## 4 Discussion and Possible Study Limitations
Although the infiltration volume is increased, it can only be increased by a certain level, and once the saturation point is reached, the runoff rates will be high. This issue is also reflected in the changes in peak discharge. While the peak discharge volume is consistently reduced, this reduction in high discharge events is comparably small. Although the strategies may be effective in moderate rainfall, their effectiveness decreases when faced with extreme and prolonged rainfall events. Events 1 and 3 resulted in differing performance of the NbS, likely due to large differences in precipitation intensity. Both are extreme rainfall events, with Event 1 having a return period (RP) of >100 years and Event 3 having a RP of >250 years. However, Event 1 has a very short duration (<8 h), whereas Event 3 is much longer (>50 h). While Event 3 has more rainfall in total, its lower average intensity (5.04 mm/h) allows the implemented solutions to work more efficiently by having more time to infiltrate and manage the water. In contrast, in Event 1, the higher average rainfall intensity (11.42 mm/h) causes a rapid accumulation of runoff, overcoming the capacity of the solutions to reduce the runoff volume, resulting in a smaller abatement. This highlights the difference in NbS response depending on the nature of the event. The CN method factors in precipitation intensity when calculating runoff volume [34], which may explain this relationship. The modelled reductions in runoff volume appear to change with the starting CN. This is apparent when the results from Events 3 and 10 are considered. They have comparable original runoff volumes (Table 5), but the NbS perform very differently. Event 10 sees a runoff volume reduction of 1.4% with all NbS, whereas Event 3 has a reduction of 18.3% for the same scenario. Event 3 has an average precipitation intensity of 5.04 mm/hr, and Event 10 has an average precipitation intensity of 1.95 mm. This contradicts the idea that higher intensities reduce the effectiveness of the NbS. A possible cause is the starting CN of the two models. Event 3 has the lowest starting CN of all models, with 36. Event 10 has the highest starting CN, with 88 (Table 2). Both deviate significantly from the average calibrated CN of 66.43 across all events. Therefore, the CN changes due to NbS implementation represent a greater proportion in terms of reduction in Event 3 than in Event 10 (a reduction in CN of 2.44% and 1.00%, respectively). This research supports existing literature on the potential of NbS for runoff management. The green roots in this study had a moderate impact, which varied with rainfall volume. This result correlates strongly with a study performed in Denmark, which showed very similar decreases in runoff volume [77]. Permeable paving had the best performance in this study and was shown to be effective in other locations. In a case in Australia, permeable paving reduced the peak flows by 7-16%, which is comparable to the results in this case study [78]. The limited effectiveness of retention ponds correlates with a similar modelled implementation in southeastern US [79]. However, retention pond effectiveness varies greatly depending on the dimensions used and the dynamics of the watershed they are implemented in. Large-scale NbS, such as land use changes, tend to perform well [39; 40]; however, they are not applicable to small watersheds, such as in this case study. For small urban catchments, a combination of small-scale measures is often the most effective solution [2; 80], a statement, which this study also supports. The outflow structures allowed for relatively high discharges in order for the model to function. This resulted in ponds not appearing as effective at reducing peak discharges and not providing water storage for longer durations, as water flowed out of the ponds immediately.