Argentine Canola (Brassica napus L.) is an economically successful crop on the Canadian Prairies. The 1999 growing season had a record area seeded of 5,598,700 hectares, declining slightly to 4,894,600 hectares in 2000. Since 1997. canola has been ranked as Manitoba's most valuable agricultural commodity. Although canola is an important contributor to the Canadian economy, little research has been conducted at the field level to determine how crop phenological stage and ground cover respond to weather variables such as temperature. Such basic agronomic knowledge is essential for successful agrometeorological modeling. The objectives of this project were to develop a methodology for estimating phenological development and fractional leaf area of canola using temperature, and to further evaluate the accuracy of top-zone (10 cm depth) soil moisture modeled from a Canola Phenology and Water-Use Model. Five test sites within Agro-Manitoba were used during the 1999 growing season, while three test sites were used in 2000. Weekly field observations were conducted during the growing season to determine the phenological stage of the crop, the amount of ground cover, and near surface soil moisture. Daily maximum and minimum temperatures and rainfall data were obtained from the nearest Environment Canada weather station. The fungal infection Sclerotinia (Sclerotinia sclerotiorum (Lib.) de Bary) costs prairie canola producers approximately $260 million annually as a result of yield loss and management techniques requiring expensive fungicide applications. The current model for predicting sclerotinia stem rot on the Canadian Prairies estimates the risk of infection based on crop phenological stage and soil moisture estimates derived from the Raddatz model. However, the current model is regional in nature and is limited because crop stage is estimated using a simple growing degree-day (GDD) above 5oC, while soil moisture is modeled using a coupled atmosphere-crop-soil agrometeorological model, which utilizes the simple GDD relationship to estimate fractional leaf area. This study determined that a GDD above 5oC was an inadequate estimator of crop phenology and that the P-Days system, utilizing base, optimal, and maximum temperature thresholds of 5, 17, and 30oC, respectively was an overall better estimator of crop phenology. Further results indicated that fractional leaf area was better estimated from P-Days(5,17,30) than from GDD used in the original model. Observed and modeled top-zone soil moisture values were compared. The relatively low R2 of 0.60 suggests that poor estimates of soil moisture was linked to the use of off-site precipitation data and perhaps linked to the inaccurate estimation of fractional leaf area from GDD above 5oC.