Journal of Cold Regions Engineering

The Federal Highway Administration (FHwA) method and frost-tube measurements are used in Wisconsin to determine the timing and duration of spring load restrictions. In both methods, depth of freeze or thaw is used to determine when to apply load restrictions and to determine their duration. Average daily air temperatures are used in the FHwA method to predict the start and end of freeze and/or thaw. Frost tubes are used to directly determine depth of freeze and/or thaw. An analysis is conducted to compare these two methods using air-temperature data (for the FHwA method) and frost-tube data obtained in Wisconsin. The analysis shows that differences exist between predicted (FHwA method) and measured (frost tubes) freeze and thaw conditions. The FHwA method is early (unconservative) in predicting the start of freeze and late (unconservative) in predicting the start of thaw. However, the method is late (conservative) when used to predict the end of thaw. A case history is also presented to compare the two methods.

The air-freezing index (AFI) is a measure of the combined magnitude and duration of air temperatures above and below freezing for a winter season. The 100-y return period of the AFI has been found to be an indicator of the amount of insulation required to protect a building foundation from frost heave and has been used to develop frost-protected shallow foundation (FPSF) design criteria. FPSF has recently been accepted as a change to U.S. building codes with resulting annual construction savings estimated at $300 million nationally for new residential homes. Previous work has found that different probability distributions can produce significantly different estimates of the 100-y return period of the AFI and thus the amount of insulation required in FPSF. To determine which of several probability distributions best fit the AFI sample data, a goodness-of-fit test and graphical analyses have been applied to locations which have long-term and high-quality climate records. Results indicate that the Weibull probability distribution is the best choice for estimating 100-y return periods of the AFI for all U.S. climate regimes.

Evaluation of alternatives to reduce the severity of ice-jam flooding requires the development of probability distributions for ice-affected stage at nongauged locations along a river reach. Difficulties arise as the ice-affected peak stage is not only a function of discharge and channel hydraulic properties, as is the case for the open water period, but is also influenced by the location, extent, thickness, and roughness of ice jams. This paper presents a new method for estimating winter peak stage along a river reach by dividing the record of winter peak discharges into distinct ice-jam and no–ice-jam populations. Rating curves may then be developed for each population using gradually varied-flow analysis and existing equilibrium ice-jam theory. Stage-probability distributions for the ice jam and no–ice-jam populations may then be combined into a single stage-frequency relationship representing the entire winter period. A case study is presented, in which the method is used to develop probability distributions for the annual maximum stage along the Winooski River at Montpelier, Vt. Viewed in the context of the historical record, the method yields reasonable results.