Abstract:Many studies have identified the potential of rainwater harvesting (RWH) systems to simultaneously augment potable water supply and reduce delivery of uncontrolled stormwater flows to downstream drainage networks. Potentially, such systems could also play a role in the controlled delivery of water to urban streams in ways which mimic baseflows. The performance of RWH systems to achieve these three objectives could be enhanced using Real-Time Control (RTC) technology to receive rainfall forecasts and initiate pre-storm release in real time, although few studies have explored such potential. We used continuous simulation to model the ability of a range of allotment-scale RWH systems to simultaneously deliver: (i) water supply; (ii) stormwater retention; and (iii) baseflow restoration. We compared the performance of RWH systems with RTC technology to conventional RWH systems and also systems designed with a passive baseflow release, rather than the active (RTC) configuration. We found that RWH systems employing RTC technology were generally superior in simultaneously achieving water supply, stormwater retention and baseflow restoration benefits compared with the other types of system tested. The active operation provided by RTC allows the system to perform optimally across a wider range of climatic conditions, but needs to be carefully designed. We conclude that the active release mechanism employing RTC technology exhibits great promise; its ability to provide centralised control and failure detection also opens the possibility of delivering a more reliable rainwater harvesting system, which can be readily adapted to varying climate over both the short and long term.

Use of real time control (RTC) technology in rainwater harvesting systems can improve performance across water supply, flood protection, and environmental flow provision. Such systems make the most of rainfall forecast information, to release water prior to storm events and thus minimize uncontrolled overflows. To date, most advanced applications have adopted 24-hr forecast information, leaving longer-term forecasts largely untested. In this study, we aimed to predict the performance of four different RTC strategies, based on different forecast lead time and preferred objectives. RTC systems were predicted to yield comparatively less harvested rainwater than conventional passive systems but delivered superior performance in terms of flood mitigation and delivery of environmental water for streamflow restoration. More importantly, using a 7-day rainfall forecast was shown to enhance the ability of RTC in mitigating flood risks and delivering an outflow regime that is close to the natural (reference) streamflow. Such a finding suggests that RTC combined with 7-day forecast can enhance the functionality of rainwater harvesting systems to restore and even mimic the entire natural flow regimes in receiving streams. This also opens up a new opportunity for practitioners to implement smart technology in managing urban stormwater in a range of contexts and for a range of stream health objectives. Plain Language Summary "Smart tanks" based on real time control is increasingly used in rainwater harvesting systems to address water shortages, urban flooding, and streams depleted of flow. Smart tanks, controlled by real time control, can use a range of digital information (e.g., rainfall forecast) to make optimal decisions to release some tank water before heavy rain, to reduce flood risks, while still supply water to households. Globally, most uses of this technology use 1-day forecasts of rainfall. To understand the effect of longer prediction window, we compared four strategies using either 1-day or 7-day rainfall forecast and modeled their performance using specialized computer code. We found that smart tanks using 7-day rainfall forecasts are superior in reducing urban flood risks and restoring baseflows to streams. More importantly, they can release the tank water in a pattern that is similar to natural streamflow, thus helping to restore and sustain healthy waterway habitats. Our study is the first reported application of 7-day forecast information in smart control rainwater tanks. It opens up a new opportunity in managing urban water in a range of contexts and for a range of stream health objectives.

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River water is necessary for production, livelihood and ecological balance [1]. Changes in river runoff directly affect the development and utilization of water resources [2] and thereby societal and economic development [3]. Studying the evolution of runoff and its influencing factors can provide a scientific basis for the management, protection and sustainable use of water resources [4, 5]. The change in river runoff is an important manifestation of climatic influence, especially precipitation and human activities in basins [6]. Thus, river runoff is an active area in global change research [7,8]. The fifth assessment report of the United Nations Intergovernmental Panel on Climate Change (IPCC) predicts that in the 21 st century, global climate change will increase surface runoff in high-latitude regions and humid tropical regions and decrease surface runoff in most arid subtropical regions and Mediterranean regions [7]. However, the causes of runoff changes are complex. Although climate change [8, 9] (e.g., precipitation) is the main influence in river runoff changes, the potential increase in evapotranspiration is also considered to be

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 Four contrasting Real-Time Control strategies were applied to simulated rainwater harvesting systems  Long lead-time rainfall forecast (7-day) enhanced the ability to reduce flood risk and restore baseflow, with little impact on water supply efficiency  Using long lead-time rainfall forecast has the potential to holistically restore natural flow regimes.

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Rapid urbanization since the mid−20th century has created critical challenges for water management. Population growth and dwindling freshwater resources imperil water security globally (Vörösmarty et al., 2010). Landscape change through increased impervious cover decrease infiltration and evapotranspiration in the urban environment (Barron et al., 2013;Haase, 2009), resulting in excessive surface runoff and increased peakflow, increasing flooding risks (Nirupama & Simonovic, 2006). Such a gross change to the natural water cycle also commonly reduces groundwater recharge and stream baseflow (Bhaskar, Beesley, et al., 2016;Ferguson & Suckling, 1990;Rose & Peters, 2001). The conventional hydraulically-efficient drainage network, which directly connects surface runoff to the receiving water, further perturbs the natural flow regimes through increased frequency and magnitude of stormwater flow (Leopold, 1968), along with reduced recession time (Burns et al., 2005). These hydrological changes drive substantial geomorphic modification (Hammer, 1972;Russell et al., 2020), habitat loss and