Improved seasonal prediction of harmful algal blooms in Lake Erie using large-scale climate indices

Abstract

A machine learning approach based on nutrient loading observations and physical large scale climate indices improves early seasonal prediction of harmful algal bloom activity between July and October in Lake Erie, which can help local fisheries management.