Detecting subsurface phytoplankton layer in Qiandao Lake using shipborne lidar.

Area of Science:

• Limnology
• Optical Oceanography
• Remote Sensing

Background:

• Qiandao Lake exhibits thermal stratification during summer, necessitating study of its aquatic ecosystem structure.
• Traditional in-situ methods for observing vertical water quality and phytoplankton are time-consuming and labor-intensive.
• Lidar technology, while advanced in oceanic studies, remains underutilized in inland water research, particularly for subsurface plankton detection.

Purpose of the Study:

• To investigate the applicability of lidar for identifying subsurface phytoplankton layers in Qiandao Lake.
• To introduce a novel, rapid method for detecting phytoplankton layers using lidar data.
• To assess lidar's potential as a monitoring tool for inland water stratification.

Main Methods:

• Deployment of lidar technology for profiling water bodies.
• Development and application of a simple, fast phytoplankton layer detection algorithm.
• Comparison of lidar-derived data with in-situ measurements of chlorophyll and phycocyanin.

Main Results:

• A strong correlation was observed between lidar-detected layers and in-situ measurements of the subsurface chlorophyll maximum layer (SCML) and phycocyanin maximum layer.
• The developed lidar-based detection method proved effective in identifying subsurface phytoplankton layers.
• Primary findings confirm lidar's utility for subsurface phytoplankton layer detection in this inland lake environment.

Conclusions:

• Lidar technology is a viable and effective tool for detecting subsurface phytoplankton layers in thermally stratified inland lakes.
• The introduced detection method provides a fast and efficient approach for phytoplankton layer identification.
• Lidar monitoring offers a promising advancement for studying aquatic ecosystem structures and thermal stratification in inland waters.