Agriculture is a critical sector of the US economy. Both weather and soil conditions are important factors in the agricultural decision-making process. Unfortunately, at this time, both the weather and the soil predictions necessary to adequately model the agricultural environment are lacking. By combining the weather forecast data from the NCAR DICast™ system with the Land-Surface Modeling system called the High-Resolution Land Data Assimilation System (HRLDAS) to generate high resolution soil temperature and moisture forecasts that in turn drive agriculture-specific models, weather forecasts can be used in agricultural applications such as pest and crop models. After the research and development efforts are completed, the output from this new land surface modeling system will be provided to over 60,000 agricultural users via the DTN/Meteorlogix Decision Support System, DTN Online. The overall system, results to date, and plans for the future are discussed.