적조모형의 분류 및 성능평가 기법
Classification and Performance Evaluation Methods of an Algal Bloom Model
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초록
적조에 관한 관심이 고조되면서 적조모형 개발에 관한 연구가 활발하게 지속적으로 추진되어 다양한 적조모형이 개발·적용되고 있는 실정이다. 적조는 연안생태환경 및 양식어업에 직접적인 피해를 주며, 모형을 이용한적조 발생 및 이동양상의 정확한 예측결과는 사전 피해저감 대책수립 및 관리에 활용할 수 있기 때문에 모형의 예측 성능평가도 중요하다. 그러나 적조모형은 적조생물을 포함하는 생태모형 또는 환경생태모형이라는 유사한 용어가 명확한 구분 없이 사용되고 있어 혼동을 유발하고 있다. 각각의 모형은 유사한 용어를 사용한다 할지라도 모형의 개발 목표, 구조와 예측성능에서 차이가 나기 때문에 적절한 기준에 근거한 분류와 오차분석에 근거한 모형의성능평가가 요구된다. 따라서 본 연구에서는 다양한 적조 모형의 구조 및 요소모형을 고려한 분류기준을 제시하고, 분류된 적조모형의 구조를 고려한 장·단점 및 한계를 제시하고, 모형 활용과정에서 실질적으로 가장 중요한 정량적인 성능평가(오차평가) 기법을 제안한다. 모형의 성능평가는 모형의 보정 및 검정과정으로 분류하여 제시하였다. 제시된 기준이나 기법은 모형의 불확실성을 고려한 정책결정 및 대책수립, 환경관리에 기여할 것으로 판단된다.
Abstract
A number of algal bloom models (red-tide models) have been developed and applied to simulate the redtidegrowth and decline patterns as the interest on the phytoplankton blooms has been continuously increased. Thequantitative error analysis of the model is of great importance because the accurate prediction of the red-tideoccurrence and transport pattern can be used to setup the effective mitigations and counter-measures on the coastalecosystem, aquaculture and fisheries damages. The word “red-tide model” is widely used without any cleardefinitions and references. It makes the comparative evaluation of the ecological models difficult and confusable. Itis highly required to do the performance test of the red-tide models based on the suitable classification andappropriate error analysis because model structures are different even though the same/similar words (e.g., red-tide,algal bloom, phytoplankton growth, ecological or ecosystem models) are used. Thus, the references on the modelclassification are suggested and the advantage and disadvantage of the models are also suggested. The processes andmethods on the performance test (quantitative error analysis) are recommend to the practical use of the red-tidemodel in the coastal seas. It is suggested in each stage of the modeling procedures, such as verification, calibration,validation, and application steps. These suggested references and methods can be attributed to the effective/efficientmarine policy decision and the coastal ecosystem management plan setup considering the red-tide and/or ecologicalmodels uncertainty.
참고문헌 (27)
- Baretta, J. W., "The European regional seas ecosystem model, a complex marine ecosystem model", Netherlands Journal of Sea Research, 33(3, pp.4) (1995), 233~246
- Beck, M. B., "Uncertainty and Forecasting of Water Quality", pp.3~68 (1983)
- Blauw, A. N., "GEM: a general ecological model for estuaries and coastal waters", Hydrobiologia, 618, pp.175~198 (2009)
- Box, G. E. P., "Time Series Analysis, Forecasting and Control Sec. 1.3" (2008), John Wiley & Sons
- Rates, Constants, and Kinetics Formulations in Surface Water Quality Modeling, "Bowie, G. L.", EPA, ~, pp.Environmental Research Lab., EPA (1985), 600[DOI]
- Castellani, M., "A mass-balance pelagic ecosystem model with size-structured behaviourally adaptive zooplankton and fish", Ecological Modelling, 251, pp.54~63 (2013)
- 조범준, "화학적산소요구량의 총유기탄소 변환을 위한 이상자료의 탐지와 처리", 한국해안·해양공학회논문집, 26(4), pp.207~216 (2014), 한국해안,해양공학회[DOI]
- Dowd, M., "A sequential Monte Carlo approach for marine ecological prediction", Environmetrics, 17, pp.435~455 (2006)
- Edwards, A.M., "Oscillatory behaviour in a three-component plankton population model", Dynamics and Stability of Systems, 11(4), pp.347~370 (1996)
- Eykhoff, P., "System Identification, Parameter and State Estimation, Chap. 1" (1974), John Wiley & Sons
- Franks, P. J. S., "NPZ models of plankton dynamics: Their construction, coupling to physics, and application", Review, J. of Oceanography, 58, pp.379~387 (2002)
- Glover, D. M., "Modeling Methods for Marine Science" (2011), Cambridge University Press
- Hai, D-N, "Development of Phaeocystis globosa blooms in the upwelling water of the South Central coast of Viet Nam", J. of Marine Systems, 83(3-4), pp.253~262 (2010)
- Jorgensen, S.E, "Fundamentals of Ecological Modeling Chap. 2" (2001), Elsevier
- Kawamiya, M., "An ecological-physical coupled model applied to Station Para", J. of Oceanography, 51, pp.635~664 (1995)
- Kishi, M. J., "A review of the NEMURO and NEMURO.FISH models and their application to marine ecosystem investigations", Review, J. of Oceanography, 67, pp.3~16 (2011)
- Lee, D. I., "Coastal environmental assessment and management by ecological simulation in Yeoja Bay, Korea", Estuarine, Coastal and Shelf Science, 80, pp.495~508 (2008)
- Lenes, J. M., "Simulating cell death in the termination of Karenia brevis blooms: implications for predicting aerosol toxity vectors to humans", Marine Ecology Progress Series, 493, pp.71~81 (2013)
- Li, H., "Scaling and Uncertainty Analysis in Ecology:Methods and Applications", pp.45~66 (2006), Springer
- Mandal, S., "Modeling nutrient (dissolved inorganic nitrogen) and plankton dynamics at Sagar Island of Hooghly-Malta estuarine system", West Bengal, India, Natural Resource Modeling, 25(4), pp.629~652 (2012)
- Mann, K.H., "Dynamics of Marine Ecosystems, Biological-Physical Interactions in the Oceans" (2006), Blackwell Pub
- Martin, J.L., "Hydrodynamics and Transport for Water Quality Modeling, Part IV" (1999), Lewis Publishers
- National Fisheries Research and Development Institute, "Handbook of Marine Harmful Algal Blooms in Korean Waters", ~ (2002)
- Robson, B.J., "Three-dimensional modelling of a Microcystis bloom event in the Swan River estuary, Western Australia", Ecological Modeling, 174, pp.203~222 (2004)
- 손주원, "한국 연안수에서 총유기탄소 및 화학적 산소요구량 분포 특성", 바다, 8(3), pp.10~326 (2003), 한국해양학회
- Sun, K., "Nutrient-controlled growth of Skeletonema costatum: an applied model", Chinese Journal of Oceanology and Limnology, 32(3), pp.608~625 (2014)
- Velo-Suarez, L., "Application of a 3D Lagrangian model to explain the decline of a Dinophysis acuminita bloom in the Bay of Biscay", J. of Marine Systems, 83(3-4), pp.242~252 (2010)