Storm water pollution modelling: buildup of dust and dirt on surfaces subject to runoff

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Abstract
Many runoff models are currently in use to predict both the quantity and quality of storm water runoff. In most models, the quality algorithms need further development to gain the confidence of model users. The writers have attempted to disaggregate the accumulation process and to develop improved algorithms for pollutant buildup. The factors and processes that affect buildup include atmospheric dustfall due to plumes of dust-laden air, wind effects, vehicles, intentional removals (e.g., street cleaning), special activities (such as construction and demolition), biological decomposition, and population-related activities (e.g., vegetation density, insecticides, herbicides, fertilizers, and lawn cutting). Mathematical expressions for each of these mechanisms are presented and utilized to develop algorithms in the RUNOFF module of the SWMM3 package.A separate multiregression model is used to generate atmospheric dustfall from meteorological information; this is input to the new program (NEWBLD) to calculate pollutant accumulation on individual subcatchments. NEWBLD is interfaced with the RUNOFF block of SWMM3. A sensitivity analysis is carried out using data for the Chedoke Creek catchment in Hamilton, Ontario. The modified version of the SWMM3 RUNOFF block developed herein by incorporating the new water quality algorithms is called CHGQUAL. It is applied to an urban catchment in Hamilton, Ontario. Key words: storm water models, dust and dirt buildup, storm water pollution, urban hydrology, air pollution.

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