Date of Award

9-1984

Degree Type

Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Civil Engineering

Supervisor

Dr. W. James

Abstract

The fact that considerable quantities of solids, toxic metals and hazardous contaminants are washed off urban surfaces has been well documented in recent literature.

It is generally recognised that urban runoff models predict runoff quantity quite well. However, due to lack of understanding of the various processes involved in pollutant buildup, washoff and routing and insufficient, and faulty data collection, urban runoff models depict runoff quality poorly. This research therefore attempts to introduce new concepts and algorithms, based on the physical processes involved, to improve runoff quality prediction. The problem has been segmented into three broad areas: a) pollutant buildup, b) pollutant washoff and, c) routing and fate of pollutants.

The interaction of addition and removal processes in pollutant buildup has been further disaggregated. Estimates are made of the daily mass balance of pollutants over a dry period, considering meteorological and geographical effects. Additions from atmospheric dustfall, vehicles, population and special activities; removal due to biological decay, vehicle and wind created eddies and intentional removals (street sweeping) are formulated individually. Scavenging of aerosols and gases and washoff from canopies during precipitation are also modelled and added to conventional washoff. Expressions for the impact of raindrops, shear due to overland flow, and vehicle-induced eddies are used to develop a new washoff equation which is compared to conventional washoff equations. An established pollutant routing algorithm is modified to minimise summation error. All these pollutant concentration prediction algorithms are interfaced with one of the most comprehensive models, the Storm Water Management Model Version 3 (SWMM3), preserving the runoff quantity prediction algorithms. Provision has been made for variable time steps for both runoff quantity and quality. The modified SWMM3 is called CHGQUAL in the present work. CHGQUAL was applied to the Chedoke Creek Catchment in Hamilton, Canada, for verification, calibration and validation. The pollutional parameters used in the study are suspended solids(SS), biochemical oxygen demand (BOD), total nitrogen (TKN) and total phosphorous (TP). The CHGQUAL computed pollutant concentration results were statistically compared to both SWMM3 results and observed data.

The new runoff water quality algorithms showed improved predictability for the test catchment. The CHGQUAL model can readily be applied to other catchments.

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