Theoretical analysis of urban runoff pollutographs: identification of characterization variables and impact

This research presents a novel methodology to determine runoff water retention volumes that allow the design of storage tanks for storm sewer overflows. It is based on the use of the Stormwater Management Model (SWMM) to generate hydrographs and runoff pollutographs of a fictional urban basin. Three pollutants (TS, BOD5 and TN) are simulated for a given set of rains and the values taken by a proposed set of characterization variables for the pollutographs obtained are analysed. Correlation and determination coefficients that exist between the different variables are analysed while also performing a multivariate characterization using PCA and cluster analysis. In the case study presented, using IDF curves of the studied city, a probability of occurrence (Tr) is assigned to the values taken by the proposed characterization variables. To assess the impact and identify the most unfavourable pollutographs within the set of selected rains, impact evaluation variables (IEV's) are established, based on the proposed characterization variables and by simulating the discharge to a receiving water body (river with initial concentration and constant flow). Finally, a storm sewer overflow is simulated, deriving a maximum flow for purification, and dimensioning retention tanks for different fractions of the total volume of runoff to control the maximum values of a specific IEV impact evaluation variable. Taking a design return period Tr-ssd >= 10 years, the results obtained in the study case were 146.50 m(3)/ha imp for a 100% retention of the total runoff volume and 117.20 m(3)/ha imp for an 80% retention.

Automated summary

This research introduces a new methodology for determining the retention volumes of runoff water in storage tanks designed for storm sewer overflows. The study utilizes the Stormwater Management Model (SWMM) to generate hydrographs and runoff pollutographs for an imaginary urban basin. By simulating three pollutants (TS, BOD5, and TN) under a given set of rainfall conditions, the values of proposed characterization variables for the obtained pollutographs are analyzed. Correlation and determination coefficients between different variables are examined, along with multivariate characterization using PCA and cluster analysis. In the case study, IDF curves of a specific city are used to assign probabilities of occurrence (Tr) to the values of the proposed characterization variables. Impact evaluation variables (IEVs) are established based on the proposed characterization variables, and the discharge into a receiving water body is simulated to assess the impact and identify the most unfavorable pollutographs within the selected rainfall events. Finally, a storm sewer overflow is simulated to determine the maximum flow for purification and to size retention tanks for different fractions of the total runoff volume, aiming to control the maximum values of a specific IEV impact evaluation variable. With a design return period of Tr-ssd >= 10 years, the results of the case study were 146.50 m(3)/ha imp for 100% retention and 117.20 m(3)/ha imp for 80% retention.