During adverse winter weather events, maintenance managers are presented with several challenges in terms of controlling snow and ice on pavement surfaces. In order to maintain an optimal level of service along a roadway, winter maintenance practitioners are required to make effective decisions regarding treatment strategies (e.g., types, timing, rates, and location), as these decisions have considerable impact on roadway safety and efficiency. Moreover, poor decisions can have unfavorable economic and environmental consequences. In 2001, the Federal Highway Administration (FHWA) initiated a program in an attempt to address the road weather related challenges associated with winter maintenance operations. Through this program, the Maintenance Decision Support System (MDSS) was created. This system is designed to provide winter maintenance managers and crews with objective guidance regarding the most appropriate treatment strategies to employ during adverse weather events.

Based on its success, it is anticipated that the MDSS software will provide a framework for extending current road weather decision support capabilities to other segments of roadway operations such as traffic management and maintenance beyond snow and ice control. A key requirement within all sectors of roadway operations is the need for accurate, timely diagnoses and forecasts of the state of the roadway. In the past, the MDSS has utilized SNTHERM, a one-dimensional mass and energy balance model developed by the U.S. Army Cold Regions Research and Environmental Laboratory (CRREL), to support the forecasting of pavement temperatures and pavement conditions; however, this model is no longer supported, leading to the need to implement a new pavement condition model. Through research and examination of publicly available models, a Canadian model called Model of the Environment and Temperature of the Roads (METRo) was identified as a leading replacement. METRo is a physically-based numerical model developed by Environment Canada and run operationally since the late 90s.

This paper describes the use of METRo as a road condition forecast model within the MDSS framework, as well as its potential application to other roadway decision support tools and modules. Discussion topics include, but are not limited to, the challenges associated with its implementation, the benefits of using the model as part of a decision support application, and a preliminary assessment of its performance under disparate road weather conditions.