半封闭型海湾水环境参数时空变化的研究
|
摘要
河口及近岸海域中水体的流动特征及其中物质的传输特性是进一步研究其它海洋过程,包括海洋环境和海洋生态过程的基础。本文针对半封闭型海湾这一典型的水体环境,对其中表征水体物质传输的余流特征进行了研究,并对传输时间尺度等水环境特征参数的时空变化进行了探索,在此基础上建立了一个以浮游生物为主的海洋生态系统数值模型并进行了初步的应用。
本文采用基于三维不可压缩流体运动基本方程的水动力模型,对水体流动及其中物质成分的传输进行了数值模拟研究。模型中引入了垂向混合σ坐标以增加模型在水体上层的模拟精度,并在计算中采用欧拉传输和拉格朗日粒子跟踪两种不同的方法处理物质传输现象。
论文针对半封闭型海湾,考虑了潮致余流、风生-潮致余流等情况,同时结合了欧拉余流与拉格朗日余流的对比,对半封闭型海湾的余流结构进行了研究。以此为基础,引入了滞留时间和游弋时间等传输时间尺度,对两种不同的传输时间尺度所具有的区域特征上的差异和在各季节中呈现的特征进行了分析,同时也分析了河流径流对传输时间尺度的影响。并比较了拉格朗日粒子追踪方法和采用人工示踪剂的欧拉法在计算传输时间尺度上的差异。通过以上对传输时间尺度在时间和空间上具有的特征所进行的研究,揭示了半封闭型海湾中水体的传输特征及与外洋水体的交换特征,这些结论是研究水体中物质传输规律的基础。
在三维水动力模型基础上对半封闭型海湾中的温度、盐分的变化过程进行了长期的模拟预测,经与实测资料对比发现模型可以较好地再现海湾内温盐的时空变化规律。这也是进一步进行生态系统模拟的基础。在此基础上建立了包含氮磷等循环的以浮游生物为主体的海洋生态系统模块,与水动力学模型耦合并应用于相应的海域,这些将为今后进行溶解氧及浮游植物生物量分布等的研究预测提供基础。
The hydrodynamics and mass transport characteristics in estuarine and coastal zones are basis for understanding the interactions between physical processes and marine ecosystem dynamics. The study on residual current structure, the transportation of water body and mass composition within the typical semi-enclosed bay are carried out by numerical simulation. Meanwhile, the spatio-temporal variation of water environmental parameters such as transport time scales are numerically modeled and studied. A marine ecosystem model consisting of lower trophic levels is developed and applied to the water environment system of a typical semi-enclosed bay.
The current and the mass transportation are studied based on the three dimensional incompressible viscous fluid dynamics model and the tracing techniques including both Eulerian approach and Lagrangian particle tracing approach are applied. The vertical hybrid-layered sigma coordinate is implemented in the model in order to enhance the numerical resolution in the upper layers of the bay.
The structures of residual current caused by different dynamic forces including tide, wind, river run-off etc. in the semi-enclosed bay are studied. The calculated results of the Euler residual current and the Lagrange residual current are compared. Moreover, transport time scales such as residence time and age are introduced into the numerical model, and the patterns showed in their histograms of different areas and in the seasonal variation of horizontal distribution are discussed. We also compare the computed difference of transport time scales between Lagrangian particle trajectory method and Eulerian artificial tracer. Results show mass transport characteristics within the bay and water exchange characteristics between ocean and the semi-enclosed bay, all of which are foundation for the understanding of mass transportation in the water environment system.
Based on the three dimensional hydrodynamical model, long-term variations of temperature and salinity are simulated, which is necessary for the prediction of statement variables such as dissolved oxygen and phytoplankton biomass. Good agreement is found between the in-situ data and the numerical calculated results. Further the biological module including the loops of nitrogen and phosphorus is developed and coupled to the three dimensional hydrodynamical model. The biological module is applied to the corresponding sea area in a simple case. It shows that the biological module coupled to the three dimensional hydrodynamic model has the potential to be used for the prediction of dissolved oxygen and organism biomass in marine ecosystem.
本文采用基于三维不可压缩流体运动基本方程的水动力模型,对水体流动及其中物质成分的传输进行了数值模拟研究。模型中引入了垂向混合σ坐标以增加模型在水体上层的模拟精度,并在计算中采用欧拉传输和拉格朗日粒子跟踪两种不同的方法处理物质传输现象。
论文针对半封闭型海湾,考虑了潮致余流、风生-潮致余流等情况,同时结合了欧拉余流与拉格朗日余流的对比,对半封闭型海湾的余流结构进行了研究。以此为基础,引入了滞留时间和游弋时间等传输时间尺度,对两种不同的传输时间尺度所具有的区域特征上的差异和在各季节中呈现的特征进行了分析,同时也分析了河流径流对传输时间尺度的影响。并比较了拉格朗日粒子追踪方法和采用人工示踪剂的欧拉法在计算传输时间尺度上的差异。通过以上对传输时间尺度在时间和空间上具有的特征所进行的研究,揭示了半封闭型海湾中水体的传输特征及与外洋水体的交换特征,这些结论是研究水体中物质传输规律的基础。
在三维水动力模型基础上对半封闭型海湾中的温度、盐分的变化过程进行了长期的模拟预测,经与实测资料对比发现模型可以较好地再现海湾内温盐的时空变化规律。这也是进一步进行生态系统模拟的基础。在此基础上建立了包含氮磷等循环的以浮游生物为主体的海洋生态系统模块,与水动力学模型耦合并应用于相应的海域,这些将为今后进行溶解氧及浮游植物生物量分布等的研究预测提供基础。
The hydrodynamics and mass transport characteristics in estuarine and coastal zones are basis for understanding the interactions between physical processes and marine ecosystem dynamics. The study on residual current structure, the transportation of water body and mass composition within the typical semi-enclosed bay are carried out by numerical simulation. Meanwhile, the spatio-temporal variation of water environmental parameters such as transport time scales are numerically modeled and studied. A marine ecosystem model consisting of lower trophic levels is developed and applied to the water environment system of a typical semi-enclosed bay.
The current and the mass transportation are studied based on the three dimensional incompressible viscous fluid dynamics model and the tracing techniques including both Eulerian approach and Lagrangian particle tracing approach are applied. The vertical hybrid-layered sigma coordinate is implemented in the model in order to enhance the numerical resolution in the upper layers of the bay.
The structures of residual current caused by different dynamic forces including tide, wind, river run-off etc. in the semi-enclosed bay are studied. The calculated results of the Euler residual current and the Lagrange residual current are compared. Moreover, transport time scales such as residence time and age are introduced into the numerical model, and the patterns showed in their histograms of different areas and in the seasonal variation of horizontal distribution are discussed. We also compare the computed difference of transport time scales between Lagrangian particle trajectory method and Eulerian artificial tracer. Results show mass transport characteristics within the bay and water exchange characteristics between ocean and the semi-enclosed bay, all of which are foundation for the understanding of mass transportation in the water environment system.
Based on the three dimensional hydrodynamical model, long-term variations of temperature and salinity are simulated, which is necessary for the prediction of statement variables such as dissolved oxygen and phytoplankton biomass. Good agreement is found between the in-situ data and the numerical calculated results. Further the biological module including the loops of nitrogen and phosphorus is developed and coupled to the three dimensional hydrodynamical model. The biological module is applied to the corresponding sea area in a simple case. It shows that the biological module coupled to the three dimensional hydrodynamic model has the potential to be used for the prediction of dissolved oxygen and organism biomass in marine ecosystem.
引文
陈宗镛. 1980.潮汐学.北京:科学出版社. 301pp.
冯士筰. 1988.论浅海环流及其输运的流体动力学基础.清华大学工程力学与工程热物理学术会议论文集,清华大学出版社, pp199-208.
黄良民,钱宏林,李锦蓉. 1994.大鹏湾赤潮多发区的叶绿素a分布与环境关系初探.海洋与湖沼,25(2): 197-205.
黄奕华,楚建华,齐雨藻. 1997.盐田海域骨条藻数量的多元分析.海洋与湖沼,28(2): 121-127.
刘成,王兆印,何耘,等. 2003.环渤海湾诸河口水质现状的分析.环境污染与防治,25(4): 222-225.
刘桂梅,孙松,王辉. 2003.海洋生态系统动力学模型及其研究进展.地球科学进展,18(3): 427-732.
刘英,曾广钊. 2004.关于两种生态学种群相互作用的建模方法的比较和应用.韶关学院学报(自然科学版), 25(12): 8-10.
齐雨藻,黄伟建,邱璇鸿. 1991.大鹏湾夜光藻种群动态的时间序列模式.暨南大学学报, 2(3): 96-103.
齐雨藻,等. 2003.中国沿海赤潮.北京:科学出版社. 348pp.
唐启升,苏纪兰. 2000.中国海洋生态系统动力学研究I.关键科学问题与研究发展战略. 北京:科学出版社.
王安利,王维娜. 1995.虾池赤潮与环境因子关系的研究.海洋学报,17(2): 128-133.
王寿松,冯国灿,夏综万,等. 1994.大鹏湾夜光藻赤潮发生要素的结构分析.海洋与湖沼, 25(2): 146-151.
魏皓,赵亮. 2003.渤海浮游植物生物量与初级生产力变化的三维模拟.海洋学报,25(S2):151-156.
夏综万,于斌,史键辉,等. 1997.大鹏湾的赤潮生态仿真模型.海洋与湖沼,28(5): 468-474.
赵冬至,赵玲,张丰收. 2003.我国海域赤潮灾害的类型、分布与变化趋势.海洋环境科学, 22(3): 7-11.
Aksnes D L, Lie U. 1990. A coupled physical-biological pelagic model of a shallow sill fjord. Estuarine, Coastal and Shelf Science, 31: 459-486.
Baird M E, Oke P, Suthers I M, et al. 2004. A plankton population model with biomechanical descriptions of biological processes in an idealized 2D ocean basin. Journal of Marine Systems, 50: 199-222.
Baird M E, Timko P G, Suthers I M, et al. 2006a. Coupled physical-biological modelling study of the East Australian Current with idealised wind forcing: Part I. Biological model intercomparison. J. Mar. Syst. 59: 249-270.
Baird M E, Timko P G, Suthers I M, et al. 2006b. Coupled physical–biological modelling study of the East Australian current with idealised wind forcing. Part II: Dynamical analysis. J. Mar. Syst. 59: 271-291.
Baretta J W, Ebenhoh W, Ruardaij P. 1995. The European Regional Seas Ecosystem Model(ERSEM): a complex marine ecosystem model. Neth. J. Sea Res., 33: 233-246.
Basterretxea G, Garces E, Jordi A, et al. 2005. Breeze conditions as a favoring mechanism of Alexandrium taylori blooms at a Mediterranean beach. Estuarine, Coastal and Shelf Science, 62: 1-12.
Beckmann A, Hense I. 2004. Torn between extremes: the ups and downs of phytoplankton. Ocean Dynamics, 54: 581-592.
Burchard H, Bolding K. 2002. GETM– a general estuarine transport model. Scientific documen- tation, Tech. Rep. EUR 20253 EN , European Commission.
Beukenma J, Baratta B J, eds. 1995. European Regioonal Seas Ecosystem Model-I. Neth. J. Sea Res., 33(3/4).
Bilgili A, Proehl J A, Lynch D R, et al. 2005. Estuary/ocean exchange and tidal mixing in a Gulf of Maine Estuary: A Lagrangian modeling study. Estuarine, Coastal and Shelf Science, 65(4): 607-624.
Bolin B, Rodhe H. 1973. A note on the concepts of age distribution and transit time in natural reservoirs. Tellus, 25: 58-62.
Bryan K. 1969. A numerical method for the study of the world ocean. Journal of Computational Physics, 4: 347-376.
Choi K W, Lee J H W. 2004. Numerical determination of flushing time for stratified water bodies. Journal of Marine Systems, 50(3-4): 263-281.
Cucco A, Umgiesser G. 2006. Modeling the Venice Lagoon residence time. Ecological Modelling, 193: 34-51.
Cucco A, Umgiesser G, Ferrarin C, et al. 2009. Eulerian and lagrangian transport time scales of a tidal active coastal basin. Ecological Modelling, 220: 913-922.
Davies A M. 1987. Spectral models in continental shelf sea oceanography // Heaps N S, ed. Three-dimensional Coastal Ocean Models. American Geophysical Union, Washington, DC(USA) , 71-106.
Davies A M. 1994. On the complementary nature of observational data, scientific understanding and model complexity: the need for a range of models. Journal of Marine Systems, 5(6): 406-408.
Deleersnijder E, Campin J M, Delhez E J. 2001. The concept of age in marine modelling I. Theory and preliminary model results. Journal of Marine Systems, 28: 229-267.
Delhez E J, Campin J M, Hirst A C, et al. 1999. Toward a general theory of the age in ocean modelling. Ocean Modelling, 1: 17-27.
Delhez E J, Deleersnijder E. 2002. The concept of age in marine modelling II. Concentration distribution function in the English Channel and the North Sea. Journal of Marine Systems, 31: 279-297.
Delhez E J, Heemink A W Deleersnijder E. 2004.Residence time in a semi-enclosed domain from the solution of an adjoint problem. Estuarine, Coastal and Shelf Science, 61: 691-702.
Droop M R. 1974. The nutrient status of algal cells in continuous culture. Journal of the Marine Biological Association of the United Kingdom, 54: 825-855.
England M H. 1995. The age of water and ventilation timescales in a global ocean model. J. Phys. Oceanogr. 25: 2756-2777.
Eppley R W, Thomas W H. 1968. Comparison of half-saturation constants for growth and nitrate uptake of marine phytoplankton. Journal of Phycology, 5(4): 375-379.
Feng S. 1986. A three-dimensional weakly nolinear dynamics on tide-induced Lagrangian residual current and mass-transport. Chinese Journal of Oceanology and Limnology, 4(2):139.
Feng S. 1987. A three-dimensional weakly nolinear model of tide-induced Lagrangian residual current and mass-transport, with an application to the Bohai Sea. // Nihoul J C J, Jamart B M, ed. Three-dimensional Models of Marine and Estuarine Dynamics. Elsevier Science Pub. Com., Amsteradam-Oxford-New York, 471-488.
Feng S. et al. 1990. Lagrangian residual current and long-term transport processes in a weakly nonlinear baroclinic system, Physics of Shallow Seas. China Ocean Press, Beijing, 3-20.
Field J G, Hempel G, Summerhayes C P.著,吴克勤,林宝法,祁冬梅译, 2004. 2020年的海洋:科学、发展趋势和可持续发展面临的挑战.北京:海洋出版社.
Fujii M, Nojiri Y, Yamanaka Y, et al. 2002. A one dimensional ecosystem model applied to time series Station KNOT. Deep-Sea Res. II, 49: 5441–5461.
GEOHAB. 2001. Global Ecology and Oceanography of Harmful Algal Blooms, Science Plan. P. Glibert and G. Pitcher (eds). SCOR and IOC, Baltimore and Paris. 87 pp.
GEOHAB. 2003. Global Ecology and Oceanography of Harmful Algal Blooms, Implementation Plan. P. Gentien, G. Pitcher, A. Cembella, P. Glibert (Eds.). SCOR and IOC, Baltimore and Paris. 36 pp.
Guo X, Yanagi T. 1994. Three Dimensional Structure of the Tidal Currents in Tokyo Bay, Japan. La mer, , 32: 173-185.
Haidvogel D B, Beckmann A. 1999.Numerical ocean circulation modeling. London: Imperial College Press, 318pp.
Heaps N S. 1972. On the numerical solution of the three-dimensional equations for tides and storm surges. Mem. Soc. R. Sci. Liege., 6(2): 143-180.
Heaps N S. 1987. Three-Dimensional Coastal Ocean Models. American Geophysical Union, Washington, DC(USA), 1-16.
Inoue M, Wiseman W J. 2000. Transport, Mixing and Stirring Processes in a Louisiana Estuary: A Model Study. Estuarine, Coastal and Shelf Science, 50(4): 449-466.
John J W, et al. 2002. A numerical analysis of landfall of the 1979 red tide of Karenia brevis along the west coast of Florida. Continental Shelf Research, 22: 15-38.
Kawamiya M. 2003. An eddy-permitting, coupled ecosystem-circulation model of the Arabian Sea: comparison with observations. Journal of Marine Systems, 38: 221-257.
Kawamiya M, Kishi M J, Suginohara N. 2000a. An ecosystem model for the North Pacific embedded in a general circulation model: Part I. Model description and characteristics of spatial distributions of biological variables. Journal of Marine Systems, 25: 129-157.
Kawamiya M, Kishi M J, Suginohara N. 2000b. An ecosystem model for the North Pacific embedded in a general circulation model: Part II. Mechanisms forming seasonal variations of chlorophyll. Journal of Marine Systems, 25: 159-178.
Kawamiya M, Kishi M J, Yamanaka Y, et al. 1995. An ecological–physical coupled model applied to Station Papa. J. Oceanogr. 51: 635-664.
Kawamiya M, Kishi M J, Yamanaka Y, et al. 1997. Obtaining reasonable results in different oceanic regimes with the same ecological-physical coupled model. J. Oceanogr. 53: 397-402.
Kishi M J, Ikeda S, 1986. Population dynamics of‘Red Tide’organisms in eutrophicated coastal waters-numerical experiment of phytoplankton bloom in the East Seto Inland Sea, Japan. Ecological Modelling, 31: 145-174.
Kishi M J, Motono H, Kashiwai M, et al. 2001. An ecological–physical coupled model with ontogenetic vertical migration of zooplankton in the northwestern Pacific. J. Oceanogr. 57: 499-507.
Longuet-Higgins M S. 1969. On the transport of mass by time-varying ocean currents. Deep Sea Research, 16: 431.
Lotka A J. 1925. Elements of Physical Biology. Williams and Wilkins, Baltimore.
Luyten P J, Jones J E, Proctor R, et al. 1999. COHERENS-A Coupled Hydrodynamical-Ecological Model for Regional and Shelf Seas: User Documentation. Technical report, MUMM Report, Management Unit of the Mathematical Models of the North Sea, 914pp.
Mariani P, Botte V, Ribera M. 2005. An object-oriented model for the prediction of turbulence effects on plankton. Deep-Sea Research II, 52: 1287-1307.
May R, 1976. Simple mathematical models with very complicated dynamics. Nature, 261: 459-467.
McGillicuddy D J, Anderson D M, Lynch D R, et al. 2005. Mechanisms regulating large-scale seasonal fluctuations in Alexandrium fundyense populations in the Gulf of Maine: results from a physical-biological model. Deep-Sea Research II, 52 (19-21): 2698-2714.
Mellor G L, Yamada T. 1974. A hierarchy of turbulence closure models for planetary boundary layers. Journal of the Atmospheric Sciences, 31: 1791-1806.
Moll A. 1998. Regional distribution of primary production in the North Sea simulated by a three-dimensional model. Journal of Marine Systems, 16(1-2): 151-170.
Moll A. 2000. Assessment of three-dimensional physical-biological ECOHAM1 simulations by quantified validation for the North Sea with ICES and ERSEM data. Journal of Marine Science, 57: 1060-1068.
Moll A, Radach G. 2003. Review of three-dimensional ecological modeling related to the North Sea shelf system: Part 1. models and their results. Progress in Oceanography, 57: 175-217.
Monsen N E, Cloern J E, Lucas L V, et al. 2002. A Comment on the Use of Flushing Time, Residence Time, and Age as Transport Time Scales. Limnology and Oceanography, 47(5): 1545-1553.
Muttil N, Lee J HW. 2005. Genetic programming for analysis and real-time prediction of coastal algal blooms. Ecological Modelling, 189: 363–376.
Nakata K. 1993. Ecosystem model: its formulation and estimation method for unknown rate parameters. J. Adv. Mar. Tech. Conf., 8: 99-138. (In Japanese)
Oliveira A, Baptista A M. 1997. Diagnostic modeling of residence times in estuaries. Water Resources Research, 33(8): 1935-1946.
Oliveira A, Fortunato A B, Pinto L. 2006a. Modelling the hydrodynamics and the fate of passive and active organisms in the Guadiana esturary. Estuarine, Coastal and Shelf Science, 70: 76-84.
Oliveira A, Fortunato A B, Rego J R. 2006b. Effect of morphological changes on the hydrodynamics and flushing properties of theóbidos lagoon (Portugal). Continental Shelf Research, 26(8): 917-942.
Phillips N A. 1957. A coordinate system having some special advantages for numerical forecasting. J. Meteor., 14: 184-185.
Ribbe J, Wolff J O, Staneva J, et al. 2008. Assessing water renewal time scales for marine environments from three-dimensional modelling: A case study for Hervey Bay, Australia. Environmental Modelling & Software, 23: 1217-1228.
Riley G A, Stommel H B. 1949. Quantitative ecology of the plankton of the western North Atlantic. Bull Bingham Oceanogr Coll, 12: 1-169.
Rosati A, Miyakoda K. 1988. A general circulation model for upper ocean simulation. Journal of Physical Oceanography, 18: 1601-1626.
Sandery P A, K?mpf J. 2007. Transport timescales for identifying seasonal variation in Bass Strait, south-eastern Australia. Estuarine, Coastal and Shelf Science, 4: 684-696.
Shen J, Haas L. 2004. Calculatine age and residence time in the tidal York River using three-dimensional model experiments. Estuarine, Coastal and Shelf Science, 61: 449-461.
Shen J, Wang H V. 2007. Determining the age of water and long-term transport timescale of the Chesapeake Bay. Estuarine, Coastal and Shelf Science, 74: 585-598.
Skogen M D, Svendsen E, Berntsen J, et al. 1995. Modelling the primary production in the North Sea using a coupled 3-demensional physical chemical biological ocean model. Estuarine, Coastal and Shelf Science, 41: 545-565.
Smagorinsky J. 1963. General circulation experiments with the primitive equations I. The basic experiment. Monthly Weather Review, 91: 99-165.
Steel J H. 1962. Environmental control of phytosynthesis in the sea. Limnol Oceanogr, 7: 137-150.
Stock C A, McGillicuddy D J, Solow A R, et al. 2005. Evaluating hypotheses for the initiation and development of Alexandrium fundyense blooms in the western Gulf of Maine using a coupled physical-biological model. Deep-Sea Research II, 52: 2715-2744.
Takeoka H. 1984a. Fundamental concepts of exchange and transport time scales in a coastal sea. Continental Shelf Research, 3(3): 311-326.
Takeoka H. 1984b. Exchange and transport time scales in the Seto Inland Sea. Continental Shelf Research, 3(4): 327-341.
Tee T K. 1976. Tide-induced residual current: A 2-D nonlinear numerical model, J. Mar. Res., 31: 603.
UNESCO. 1981. Tenth report of the joint panel on oceanographic tables and standards. UNESCO Technical Papers in Marine Science No. 36, UNESCO, Paris.
Unoki S, Okazaki M, Nagashima H. 1980. The circulation and oceanic condition in Tokyo Bay. Report of Physical Oceanography Laboratory in Physical-Chemical Institute, No.4.
Van den Berg A J, Ridderinkhof H, Riegman R, et al. 1996. Influence of variability in transport on phytoplankton biomass and composition in the southern North Sea: a modeling approach. Continent Shelf Res., 16(7): 907-931.
Woods J D. 2005. The Lagrangian Ensemble metamodel for simulating plankton ecosystems. Progress in Oceanography, 67: 84-159.
Woods J D, Perilli A, Barkmann W. 2005. Stability and predictability of a Virtual Plankton Ecosystem created by an individual-based model. Progress in Oceanography, 67: 43-83.
Yamanaka Y, Yoshie N, Fujii M, et al. 2004. An ecosystem model coupled with nitrogen–silicon–carbon cycles applied to Station A7 in the Northwestern Pacific. Journal of Oceanography, 60(2): 227-241.
Yanagi T, Yamamoto T, Koizumi Y, et al. 1995. A numerical simulation of red tide formation. Journal of Marine Systems, 6: 269-285.
Yuan D, Lin B, Falconer R. 2007. A modelling study of residence time in a macro-tidal estuary. Estuarine, Coastal and Shelf Science, 71: 401-411.
Zimmerman J. 1976. Mixing and flushing of tidal embayments in the Western Dutch Wadden Sea, Part I: Distribution of salinity and calculation of mixing time scales. Netherlands Journal of Sea Research, 10: 149-191.
冯士筰. 1988.论浅海环流及其输运的流体动力学基础.清华大学工程力学与工程热物理学术会议论文集,清华大学出版社, pp199-208.
黄良民,钱宏林,李锦蓉. 1994.大鹏湾赤潮多发区的叶绿素a分布与环境关系初探.海洋与湖沼,25(2): 197-205.
黄奕华,楚建华,齐雨藻. 1997.盐田海域骨条藻数量的多元分析.海洋与湖沼,28(2): 121-127.
刘成,王兆印,何耘,等. 2003.环渤海湾诸河口水质现状的分析.环境污染与防治,25(4): 222-225.
刘桂梅,孙松,王辉. 2003.海洋生态系统动力学模型及其研究进展.地球科学进展,18(3): 427-732.
刘英,曾广钊. 2004.关于两种生态学种群相互作用的建模方法的比较和应用.韶关学院学报(自然科学版), 25(12): 8-10.
齐雨藻,黄伟建,邱璇鸿. 1991.大鹏湾夜光藻种群动态的时间序列模式.暨南大学学报, 2(3): 96-103.
齐雨藻,等. 2003.中国沿海赤潮.北京:科学出版社. 348pp.
唐启升,苏纪兰. 2000.中国海洋生态系统动力学研究I.关键科学问题与研究发展战略. 北京:科学出版社.
王安利,王维娜. 1995.虾池赤潮与环境因子关系的研究.海洋学报,17(2): 128-133.
王寿松,冯国灿,夏综万,等. 1994.大鹏湾夜光藻赤潮发生要素的结构分析.海洋与湖沼, 25(2): 146-151.
魏皓,赵亮. 2003.渤海浮游植物生物量与初级生产力变化的三维模拟.海洋学报,25(S2):151-156.
夏综万,于斌,史键辉,等. 1997.大鹏湾的赤潮生态仿真模型.海洋与湖沼,28(5): 468-474.
赵冬至,赵玲,张丰收. 2003.我国海域赤潮灾害的类型、分布与变化趋势.海洋环境科学, 22(3): 7-11.
Aksnes D L, Lie U. 1990. A coupled physical-biological pelagic model of a shallow sill fjord. Estuarine, Coastal and Shelf Science, 31: 459-486.
Baird M E, Oke P, Suthers I M, et al. 2004. A plankton population model with biomechanical descriptions of biological processes in an idealized 2D ocean basin. Journal of Marine Systems, 50: 199-222.
Baird M E, Timko P G, Suthers I M, et al. 2006a. Coupled physical-biological modelling study of the East Australian Current with idealised wind forcing: Part I. Biological model intercomparison. J. Mar. Syst. 59: 249-270.
Baird M E, Timko P G, Suthers I M, et al. 2006b. Coupled physical–biological modelling study of the East Australian current with idealised wind forcing. Part II: Dynamical analysis. J. Mar. Syst. 59: 271-291.
Baretta J W, Ebenhoh W, Ruardaij P. 1995. The European Regional Seas Ecosystem Model(ERSEM): a complex marine ecosystem model. Neth. J. Sea Res., 33: 233-246.
Basterretxea G, Garces E, Jordi A, et al. 2005. Breeze conditions as a favoring mechanism of Alexandrium taylori blooms at a Mediterranean beach. Estuarine, Coastal and Shelf Science, 62: 1-12.
Beckmann A, Hense I. 2004. Torn between extremes: the ups and downs of phytoplankton. Ocean Dynamics, 54: 581-592.
Burchard H, Bolding K. 2002. GETM– a general estuarine transport model. Scientific documen- tation, Tech. Rep. EUR 20253 EN , European Commission.
Beukenma J, Baratta B J, eds. 1995. European Regioonal Seas Ecosystem Model-I. Neth. J. Sea Res., 33(3/4).
Bilgili A, Proehl J A, Lynch D R, et al. 2005. Estuary/ocean exchange and tidal mixing in a Gulf of Maine Estuary: A Lagrangian modeling study. Estuarine, Coastal and Shelf Science, 65(4): 607-624.
Bolin B, Rodhe H. 1973. A note on the concepts of age distribution and transit time in natural reservoirs. Tellus, 25: 58-62.
Bryan K. 1969. A numerical method for the study of the world ocean. Journal of Computational Physics, 4: 347-376.
Choi K W, Lee J H W. 2004. Numerical determination of flushing time for stratified water bodies. Journal of Marine Systems, 50(3-4): 263-281.
Cucco A, Umgiesser G. 2006. Modeling the Venice Lagoon residence time. Ecological Modelling, 193: 34-51.
Cucco A, Umgiesser G, Ferrarin C, et al. 2009. Eulerian and lagrangian transport time scales of a tidal active coastal basin. Ecological Modelling, 220: 913-922.
Davies A M. 1987. Spectral models in continental shelf sea oceanography // Heaps N S, ed. Three-dimensional Coastal Ocean Models. American Geophysical Union, Washington, DC(USA) , 71-106.
Davies A M. 1994. On the complementary nature of observational data, scientific understanding and model complexity: the need for a range of models. Journal of Marine Systems, 5(6): 406-408.
Deleersnijder E, Campin J M, Delhez E J. 2001. The concept of age in marine modelling I. Theory and preliminary model results. Journal of Marine Systems, 28: 229-267.
Delhez E J, Campin J M, Hirst A C, et al. 1999. Toward a general theory of the age in ocean modelling. Ocean Modelling, 1: 17-27.
Delhez E J, Deleersnijder E. 2002. The concept of age in marine modelling II. Concentration distribution function in the English Channel and the North Sea. Journal of Marine Systems, 31: 279-297.
Delhez E J, Heemink A W Deleersnijder E. 2004.Residence time in a semi-enclosed domain from the solution of an adjoint problem. Estuarine, Coastal and Shelf Science, 61: 691-702.
Droop M R. 1974. The nutrient status of algal cells in continuous culture. Journal of the Marine Biological Association of the United Kingdom, 54: 825-855.
England M H. 1995. The age of water and ventilation timescales in a global ocean model. J. Phys. Oceanogr. 25: 2756-2777.
Eppley R W, Thomas W H. 1968. Comparison of half-saturation constants for growth and nitrate uptake of marine phytoplankton. Journal of Phycology, 5(4): 375-379.
Feng S. 1986. A three-dimensional weakly nolinear dynamics on tide-induced Lagrangian residual current and mass-transport. Chinese Journal of Oceanology and Limnology, 4(2):139.
Feng S. 1987. A three-dimensional weakly nolinear model of tide-induced Lagrangian residual current and mass-transport, with an application to the Bohai Sea. // Nihoul J C J, Jamart B M, ed. Three-dimensional Models of Marine and Estuarine Dynamics. Elsevier Science Pub. Com., Amsteradam-Oxford-New York, 471-488.
Feng S. et al. 1990. Lagrangian residual current and long-term transport processes in a weakly nonlinear baroclinic system, Physics of Shallow Seas. China Ocean Press, Beijing, 3-20.
Field J G, Hempel G, Summerhayes C P.著,吴克勤,林宝法,祁冬梅译, 2004. 2020年的海洋:科学、发展趋势和可持续发展面临的挑战.北京:海洋出版社.
Fujii M, Nojiri Y, Yamanaka Y, et al. 2002. A one dimensional ecosystem model applied to time series Station KNOT. Deep-Sea Res. II, 49: 5441–5461.
GEOHAB. 2001. Global Ecology and Oceanography of Harmful Algal Blooms, Science Plan. P. Glibert and G. Pitcher (eds). SCOR and IOC, Baltimore and Paris. 87 pp.
GEOHAB. 2003. Global Ecology and Oceanography of Harmful Algal Blooms, Implementation Plan. P. Gentien, G. Pitcher, A. Cembella, P. Glibert (Eds.). SCOR and IOC, Baltimore and Paris. 36 pp.
Guo X, Yanagi T. 1994. Three Dimensional Structure of the Tidal Currents in Tokyo Bay, Japan. La mer, , 32: 173-185.
Haidvogel D B, Beckmann A. 1999.Numerical ocean circulation modeling. London: Imperial College Press, 318pp.
Heaps N S. 1972. On the numerical solution of the three-dimensional equations for tides and storm surges. Mem. Soc. R. Sci. Liege., 6(2): 143-180.
Heaps N S. 1987. Three-Dimensional Coastal Ocean Models. American Geophysical Union, Washington, DC(USA), 1-16.
Inoue M, Wiseman W J. 2000. Transport, Mixing and Stirring Processes in a Louisiana Estuary: A Model Study. Estuarine, Coastal and Shelf Science, 50(4): 449-466.
John J W, et al. 2002. A numerical analysis of landfall of the 1979 red tide of Karenia brevis along the west coast of Florida. Continental Shelf Research, 22: 15-38.
Kawamiya M. 2003. An eddy-permitting, coupled ecosystem-circulation model of the Arabian Sea: comparison with observations. Journal of Marine Systems, 38: 221-257.
Kawamiya M, Kishi M J, Suginohara N. 2000a. An ecosystem model for the North Pacific embedded in a general circulation model: Part I. Model description and characteristics of spatial distributions of biological variables. Journal of Marine Systems, 25: 129-157.
Kawamiya M, Kishi M J, Suginohara N. 2000b. An ecosystem model for the North Pacific embedded in a general circulation model: Part II. Mechanisms forming seasonal variations of chlorophyll. Journal of Marine Systems, 25: 159-178.
Kawamiya M, Kishi M J, Yamanaka Y, et al. 1995. An ecological–physical coupled model applied to Station Papa. J. Oceanogr. 51: 635-664.
Kawamiya M, Kishi M J, Yamanaka Y, et al. 1997. Obtaining reasonable results in different oceanic regimes with the same ecological-physical coupled model. J. Oceanogr. 53: 397-402.
Kishi M J, Ikeda S, 1986. Population dynamics of‘Red Tide’organisms in eutrophicated coastal waters-numerical experiment of phytoplankton bloom in the East Seto Inland Sea, Japan. Ecological Modelling, 31: 145-174.
Kishi M J, Motono H, Kashiwai M, et al. 2001. An ecological–physical coupled model with ontogenetic vertical migration of zooplankton in the northwestern Pacific. J. Oceanogr. 57: 499-507.
Longuet-Higgins M S. 1969. On the transport of mass by time-varying ocean currents. Deep Sea Research, 16: 431.
Lotka A J. 1925. Elements of Physical Biology. Williams and Wilkins, Baltimore.
Luyten P J, Jones J E, Proctor R, et al. 1999. COHERENS-A Coupled Hydrodynamical-Ecological Model for Regional and Shelf Seas: User Documentation. Technical report, MUMM Report, Management Unit of the Mathematical Models of the North Sea, 914pp.
Mariani P, Botte V, Ribera M. 2005. An object-oriented model for the prediction of turbulence effects on plankton. Deep-Sea Research II, 52: 1287-1307.
May R, 1976. Simple mathematical models with very complicated dynamics. Nature, 261: 459-467.
McGillicuddy D J, Anderson D M, Lynch D R, et al. 2005. Mechanisms regulating large-scale seasonal fluctuations in Alexandrium fundyense populations in the Gulf of Maine: results from a physical-biological model. Deep-Sea Research II, 52 (19-21): 2698-2714.
Mellor G L, Yamada T. 1974. A hierarchy of turbulence closure models for planetary boundary layers. Journal of the Atmospheric Sciences, 31: 1791-1806.
Moll A. 1998. Regional distribution of primary production in the North Sea simulated by a three-dimensional model. Journal of Marine Systems, 16(1-2): 151-170.
Moll A. 2000. Assessment of three-dimensional physical-biological ECOHAM1 simulations by quantified validation for the North Sea with ICES and ERSEM data. Journal of Marine Science, 57: 1060-1068.
Moll A, Radach G. 2003. Review of three-dimensional ecological modeling related to the North Sea shelf system: Part 1. models and their results. Progress in Oceanography, 57: 175-217.
Monsen N E, Cloern J E, Lucas L V, et al. 2002. A Comment on the Use of Flushing Time, Residence Time, and Age as Transport Time Scales. Limnology and Oceanography, 47(5): 1545-1553.
Muttil N, Lee J HW. 2005. Genetic programming for analysis and real-time prediction of coastal algal blooms. Ecological Modelling, 189: 363–376.
Nakata K. 1993. Ecosystem model: its formulation and estimation method for unknown rate parameters. J. Adv. Mar. Tech. Conf., 8: 99-138. (In Japanese)
Oliveira A, Baptista A M. 1997. Diagnostic modeling of residence times in estuaries. Water Resources Research, 33(8): 1935-1946.
Oliveira A, Fortunato A B, Pinto L. 2006a. Modelling the hydrodynamics and the fate of passive and active organisms in the Guadiana esturary. Estuarine, Coastal and Shelf Science, 70: 76-84.
Oliveira A, Fortunato A B, Rego J R. 2006b. Effect of morphological changes on the hydrodynamics and flushing properties of theóbidos lagoon (Portugal). Continental Shelf Research, 26(8): 917-942.
Phillips N A. 1957. A coordinate system having some special advantages for numerical forecasting. J. Meteor., 14: 184-185.
Ribbe J, Wolff J O, Staneva J, et al. 2008. Assessing water renewal time scales for marine environments from three-dimensional modelling: A case study for Hervey Bay, Australia. Environmental Modelling & Software, 23: 1217-1228.
Riley G A, Stommel H B. 1949. Quantitative ecology of the plankton of the western North Atlantic. Bull Bingham Oceanogr Coll, 12: 1-169.
Rosati A, Miyakoda K. 1988. A general circulation model for upper ocean simulation. Journal of Physical Oceanography, 18: 1601-1626.
Sandery P A, K?mpf J. 2007. Transport timescales for identifying seasonal variation in Bass Strait, south-eastern Australia. Estuarine, Coastal and Shelf Science, 4: 684-696.
Shen J, Haas L. 2004. Calculatine age and residence time in the tidal York River using three-dimensional model experiments. Estuarine, Coastal and Shelf Science, 61: 449-461.
Shen J, Wang H V. 2007. Determining the age of water and long-term transport timescale of the Chesapeake Bay. Estuarine, Coastal and Shelf Science, 74: 585-598.
Skogen M D, Svendsen E, Berntsen J, et al. 1995. Modelling the primary production in the North Sea using a coupled 3-demensional physical chemical biological ocean model. Estuarine, Coastal and Shelf Science, 41: 545-565.
Smagorinsky J. 1963. General circulation experiments with the primitive equations I. The basic experiment. Monthly Weather Review, 91: 99-165.
Steel J H. 1962. Environmental control of phytosynthesis in the sea. Limnol Oceanogr, 7: 137-150.
Stock C A, McGillicuddy D J, Solow A R, et al. 2005. Evaluating hypotheses for the initiation and development of Alexandrium fundyense blooms in the western Gulf of Maine using a coupled physical-biological model. Deep-Sea Research II, 52: 2715-2744.
Takeoka H. 1984a. Fundamental concepts of exchange and transport time scales in a coastal sea. Continental Shelf Research, 3(3): 311-326.
Takeoka H. 1984b. Exchange and transport time scales in the Seto Inland Sea. Continental Shelf Research, 3(4): 327-341.
Tee T K. 1976. Tide-induced residual current: A 2-D nonlinear numerical model, J. Mar. Res., 31: 603.
UNESCO. 1981. Tenth report of the joint panel on oceanographic tables and standards. UNESCO Technical Papers in Marine Science No. 36, UNESCO, Paris.
Unoki S, Okazaki M, Nagashima H. 1980. The circulation and oceanic condition in Tokyo Bay. Report of Physical Oceanography Laboratory in Physical-Chemical Institute, No.4.
Van den Berg A J, Ridderinkhof H, Riegman R, et al. 1996. Influence of variability in transport on phytoplankton biomass and composition in the southern North Sea: a modeling approach. Continent Shelf Res., 16(7): 907-931.
Woods J D. 2005. The Lagrangian Ensemble metamodel for simulating plankton ecosystems. Progress in Oceanography, 67: 84-159.
Woods J D, Perilli A, Barkmann W. 2005. Stability and predictability of a Virtual Plankton Ecosystem created by an individual-based model. Progress in Oceanography, 67: 43-83.
Yamanaka Y, Yoshie N, Fujii M, et al. 2004. An ecosystem model coupled with nitrogen–silicon–carbon cycles applied to Station A7 in the Northwestern Pacific. Journal of Oceanography, 60(2): 227-241.
Yanagi T, Yamamoto T, Koizumi Y, et al. 1995. A numerical simulation of red tide formation. Journal of Marine Systems, 6: 269-285.
Yuan D, Lin B, Falconer R. 2007. A modelling study of residence time in a macro-tidal estuary. Estuarine, Coastal and Shelf Science, 71: 401-411.
Zimmerman J. 1976. Mixing and flushing of tidal embayments in the Western Dutch Wadden Sea, Part I: Distribution of salinity and calculation of mixing time scales. Netherlands Journal of Sea Research, 10: 149-191.