Operational Coupled Modelling to Assess Water Quality in Lake Watersheds in Upstate New York

Abstract

Under the auspices of The Jefferson Project at Lake George, a collaborative effort between IBM Research, Rensselaer Polytechnic Institute and The FUND for Lake George, we have developed an integrated modelling and observing system for the atmospheric, hydrological, hydrodynamic and ecological aspects of lakes and their surrounding watersheds. The initial testbed of this capability was started almost six years ago at Lake George, which is located in the Adirondack State Park region of upstate New York, about 350 km north of New York City. It is a glacial, oligotrophic water body of unusually high clarity, which has been experiencing ecological changes in recent years with the influx of invasive species and increasing levels of salt (NaCl) from road de-icing agents as well as nutrient loading from storm water runoff, and the accompanying deterioration of water quality. These changes have been observed through longitudinal studies in the region over the last few decades. This first testbed includes real-time access to over 500 sensors that support adaptive sampling driven by forecasted conditions from the models. These data are used for model verification, and to improve model initial conditions via data assimilation. To enable data sharing and software reuse, community data models have been adopted, which also drive geometric modelling to enable fixed and interactive visualizations. The modelling starts with numerical weather prediction to 333m horizontal resolution for forcing lake circulation and runoff models using the community WRF-ARW model. To address hydrological forcing of the lake, the community WRF-Hydro model is used, employing gridded stream routing at 41m resolution. The model has been extended for the transport of dissolved salt. For lake circulation, a community hydrodynamic model, SUNTANS, has been deployed with variable horizontal resolution from ~27m to ~70m. It forces a simple ecological model, which considers nutrients, phytoplankton, zooplankton, small and large detritus, and oxygen to evaluate relative growth of phyto- and zoo-plankton. Over the last two years, these capabilities have been extended to two additional watersheds in New York State, particularly to evaluate signatures for harmful algal blooms. These two lakes are Skaneateles in the Finger Lakes region and Chautauqua in western New York near Lake Erie. We will present an overview of each of these models along with the results to date, including the model coupling and computing infrastructure required for operations. We will also discuss the automation for the coupled execution, including monitoring, visualization and validation. In addition, we will outline recommendations for future work.