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An increasing interest in retrofitting rooftops as green roofs require improved understanding of the impact on runoff within urban catchments. In this study, a model of Risvollan, an urban catchment in the coastal city of Trondheim, Norway was built using the PCSWMM (Storm Water Management Model) model version 7.2.2780. Rooftops in the catchment were retrofitted as green (vegetated) or grey (non-vegetated – expanded clay, detention-based) roofs. The detention impact was evaluated for nine scenarios using three exceedance thresholds by measuring runoff at the catchment outlet. It was found that implementing green roofs on as little as 11% of the roof area can substantially reduce maximum flows. The implementation of the grey roofs outperformed the green roofs in all the investigated aspects: duration, number, and volume. The study provides insight to urban planners and decision-makers in how to quantify the contribution of rooftop detention to runoff reduction for stormwater management. [ABSTRACT FROM AUTHOR]

Climate change combined with urbanization increases the performance demand on urban drainage systems. Green roofs are one of the most used green infrastructure measures to alleviate the pressure on the urban drainage system through the detention and retention of runoff. The rational method with the runoff coefficient (C) is one of the most commonly used design tools for stormwater design in Norway. This method relies on a runoff coefficient being available for green roofs, which is typically not the case. This paper compares laboratory and experimental field studies to investigate runoff coefficients from different types of detention-based roofs. The methodology described in the German 'FLL Guideline', one of the world's most commonly used green roof standards, was used to measure the runoff coefficients for the different components making up a typical green roof. The contribution from each layer is reflected in the runoff coefficients. The runoff coefficients from the field experiments were calculated using observed precipitation and runoff from existing green roofs in Oslo, Trondheim, Sandnes, and Bergen, Norway. Events that had a cumulative precipitation comparable to the laboratory events, but longer durations, were selected. These events gave significantly lower and varying runoff coefficients, clearly demonstrating the limitation of choosing a suitable runoff coefficient for a given roof. However, laboratory experiments are important in understanding the underlying flow processes in the different layers in a detention-based roof. [ABSTRACT FROM AUTHOR]

Rooftop retrofitting targets the largest land-use type available for reduction in impervious surfaces area in urban areas. Extensive green and grey roofs offer solution for retention and detention of stormwater in densely developed urban areas. Among the available green roof types, the extensive green roof has become a popular selection and commonly adopted choice. These solutions provide multiple benefits for stormwater and environmental management due to stormwater retention and detention capacities. The Storm Water Management Model (SWMM) 5.1.012 with Low Impact Development (LID) Controls was used to model the hydrological performance of a green and a grey (non-vegetated detention roof based on extruded lightweight aggregates) roof (located in the coastal area of Trondheim, Norway) by defining the physical parameters of individual layers in LID Control editor. High-resolution 1-min data from a previously monitored green and grey roof were used for calibration. Six parameters within the individual LID layers: soil (four parameters) and drainage mat (two parameters) were selected for calibration. After calibration, the SWMM model simulated runoff with a Nash-Sutcliffe model efficiency (NSME) of 0.94 (green roof) and 0.78 (grey roof) and a volume error of 3% for the green roof, and 10% for the grey roof. Validation of the calibrated model indicates good fit between observed and simulated runoff with a NSME of 0.88 (green roof) and 0.81 (grey roof) and with volume errors of 29% (green roof) and 11% (grey roof). Concerning the snowmelt modelling, the calibrated model showed a NSME of 0.56 (green roof) and 0.37 (grey roof) through the winter period. However, regarding volume errors, additional model development for winter conditions is needed; 30% (green roof) and 11% (grey roof). Optimal parameter sets were proposed within both the green and grey configurations. The results from calibration and especially validation indicated that SWMM could be used to simulate the performance of different rooftop solutions. The study provides insight for urban planners of how to target and focus the implementation of rooftop solutions as stormwater measures. • Green and grey roof were modelled with the SWMM model. • The model was separately tested for periods with and without snow. • The SWMM model reproduced runoff hydrographs well for both calibration and validation periods. • However, the calibrated parameter sets may only be valid in this model. • Snowmelt modelling using the SWMM model was only partly successful. [ABSTRACT FROM AUTHOR]