Rainwater harvesting potential: the Turin case for an analysis at the urban scale

The population growth and its concentration within cities, on the one hand lead to an increment of water demand and on the other hand affect the urban water cycle with frequent urban flood events associated to rain extreme events. New approaches to the water management are currently being developed where a role is assigned to rain water harvesting (RWH). RWH provides water for non-potable uses (private and public, indoor and outdoor), reducing water consumption. Moreover, RWH allows to partially retain water on site, reducing the probability of failures of the sewerage system during heavy rain events.

These positive effects are easily evaluable at a building scale when well-known behavioral models are used, while the evaluation becomes often more complex at an urban scale, due to the lack of characteristics and demographic data about all the buildings in the city. In our work, we consider RWH impact at the urban scale, by means of the representative building concept.

We focus on several hypothetical retrofitting scenarios for the residential buildings of Turin (Italy): 1) domestic use of rainwater (e.g., toilet flushing and the washing machine), where buildings are independent of each other, and 2) two public uses of rainwater (the irrigation of public green areas and street washing), for which we have hypothesized that the rainwater collection takes place at a district scale. We estimate a reduction of 42% in the non-potable water consumption for domestic use (values vary across the municipal districts from 29% to 62%, according to the characteristics of the buildings), while for irrigation and street washing, that require a lower amount of water, about 80% of the water can be provided by RWH. The highest reduction of the flow peak conveyed to the sewerage system during extreme storms is reached in the domestic use scenario (about 60%, quite constant across the city), while for public uses the retention capacity is very low.

Finally, our estimations based on historical rainfall series are examined against different climate change scenarios.