New conceptualization and quantification method of first-flush in urban catchments: A modelling study

A major challenge for runoff pollution control lies in the quantification and identification of the first-flush. At present, there is a lack of reasonable theoretical methods to guide engineering practices. To remedy this deficiency, a novel method of cumulative pollutant mass vs. cumulative runoff volume (M(V)) curve simulation is proposed in this study. Subsequently, the first-flush phenomenon was redefined based on the M(V) curve simulation and demonstrate that the first-flush exists until the derivative of the simulated M(V) curve is equal to 1 (Ft ' = 1). Consequently, a math-ematical model for first-flush quantification was developed. The Root-Mean-Square-Deviation (RMSD) and Pearson's Correlation Coefficient (PCC), as objective functions, were used to evaluate the performance of the model and the Elementary-Effect (EE) method was used to analyze the sensitivity of the parameters. The results indicated the satisfac-tory accuracy of the M(V) curve simulation and first-flush quantitative mathematical model. The NSE values exceeding 0.8 and 0.938, respectively, were obtained by analyzing 19 rainfall-runoff data for Xi'an, Shaanxi Province, China. The wash-off coefficient r was demonstrably the most sensitive factor influencing the model performance. Therefore, in-teractions between r and the other model parameters should be focused on to highlight the overall sensitivities. Overall, this study posits a novel paradigm shift from the traditional dimensionless definition criterion to redefine and quantify first-flush, which has significant implications for urban water environment management.

Automated summary

This study proposes a novel method for simulating the cumulative pollutant mass vs. cumulative runoff volume (M(V)) curve and redefines the first-flush phenomenon based on this simulation. A mathematical model for first-flush quantification is developed and found to be accurate through analyzing rainfall-runoff data. This research has significant implications for urban water environment management.