Abstract
This paper compares the use of simple regression equations of three commonly used pollutant build-up and wash-off functions, namely linear, power and exponential functions, to estimate event pollutant loads. The comparative study indicated that, event loads are better estimated as power functions of storm-related independent variables. On the notion that rainfall data are more readily available, easy and less expensive to collect than runoff data, the calibrated model was verified using rainfall volume as independent variable. The verified model was then used to develop load-duration-intensity curves to serve as predictive tools. Planners and engineers can use these predictive tools to obtain an approximate estimate of event pollutant loads in storm runoff from Alexandra (and also other townships with similar physical, land-use, climatic and hydraulic characteristics and water quality issues) for the purpose of managing or improving drainage conditions in the township.
Highlights
Inadequate sanitation and drainage is one of the major environmental and health problems facing high-density low-income settlements in South Africa today
The backlog in sanitation and drainage includes solid waste, sewage, grey-water and severely contaminated stormwater runoff. In these areas the paths are often merged; sewage, greywater, solid waste and contaminated runoff enter surface drains, eventually discharging into streams, rivers and impoundments that are used for drinking water supply and recreation
The principal reason for this situation is the high cost of conventional drainage and treatment practices. It is for this same reason that the Water Research Commission of South Africa initiated a project to look into appropriate technology options that are feasible for rural and peri-urban drainage
Summary
Inadequate sanitation and drainage is one of the major environmental and health problems facing high-density low-income settlements in South Africa today. The best regression model (involving rainfall-related variables) is further used to develop load-duration-intensity (LDI) curves for prediction of storm runoff loads. Previous studies conducted in South Africa have concentrated on the use of linear regression technique/model to estimate storm loads.
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