The smart rain barrel (SRB) represents a micro storage developed as an IoT-based solution for advanced rainwater harvesting. The SRB consists of a conventional rain barrel available in normal hardware stores and is extended through a remote controllable discharge valve. Measurement data (e.g. filling depth) as well as control commands are exchanged via the low power wide area network LoRaWAN. To overcome the limitations of small storage volumes, high-resolution weather forecasts are used to increase detention volume, while ensuring a sufficient collection of rainwater for irrigation purposes. The SRBs allow an individual control of each unit as well as an easy installation at households, supporting therefore a large-scale retrofitting of existing urban drainage with additional storage volume.

To demonstrate the effectiveness of the SRB, a two-stage process was chosen. First, our experiences with a developed prototype are presented, which is under operation at the university campus of Innsbruck during the summer half-years since 2018. The second step includes a model-based upscaling to investigate the effects of a hypothetical retrofitting of SRBs on a real urban water infrastructure of an alpine municipality with 2 500 inhabitants. Therefore, the open source software “smartin” was developed integrating python packages for SWMM5 and EPANET2 into a coupled model. For the simulations, degree of penetration was varied between 25% and 100%, corresponding to 95 and 380 SRBs, and different control strategies (e.g. different forecast horizons of the weather forecasts) were applied. The results show that already a simple control strategy can clearly improve the integrated system performance (e.g. reduced combined sewer overflows and drinking water demand) compared to uncontrolled rain barrels.

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The smart rain barrel (SRB) represents a micro storage developed as an IoT-based solution for advanced rainwater harvesting. The SRB consists of a conventional rain barrel available in normal hardware stores and is extended through a remote controllable discharge valve. Measurement data (e.g. filling depth) as well as control commands are exchanged via the low power wide area network LoRaWAN. To overcome the limitations of small storage volumes, high-resolution weather forecasts are used to increase detention volume, while ensuring a sufficient collection of rainwater for irrigation purposes. The SRBs allow an individual control of each unit as well as an easy installation at households, supporting therefore a large-scale retrofitting of existing urban drainage with additional storage volume.

To demonstrate the effectiveness of the SRB, a two-stage process was chosen. First, our experiences with a developed prototype are presented, which is under operation at the university campus of Innsbruck during the summer half-years since 2018. The second step includes a model-based upscaling to investigate the effects of a hypothetical retrofitting of SRBs on a real urban water infrastructure of an alpine municipality with 2 500 inhabitants. Therefore, the open source software “smartin” was developed integrating python packages for SWMM5 and EPANET2 into a coupled model. For the simulations, degree of penetration was varied between 25% and 100%, corresponding to 95 and 380 SRBs, and different control strategies (e.g. different forecast horizons of the weather forecasts) were applied. The results show that already a simple control strategy can clearly improve the integrated system performance (e.g. reduced combined sewer overflows and drinking water demand) compared to uncontrolled rain barrels.

**[Access the Conference Proceedings Paper on ASCE Library](https://doi.org/10.1061/9780784483466.024)** 

Model-based Upscaling of the IoT Based Smart Rain Barrel – An Integrated Analysis of the Urban Water Cycle

Created in 1999, the Environmental & Water Resources Institute (EWRI) is the recognized leader within ASCE for the integration of technical expertise and public policy in the planning, design, construction, and operation of environmentally sound and sustainable infrastructure impacting air, land and water resources.

[Paper Proceedings](https://doi.org/10.1061/9780784483466)

Conference DOI: https://doi.org/10.26226/m.6329c39b68fb0e00131f77d2