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Distribution of Zooplankton by ADCP's Echo Intensity in the Coastal Water used Yellow Loess (다층 도플러 유속계(ADCP)를 이용한 황토 살포 해역의 플랑크톤 평가)

  • Park, Ju-Sam;Choo, Hyo-Sang;Moon, Sung-Ryong
    • Journal of the Korean Society of Marine Environment & Safety
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    • 제16권2호
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    • pp.141-151
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    • 2010
  • Harmful algal blooms (HABs), commonly known as red tides, are aquatic phenomena caused by the rapid growth and accumulation of certain microalgae, which can lead to marked discoloration of surface waters, and severe impacts on public health, commerce, and the environment. In South Korea, the red tides have been a serious and recurrent problem, especially along the south coast. Plenty of yellow loess was used to control an outbreak of the red tides for 15 years from 1996 until now. Yellow loess was almost sprayed in the vicinity of a large fish farming industry. In this research, the distribution characteristics and density distribution of zooplankton were investigated in autumn (Oct. 2008) and spring (Apr. 2009) using volume backscattering strength (SV) calculated by the zooplankton collected with north pacific standard (NORPAC) net and the echo intensity measured with ADCP at stations on the study area in the spraying ocean of yellow loess (SOYL), and the non-spraying ocean of yellow ocean (NOYL) by the red tide generating every year. The species number and the individuals per unit volume of the zooplankton collected in NOYL was high and it which was collected in SOYL was low. As a result of comparing the volume backscattering strength ($SV_c$) calculated by species and length of the zooplankton collected with NORPAC net with the volume backscattering strength ($SV_m$) calculated by the echo intensity measured with ADCP at stations on the study area, although $SV_c$ and $SV_m$ of NOYL were generally in agreement, $SV_m$ of SOYL was higher than $SV_c$ 4.3dB, i.e. ADCP is greatly influenced by suspended solid in SOYL. The horizontal distribution map of $SV_m$ at the study area in autumn (Oct. 2008) and spring (Apr. 2009) was drawn. $SV_m$ of SOYL is higher than NOYL and autumn is higher than spring. $SV_m$ can suppress the overestimate or underestimate of $SV_c$.