Estimates of flood skew are inaccurate and the inaccuracy influences flood discharge estimates using the log Pearson Type III distribution. The skew map is commonly used despite the fact that it's inaccurate, lacks a conceptual basis, and does not reflect watershed processes. Attempts at regionalizing station skew using regression analysis have only provided marginal improvements in accuracy, possibly because the predictor variables are not good indicators of the physical characteristics that influence the variation in skewness. Therefore, a new approach is needed to improve skew estimates. This research explored the potential of using a distributed model that includes predictor variables that better represent watershed storage. The results showed that watershed storage is the main factor that affects flood skew, and that increases in watershed storage causes flood skews to be algebraically more negative.