To identify the most intense events for each stream, we derived an equation that would compute a flow index, which would put each event on a level playing field for comparison. When considering just largest single day rises, we acknowledged 24-hour events which had a 50% fall in flow relative to the rise during the previous 24 hours. This isolates the high-rate events that we are most interested in. One issue we quickly discovered was the issue created by snowmelt events. Often a smaller rain event could show up as a massive flood in a small basin if the rain was caused by a system that simultaneously melted the snowpack. In order to purify the record, we only considered storms from April through November and checked each event in those two end months to ensure their validity.
Once we compiled all the events for each station, we ranked the top forty events for each to facilitate our analysis. Assuming there are forty events in forty years, on average, a top forty event should happen each year in each stream. However, this is not what we found. There are some years that are much wetter than those around them, and a couple of years have effectively zero events. It is presumable that year-to-year variability will occur. However, after separating streams into groups by urban characteristics, the variability differs between groups. Further analysis of why events happen when and where they do could lead to correlation with other atmospheric phenomena.