The first‐order surface pollutant washoff model is examined under noise‐corrupted runoff conditions. Statistics of the pollutant load are derived using the derived probability distribution concept and verified using Monte Carlo simulations. The investigation demonstrates that under noise‐corrupted runoff conditions a bias is introduced in the estimate of the pollutant load. The bias is sensitive to: (1) The time step of the simulation; (2) the variance of the noise in runoff; and (3) the time from the start of the simulation (duration of the simulation). Statistics are derived for both the incremental pollutant washoff load (ΔP) and the mass of pollutant remaining on the street surface (P), The results of this study can be incorporated in any rainfall‐runoff model (e.g., SWMM, STORM, etc.) that makes use of the first‐order pollutant washoff model.
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