A modified Morris screening protocol for sensitivity analysis and calibration of green roof parameters in SWMM

In the calibration process of urban flood and non-point source pollution models, obtaining sufficient site-specific sensitive parameters and their variation trends remains challenging. In this study, a modified Morris screening method was established and used to evaluate the parameters of the green roof module in the SWMM model. This method involved fixing the values of all other parameters while varying a selected parameter X(i) within its defined range, applying multiple iterations of changes at a fixed percentage (10 %) to compute the corresponding model output values. The aim was to specify the impact and significance of hydrological parameters on runoff volume cut-off and water quality indicators under different return periods, and to further improve the prediction accuracy of the SWMM in simulating real rainfall events. Results revealed that Soil-T (soil layer thickness) and Surface-BH (surface layer storage depth) exhibited the highest sensitivity to total runoff production. Specifically, the sensitivity values of Soil-T exceeded 1.0 under 0.5-year and 1-year return periods, indicating its dominant role in runoff generation, while Surface-BH demonstrated a sensitivity value close to 2.0 at 0.5-year return period, showing its strong impact on peak flow. For these high-sensitivity parameters, the manual trial-and-error method was used for parameter refinement. Optimal simulation accuracy (E_NS > 0.75) was achieved when Soil-T and Surface-BH were set within ranges of 86–95 mm and 18–22 mm, respectively, across six representative rainfall events. This study provides a new method to determine the optimal parameter combinations for calibrating the SWMM model, and its high accuracy offers a scientific basis for design and optimization of urban drainage systems, particularly in response to extreme rainfall events, which is helpful to the sustainability and resilience of cities.