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The winter weather severity plays a crucial role in determining the resources required for winter maintenance activities. This study utilized nonlinear models to examine the relationship between winter weather variables (temperature, wind speed, and snowfall) and winter maintenance expenditures (labor, material, and equipment) based on data from the state of Illinois. The data were collected and aggregated by year and district to align with the expenditure data, and the state was divided into three climatic zones, with separate models developed for each. The ROUT method was employed to identify and eliminate outliers before conducting nonlinear modelling. The best-fitting model was selected using cross-validation and R2 evaluation. The results demonstrate that the chosen nonlinear models effectively depict the connection between winter weather and winter maintenance expenses. These findings can aid agencies in efficiently allocating resources for winter maintenance. [ABSTRACT FROM AUTHOR]

Abstract A relationship between winter weather and survival of northern ungulates has long been established, yet the possible roles of biological (e.g., nutritional status) and environmental (e.g., weather) conditions make it important to determine which potential limiting factors are most influential. Our objective was to examine the potential effects of individual (body mass and age) and extrinsic (winter severity and snowmelt conditions) factors on the magnitude and timing of mortality for adult (>2.5 years old) female white‐tailed deer (Odocoileus virginianus [Zimmerman, 1780]) during February–May in the Upper Peninsula of Michigan, USA. One hundred and fifty deer were captured and monitored during 2009–2015 in two areas with varying snowfall. February–May survival ranged from 0.24 to 0.89 (mean = 0.69) across years. Mortality risk increased 1.9% with each unit increase in cumulative winter severity index, decreased 8.2% with each cumulative snow‐free day, and decreased 4.3% with each kg increase in body mass. Age and weekly snow depth did not influence weekly deer survival. Predation, primarily from coyote (Canis latrans [Say, 1823]) and wolves (Canis lupus [L., 1758]), accounted for 78% of known‐cause mortalities. Our results suggest that cumulative winter severity, and possibly to a lesser degree deer condition entering winter, impacted deer winter survival. However, the timing of spring snowmelt appeared to be the most influential factor determining late‐winter mortality of deer in our study. This supports the hypothesis that nutrition and energetic demands from weather conditions are both important to northern ungulate winter ecology. Under this model, a delay of several weeks in the timing of spring snowmelt could exert a large influence on deer survival, resulting in a survival bottleneck.

A relationship between winter weather and survival of northern ungulates has long been established, yet the possible roles of biological (e.g., nutritional status) and environmental (e.g., weather) conditions make it important to determine which potential limiting factors are most influential.Our objective was to examine the potential effects of individual (body mass and age) and extrinsic (winter severity and snowmelt conditions) factors on the magnitude and timing of mortality for adult (>2.5 years old) female white‐tailed deer (Odocoileus virginianus [Zimmerman, 1780]) during February–May in the Upper Peninsula of Michigan, USA.One hundred and fifty deer were captured and monitored during 2009–2015 in two areas with varying snowfall. February–May survival ranged from 0.24 to 0.89 (mean = 0.69) across years. Mortality risk increased 1.9% with each unit increase in cumulative winter severity index, decreased 8.2% with each cumulative snow‐free day, and decreased 4.3% with each kg increase in body mass. Age and weekly snow depth did not influence weekly deer survival. Predation, primarily from coyote (Canis latrans [Say, 1823]) and wolves (Canis lupus [L., 1758]), accounted for 78% of known‐cause mortalities.Our results suggest that cumulative winter severity, and possibly to a lesser degree deer condition entering winter, impacted deer winter survival. However, the timing of spring snowmelt appeared to be the most influential factor determining late‐winter mortality of deer in our study. This supports the hypothesis that nutrition and energetic demands from weather conditions are both important to northern ungulate winter ecology. Under this model, a delay of several weeks in the timing of spring snowmelt could exert a large influence on deer survival, resulting in a survival bottleneck. [ABSTRACT FROM AUTHOR]

Abstract Severe weather conditions, especially snow and ice during the winter season, threaten surface transportation nationwide and impact roadway safety and mobility. In particular, snow and ice decrease pavement friction and vehicle maneuverability, causing slower speeds, reducing roadway capacity, and increasing crash risk. These stressors make road maintenance during winter a pressing concern. The annual cost of winter highway maintenance in the United States is approximately $2.3 billion; however, evaluating the performance of such maintenance activities is difficult. To address this difficulty, the storm's severity should be standardized to measure performance against storm severity. Studies have been conducted to develop winter severity indices that can measure the difficulty in maintaining the targeted level of service due to storms in North America. Given the diverse approaches catalogued within these studies, there is a critical need for a comprehensive and organized literature synthesis to summarize existing approaches and to provide guidance for future winter severity index–development. To address this objective, this study investigated existing winter weather severity indices and classified the indices into different groups based on their development process and their similarities. In total, 19 winter severity indices were identified and sorted into seven groups. Subsequently, the key meteorological variables (i.e., temperature, snow, wind, and freezing rain) that have been used by other transportation agencies to develop winter severity indices were identified and explained in detail. Finally, the relevance of previous winter severity indices to future winter severity index–development was discussed and meteorological variables that can potentially be incorporated into the model were identified. This literature synthesis consolidates the current knowledge regarding winter severity indices and provides future guidance for developing an effective and reliable winter severity index. Highlights • Winter severity indices should be reproduceable and transferrable. • Winter severity indices should be designed for local needs and environmental variability. • Temperature and snowfall are the most common weather variables considered. • Approximately half of all states use some type of winter severity index. • Most winter severity indices are computed seasonally and regionally. [ABSTRACT FROM AUTHOR]

Snow removal and ice control are critical to the safe and efficient use of roadways in much of the world. Tools that help road authorities plan for, assess, and communicate about winter maintenance activities are increasingly being sought. Weather indices that rate the severity of winter conditions in a given period at a particular location are one subset of such tools. Although several winter severity indices have been developed, many of these are complex and of limited practical use for road authorities. In this research, an approach for developing a simple-touse, locally calibrated winter severity index (WSI) is outlined. The approach relies primarily on mathematical optimization but is flexible enough to allow expert knowledge to be incorporated. This approach is used in developing a WSI for the provincial highway system of the province of Alberta, Canada. The WSI assigns each day a weather score based on seven weather attributes and one seasonal adjustment factor. By using a classification and regression approach, the eight components are based on attribute-specific thresholds that then trigger a score. These daily scores are aggregated to the 14-day period and are correlated to maintenance activities. The WSI for Alberta highways has strong fit with maintenance activity that occurred, when measured as vehicle hours. At the 14-day level, the R2 values for vehicle hours vary from 0.776 to 0.936 for eight contract areas, and when the data are aggregated over space or time, the fit improves further. This research illustrates how site-specific WSIs can be developed for road authorities through the use of optimization that alters the weather attribute thresholds and scores, reflecting the specific maintenance regimes in that location. [ABSTRACT FROM AUTHOR]