Incorporating smart tools and technologies into Green Stormwater Infrastructure (GSI)I has been identified as a natural next step for stormwater management. A plethora of smart stormwater management systems have been proposed, mostly by integrating sensing, control, communication, and computing capabilities. These advancements can augment the operation, performance, and capacity of existing or new infrastructure through enhanced data capture, analysis, and control of infrastructure systems. These methods have been tested in the realm of water management for monitoring, controlling, and managing water volume and quality, and for supporting decision-making practices in water distribution networks.
1. Introduction
Of the numerous adverse impacts of urbanization, stormwater hazards hold particular prominence due to their substantial contribution to global-scale natural disasters, exacerbated by ongoing climate change. Acknowledging these hazards, diverse global initiatives have sought to implement ecosystem services techniques and nature-based solutions (NBS), including green stormwater infrastructure (GSI)
[1][2][3][4,5,6]. GSI carries significant implications for attenuating the impacts of heat island effect, boosting stormwater management capacity, mitigating climate change effects, and reducing environmental pollution
[4][5][6][7,8,9]. The preponderance of literature supporting GSI attests to the substantial groundwork in this sphere, substantiating the well-established nature of knowledge in this field.
However, the advent of the Information Age has introduced a set of unique challenges to stormwater management. A significant evolution in data collection methods has been spurred by the proliferation of the Internet of Things (IoT)
[7][8][10,11]. Conceptualized by the MIT Auto-ID Laboratory in 1999, the IoT has fueled investigations into the transformation of urban systems into “smart cities”, enabled by technological advancements in computation, information and communication technology, IoT, robotics, and autonomous systems
[9][10][11][12,13,14]. The emergence of “smart cities” has led to the exploration of technologies that can be harnessed to more efficiently monitor and manage GSI and NBS. These advancements are critical for helping cities adapt to climate change and deliver ecosystem services more effectively
[12][13][14][15,16,17]. Such interventions pave the way for sustainability, transforming cities into intricate social–ecological–technological systems, wherein technology and environmental functionality dictate the necessary changes
[14][15][16][17,18,19].
Incorporating smart tools and technologies into GSI has been identified as a natural next step for stormwater management. A plethora of smart stormwater management systems have been proposed, mostly by integrating sensing, control, communication, and computing capabilities. These advancements can augment the operation, performance, and capacity of existing or new infrastructure through enhanced data capture, analysis, and control of infrastructure systems. These methods have been tested in the realm of water management for monitoring, controlling, and managing water volume and quality, and for supporting decision-making practices in water distribution networks
[17][18][19][20][21][22][20,21,22,23,24,25]. Despite these strides, the integration of emergent smart technologies in GSI faces multiple challenges. One significant barrier is the lack of standardization in the terminology used in IoT literature, which impedes efficient information retrieval and summarization
[23][26]. For a concept to attain widespread dissemination, innovation, and further adaptation, it necessitates maturation, particularly when delineating requisite standards to orchestrate workflows across diverse applications. However, discerning the degree of relevance remains an intricate endeavor
[24][27]. In pragmatic applications, synchronization of proprietary formats across devices facilitates manufacturers in amalgamating data from heterogeneous formats, thereby engendering a standardized system
[25][26][28,29]. A judicious approach might encompass a comprehensive aggregation and classification of salient terminologies. This could subsequently be bolstered by promoting ubiquitous recognition and utilization of these terms, culminating in the standardization of protocols in the operational phase. The second obstacle lies in defining the relevance of the literature to the IoT, as the term “smart” might be restricted to a buzzword merely illustrating a new development trend. Consequently, this vague representation risks oversimplifying a plethora of related applications
[23][26]. “Smart” stormwater systems are defined as those that utilize the Internet of Things (IoT) and associated technologies to achieve more responsive, efficient, and sustainable management of stormwater runoff. This involves the integration of sensors, controllers, actuators, and wireless communication modules. By fitting stormwater management components such as rainwater harvesting and water quality monitoring equipment with these devices, cities can function as real-time, distributed treatment plants. These systems can be linked to existing stormwater infrastructure through reliable and cost-effective actuators, such as valves and pumps, allowing for precise water flow control. Moreover, real-time data on water quantity and quality are collected, stored in cloud databases, and subsequently analyzed for further network-wide distribution as required. This dynamic nature of “smart” systems, which can adapt their operations in response to individual storm events, sets them apart from traditional static stormwater infrastructure that does not offer such real-time monitoring and control capabilities
[27][30].
The term “IoT” denotes the information network resulting from interconnecting various sensing devices to the internet. The overarching objective of IoT is to facilitate connections and interactions between people and objects through an information network
[28][34].
“Smart technology” is characterized by the ability to sense, monitor (collect data), communicate, manage, analyze, integrate, regulate, or optimize equipment in a methodical manner. This broad category encompasses standalone devices with inherent “smart” functionalities as well as technologies that can be retrofitted to improve the operational efficiency of other tools or networks. Owing to the diverse range of technologies encompassed within “smart technologies”, it becomes challenging to collate all applications. Furthermore, varying degrees of “smartness” may exist, necessitating the discernment of what can be technically classified as “smart”
[23][26].
The term “smart” finds its roots in the established research field of real-time control (RTC) for stormwater management
[23][29][30][31][32][26,35,36,37,38]. RTC is predicated on the continuous monitoring of process data (such as water levels and flow) and dynamic adjustments of flow conditions using flow control devices (e.g., pumps, sluice gates, and movable weirs) for the real-time management of existing urban design systems
[33][34][39,40]. RTC systems can be classified as local control systems or system-wide control systems, based on their complexity and control scope
[33][35][39,41]. RTC potentially offers a cost-effective solution, contingent upon the system type and scale
[36][42].
Information and Communication Technology (ICT) refers to the technical and application systems leveraging contemporary information technologies such as computers, communication, and network technology for acquiring, processing, transmitting, and sharing information. ICT’s utility extends across multiple sectors, including data collection, monitoring, intelligent control, and optimization in stormwater management systems.
An active control system involves the use of a device, such as an actuator, to influence an asset in some way. Either local or global control systems may drive the actuator. Notably, assets utilizing mechanical principles, such as vortex flow controls to regulate flow velocities, are not included in active control
[23][26].
2. Internet of Things Technologies in Green Stormwater Infrastructure
The application scales of GSI are diverse and can be categorized into four distinct approaches. At the property level, the focus lies on green roofs and smart rain barrels, while bioretention systems are utilized for drainage at the street level. Stormwater detention ponds have a broader scope of application, ranging from neighborhood to watershed scales. An overview of these strategies’ design, operation, and experimental results, in addition to how IoT technology intervenes in each to enhance existing beneficial effects or to broaden the range of potential applications for the device, is presented [37][67].
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Green roofs
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Urban expansion often results in an increase in impervious surface area, disrupting natural water cycles and contributing to the prevalent urban challenges of flooding and urban heat islands. In contemporary cities, rooftops constitute approximately 40–50% of the total impervious surface area. GSI, including green roofs, is broadly acknowledged as a best practice for stormwater management. Green roofs offer additional benefits such as mitigation of urban heat island effects
[38][39][68,69], and building energy savings through evapotranspiration and insulation
[40][41][42][70,71,72]. However, plant health is pivotal to the success of green roofs, and negligence during prolonged drought can lead to adverse impacts. Traditional rainwater harvesting systems can also encounter limitations
[31][43][44][37,73,74]. Hence, IoT technology can be leveraged for tasks such as monitoring soil conditions or irrigating plants.
The use of IoT technology in the context of green roofs is primarily observed in the monitoring and optimization of these systems for enhanced performance. Research indicates that green roofs have the capacity to hold stormwater, thereby mitigating peak flows and runoff
[45][46][47][75,76,77]. Principato et al.
[48][78] examined the use of movable gates with RTC in an urban basin to reduce combined sewer overflows, comparing scenarios using IoT and RTC with passive green roofs. They constructed a remote monitoring system to measure evapotranspiration from a large green roof test patch using a modified weighing lysimeter
[48][78]. In another study
[42][72], a large green roof test plot was monitored remotely to measure evapotranspiration using a customized weighing lysimeter. The system included a network of digital load cells communicating with a microcomputer via the i2c protocol, uploading data to cloud storage regularly. The real-time data capture of test module ET rates endorsed the significance of active sensor systems in advancing green roof technology and integrating ET performance into the design process. These findings imply that advancements in green roof performance monitoring technology could allow for more efficient deployment and maintenance. Extended green roofs, also known as passive green roofs, are designed to require less irrigation and maintenance. A previous study on RTC at the same basin reported that the arrangement coupling RTC with a passive green roof was most effective in reducing overflows
[49][79].
Green roofs operated by RTC can retain water for an extended duration by closing a control valve, which enhances the heat reduction impact and generates anaerobic zones for water treatment
[37][50][51][67,80,81]. Similar outcomes can be achieved by merging various configurations of RTC sluice gates with scenarios where the system includes green infrastructure (e.g., green roofs, permeable paving)
[52][59].
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Smart rain barrels
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Rain barrels serve as compact rainwater collection devices, typically positioned under a house’s gutter to accumulate rainwater from the roof. This collected rainwater finds utility in nonpotable applications such as watering gardens, irrigating lawns, or washing vehicles. Rain barrels principally function to reduce rainwater flow into drains, consequently alleviating pressure on city drainage systems. An advancement on this conventional technology is the Smart Rain Barrel (SRB), an IoT-empowered microstorage system specifically designed to enable sophisticated rainwater harvesting methods. It typically comprises a standard rain barrel paired with a remotely controllable release valve, forming a control system that enables novel modes of operation. Communication modules and other auxiliary components may also be included.
SRB has been extensively explored in a series of studies conducted by Oberascher, M. et al.
[50][51][53][54][80,81,82,83]. In one of these investigations, the SRB was incorporated into a smart city pilot project that monitored every water inflow and outflow on the campus of the University of Innsbruck in Austria. The study employed weather forecasts and time-controlled filling levels of different GSI structures, along with connected sewer systems, for RTC. It was demonstrated that installation location and the storage capacity of the rain barrels could result in flood reduction ranging from 18 to 40%, even though only a rudimentary automated control system was employed
[53][82]. Another study
[55][84] aimed to address the limitations of small water storage capacity and to leverage high-resolution weather forecasts to increase the retention volume while ensuring adequate rainwater collection for irrigation. The research built upon existing SRB models to scrutinize the impact of hypothetical SRB retrofits on the urban water infrastructure (both drainage and water supply systems) of an Alpine city with 2900 residents. The open-source program “Smartin” was developed to merge Python programs SWMM5 and EPANET2 into a coupled model. The study discovered that compared to an unmanaged rain barrel, simple control strategies could significantly augment the performance of an integrated system. For example, such strategies were found to decrease combined sewer overflows and water demand
[56][85].
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Bioretention cells
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Bioretention cells serve as water treatment systems that are either naturally occurring or artificially engineered. They are usually characterized by a biodiverse environment such as a wetland, pond, or flooded area
[57][86]. Employing the mechanisms intrinsic to biodiversity and natural ecosystems, bioretention cells purify and store water. They achieve this by transforming pollutants and nutrients within the water into biomass and sediment, aided by the actions of plants, algae, microorganisms, and other organisms
[58][87].
These water treatment systems not only curtail water pollutants but also regulate water flow and quality, thereby enhancing the water’s overall condition. Their applications range from urban water management and ecological restoration to flood control, making them a sustainable solution for water management
[59][88]. Bioretention cells are particularly advantageous and show immense potential in addressing stormwater quality. However, the efficacy of these systems in treating water quality varies across studies. Such variations in outcomes are often attributed to suboptimal design, inconsistent pollutant loading, and the challenge of removing lower pollutant concentrations compared to higher ones
[57][58][59][86,87,88].
One study
[60][89] analyzed multiple RTC schemes to improve water quality in bioretention towers, indicating that water quality improvement is contingent on nutrient presence. Another key aspect of bioretention cell design relates to effluent storage for reuse, requiring effective treatment of contaminants and pathogens to adhere to region-specific reuse legislation
[61][62][63][90,91,92]. Another research endeavor
[63][92] investigated two cost-effective strategies to treat stormwater for collection and reuse through bioretention basins. The authors discerned that RTC enabled bioretention to lessen the adverse impacts of both short- and long-term drought periods and to mitigate the effects of mass influx on fecal microbial processing. Yet, the study did not ascertain how inaccurate predictions influence the bioretention performance of RTC. As a result, there is a need for additional research to evaluate the feasibility of utilizing rainfall forecasting models for RTC-based bioretention
[37][67].
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Stormwater detention ponds
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Traditional stormwater detention ponds are designed to mitigate flooding. In one study
[64][93], a two-stage detention basin was constructed. The upper stage remains dry except during storm events, while the lower stage includes a small outlet to facilitate pollutant settling. Dry detention basins, which remain dry even during rainstorms, have also been considered to prevent the propagation of mosquitoes in stagnant water
[65][94]. Such factors must be taken into account in planning for both conventional and sustainable drainage systems
[66][67][95,96]. Leveraging the power of IoT in stormwater detention ponds opens up new possibilities for effective stormwater management. By integrating sensors, actuators, and wireless communication devices, real-time monitoring of weather conditions and rainfall parameters can be achieved, allowing dynamic flow control at multiple sites
[27][68][30,97]. This smart system integration can elevate the capabilities of stormwater ponds, making their management strategies more adaptable and responsive to changing climatic and environmental conditions
[69][70][71][72][53,98,99,100].
Smart stormwater ponds primarily control flooding by retaining a portion of incoming water and regulating outflows
[73][101]. The volume of water they discharge is largely determined by the type and size of the outlet structure. Typically, stormwater detention ponds incorporate both a secondary overflow outlet to manage pond storage during the rainy season, and at least one primary outlet to control regulated flow from the pond, such as a weir, orifice, or riser-type outflow
[74][102]. Stormwater detention ponds are further classified as in-line and off-line. Off-line basins do not interfere with sediment movement and fish migration, unlike in-line basins that can cause upstream flooding due to water accumulation
[73][101]. The integration of IoT in off-line basins enables the optimization of the drainage system’s performance based on its state, primarily controlling inflow and initiating diversion after the river flow reaches a critical threshold. For example, one study
[75][48] compared flood reduction between active flow diversion control and passive structural control applied to an off-line detention basin. The results showed a 2–3-fold higher flood reduction with active control.
3. Conclusions
The integration of IoT with GSI is an emerging field with remarkable potential to revolutionize urban stormwater management. While the field is still in its early stages, significant contributions from countries including the United States, Canada, Italy, China, and Australia indicate a worldwide recognition of the potential of IoT-enhanced GSI. The versatility of GSI applications, including green roofs, smart rain barrels, bioretention systems, and stormwater detention ponds, allows for diverse implementation scales. IoT technology enhances these applications by broadening their range, improving their efficiency, and offering RTC and optimization. Furthermore, the integration of IoT and GSI is expected to provide resilience in the face of environmental uncertainties and optimize rainwater harvesting and utilization. However, despite the substantial potential of the IoT–GSI intersection, the existing body of research reveals several limitations and challenges. These include the necessity for additional monitoring and control mechanisms, the development of predictive optimization strategies, and the requirement of extensive scalability for smaller applications such as green roofs and rain barrels to make a significant impact. Additionally, a comprehensive cost–benefit analysis must be considered for the successful and widespread adoption of these technologies.
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