Table of Contents

    Topic review

    Green Stormwater Infrastructure

    View times: 29
    Submitted by: Nicole Barclay

    Definition

    Green stormwater infrastructure (GSI), a nature-inspired, engineered stormwater management approach that mimics natural hydrological processes to improve water quality and reduce localized flooding events.

    1. Introduction

    Urbanization can affect the hydrologic functions of urban watersheds and precipitation patterns [1][2][3][4][5]. The consequential increased use of impervious surfaces results in substantial increments of stormwater runoff volume and peak flow [6]. Thus, the transition from the conventional approach into a more sustainable stormwater management paradigm which includes green stormwater infrastructure (GSI), is indispensable to reducing substantial environmental, economic, and social damage [7][8][9]. Hence, there is also a need to understand the hindrances and limitations in GSI implementation. 

    GSI offers a promising solution to stormwater management by mimicking natural hydrological processes to reduce localized flooding events and water quality improvement through decentralized natural or engineered processes to treat stormwater runoff at its source [10]. In the US (United States), awareness of GSI has slowly increased over the past two decades. Its historical progress in stormwater management and background knowledge is documented in several in-depth publications [11][12][13][14]. Research teams across nations have developed various GSI practices and in addition, retrofits and hybrid measures on different spatial scales (such as watershed scale and site scale, etc.) with diverse primary purposes have been developed [15][16][17][18][19][20]. The details on these practices are well documented in the literature [21][22][23][24][25][26][27][28].

    Numerous studies have evaluated the performance of GSI, particularly in economic and technical aspects [14][29][30][31][32]. GSI provides extra benefits to the community, such as raising property values, enriching life quality, and providing adaptable climate resilience [33][34][35]. Urban stormwater management has advanced gradually over the last two decades, thus various terminologies are used to define new principles and practices, where the concepts behind them often overlap [14][36]. Using these different terms may reduce effective communication in certain circumstances, such as when documenting all the alternative stormwater practices used in the US to assess their performance in general [36]. To avoid confusion, the term GSI was used throughout this work in referring to all types of multi-purpose structural stormwater management practices that involve natural processes for runoff volume and water quality control.

    Despite the progress, there are limited study efforts on non-technical factors, such as public perceptions and knowledge, that could explain the slow advancement in the wide adaptation of GSI to the desired level for stormwater management and sustainability capacity building [37]. The contradiction between the low implementation rate of GSI in major regions of the US and the actual demand to address climate change impacts suggests that certain factors are hindering the relevant decision-making processes [38][39]. Furthermore, a study discovered the mismatch in the percentage of their survey participants that expressed an intention to support GSI and the number of those who actually adopted GSI [40]. This result is in agreement with the findings in an exhaustive review [41]. Irrational decision-making behaviors in energy-related decisions have been interpreted through the cognitive bias perspective [42][43], where cognitive biases can be defined as a belief that hampers one’s ability to make rational decisions given the facts and evidence [44]. It has been supported by various studies that cognitive biases are influential in decision making and planning [44]. Yet, little attention has been given to the potential influence of cognitive biases in GSI implementation, despite numerous studies on perceptions of various GSI stakeholder groups [45][46][47]. This study aims to bridge this knowledge gap.

    Historically, quantitative decision support tools have been developed with the main aim to maximize GSI performance to control runoff and water pollution and to be cost-effective [48][49][50][51][52]. On the other hand, despite the extensive attempts made to expand the assessment work to include the social aspect of decision support [17][48][53][54][55][56][57][58][59][60][61][62][63][64], they lack a deeper understanding of the public perceptions and associated cognitive bias perspective to resolve the implementation dilemma from a bottom-up approach [65] as examined in other environmental issues [43][44]. This shortcoming can affect the expected outcomes envisioned by major decision-makers [42][66]. This study focuses on the barriers that could be linked to biased perceptions due to social factors in GSI development and implementation.

    This work was conducted to examine the relevant social factors through the lens of cognitive biases, which may lead to implementation barriers during GSI adoption processes. The scope of social factors can vary significantly as they are commonly assessed in combination with factors from other dimensions, such as socio-ecological, social-cultural, socio-economic, and socio-technical factors [10][67][68][69][70]. We use a concept adapted from Gifford and Nilsson [71] to define social factors as the internal differences among people and the contextual factors that define them in this study. This study aims to understand the potential connections of cognitive biases with these barriers, and to recommend an approach to analyze and address the associated problems. Studies have been conducted to analyze cognitive biases with agent-based modeling (ABM) in various contexts [72][73][74]. However, no study has done a similar analysis in the context of GSI implementation. ABM is a methodology that can incorporate the autonomy, heterogeneity, and adaptability of individuals in a social system to study the resulting global patterns through a bottom-up approach [75][76]. It is also an approach that can carry exploratory simulations for a deeper understanding of the underlying adaptive behaviors and interactions that could lead to the emergence of phenomena that was previously overlooked [40]. However, the models developed solely based on social and physical science are usually fragmented in their fields, rely on qualitative analysis, or are difficult to incorporate into quantitative models [77].

    2. Identified Social Barriers to GSI Implementation

    The barriers to GSI have been studied by numerous international research teams, ranging from individual perceptions and attitudes, financial burdens, resource allocations, and governance rigidity to conflicts across institutions [45][67][79][83][84][85][86]. Barriers originating from social factors may be harder to address, as the values of which are usually difficult to quantify yet should not be overlooked [55][58][65]. Barriers primarily identified as associated with social factors, in terms of their potential influence on the implementation of GSI, are attributed to three main categories from the literature. They mostly cover governance discord, public participation, and demographic constraints (Table 1). Governance refers to the inconsistent strategies among or within governance entities; public participation refers to the involvement of the public in the decision-making of GSI regulations and collaborations; and demographic constraints refers to the general demographic factors, social norms, and perceived environmental concerns. However, there always is a possibility of unrecognized social factors in the published studies. For example, though not directly addressing the issues in stormwater management adaptation, a study brought forth the dilemma in regenerating historical cities of which preserving the historical cores were paramount [87]. It is thinkable that advancing GSI in such areas may encompass greater complexities than others. Additionally, the underlying interrelations across infrastructure sectors and even industries are also likely to influence sustainable decision-making in general [88][89].

    Table 1. Relevant social factors that could influence the implementation of GSI in the US.

    Social Barriers

    Barrier Subcategories

    GSI Types

    Spatial Scales

    Location

    Stakeholder

    Study Methods

    Source

    Demographic constraints & public engagement

    Race, ownership status, relevant knowledge of GSI, knowledge dissemination platform

    Rainwater harvesting, pervious paving, rain gardens, lawn depression

    Sub-watershed

    Two sub-watersheds
    in Chesapeake Bay watershed

    Private landowners

    Knowledge, attitude,
    and practice questionnaire

    [90]

    Age, education, homeownership, prior experience of floods, lack of awareness, underuse of social capital

    Rain barrels, rain gardens, and permeable pavement

    Region

    Knoxville, TN

    Private landowners (households)

    Survey

    [91]

    Governance

    Limited focus on the multifactional of GSI to respond to local needs, lack of interdepartmental collaboration, and private-public partnership

    Green alleys with various GSI features

    Region

    Various locations in the US

    Government agencies, non-governmental organizations (NGOs),
    community groups

    Narrative analysis

    [34]

    Conflicting visions in hydro-social relations

    GSI in general

    Region

    Chicago, IL, and Los Angeles, CA

    Government entities, NGOs

    Interviews, participant observation, literature review, survey

    [92]

    Leadership in transitioning governance (informal, multiorganizational)

    GSI in general

    Region

    Ohio

    Community
    NGOs, environmental NGOs/land trust, federal government, local government/regional
    authority, university

    /contractor

    Social network analysis survey

    [93]

    Departmental silos (stakeholders’ multiple and competing social perspectives)

    GSI in general

    Region

    Chicago, IL

    NGOs, governmental entities

    Q-methodology

    [94]

    Tensions and convergences among different management strategies

    GSI in general

    Region

    Pittsburgh, PA

    Community organizations, municipalities, advocacy
    groups

    Interviews, participant observation

    [95]

    Conflicting perceptions, implementation priority, limited focus on the multifunctionality during planning

    GSI in general

    Region

    New York, NY

    Agencies,
    city departments, national and local nonprofits, research institutions

    Spatial analyses, survey, interview, participant observation

    [78]

    Inequity for disadvantaged communities

    GSI in general

    Sub-watershed

    Los Angeles, CA

    Government agencies, non-profits, community organizations, and others

    Statistical analyses

    [96]

    Public engagement

    Failing to recognize the values of social capitals for long-term productivity

    Rain gardens, rain barrels

    Household site

    Cincinnati, OH

    Landowners

    Experimental reverse auction

    [97]

    Perception (status quo bias)

    Rain gardens, bio-swales, green alleys with permeable pavement

    Region

    Cincinnati, OH, and Seattle, WA

    Engineering graduate students

    Functional near-infrared spectroscopy

    [38][97]

    Ineffective information dissemination, underuse of social capital

    Rain barrels, rain gardens,
    permeable pavement

    Region

    Washington DC

    Homeowners

    Voluntary stormwater retrofit program with statistical analyses

    [98]

    Stormwater context (perception of neighborhood-level challenges, town-level stormwater regulation)

    Rainwater harvesting, rain gardens, permeable
    pavers, infiltration trenches, and tree box filters

    Cross-scale

    Vermont

    Residents

    Statewide survey

    [79]

    Depreciation of community involvement (expertise, education)

    GSI in general

    Region

    Houston, TX

    Researchers, community

    Participatory action research

    [99]

    Governance & public engagement

    Lack of awareness and responsibility for maintenance, education programs not aligned with local preferences

    Stormwater ponds

    Community

    Southwest Florida

    Homeowners, governmental entities

    Survey, interviews

    [100]

    Lack of awareness, ineffective regulation enforcement

    Stormwater ponds

    Region

    Manatee County, FL

    Landscape professionals, residents, government agents

    Interviews, surveys, participant observation, and literature review

    [101]

    Lack of awareness, understanding, and sense of responsibility; geographic disconnection between watersheds and governing
    entities; fragmentation of responsibility
    among stakeholder groups

    GSI in general

    Region

    Cleveland, OH, and Milwaukee, WI

    Practitioners (regional sewer districts, local governments, community development organizations)

    Interviews

    [28]

    Lack of awareness and adaptivity in policies to prioritize GSI measures to align with local values

    Bioswales, green roofs, street trees, parks &
    natural areas, community gardens, and permeable playgrounds

    Region

    New York, NY

    Residents and practitioners (individuals
    professionally engaged in the siting, design, maintenance,
    public engagement, and/or monitoring of GSI programs)

    Preference assessment survey and semi-structured interviews

    [46]

    Outdated regulatory constructs, conflicted views among gray and green advocates, jurisdictional overlap, influences of social media coverage, leadership gaps or influence of lobbying

    GSI in general

    \

    USA

    Residents, governmental entities, engineers

    Narrative analysis

    [102]

    The unclear distribution of responsibilities among stakeholders can impede the decision-making processes associated with GSI implementation. Particularly, the general public’s involvement is the fundamental building block that could be influential in shaping the direction of GSI implementation [17][28][47]. Dhakal and Chevalier [83] stated in their study that, above all challenges, cognitive barriers and socio-institutional factors should be the primary issue to focus on. Furthermore, the multi-sector benefits will only be nuanced if the public is not willing to implement GSI [103]. Similarly, one study stated that sustainable GSI implementation would necessitate the need for structured public participation and local partnerships. They emphasized that, in addition to putting more reach effort onto comprehensive cost-benefit evaluations on GSI, such needed engagement would fortress the networks of non-governmental organizations, county and state agencies, municipal sewer districts, and federal research support, which could lead to a faster adaptation of GSI on larger scales [104]. Therefore, the barriers to the general public to accept GSI are crucial to dissect these aforementioned disconnections and provide practical yet effective decision support. To date, there is a limited number of conceptual frameworks that capture social factors in GSI implementation processes (Table 2). Yet there still is a need for quantitative analysis measures for better decision support for case-based GSI adoption using standardized methods that could assist in horizontal comparison and further knowledge transfer. The frameworks listed in Table 2 were categorized based on their main purpose: Classification scheme (proposed to enhance terminology clarity), planning strategy (suggesting new approaches to be adopted in current management regimes), process conceptualization (promoting a better understanding of complex socio-infrastructure systems), and framework efficacy assessment (evaluating the existing frameworks’ usefulness in promoting GSI implementation).

    Table 2. Conceptual frameworks that consider social factors in GSI implementation processes.

    Framework Nature

    Social Factors

    Sub-Categories

    Stakeholders

    Method

    Scale

    Source

    Classification Scheme

    Governance, stakeholder engagement

    Stakeholder interactions, governance, political contexts

    Individuals and groups involved in rule-making processes, property owners

    Social-ecological services framework

    Cross-scale

    [54]

    Public engagement, governance

    Policy instrument assessment

    Citizens

    Policy instrumentations scheme

    Region

    [56]

    Public engagement, governance

    Ownership status, political power

    Governmental entities

    Topology framework

    Region

    [64]

    Planning Strategy

    Governance, demographic constraints

    Equitable GSI distribution, age, income, education, ownership status

    Governmental entities, residents

    Green infrastructure equity index

    Region

    [60]

    Public engagement, governance

    Multifunctional strategy, multisectoral communication

    All involved in decision-making processes

    Millennium ecosystem assessment classification-based framework

    Cross-scale

    [105]

    Governance, public engagement, demographic restraints

    Adaptive governance, stakeholder participation, inclusion

    Governance, nongovernmental organizations, communities, academia, industry

    Adaptive socio-hydrology framework

    Cross-scale

    [106]

    Public engagement

    Interdisciplinary collaboration, university-stakeholder partnership, institutional capacity

    Universities

    Integrated framework combining social-ecological dynamics, knowledge to action processes, organizational innovation

    Region

    [63]

    Process Conceptualization

    Public engagement

    Community participation in three themes (context, participation processes and outputs, and implementation results)

    City, federal government agencies, community residents, and community NGOs

    Public participation conceptual model

    Watershed

    [61]

    Public engagement, governance

    Low stakeholder buy-in, discoordination in management objectives and goal among stakeholders, lack of awareness

    Government researchers, stormwater managers, and community organizers

    Adaptive management framework

    Site

    [62]

    Governance, public engagement, demographic restraints

    Stakeholder interactions, governance and political contexts

    All that are involved in stormwater management

    Integrated structure-actor-water framework

    Cross-scale

    [55]

    Public engagement, governance

    Hybrid governance envisioning (management and monetary responsibilities)

    Regulatory agencies, residents

    Multi-criteria governance framework

    Cross-scale

    [17]

    Public engagement, governance

    Perceptions, stewardship, human-environment interactions

    Residents

    Coupled human and natural systems framework

    Region

    [58]

    Existing Framework Efficacy Assessment

    Governance

    Governance, capacity, urbanization rate, burden of disease, education rate, political instability

    Government agencies, NGOs

    City Blueprint® Approach

    Region

    [53]

    Public engagement, governance

    Community education and awareness campaign, multifunctional strategy

    Residents, governmental entities

    Socio-ecological framework

    Watershed

    [107]

    The entry is from 10.3390/hydrology8010010

    References

    1. Ntelekos, A.; Oppenheimer, M.; Smith, J.A.; Miller, A.J. Urbanization, climate change and flood policy in the United States. Clim. Chang. 2010, 103, 597–616.
    2. Blöschl, ; Ardoin-Bardin, S.; Bonell, M.; Dorninger, M.; Goodrich, D.; Gutknecht, D.; Matamoros, D.; Merz, B.; Shand, P.; Szolgay, J. At what scales do climate variability and land cover change impact on flooding and low flows? Hydrol. Process. 2007, 21, 1241–1247.
    3. Brath, ; Montanari, A.; Moretti, G. Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty). J. Hydrol. 2006, 324, 141–153.
    4. Recanatesi, ; Petroselli, A. Land Cover Change and Flood Risk in a Peri-Urban Environment of the Metropolitan Area of Rome (Italy). Water Resour. Manag. Int. J. Publ. Eur. Water Resour. Assoc. 2020, 34, 4399–4413.
    5. Wang, ; Liu, J.; Kubota, J.; Chen, L. Effects of land‐use changes on hydrological processes in the middle basin of the Heihe River, northwest China. Hydrol. Process. Int. J. 2007, 21, 1370–1382.
    6. Barbosa, E.; Fernandes, J.N.; David, L.M. Key issues for sustainable urban stormwater management. Water Res. 2012, 46, 6787–6798.
    7. Howard, K.; Bowen, M.P.; Antoine, R.W. Reducing Phosphorus Contamination in Stormwater Runoff. In Proceedings of the Howard2016ReducingPC, Norfolk, VA, USA, 4 March 2016.
    8. McIntyre, K.; Lundin, J.I.; Cameron, J.R.; Chow, M.I.; Davis, J.W.; Incardona, J.P.; Scholz, N.L. Interspecies variation in the susceptibility of adult Pacific salmon to toxic urban stormwater runoff. Environ. Pollut. 2018, 238, 196–203.
    9. Tsihrintzis, A.; Hamid, R. Modeling and management of urban stormwater runoff quality: A review. Water Resour. Manag. 1997, 11, 136–164.
    10. Chini, M.; Canning, J.F.; Schreiber, K.L.; Peschel, J.M.; Stillwell, A.S. The Green Experiment: Cities, Green Stormwater Infrastructure, and Sustainability. Sustainability 2017, 9, 105, doi:10.3390/su9010105.
    11. Walsh, J.; Booth, D.B.; Burns, M.J.; Fletcher, T.D.; Hale, R.L.; Hoang, L.N.; Livingston, G.; Rippy, M.A.; Roy, A.H.; Scoggins, M.; et al. Principles for urban stormwater management to protect stream ecosystems. Freshw. Sci. 2016, 35, 398–411, doi:10.1086/685284.
    12. Roy, H.; Wenger, S.J.; Fletcher, T.D.; Walsh, C.J.; Ladson, A.R.; Shuster, W.D.; Thurston, H.W.; Brown, R.R. Impediments and solutions to sustainable, watershed-scale urban stormwater management: Lessons from Australia and the United States. Environ. Manag. 2008, 42, 344–359.
    13. NRC. Urban Stormwater Management in the United States; National Academies Press: Washington, DC, USA,
    14. Li, ; Peng, C.; Chiang, P.-C.; Cai, Y.; Wang, X.; Yang, Z. Mechanisms and applications of green infrastructure practices for stormwater control: A review. J. Hydrol. 2019, 568, 626–637.
    15. Yang, ; Li, S.J. Green Infrastructure Design for Stormwater Runoff and Water Quality: Empirical Evidence from Large Watershed-Scale Community Developments. Water 2013, 5, 2038–2057, doi:10.3390/w5042038.
    16. Wise, ; Braden, J.; Ghalayini, D.; Grant, J.; Kloss, C.; MacMullan, E.; Morse, S.; Montalto, F.; Nees, D.; Nowak, D. Integrating valuation methods to recognize green infrastructure’s multiple benefits. Low Impact Dev. 2010, 2010, 1123–1143.
    17. Porse, Stormwater governance and future cities. Water 2013, 5, 29–52.
    18. Cherrier, ; Klein, Y.; Link, H.; Pillich, J.; Yonzan, N. Hybrid green infrastructure for reducing demands on urban water and energy systems: A New York City hypothetical case study. J. Environ. Stud. Sci. 2016, 6, 77–89.
    19. Malinowski, A.; Wu, J.S.; Pulugurtha, S.; Stillwell, A.S. Green Infrastructure Retrofits with Impervious Area Reduction by Property Type: Potential Improvements to Urban Stream Quality. J. Sustain. Water Built Environ. 2018, 4, 04018012.
    20. Golden, E.; Hoghooghi, N. Green infrastructure and its catchment‐scale effects: An emerging science. Wiley Interdiscip. Rev. Water 2018, 5, e1254.
    21. Berndtsson, C. Green roof performance towards management of runoff water quantity and quality: A review. Ecol. Eng. 2010, 36, 351–360.
    22. Chui, F.M.; Liu, X.; Zhan, W. Assessing cost-effectiveness of specific LID practice designs in response to large storm events. J. Hydrol. 2016, 533, 353–364.
    23. Jennings, A.; Adeel, A.A.; Hopkins, A.; Litofsky, A.L.; Wellstead, S.W. Rain barrel–urban garden stormwater management performance. J. Environ. Eng. 2012, 139, 757–765.
    24. Liu, ; Sample, D.J.; Bell, C.; Guan, Y. Review and Research Needs of Bioretention Used for the Treatment of Urban Stormwater. Water 2014, 6, 1069–1099.
    25. Saraswat, ; Kumar, P.; Mishra, B.K. Assessment of stormwater runoff management practices and governance under climate change and urbanization: An analysis of Bangkok, Hanoi and Tokyo. Environ. Sci. Policy 2016, 64, 101–117.
    26. Tavakol-Davani, ; Goharian, E.; Hansen, C.H.; Tavakol-Davani, H.; Apul, D.; Burian, S.J. How does climate change affect combined sewer overflow in a system benefiting from rainwater harvesting systems? Sustain. Cities Soc. 2016, 27, 430–438.
    27. Vacek, ; Struhala, K.; Matějka, L. Life-cycle study on semi intensive green roofs. J. Clean. Prod. 2017, 154, 203–213.
    28. Keeley, ; Koburger, A.; Dolowitz, D.P.; Medearis, D.; Nickel, D.; Shuster, W. Perspectives on the Use of Green Infrastructure for Stormwater Management in Cleveland and Milwaukee. Environ. Manag. 2013, 51, 1093–1108, doi:10.1007/s00267-013-0032-x.
    29. Copeland, Green Infrastructure and Issues in Managing Urban Stormwater; Congressional Research Service: Washington, DC, USA, 2016.
    30. Zhang, ; Chui, T.F.M. A comprehensive review of spatial allocation of LID-BMP-GI practices: Strategies and optimization tools. Sci. Total Environ. 2018, 621, 915–929.
    31. Eckart, ; McPhee, Z.; Bolisetti, T. Performance and implementation of low impact development—A review. Sci. Total Environ. 2017, 607, 413–432.
    32. Li, ; Fletcher, T.D.; Duncan, H.P.; Burns, M.J. Can stormwater control measures restore altered urban flow regimes at the catchment scale? J. Hydrol. 2017, 549, 631–653.
    33. Gordon, L.; Quesnel, K.J.; Abs, R.; Ajami, N.K. A case-study based framework for assessing the multi-sector performance of green infrastructure. J. Environ. Manag. 2018, 223, 371–384, doi:10.1016/j.jenvman.2018.06.029.
    34. Newell, P.; Seymour, M.; Yee, T.; Renteria, J.; Longcore, T.; Wolch, J.R.; Shishkovsky, A. Green Alley Programs: Planning for a sustainable urban infrastructure? Cities 2013, 31, 144–155, doi:10.1016/j.cities.2012.07.004.
    35. Venkataramanan, ; Packman, A.I.; Peters, D.R.; Lopez, D.; McCuskey, D.J.; McDonald, R.I.; Miller, W.M.; Young, S.L. A systematic review of the human health and social well-being outcomes of green infrastructure for stormwater and flood management. J. Environ. Manag. 2019, 246, 868–880, doi:10.1016/j.jenvman.2019.05.028.
    36. Fletcher, D.; Shuster, W.; Hunt, W.F.; Ashley, R.; Butler, D.; Arthur, S.; Trowsdale, S.; Barraud, S.; Semadeni-Davies, A.; Bertrand-Krajewski, J.-L. SUDS, LID, BMPs, WSUD and more–The evolution and application of terminology surrounding urban drainage. Urban Water J. 2015, 12, 525–542.
    37. Thornton, ; Laurin, C. Soft sciences and the hard reality of lake management. Lake Reserv. Manag. 2005, 21, 203–208.
    38. Hu, ; Shealy, T. Overcoming Status Quo Bias for Resilient Stormwater Infrastructure: Empirical Evidence in Neurocognition and Decision-Making. J. Manag. Eng. 2020, 36, doi:10.1061/(asce)me.1943–5479.0000771.
    39. Olorunkiya, ; Fassman, E.; Wilkinson, S. Risk: A fundamental barrier to the implementation of low impact design infrastructure for urban stormwater control. J. Sustain. Dev. 2012, 5, 27.
    40. Rasoulkhani, ; Logasa, B.; Presa Reyes, M.; Mostafavi, A. Understanding fundamental phenomena affecting the water conservation technology adoption of residential consumers using agent-based modeling. Water 2018, 10, 993.
    41. Battaglio, P., Jr.; Belardinelli, P.; Bellé, N.; Cantarelli, P. Behavioral public administration ad fontes: A synthesis of research on bounded rationality, cognitive biases, and nudging in public organizations. Public Adm. Rev. 2019, 79, 304–320.
    42. Klotz, Cognitive biases in energy decisions during the planning, design, and construction of commercial buildings in the United States: An analytical framework and research needs. Energy Effic. 2011, 4, 271–284.
    43. Zhou, ; Chen, H.; Xu, S.; Wu, L. How cognitive bias and information disclosure affect the willingness of urban residents to pay for green power? J. Clean. Prod. 2018, 189, 552–562.
    44. Acciarini, ; Brunetta, F.; Boccardelli, P. Cognitive biases and decision-making strategies in times of change: A systematic literature review. Manag. Decis. 2020, doi:10.1108/MD-07-2019-1006.
    45. Barnhill, ; Smardon, R. Gaining ground: Green infrastructure attitudes and perceptions from stakeholders in Syracuse, New York. Environ. Pract. 2012, 14, 6–16.
    46. Miller, M.; Montalto, F.A. Stakeholder perceptions of the ecosystem services provided by Green Infrastructure in New York City. Ecosyst. Serv. 2019, 37, 100928.
    47. O’Donnell, ; Maskrey, S.; Everett, G.; Lamond, J. Developing the implicit association test to uncover hidden preferences for sustainable drainage systems. Philos. Trans. R. Soc. A 2020, 378, 20190207.
    48. Wu, ; Song, H.; Wang, J.; Friedler, E. Framework, Procedure, and Tools for Comprehensive Evaluation of Sustainable Stormwater Management: A Review. Water 2020, 12, 1231.
    49. Van Oijstaeijen, ; Van Passel, S.; Cools, J. Urban green infrastructure: A review on valuation toolkits from an urban planning perspective. J. Environ. Manag. 2020, 267, doi:10.1016/j.jenvman.2020.110603.
    50. Pellicani, ; Parisi, A.; Iemmolo, G.; Apollonio, C. Economic risk evaluation in urban flooding and instability-prone areas: The case study of San Giovanni Rotondo (Southern Italy). Geosciences 2018, 8, 112.
    51. Carrera, ; Standardi, G.; Bosello, F.; Mysiak, J. Assessing direct and indirect economic impacts of a flood event through the integration of spatial and computable general equilibrium modelling. Environ. Model. Softw. 2015, 63, 109–122.
    52. Huizinga, ; De Moel, H.; Szewczyk, W. Global Flood Depth-Damage Functions: Methodology and the Database with Guidelines; Joint Research Centre (Seville Site): Sevilla, Spain, 2017.
    53. Feingold, ; Koop, S.; van Leeuwen, K. The City Blueprint Approach: Urban Water Management and Governance in Cities in the U.S. Environ. Manag. 2018, 61, 9–23, doi:10.1007/s00267-017-0952-y.
    54. Flynn, D.; Davidson, C.I. Adapting the social-ecological system framework for urban stormwater management: The case of green infrastructure adoption. Ecol. Soc. 2016, 21, doi:10.5751/es-08756-210419.
    55. Hale, L.; Armstrong, A.; Baker, M.A.; Bedingfield, S.; Betts, D.; Buahin, C.; Buchert, M.; Crowl, T.; Dupont, R.R.; Ehleringer, J.R.; et al. iSAW: Integrating Structure, Actors, and Water to study socio-hydro-ecological systems. Earths Future 2015, 3, 110–132, doi:10.1002/2014ef000295.
    56. Lieberherr, ; Green, O.O. Green Infrastructure through Citizen Stormwater Management: Policy Instruments, Participation and Engagement. Sustainability 2018, 10, doi:10.3390/su10062099.
    57. Schirmer, ; Dyer, F. A framework to diagnose factors influencing proenvironmental behaviors in water-sensitive urban design. Proc. Natl. Acad. Sci. USA 2018, 115, E7690–E7699, doi:10.1073/pnas.1802293115.
    58. Shandas, Neighborhood change and the role of environmental stewardship: A case study of green infrastructure for stormwater in the City of Portland, Oregon, USA. Ecol. Soc. 2015, 20, doi:10.5751/es-07736-200316.
    59. William, ; Garg, J.; Stillwell, A.S. A game theory analysis of green infrastructure stormwater management policies. Water Resour. Res. 2017, 53, 8003–8019, doi:10.1002/2017wr021024.
    60. Heckert, ; Rosan, C.D. Developing a green infrastructure equity index to promote equity planning. Urban For. Urban Green. 2016, 19, 263–270, doi:10.1016/j.ufug.2015.12.011.
    61. Barclay, ; Klotz, L. Role of community participation for green stormwater infrastructure development. J. Environ. Manag. 2019, 251, doi:10.1016/j.jenvman.2019.109620.
    62. Chaffin, C.; Shuster, W.D.; Garmestani, A.S.; Furio, B.; Albro, S.L.; Gardiner, M.; Spring, M.; Green, O.O. A tale of two rain gardens: Barriers and bridges to adaptive management of urban stormwater in Cleveland, Ohio. J. Environ. Manag. 2016, 183, 431–441, doi:10.1016/j.jenvman.2016.06.025.
    63. Hart, D.; Bell, K.P.; Lindenfeld, L.A.; Jain, S.; Johnson, T.R.; Ranco, D.; McGill, B. Strengthening the role of universities in addressing sustainability challenges: The Mitchell Center for Sustainability Solutions as an institutional experiment. Ecol. Soc. 2015, 20, doi:10.5751/es-07283-200204.
    64. Young, ; Zanders, J.; Lieberknecht, K.; Fassman-Beck, E. A comprehensive typology for mainstreaming urban green infrastructure. J. Hydrol. 2014, 519, 2571–2583, doi:10.1016/j.jhydrol.2014.05.048.
    65. Baptiste, K.; Foley, C.; Smardon, R. Understanding urban neighborhood differences in willingness to implement green infrastructure measures: A case study of Syracuse, NY. Landsc. Urban Plan. 2015, 136, 1–12.
    66. Das, ; Teng, B.S. Cognitive biases and strategic decision processes: An integrative perspective. J. Manag. Stud. 1999, 36, 757–778.
    67. Turner, K.; Jarden, K.; Jefferson, A. Resident perspectives on green infrastructure in an experimental suburban stormwater management program. Cities Environ. 2016, 9, 4.
    68. Tayouga, J.; Gagné, S.A. The socio-ecological factors that influence the adoption of green infrastructure. Sustainability 2016, 8, 1277.
    69. Kati, ; Jari, N. Bottom-up thinking—Identifying socio-cultural values of ecosystem services in local blue–green infrastructure planning in Helsinki, Finland. Land Use Policy 2016, 50, 537–547.
    70. Staddon, ; Ward, S.; De Vito, L.; Zuniga-Teran, A.; Gerlak, A.K.; Schoeman, Y.; Hart, A.; Booth, G. Contributions of green infrastructure to enhancing urban resilience. Environ. Syst. Decis. 2018, 38, 330–338.
    71. Gifford, ; Nilsson, A. Personal and social factors that influence pro‐environmental concern and behaviour: A review. Int. J. Psychol. 2014, 49, 141–157.
    72. Sobkowicz, Opinion Dynamics Model Based on Cognitive Biases of Complex Agents. J. Artif. Soc. Soc. Simul. 2018, 21, 8.
    73. Chen, -H.; Gostoli, U. Behavioral macroeconomics and agent-based macroeconomics. In Proceedings of the Distributed Computing and Artificial Intelligence, 11th International Conference, Salamanca, Spain, 4–6 June 2014; pp. 47–54.
    74. Xu, ; Liu, R.; Liu, W. Individual bias and organizational objectivity: An agent-based simulation. J. Artif. Soc. Soc. Simul. 2014, 17, 2.
    75. Bruch, ; Atwell, J. Agent-based models in empirical social research. Sociol. Methods Res. 2015, 44, 186–221.
    76. Gray, ; Hilton, J.; Bijak, J. Choosing the choice: Reflections on modelling decisions and behaviour in demographic agent-based models. Popul. Stud. 2017, 71, 85–97.
    77. Bharathy, K. Agent Based Human Behavior Modeling: A Knowledge Engineering Based Systems Methodology for Integrating Social Science Frameworks for Modeling Agents with Cognition, Personality and Culture. Dissertation. University of Pennsylvania, Philadelphia, PA, 2006. Dissertations available from ProQuest. AAI3246140.
    78. Meerow, The politics of multifunctional green infrastructure planning in New York City. Cities 2020, 100, doi:10.1016/j.cities.2020.102621.
    79. Coleman, ; Hurley, S.; Rizzo, D.; Koliba, C.; Zia, A. From the household to watershed: A cross-scale analysis of residential intention to adopt green stormwater infrastructure. Landsc. Urban Plan. 2018, 180, 195–206, doi:10.1016/j.landurbplan.2018.09.005.
    80. Haselton, G.; Nettle, D.; Murray, D.R. The evolution of cognitive bias. Handb. Evol. Psychol. 2015, 1–20, doi:10.1002/9780470939376.ch25.
    81. Bukszar, , Jr. Strategic bias: The impact of cognitive biases on strategy. Can. J. Adm. Sci./Rev. Can. Sci. Adm. 1999, 16, 105–117.
    82. Moher, ; Liberati, A.; Tetzlaff, J.; Altman, D.G.; Group, P. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009, 6, e1000097.
    83. Dhakal, P.; Chevalier, L.R. Managing urban stormwater for urban sustainability: Barriers and policy solutions for green infrastructure application. J. Environ. Manag. 2017, 203, 171–181, doi:10.1016/j.jenvman.2017.07.065.
    84. Qiao, -J.; Kristoffersson, A.; Randrup, T.B. Challenges to implementing urban sustainable stormwater management from a governance perspective: A literature review. J. Clean. Prod. 2018, 196, 943–952.
    85. Winz, ; Brierley, G.; Trowsdale, S. Dominant perspectives and the shape of urban stormwater futures. Urban Water J. 2011, 8, 337–349, doi:10.1080/1573062x.2011.617828.
    86. Bain, ; Elliott, E.; Thomas, B.; Shelef, E.; River, M. Green Infrastructure for Stormwater Management: Knowledge Gaps and Approaches; University of Pittsburgh: Pittsburgh, PA, USA, 2019.
    87. Chahardowli, ; Sajadzadeh, H.; Aram, F.; Mosavi, A. Survey of Sustainable Regeneration of Historic and Cultural Cores of Cities. Energies 2020, 13, 2708.
    88. Laspidou, S.; Mellios, N.K.; Spyropoulou, A.E.; Kofinas, D.T.; Papadopoulou, M.P. Systems thinking on the resource nexus: Modeling and visualisation tools to identify critical interlinkages for resilient and sustainable societies and institutions. Sci. Total Environ. 2020, 717, 137264.
    89. Nosratabadi, ; Mosavi, A.; Shamshirband, S.; Kazimieras Zavadskas, E.; Rakotonirainy, A.; Chau, K.W. Sustainable business models: A review. Sustainability 2019, 11, 1663.
    90. Maeda, K.; Chanse, V.; Rockler, A.; Montas, H.; Shirmohammadi, A.; Wilson, S.; Leisnham, P.T. Linking stormwater Best Management Practices to social factors in two suburban watersheds. PLoS ONE 2018, 13, doi:10.1371/journal.pone.0202638.
    91. Mason, R.; Ellis, K.N.; Hathaway, J.M. Urban flooding, social equity, and “backyard” green infrastructure: An area for multidisciplinary practice. J. Community Pract. 2019, doi:10.1080/10705422.2019.1655125.
    92. Cousins, J. Structuring Hydrosocial Relations in Urban Water Governance. Ann. Am. Assoc. Geogr. 2017, 107, 1144–1161, doi:10.1080/24694452.2017.1293501.
    93. Chaffin, C.; Floyd, T.M.; Albro, S.L. Leadership in informal stormwater governance networks. PLoS ONE 2019, 14, doi:10.1371/journal.pone.0222434.
    94. Cousins, J. Infrastructure and institutions: Stakeholder perspectives of stormwater governance in Chicago. Cities 2017, 66, 44–52, doi:10.1016/j.cities.2017.03.005.
    95. Finewood, H. Green Infrastructure, Grey Epistemologies, and the Urban Political Ecology of Pittsburgh’s Water Governance. Antipode 2016, 48, 1000–1021, doi:10.1111/anti.12238.
    96. Porse, Open data and stormwater systems in Los Angeles: Applications for equitable green infrastructure. Local Environ. 2018, 23, 505–517, doi:10.1080/13549839.2018.1434492.
    97. Green, O.; Shuster, W.D.; Rhea, L.K.; Garmestani, A.S.; Thurston, H.W. Identification and induction of human, social, and cultural capitals through an experimental approach to stormwater management. Sustainability 2012, 4, 1669–1682.
    98. Lim, C. An empirical study of spatial-temporal growth patterns of a voluntary residential green infrastructure program. J. Environ. Plan. Manag. 2018, 61, 1363–1382, doi:10.1080/09640568.2017.1350146.
    99. Meyer, A.; Hendricks, M.; Newman, G.D.; Masterson, J.H.; Cooper, J.T.; Sansom, G.; Gharaibeh, N.; Horney, J.; Berke, P.; van Zandt, S.; et al. Participatory action research: Tools for disaster resilience education. Int. J. Disaster Resil. Built Environ. 2018, 9, 402–419, doi:10.1108/ijdrbe-02-2017-0015.
    100. Monaghan, ; Hu, S.C.; Hansen, G.; Ott, E.; Nealis, C.; Morera, M. Balancing the Ecological Function of Residential Stormwater Ponds with Homeowner Landscaping Practices. Environ. Manag. 2016, 58, 843–856, doi:10.1007/s00267-016-0752-9.
    101. Persaud, ; Alsharifa, K.; Monaghan, P.; Akiwumi, F.; Morera, M.C.; Ott, E. Landscaping practices, community perceptions, and social indicators for stormwater nonpoint source pollution management. Sustain. Cities Soc. 2016, 27, 377–385, doi:10.1016/j.scs.2016.08.017.
    102. Shuster, D.; Garmestani, A.S. Adaptive exchange of capitals in urban water resources management: An approach to sustainability? Clean Technol. Environ. Policy 2015, 17, 1393–1400, doi:10.1007/s10098-014-0886-5.
    103. Baptiste, K. “Experience is a great teacher”: citizens’ reception of a proposal for the implementation of green infrastructure as stormwater management technology. Community Dev. 2014, 45, 337–352.
    104. Shuster, D.; Morrison, M.A.; Webb, R. Front-loading urban stormwater management for success–a perspective incorporating current studies on the implementation of retrofit low-impact development. Cities Environ. 2008, 1, 8.
    105. Hoover, -A.; Hopton, M.E. Developing a framework for stormwater management: Leveraging ancillary benefits from urban greenspace. Urban Ecosyst. 2019, 22, 1139–1148.
    106. Schifman, A.; Herrmann, D.L.; Shuster, W.D.; Ossola, A.; Garmestani, A.; Hopton, M.E. Situating Green Infrastructure in Context: A Framework for Adaptive Socio-Hydrology in Cities. Water Resour. Res. 2017, 53, 10139–10154, doi:10.1002/2017wr020926.
    107. Hager, W.; Belt, K.T.; Stack, W.; Burgess, K.; Grove, J.M.; Caplan, B.; Hardcastle, M.; Shelley, D.; Pickett, S.T.A.; Groffman, P.M. Socioecological revitalization of an urban watershed. Front. Ecol. Environ. 2013, 11, 28–36, doi:10.1890/120069.
    More