Evaluation of snowmelt for implementation into the Minnesota Feedlot Annualized Runoff Model

Abstract

The Minnesota Feedlot Annualized Runoff Model (MinnFARM) was designed by University of Minnesota, the University of Minnesota Extension Office and the Minnesota Pollution Control Agency (MPCA) to evaluate pollution potential to waters of the state created by surface runoff leaving an animal feedlot. State and Federal Agencies use MinnFarm results to determine compliance and rank feedlots on a standardized scale. The goal of this study is to improve the snowmelt portion of the MinnFARM model utilizing obtainable data to account for regional variations that exist throughout the Minnesota. Refinement of the snowmelt portion of the MinnFARM model is required to increase the accuracy of the seasonal aspect of the potential nutrient load leaving a livestock open lot. Observed daily snowmelt depths were computed from the daily difference in snow-water-equivalent data provided by the National Weather Service for Marshall, St. Cloud and Rushford, MN. Corresponding climate data sets were obtained for these three sites. The reliability of the observed snowmelt depths was evaluated by examining the consistency in observed depths for large events measured at Marshall. The accuracy of the Degree-Day method, Restricted-Degree-Day method, Statistical Energy-Balance Approach and Process Based Energy-Balance Approach were compared in this study. The Restricted-Degree-Day method had the strongest correlation when compared the observed snowmelt data set.