环境遥感

东海初级生产力遥感反演及其时空演化机制

展开
  • 1. 中国科学院地理科学与资源研究所,北京 100101;
    2. 中国水产科学院研究院,北京 100039
李国胜 (1963-), 男, 研究员, 博士生导师, 主要从事海陆相互作用及海洋环境遥感与GIS模拟研究。E-mail:ligs@igsnrr.ac.cn

收稿日期: 2003-01-09

  修回日期: 2003-03-05

  网络出版日期: 2003-07-25

基金资助

国家“九五”科技专项资助项目 (HY126-06-04-04)

Estimation of Ocean Primary Productivity by Remote Sensing and Introduction to Spatio-temporal Variation Mechanism for the East China Sea

Expand
  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Chinese Academy of Fishery Sciences, Beijing 100039, China

Received date: 2003-01-09

  Revised date: 2003-03-05

  Online published: 2003-07-25

Supported by

The Key Project for the National Ninth Five-Year Plan, No.HY126-06-04-04

摘要

针对基于SeaWiFS的海洋叶绿素浓度SeaBAM模型反演结果,在中国东海海域分别建立了Ⅰ、Ⅱ类水体的修订模式,反演计算获得了我国东海海域1998年各月叶绿素浓度的分布,并根据真光层深度与海水漫射衰减系数之间的关系,利用SeaWiFS的K490遥感资料反演获得的1998年各月真光层深度的分布,在VGPM模型支持下,反演计算获得了中国东海海域1998年的逐月初级生产力时空分布以及全年累积初级生产力分布状况。对东海海域海洋初级生产力逐月时空变化特征及其影响机制的初步研究结果表明,整个东海海域初级生产力的逐月变化具有明显的双峰特征,表现为冬季最低,春季迅速上升达到最高,夏季略有下降,秋季又略有回升。海域初级生产力日平均值为560.03 mg/m2/d,远高于世界亚热带海域平均状况。年平均值为236.95 g/m2/a。控制东海海洋初级生产力时空变化的主要因素可能包括叶绿素浓度分布、温度条件、长江冲淡水变化,以及真光层深度、海流锋面过程等,不同海区初级生产力时空变化的主要控制因素有所不同。

本文引用格式

李国胜,王芳,梁强,李继龙 . 东海初级生产力遥感反演及其时空演化机制[J]. 地理学报, 2003 , 58(4) : 483 -493 . DOI: 10.11821/xb200304001

Abstract

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for Case-I and Case-II water respectively. The monthly chlorophyll distributions in the East China Sea in 1998 have been obtained from this improved model on the calculation results of SeaBAM. The relative coefficient analysis between the ship-measured chlorophyll concentration and the calculation results of the improved model shows that the relative coefficient is 0.5752, which means they have obvious dependence. The fact that the coefficient of linear regressive equation is nearly 1 confirms their dependence further. Therefore, it can be said for certain that the improved model is suitable for calculation of the chlorophyll distribution for Case-I and Case-II water in the East China Sea. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With the data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distribution in the East China Sea in 1998 have been obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a, which is fit with the primary productivity obtained from the investigation in the Kuroshio zone in the East China Sea. The research on the seasonal variety mechanism of primary productivity shows that several elements that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River dilute water variety, the euphotic depth and ocean current variety etc. But the main influencing elements may be different in each local sea area.

参考文献


[1] English D C, M J Perry. Estimating biomass loss in the upper ocean using satellite imagery. EOS, 1987, 68: 1703.

[2] Eppley R W, Stewart E, Abbott M R. Estimating ocean primary production from satellite chlorophyll, introduction to regional differences and statistics for the southern California bight. J. Plankton Res., 1985, 7(1): 57-70.

[3] Michael J B, Paul G F. A consumer's guide to phytoplankton primary productivity models. Limnol. Oceanogr., 1997, 42(7): 1479-1491.

[4] Morel A, Berthon J F. Surface pigments, algal biomass profiles and potential production of the euphotic layer: relationships reinvestigated in view of remote-sensing applications. Limnol. Oceanogr., 1989, 34: 1545-1562.

[5] Ryther J H R, C S Yentsch. The estimation of phytoplankton production in the ocean from cholorophyll and light data. Limnol. Oceanogr., 1957, 2: 281-286.

[6] Smith R C, Eppley R W, Baker K S. Correlation of primary production as measured aboard ship in southern California coastal water and as estimated from satellite chlorophyll images. Marine Biology, 1982, 66: 281-288.

[7] Cadee G C. Primary production of the Guyana Coast. Netherlands Journal of Sea Research, 1975, 9(1): 126-143.

[8] Talling J F. The phytoplankton population as a compound photosynthetic system. New Phytol., 1957, 56: 133-149.

[9] Rodhe W. Standard correlation between pelagic photosynthesis and light. In: C R Goldman (ed.), Primary Productivity in Aquatic Environments. Berkeley: University of California Press, 1965, 365-381.

[10] Platt T. Primary production of the ocean water column as a function of surface light intensity: algorithms for remote sensing. Deep-Sea Res., 1986, 33: 149-163.

[11] Ryther J H, C S Yentsch. The estimation of phytoplankton production in the ocean from chlorophyll and light data. Limnol. Oceanog., 1957, 2: 281-286.

[12] Platt T, S Sathyendranath. Estimators of primary production for interpretation of remotely sensed data on ocean color. J. Geophys. Res., 1993, 98: 14561-14576.

[13] Behrenfeld M J, P G Falkowski. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnol. Oceanogr., 1997, 42: 1-20.

[14] Cao Wenxi. Marine optics monitoring technology at transitional century. In: Proceedings of Marine Monitoring High-tech Development Strategy at the Beginning of 21st Century Symposium, 2000. 127-143.
[曹文熙. 世纪之交的海洋光学监测技术. 见: 21世纪初海洋监测高新技术发展战略研讨会论文集, 2000. 127-143.]

[15] Austin R W, T J Petzold. The determination of the diffuse attenuation coefficient of sea water using the Coastal Zone Color Scanner. In: J F R Gower (ed.), Oceanography from Space. New York: Plenum Press, 1981. 239-256.

[16] Li Guosheng, Liang Qiang, Li Bailiang. Seasonal changes of the euphotic depth in the East China Sea and its dynamic mechanism. Progress in Natural Science, 2003, 13(1): 90-94.
[李国胜, 梁强, 李柏良. 东海真光层深度的遥感反演及其季节性变化机制. 自然科学进展, 2003, 13(1): 90-94.]

[17] Platt T, Sathyendranath S. Oceanic primary production: estimation by remote sensing at local and regional scales. Science, 1988, 241: 1613-1620.

[18] Gordon H R, Wang M. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. Applied Optics, 1994, 33(3): 443-452.

[19] O'Reilly J E, Maritorena S, Mitchell B G et al. Ocean color chlorophyll algorithms for SeaWiFS. Journal of Geophysical Research-Oceans, 1998, 103(C11): 24937-24953.

[20] Tassan S. An improved in-water algorithms for the determination from Thematic Mapper data in coastal waters. Int. J Remote Sens, 1993, 14: 1221-1229.

[21] Amy MacFadyen. Modeling Primary Productivity from Satellite Derived Chlorophyll in the Monterey Bay Region. 1999 Intern Papers of The Monterey Bay Aquarium Research Institute (MBARI). (http://www.mbari.org/education /internship/99interns/1999_papers.html)

[22] Fei Zunle. The distribution of chlorophyll-a and primary production in Kuroshio district of East China Sea. In: Thesis Collection of Kuroshio Investigation and Research (Vol.1). Beijing: China Ocean Press, 1987. 256-265.
[费尊乐. 东海黑潮区叶绿素a和初级生产力的分布特征. 见: 黑潮调查研究论文集. 北京: 海洋出版社, 1987. 256-266.]

[23] Ning Xiuren. Primary productivity and evaluation of fishery in the Bohai Sea, the Yellow Sea and the East China Sea. Acta Oceanologica Sinica, 1995, 17(3): 72-84.
[宁修仁. 渤黄东海初级生产力和潜在渔业生产量的评估. 海洋学报, 1995, 17(3): 72-84.]

[24] Liu Baoyin. Estimation of primary productivity in winter in the Yellow Sea and the Bohai Sea by using remote sensing information. J. Fish. China, 1984, 8(3): 227-234.
[刘宝银. 应用航天遥感信息对黄、渤海冬季初级生产力的估算. 水产学报, 1984, 8(3): 227-234.]

[25] Lu Ruihua. The fluctuations of primary productivity in the Bohai Sea waters over ten years. J of Oceanography of Huanghai & Bohai Seas, 1999, 17(3): 80-86.
[吕瑞华. 渤海水域初级生产力10年间的变化. 黄渤海海洋, 1999, 17(3): 80-86.]

[26] Lu Peiding. Estimation of primary productivity and distribution of chlorophyll-a in the Bohai Sea. Acta Oceanologica Sinica, 1984, 6(1): 90-98.
[吕培顶. 渤海水域叶绿素a的分布及初级生产力的估算. 海洋学报, 1984, 6(1): 90-98.]

[27] Zhu Mingyuan, Mao Xinghua, Lu Ruihua et al. Chlorophyall-a and primary productivity in the Yellow Sea. Journal of Oceanography of Huanghai & Bohai Seas, 1993, 11(3): 38-51.
[朱明远, 毛兴华, 吕瑞华 等. 黄海海区的叶绿素a和初级生产力. 黄渤海海洋, 1993, 11(3): 38-51.]

[28] Guo Yujie, Pan Youlian. Primary productivity research in the Yangtze River Estuary. Stud. Mar. Sin., 1992, 33: 191-199.
[郭玉洁, 潘友联. 长江口区初级生产力的研究. 海洋科学集刊, 1992, 33: 191-199.]

文章导航

/