كاربرد مدل هاي دگرسيوني در برآورد بار آلودگي رواناب شهري

Application of Regression Models in Estimation of Urban Runoff Pollution Load

A large amount of rain water is transferred to reception mainstreams (e.g. surface and ground water) in urban areas due to the increased impermeable surfaces. Urban catchmentʹs water that is produced by precipitation or snow melting is considered as one of the most important non-point pollutants. In this investigation, having discretely sampled the output drainage in 13 precipitation events in one of Isfahan catchments during autumn/winter, 2002/2003, 10 qualitative/quantitative parameters were measured to assess the general quality. Modulating the drainage pollution amount (using multivariate statistics) nitrates, total suspended solids, chemical oxygen demand and average discharge factors were considered as the main regression factors. Modulating input data through which a regression model of the least error (0.009) and the highest correlation coefficient (0.998) was designated to assess the amount of output drainage pollution. Input parameters of the model were total suspended solids and chemical oxygen demand. To assess the model accuracy, error indices were estimated using two data groups that was not which included in modulating which indicated the qualification of the model for the next stage. Using this model, total pollution amount of output drainage can be calculated for future events through measuring two input parameters. Also, another regression model was presented based on precipitation characteristics, which can be readily used, but of less accuracy. These results can be useful for water resource managers, urban programmers and those responsible for environment to control Zayande Rood River pollution, maintain environmental circumstances and carry out reasonable urban catchment management.