An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie

Abstract

Abstract. For enhanced public safety and water resource management, a three-dimensional operational lake hydrodynamic forecasting system, COASTLINES (Canadian cOASTal and Lake forecastINg modEl System), was developed. The modeling system is built upon the three-dimensional Aquatic Ecosystem Model (AEM3D) model, with predictive simulation capabilities developed and tested for a large lake (i.e., Lake Erie). The open-access workflow derives model forcing, code execution, post-processing, and web-based visualization of the model outputs, including water level elevations and temperatures, in near-real time. COASTLINES also generates 240 h predictions using atmospheric forcing from 15 and 25 km horizontal-resolution operational meteorological products from the Environment Canada Global Deterministic Forecast System (GDPS). Simulated water levels were validated against observations from six gauge stations, with model error increasing with forecast horizon. Satellite images and lake buoys were used to validate forecast lake surface temperature and the water column thermal stratification. The forecast lake surface temperature is as accurate as hindcasts, with a root-mean-square deviation <2 ∘C. COASTLINES predicted storm surges and up-/downwelling events that are important for coastal flooding and drinking water/fishery management, respectively. Model forecasts are available in real time at https://coastlines.engineering.queensu.ca/ (last access: January 2022​​​​​​​). This study provides an example of the successful development of an operational forecasting workflow, entirely driven by open-access data, that may be easily adapted to simulate aquatic systems or to drive other computational models, as required for management and public safety.