NUMERICAL OPTIMIZATION OF READILY ACQUIRED DATA TO DETERMINE MAXIMUM FROST DEPTH AND FREEZE THAW FREQUENCY

Maximum frost depth (MFD) and freeze/thaw frequency (FTF) in soils are important frost processes that affect surface topography and infrastructure. Management or infrastructure decisions that require a MFD in high altitude regions of the Southwestern United States are based on little or no scientific data. In addition, a higher FTF has been shown to increase surface erosion and frost processes in other regions of the United States. MFD and FTF should be relatively easy to acquire using readily available climate data and simple field measurements. These data coupled with predictive modeling make a cost-and time-efficient method for predicting MFD and FTF. To characterize the MFD and FTF at different depths as a proxy for frost heave of unexploded ordnance in Bellemont, Arizona, a field site was instrumented with soil temperature probes and data loggers from January 2004 through May 2005. Soil texture characteristics were determined to fully calibrate the Simultaneous Heat and Water (SHAW) transfer model used to predict soil temperature, MFD and FTF. Three scenarios were studied to determine how use of the SHAW model and readily available data were able to simulate field observed MFD and FTF. These objectives were: (1) using only readily available climate and soil data, (2) using readily available climate and soil data with a soil temperature measurement at 5cm, and (3) using readily available climate and soil data with soil temperature measurements at depths of 5 and 100 cm. Observed MFD and FTF could not be simulated using the readily available data suggested in the above scenarios. The model tended to simulate less freeze/thaw events and longer frozen periods compared to the observed frequency at all depths of 15, 50, and 100 cm. Site specific data were required to adequately determine MFD and FTF.