Modelling environmentally friendly fairways using Lagrangian trajectories: a case study for the Gulf of Finland, the Baltic Sea
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We address possibilities of minimising environmental risks using statistical features of current-driven propagation of adverse impacts to the coast. The recently introduced method for finding the optimum locations of potentially dangerous activities (Soomere et al. in Proc Estonian Acad Sci 59:156–165, 2010) is expanded towards accounting for the spatial distributions of probabilities and times for reaching the coast for passively advecting particles released in different sea areas. These distributions are calculated using large sets of Lagrangian trajectories found from Eulerian velocity fields provided by the Rossby Centre Ocean Model with a horizontal resolution of 2 nautical miles for 1987–1991. The test area is the Gulf of Finland in the northeastern Baltic Sea. The potential gain using the optimum fairways from the Baltic Proper to the eastern part of the gulf is an up to 44% decrease in the probability of coastal pollution and a similar increase in the average time for reaching the coast. The optimum fairways are mostly located to the north of the gulf axis (by 2–8 km on average) and meander substantially in some sections. The robustness of this approach is quantified as the typical root mean square deviation (6–16 km) between the optimum fairways specified from different criteria. Drastic variations in the width of the ‘corridors’ for almost optimal fairways (2–30 km for the average width of 15 km) signifies that the sensitivity of the results with respect to small changes in the environmental criteria largely varies in different parts of the gulf.
KeywordsRisk modelling Lagrangian transport Statistics of currents Baltic Sea Pollution transport Ship routing
This study was supported by the funding from the European Community’s Seventh Framework Programme (FP/2007–2013) under grant agreement no. 217246 made with the joint Baltic Sea research and development programme BONUS. The BalticWay project attempts to identify the regions in the Baltic Sea that are associated with increased risk compared to other sea areas and to propose ways to reduce the risk of them being polluted by placing activities in other areas that may provide less risk. The research was also partially supported by the Marie Curie Reintegration Grant ESTSpline (PERG02-GA-2007-224819), the targeted financing by the Estonian Ministry of Education and Science (grants SF0140077s08 and SF0140007s14) and the Estonian Science Foundation (grant no. 7413). The contribution of Anders Anbo towards the application of the TRACMASS model in the Institute of Cybernetics and the help from Kristofer Döös during its use are gratefully acknowledged. We are also grateful to Anders Höglund (SMHI) who extracted and prepared the RCO model data.
- Andrejev O, Myrberg K, Alenius P, Lundberg PA (2004a) Mean circulation and water exchange in the Gulf of Finland—a study based on three-dimensional modelling. Boreal Environ Res 9:1–16Google Scholar
- Andrejev O, Myrberg K, Lundberg PA (2004b) Age and renewal time of water masses in a semi-enclosed basin—application to the Gulf of Finland. Tellus 56A:548–558Google Scholar
- Jönsson B, Lundberg P, Döös K (2004) Baltic sub-basin turnover times examined using the Rossby Centre Ocean Model. Ambio 23:257–260Google Scholar
- HELCOM (2009) Ensuring safe shipping in the Baltic (Stankiewicz M, Vlasov, N, eds.). Helsinki Commission, Helsinki, p 18Google Scholar
- Kachel MJ (2008) Particularly sensitive sea areas. Hamburg Studies on Maritime Affairs, 13, Springer, p 376Google Scholar
- Meier HEM (2007) Modeling the pathways and ages of inflowing salt- and freshwater in the Baltic Sea. Estuar Coast Shelf Sci 74:610–627Google Scholar
- Myrberg K, Ryabchenko V, Isaev A, Vankevich R, Andrejev O, Bendtsen J, Erichsen A, Funkquist L, Inkala A, Neelov I, Rasmus K, Rodriguez Medina M, Raudsepp U, Passenko J, Söderkvist J, Sokolov A, Kuosa H, Anderson TR, Lehmann A, Skogen MD (2010) Validation of three-dimensional hydrodynamic models in the Gulf of Finland based on a statistical analysis of a six-model ensemble. Boreal Environ Res 15:453–479Google Scholar
- Soomere T, Quak E (2007) On the potential of reducing coastal pollution by a proper choice of the fairway. J Coast Res Special Issue 50:678–682Google Scholar
- Soomere T, Delpeche N, Viikmäe B, Quak E, Meier HEM, Döös K (2011) Patterns of current-induced transport in the surface layer of the Gulf of Finland. Boreal Environ Res 16(Suppl A):49–63Google Scholar
- Vandenbulcke L, Beckers J-M, Lenartz F, Barth A, Poulain P-M, Aidonidis M, Meyrat J, Ardhuin F, Tonani M, Fratianni C, Torrisi L, Pallela D, Chiggiato J, Tudor M, Book JW, Martin P, Peggion G, Rixen M (2009) Super-ensemble techniques: application to surface drift prediction. Progr Oceanogr 82:149–167CrossRefGoogle Scholar
- Viikmäe B, Soomere T, Viidebaum M, Berezovski A (2010) Temporal scales for transport patterns in the Gulf of Finland. Estonian J Eng 16:211–227Google Scholar