Cities and urban areas face new challenges in the near future. Growing urban population and the climate change related uncertainties will likely have an effect both the urban hydrological cycle and water management. Extreme weather conditions, such as high volume precipitation caused urban flooding, or the prolonged drought periods are the problems for which urban water management needs to prepare. Within the sustainable water management systems, there are many tools with the ability to mitigate the undesired effects. In urban areas, excess water can be a good source to replace the potable or ground water which is used for vegetation irrigation. Urban vegetation is artificially maintained, and requires irrigation in dry summer periods. Rainwater harvesting systems (RWHS) are used in the sustainable water management systems to reduce the water usage of drinking water and the water import into the cities. This work aimed to devise a simple method for estimating the maximal collectable rainwater for irrigation use in Szeged, Hungary. Hydrological modelling (EPA SWMM) was used to calculate maximal runoff from rooftops, which was the base of the simple irrigation water (IW) demand estimation. The maximal potential rainwater volumes that can be used for rainwater harvesting and irrigation were calculated. For the IW demand calculation, buffer zones around the rooftops of the buildings were created in different distances (10 m, 20 m, and 50 m). The land cover within these zones was categorized by vegetation and artificial surfaces. Results indicated that there are notable differences among the urban districts, some of which having high available volume of collectable rainwater, but low vegetation proportion for efficient irrigation (e.g., in the innermost part of the city center). The housing-estate district of the city – which is widespread in post-socialist and Central-European countries – can be a good choice for RHWS installation, due to the high vegetation proportion and high collectable rainwater volume. The simple methods and the comparatively easy-to-access data is expected to facilitate the rainwater harvesting estimation in urban areas.