 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/ /01/ Lagrangian model 3. METHODOLOGY RMSE (48 HOUR STEPS) RMSE (8 DAYS SIMULATION)

48 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/ /01/ /01/ /01/ /01/ /01/ /01/ /01/ 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/ /01/ Lagrangian model 3. METHODOLOGY RMSE (8 DAYS SIMULATION) RMSE (48 HOUR STEPS)

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

50  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

51  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

52 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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