## 5 Discussion
Consequently, one of the recommendations for both cities is to incorporate pervious surfaces wherever feasible (for example, in car parks, parks, and pavements), as well as to introduce gaps and implement nature-based solutions in the form of urban acupuncture [92] in the most sealed districts. Increasing urban greenery is an effective approach to reducing both the extent of impervious surfaces and the associated runoff, thereby forming a key component of strategies to mitigate flood risk. For instance, trees can reduce the amount of rainfall that reaches the soil through interception at the canopy level, which in turn reduces the peak flow of runoff. Various studies have shown that this reduction can range from 9% to as much as 70% [93; 94; 95; 96; 97; 98], depending on the intensity of the rainfall. Trees and tree pits create gaps in sealed surfaces and provide urban sites where rainwater can percolate and infiltrate into deeper soil layers, thereby reducing surface runoff. For instance, experimental studies conducted in Manchester, UK, on three small trees demonstrated a 62% reduction in runoff [86]. Similarly high results were obtained when comparing infiltration in urban areas with and without trees, i.e., infiltration in green areas was circa 60% higher [99]. Other green solutions can also significantly reduce runoff; for instance, green roofs may achieve an efficiency of 30% to 86% and can reduce peak flow by up to 93% [100]. Meanwhile, shrub-grass vegetation, when increasing to 70% coverage, has been shown to decrease average runoff by 37% [95]. Therefore, it is imperative for urban areas to both preserve existing vegetation--particularly high-quality parks, urban forests, and gardens--andintegrate nature-based solutions in regions predominantly covered by impervious surfaces. Both cities were evaluated in terms of their green space distribution, which is critical for hydrological assessments. Although the overall proportion of green areas is relatively high, averaging approximately 50%, a detailed analysis indicates that green space is markedly limited in city centres, residential areas, and zones with concentrated commercial and logistics activities. Consequently, these areas should be prioritised for future interventions, including the strategic planting of vegetation and trees. Moreover, the project emphasised that in the peripheral areas of both cities, protected green spaces--such as those along meandering riverbanks and extensive forested regions in mountainous areas--serve as natural buffers against flooding, given that both cities have experienced severe floods over the past century. The GIS analysis was also used to delineate local depressions that do not drain directly, which could potentially damage adjacent buildings and areas during flash flooding. For instance, the extraction of such GIS information is the first step in modeling short-term flash floods [101] and can also serve as a cost-effective alternative to more complex modeling approaches [102]. In both cities, several local depressions have been identified that can accumulate water during heavy rainfall. Therefore, it is recommended that these areas be given careful consideration in future urban planning, with a view toward redeveloping them into green-blue infrastructure solutions. Eventually, the multi-criteria approach (MCA), integrated with GIS data [103], was adapted to identify districts or areas within cities that are vulnerable to flooding--whether due to heavy rainfall or riverbank overflow. This combined method has been extensively used in environmental studies to produce detailed flood risk maps [104; 105], as well as hazard, vulnerability, and exposure maps [104; 106]. In the study, both cities were analysed using MCA, which highlighted specific areas that are particularly susceptible to hydrological threats and potential flooding. This approach offers land-use planners a powerful tool for making informed decisions when designing new construction projects, ensuring that developments are both resilient and sustainable.