A computerized technique was developed to identify storm runoff episodes an
d calculate storm discharges, storm loads, and storm average concentrations
for each event in datasets with up to 10,000 records. This technique was a
pplied to four watersheds within the Lake Erie drainage basin and identifie
d between 160 and 250 runoff events in each. Storm event loads and storm ev
ent mean concentrations were calculated for each runoff event for suspended
solids, total phosphorus, soluble reactive phosphorus, nitrate, and total
Kjeldahl nitrogen. The basic characteristics of the resulting data are desc
ribed, as are systematic differences as a function of watershed size, seaso
nal differences, and trends over time. Many of the results of this study re
flect the importance of nonpoint processes and improvements in agricultural
best management practices in these watersheds.