The development of relationships for predicting the impact of highway stormwater runoff is described. The predictive relationships are regression-based equations reflecting variations in the magnitude of the constituents of interest. The objective is to identify a subset of constituents that can be used as surrogates for the remaining constituents as a means of decreasing the costs of collection and measurement of highway stormwater runoff quality data.The Minnesota highway stormwater quality database complied in the late 1970's and early 1980's is employed in identifying the set of surrogate parameters. The findings indicate that total suspended solids, total dissolved solids, total volatile solids, and total organic carbon are effective surrogate parameters for numerous metals, ionic species, and nutrients. The findings also indicated that the developed ionic species constituent relationships are portable, while the metal and nutrient constituent relationships were limited to urban sites with similar environmental conditions. The development of these relationships represents a step towards remediating and preventing the problem of nonpoint source highway pollution.