Autonomous detection and sampling of water types and fronts in a coastal upwelling system by an autonomous underwater vehicle

Abstract

Coastal upwelling occurs under the combined effect of wind stress and Earth's rotation. The nutrients carried up by upwelling have great impact on primary production and fisheries. For using autonomous underwater vehicles (AUVs) to investigate complex coastal upwelling ecosystems, we have developed algorithms for an AUV to autonomously distinguish between upwelling and stratified water columns based on the vertical temperature difference between shallow and deep depths, and to accurately detect an upwelling front based on the horizontal gradient of the vertical temperature difference in the water column. During a June 2011 experiment in Monterey Bay, California, the Dorado AUV flew on a transect from an upwelling shadow region (stratified water column), through an upwelling front, and into an upwelling water column. Running our algorithms, the AUV successfully classified the three distinct water types, accurately located the narrow front, and acquired targeted water samples from the three water types. Molecular analysis of the AUV‐acquired water samples shows that mussels, calanoid copepods, and podoplean copepods were most abundant in the upwelling shadow region and nonexistent in the upwelling water column. Calanoid copepods were moderately abundant in the water samples collected from the upwelling front. These results are largely consistent with previous findings from zooplankton population surveys conducted with the Dorado AUV in Monterey Bay in 2009. The novel detecting and targeted sampling capabilities permit an AUV to autonomously conduct “surgical sampling” of a complex marine ecosystem.