Abstract

Eight software tools and analytical methods are suggested that would render very-long-term, continuous, surface water quality management modeling more productive and more credible. This chapter focuses on the US EPA Storm Water Management Model (SWMM). Two tools are described in detail: (i) a heuristic sensitivity analysis (SA) methodology written as a shell around SWMM4, and (ii) a calibration methodology. The first uses concepts from fuzzy logic and is accomplished by grouping 48 SWMM RUNOFF block parameters by hydro-logic processes and identifying the dominant processes in various limited input -parameter spaces by matching combinations of parameters to classes of hydro-meteorological events. Both were developed, integrated, and tested using a SWMM datafile for Redhill Creek in Hamilton, Ontario.

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