A project to improve the understanding and management of dangerous nearshore currents (DNCs) in the Great Lakes. By applying an object-based method for automated rip channel detection, characterization of DNCs using techniques validated under a previous CZM-funded project will be expanded from State Park beaches to all of Michigan’s Lakes Superior and Michigan coastlines. That map product, along with the data collected in the Great Lakes Current Incident Database on the conditions under which current-related incidents have occurred, will be used to formulate a new, experimental predictive algorithm for forecasting DNCs based on Great Lakes Coastal Forecasting System forecast models. Most importantly, an online geospatial decision support tool will be created that combines MTU’s nearshore current data and forecast with disparate existing resources and datasets to support local beach and coastal managers in making effective decisions to minimize coastal hazards.