Spatio-temporal optimization of the operation of real-time controlled rainwater harvesting systems to improve streamflow regimes

ABSTRACT Rainwater tanks have been a common technology for water supply, offering benefits beyond just storage by supporting water reuse, flood mitigation, and the protection of receiving water environments. Recent advances in real-time technology open up the opportunity to increase the efficiency and effectiveness of rainwater harvesting by releasing the saved water in the tanks at a controlled rate to drainage networks and receiving waters. The integration of forecasting and optimization techniques within this real-time technology can support more informed operational decisions tailored to given environmental contexts, such as delivering a more natural flow regime. This paper develops a spatio-temporal modeling framework to improve the operation of a network of real-time controlled rainwater harvesting systems. The proposed strategy optimizes the scheduling of water releases from the storage throughout the day to enhance the stability of the flow regime, which is important for in-stream ecological structure and function. The proposed strategy was observed to outperform a steady release strategy and provided more precise control over flow dynamics. The modeling framework could be adapted to meet specific flow-regime requirements of a given waterway or ecosystem, thus allowing rainwater and stormwater harvesting networks to better protect the health of receiving waters and promote sustainability.