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Citizens AND HYdrology (CANDHY): conceptualizing a transdisciplinary framework for citizen science addressing hydrological challenges

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  • Imperial College London UK & L'institut Agro Rennes France

Abstract

Widely available digital technologies are empowering citizens who are increasingly well informed and involved in numerous water, climate, and environmental challenges. Citizen science can serve many different purposes, from the “pleasure of doing science” to complementing observations, increasing scientific literacy, and supporting collaborative behaviour to solve specific water management problems. Still, procedures on how to incorporate citizens’ knowledge effectively to inform policy and decision-making are lagging behind. Moreover, general conceptual frameworks are unavailable, preventing the widespread uptake of citizen science approaches for more participatory cross-sectorial water governance. In this work, we identify the shared constituents, interfaces and interlinkages between hydrological sciences and other academic and non-academic disciplines in addressing water issues. Our goal is to conceptualize a transdisciplinary framework for valuing citizen science and advancing the hydrological sciences. Joint efforts between hydrological, computer and social sciences are envisaged for integrating human sensing and behavioural mechanisms into the framework. Expanding opportunities of online communities complement the fundamental value of on-site surveying and indigenous knowledge. This work is promoted by the Citizens AND HYdrology (CANDHY) Working Group established by the International Association of Hydrological Sciences (IAHS).
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Citizens AND HYdrology (CANDHY): conceptualizing
a transdisciplinary framework for citizen science
addressing hydrological challenges
Fernando Nardi , Christophe Cudennec , Tommaso Abrate , Candice Allouch ,
Antonio Annis , Thaine Herman Assumpção , Alice H. Aubert , Dominique
Berod , Alessio Maria Braccini , Wouter Buytaert , Antara Dasgupta , David
M. Hannah , Maurizio Mazzoleni , Maria J. Polo , Øystein Sæbø , Jan Seibert ,
Flavia Tauro , Florian Teichert , Rita Teutonico , Stefan Uhlenbrook , Cristina
Wahrmann Vargas & Salvatore Grimaldi
To cite this article: Fernando Nardi , Christophe Cudennec , Tommaso Abrate , Candice Allouch ,
Antonio Annis , Thaine Herman Assumpção , Alice H. Aubert , Dominique Berod , Alessio
Maria Braccini , Wouter Buytaert , Antara Dasgupta , David M. Hannah , Maurizio Mazzoleni ,
Maria J. Polo , Øystein Sæbø , Jan Seibert , Flavia Tauro , Florian Teichert , Rita Teutonico ,
Stefan Uhlenbrook , Cristina Wahrmann Vargas & Salvatore Grimaldi (2020): Citizens AND
HYdrology (CANDHY): conceptualizing a transdisciplinary framework for citizen science addressing
hydrological challenges, Hydrological Sciences Journal, DOI: 10.1080/02626667.2020.1849707
To link to this article: https://doi.org/10.1080/02626667.2020.1849707
© 2020 The Author(s). Published by Informa
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Publisher: Taylor & Francis & IAHS
Journal: Hydrological Sciences Journal
DOI: 10.1080/02626667.2020.1849707
Citizens AND HYdrology (CANDHY): conceptualizing a
transdisciplinary framework for citizen science addressing
hydrological challenges
Fernando Nardia,d,r,*, Christophe Cudennecb, Tommaso Abratec, Candice Allouchd,
Antonio Annisa, Thaine H. Assumpçãoe, Alice H. Aubertf, Dominique Berodc, Alessio
Maria Braccinig, Wouter Buytaerth, Antara Dasguptai, David M. Hannahj, Maurizio
Mazzolenik, Maria J. Polol, Øystein Sæbøm, Jan Seibertn, Flavia Tauroo, Florian
Teichertc, Rita Teutonicod, Stefan Uhlenbrookp, Cristina Wahrmann Vargasq, Salvatore
Grimaldio
a Water Resources Research and Documentation Centre (WARREDOC), University for
Foreigners of Perugia, Perugia, Italy;
b UMR SAS, Institut Agro, INRAE, 35000 Rennes, France;
c World Meteorological Organization (WMO), Geneva, Switzerland;
d Institute of Environment and College of Arts, Sciences & Education (CASE), Florida
International University (FIU), Miami, Florida, US;
e Integrated Water Systems and Governance, IHE Delft, Delft, the Netherlands;
f Department of Environmental Social Sciences, Eawag, Swiss Federal Institute of
Aquatic Science and Technology, Dübendorf, Switzerland;
g Department of Economics, Engineering, Society and Business Organizations (DEIM),
University of Tuscia, Viterbo, Italy;
h Department of Civil and Environmental Engineering, Imperial College London,
London, UK;
I Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai,
Maharashtra, India;
j School of Geography, Earth & Environmental Sciences, University of Birmingham,
Edgbaston. Birmingham. B15 2TT UK
k Department of Earth Sciences, Uppsala University, Uppsala, Sweden;
l Andalusian Institute for Earth System Research, University of Cordoba, Córdoba,
Spain;
m Department of Information Systems, University of Agder, Kristiansand, Norway;
n Department of Geography, University of Zurich, Zurich, Switzerland and Department
of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences,
Uppsala, Sweden;
oDepartment for Innovation in Biological, Agro-food and Forest systems (DIBAF),
University of Tuscia, Viterbo, Italy;
p International Water Management Institute (IWMI), Colombo, Sri Lanka;
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q Hydrology Department of Instituto Costarricense de Electricidad (ICE), San José,
Costa Rica.
r Fondazione Eni Enrico Mattei (FEEM), Milan, Italy
* Contact: University for Foreigners of Perugia, Piazza Fortebraccio, 06123, Perugia,
Italy. fernando.nardi@unistrapg.it
Abstract Widely available digital technologies are empowering citizens who are
increasingly well informed and involved in numerous water, climate, and environmental
challenges. Citizen science can serve many different purposes, from the “pleasure of
doing science” to complementing observations, increasing scientific literacy, and
supporting collaborative behaviour to solve specific water management problems. Still,
procedures on how to incorporate citizens’ knowledge effectively to inform policy and
decision-making are lagging behind. Moreover, general conceptual frameworks are
unavailable, preventing the widespread uptake of citizen science approaches for more
participatory cross-sectorial water governance. In this work, we identify the shared
constituents, interfaces and interlinkages between hydrological sciences and other
academic and non-academic disciplines in addressing water issues. Our goal is to
conceptualize a transdisciplinary framework for valuing citizen science and advancing the
hydrological sciences. Joint efforts between hydrological, computer and social sciences
are envisaged for integrating human sensing and behavioural mechanisms into the
framework. Expanding opportunities of online communities complement the fundamental
value of on-site surveying and indigenous knowledge. This work is promoted by the
Citizens AND HYdrology (CANDHY) Working Group established by the International
Association of Hydrological Sciences (IAHS).
Keywords citizen science; crowdsourcing, Volunteered Geographic Information (VGI);
human sensors; human behaviour; Citizens AND HYdrology (CandHy); unsolved
problems in hydrology (UPH); transdisciplinarity
1 Introduction
Interest in citizen science is growing in several disciplines (Kullenberg & Kasperowski,
2016, Njue et al., 2019), including the hydrological sciences (Figure 1). State-of-the-art
citizen science approaches, achievements and caveats in hydrology and geosciences are
currently being discussed and reviewed (Conrad and Hilchey, 2011, Assumpção et al.,
2018, Zheng et al., 2018, Njue et al., 2019, Paul et al., 2019, See, 2019).
Crowdsourcing, a specific type of citizen science (Haklay, 2013, Paul et al., 2018), is
expected to gain momentum as well as play a bigger role in water resource and risk
monitoring, (Mazzoleni et al., 2017, Mazzoleni et al., 2018) management (Uprety et al.,
2019), communication, and awareness-raising (Mukhtarov et al., 2018).
[Figure 1]
Citizens’ involvement is beneficial for studies assessing human impacts on the
hydrological cycle (Abbott et al., 2019), as well as for assessing the interlinkages
between hydroclimatic dynamics, especially extremes, and society. This is a relevant
and timely societal challenge, as evidenced by the International Association of
Hydrological Sciences (IAHS) launching the hydrological decade 2013–2022 with the
theme “Panta Rhei: Change in Hydrology and Society” (McMillan et al., 2016,
Montanari et al., 2013). Coupled water-human socio-hydrology studies interlinking the
environmental, social and economic sciences has matured, providing additional clues in
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achieving water security and sustainable development (Di Baldassarre, et al., 2013,
Young et al., 2015, Brondizio et al., 2016, Ceola et al., 2016, Mård et al., 2018, Di
Baldassarre et al., 2019). At the same time, awareness of major water, climatic and
environmental issues have stressed the importance of citizens’ engagement (Hayward,
2012, X. Liu et al., 2014, O’Brien et al., 2018).
Hydrology is therefore poised to become a major field of activity for citizen
science, which may lead both scientists and citizens to better understand the complexity
of hydrological phenomena. Citizen science constitutes, for hydrologists, an opportunity
to join efforts integrating scientific, social, economic, cultural, political and
administrative processes. Moreover, citizens’ observations and behaviour are not
bounded and biased by disciplinary preconceptions. Crowdsourcing can fill the need for
more distributed and diverse observations of the multiple sets of land, water,
atmosphere and energy variables (e.g. geology, soil type, vegetation, soil moisture,
surface and groundwater discharge, sediment yields, soil chemistry, microbial
community, air temperature and energy consumption). In this regard, transfer of
hydrological knowledge, data and tools is particularly important for addressing
knowledge gaps linked to most studies that have investigated only one of the earth’s
spheres (i.e. hydrosphere, biosphere, lithosphere or atmosphere). Citizen science
projects could address scientific challenges prompted by Critical Zone (CZ)
investigations (Brantley et al., 2016, Bui, 2016, White et al., 2015) which require the
interfacing of hydro-meteorologic, hydrologic, hydrogeologic, ecohydrologic, and
biogeochemical sciences (Banwart et al., 2013, Cudennec et al., 2016, Guswa et al.,
2020, Loiselle et al., 2016). Moreover, pressing scientific and societal challenges linked
to water, energy and food security cannot be dissociated from humans and the role they
have on the water–energy–food–ecosystem (WEFE) nexus (Carmona-Moreno et al.,
2018, Connor et al., 2020, Cudennec et al., 2018, D’Odorico et al., 2018, J. Liu et al.,
2017, Rosa et al., 2020) or on any attempt to address global environmental challenges in
the Anthropocene (Brondizio et al., 2016, Palsson et al., 2013).
The following section introduces the main definitions and concepts and the
challenges and opportunities linked to citizen science for hydrological sciences.
1.1 Citizen involvement in hydrology: from knowledge to action
The heterogeneous nature of citizen participation in water research projects allows
multiple ways for citizens and scientists to interact. As a consequence, there are also
multiple definitions of citizen science (Eitzel et al., 2017, See et al., 2016). Most
literature defines citizen science as a method applied in research, designed and
coordinated by scientists, which includes the involvement of citizens. Common
theoretical schemes and definitions of citizen science are based on the varying level of
participation by citizens. For instance, Haklay (2013) proposed four increasing levels of
involvement: 1) crowdsourcing, 2) distributed intelligence, 3) participatory science, and
4) extreme citizen science. Another consequence of this heterogeneity is that citizen
science overlaps with community-based participatory research, public participation in
science and research, participatory research, or participatory action research (Eitzel et
al., 2017). Table 1 summarises the most relevant definitions used in this manuscript. We
also introduce definitions of human sensors and citizen science for hydrological
sciences, based on concepts explained later in this work.
[Table 1]
Citizen science is dedicated to developing scientifically organized Data-
Information-Knowledge workflow performed through scientist-citizen cooperation
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(Aulov et al., 2014, Geiger and Schader, 2014, Morschheuser et al., 2016, L. Smith et
al., 2017, Vicari et al., 2019, Wiggins and Crowston, 2011) and may also include
citizen-designed experiments of scientific interest (Puri and Sahay, 2003). The value of
public engagement in research projects goes beyond the pure extension of the scientific
observation capacity (Gura, 2013). Directly involving citizens is an effective way to
account for social, economic, educational and behavioural dynamics (Chawla and
Cushing, 2007, Jollymore et al., 2017, Palsson et al., 2013). Together with more
informed communication strategies (Aulov et al., 2014, Pandya and Dibner, 2019,
Rutten et al., 2017, L. Smith et al., 2017, Vicari et al., 2019), citizen science leverages
multiple voices and local culture and conditions, which bring critical indigenous
knowledge to hydrological studies (Sivapalan, 2005). Citizens’ engagement may, thus,
have multiple beneficial outcomes from knowledge development and awareness raising
to encouraging more informed actions by concerned citizens. A large number of citizen
science projects in environmental and hydrological sciences demonstrated their positive
impacts on the sustainability and safety of natural and anthropogenic ecosystems
(Buytaert et al., 2014, Njue et al., 2019, Joint Research Centre, 2020, Federal
Crowdsourcing and Citizen Science Catalog, 2020).
1.2 Citizens’ intelligence for hydrological observations
Technological advances enabled scientists to capture hydrological processes at finer
spatial and temporal scales. However, hydrology remains a data-scarce science, with
many important variables (such as river flow, water quality, sediments, rainfall/snow
depths, and groundwater levels) being severely under-sampled. This has decisive
implications for our ability to assess and manage water resources, deal with challenges
and forecast events (Beven et al., 2020, Cudennec et al., 2020, Pecora and Lins, 2020).
Also, variables that are less used in practical applications can be crucial for the
scientific understanding of complex processes and systems. Examples include
interception volumes and their partitioning, snowmelt and sublimation fluxes, or
phenomenological and social indicators affected by hydrological processes.
Citizens using mobile devices in urban and non-urban ecosystems are generating
an unprecedented amount of data. Opportunistic sensing (definition in Table 1) is an
emerging frontier for the hydrological sciences gaining novel insights from citizens’
distributed monitoring networks of hydrological processes (McCabe et al., 2017, Tauro
et al., 2018). Social and demographic, behavioural and human dynamics data are also
voluntarily (or non-voluntarily) produced and shared by citizens through their handheld
devices or digital platforms (Smith et al., 2019). Those data are commonly referred to as
crowdsourced data (Brabham, 2008, Howe, 2006) or Volunteered Geographic
Information (VGI) (Goodchild, 2007, Haklay, 2013) (definition in Table 1). The terms
‘informal’ or ‘unstructured’ data are also used to refer to data produced by citizens,
since this data often does not conform to existing standards (Gandomi and Haider, 2015,
Melville et al., 2012, Stork, 2001).
Participatory monitoring approaches and crowdsourcing (definition in Table 1)
of citizen scientists are increasingly tested to fill this data gap in hydrology and related
disciplines, thanks to distributed volunteers using manual instruments such as the rain
gauge or more complete personal weather stations and other affordable environmental
sensors (Buytaert et al., 2014, Cunha et al., 2017, Follett and Strezov, 2015, Kullenberg
and Kasperowski, 2016, Mao et al., 2019, Trouille et al., 2019). Widely accessible
technologies allow non-experts to easily gather, analyse, visualize and share a wealth of
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earth system data (Breuer et al., 2015, Michelsen et al., 2016, Njue et al., 2019, Sermet
et al., 2019, Starkey et al., 2017, Tkachenko et al., 2017) that complements those from
traditional monitoring networks and field surveys (Davids et al., 2019, Etter et al., 2018,
Starkey et al., 2017). The interest and proactive attitude of the general public can lead
to new discoveries and improved modelling of hydrologic phenomena (Yang and Ng,
2017).
At present, affordable electronic devices (smartphones, cameras, microcontrollers,
smart watches, drones, etc.) are able to monitor not only the environment, but also
biometrics (e.g. temperature, heart rate), geolocation (i.e. GPS), and communications
(Dixon et al., 2020, Mao et al., 2019, O’Grady et al., 2016, Seibert et al., 2019, Sermet
et al., 2019, Stefanidis et al., 2013, Tauro et al., 2018, Wang et al., 2018, Yu et al.,
2017). Geo-spatial models, data and tools are also more accessible to a larger number of
users (e.g. researchers, professionals, students) than before thanks to open source
licensing (e.g. GNU General Public Licence), volunteer developers, user-friendly
interfaces, geospatial data processing and web platforms (Dallery et al., 2020, Ames et
al. 2012, Goodchild et al. 2012, Gorelick et al. 2017).
1.3 Online communities: A wealth of data and opportunities
Web-based digital platforms aggregate a growing number of users, enabling scale and
performance in crowdsourcing (Le Boursicaud et al., 2016, Fohringer et al., 2015,
Jollymore et al., 2017, Li et al., 2018, Sit et al., 2019). A group of crowdsourcers that
share a common platform to cooperate for a common goal form an online community
(OC) (definition in Table 1). OCs are used in several settings to manage the relations
among organizations and their stakeholders (Dellarocas, 2006, Leidner et al., 2010), for
mobilising people to lobby for common interests or causes (von Krogh et al., 2012,
Braccini et al., 2019), for engaging individuals on the cooperative production of
knowledge and innovation (Faraj et al., 2011, Hutter et al., 2011, Ma and Agarwal,
2007, Majchrzak et al., 2013, Braccini et al., 2018), or for sharing knowledge and
information of public interest (McLure Wasko and Faraj, 2005).OCs can also increase
engagement in and awareness of water-related challenges. At the same time, OCs
present the risk of drifts in the understanding and practices of citizens in water
management issues. These risks are significant especially when OCs adopt a social
media presence which may be influenced by opinion biases, low scientific literacy,
and/or organized forms of misinformation (e.g. “fake news”) (Baccarella et al., 2018).
Online communities allow citizen science programs to facilitate the interaction
among selected groups of citizens, such as users from a particular geographic region
(e.g. country, municipality, river basin or coastal zone), demographic category (e.g.
gender, age, religion, social status), recreational (e.g. river fishing, sailing, hiking), or
professional activity (e.g. engineers, educators, sociologists). The number of OCs,
empowered by online tools and communities (Federici et al., 2015) and digital social
networks (Liberatore et al., 2018), is significantly increasing. However, offline
communities still play a major role in many issues in both developed and developing
countries, and the two settings can also overlap.
Online communities can be applied to different aspects of water management.
Engagement of OCs in emergencies constitutes one relevant framework in which
crowdsourcing of hydrological information could be helpful for early detection, rapid
response and efficient recovery (e.g. See et al., 2016; Ernst et al., 2017).
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1.4 Citizen science for water emergency management and regional planning
Several examples exist where crowdsourcing activities have become pivotal
components of real-time emergency and post-disaster management actions (de
Albuquerque et al., 2015, Le Boursicaud et al., 2016, Huang and Xiao, 2015, Poser and
Dransch, 2010, Yadav and Rahman, 2016). In concordance, crowdsourcing is used in
the field of natural hazards (Figure 1). For instance, during the floods in South India in
2015, citizen science observations were used for real-time emergency management
(Anbalagan and Valliyammai, 2017, Naik, 2016, Pandey and Natarajan, 2016, Yadav
and Rahman, 2016). Furthermore, some citizen science projects successfully
investigated and tested the technical and procedural implementation of well-informed,
educated, and organized groups of citizens (named citizen observatories in most cases)
as effective risk mitigation measures (Montargil and Santos, 2017, Paul et al., 2018,
Wehn et al., 2015).
The added value of citizen science is also leading to the integration of citizen
observations and feedback into decision-making frameworks for participatory regional
planning (Aretano et al., 2013, Kahila-Tani et al., 2016, Kleinhans et al., 2015).
Citizen-driven efforts support effective cooperation and mutual trust between different
stakeholders. For instance, misunderstandings and conflicts that arise between water
users and managers (e.g. disputes in water allocation among different geographic
regions or economic sectors as in the WEFE nexus) can be anticipated and mitigated
with citizens’ involvement (IMoMo, 2018). Citizens’ consensus, behaviour,
perceptions, and social dynamics in general – all difficult to measure – can be quantified
(or at least assessed) and integrated into environmental and urban resource planning
through crowdsourcing (Arthur et al., 2018, Beigi et al., 2016, Huang and Xiao, 2015,
Lee et al., 2011, Michelsen et al., 2016, Tkachenko et al., 2017, Witherow et al., 2018,
Xiao et al., 2015).
1.5 Citizen science to achieve transdisciplinarity in hydrological sciences
Citizen science approaches can enlarge the scale, impact, and ‘ground-truthing’ of
hydrological sciences (Afshari et al., 2018, Buytaert et al., 2014) fostering unique
opportunities to develop transdisciplinary research (definition in Table 1).
Transdisciplinary hydrological research is a fundamental asset of studies aiming to
address water challenges (e.g. water quality, water accessibility) and extremes (e.g.
floods, droughts) while considering the interplay between socio-environmental factors
that govern human-water systems (Di Baldassarre et al., 2019, Ceola et al., 2016).
While the technology that facilitates citizen science is mature with ready-to-use
equipment and software broadly used across diverse disciplines (Blöschl et al., 2019,
Mazzoleni et al., 2017, Tauro et al., 2018, Wan et al., 2014), standardization procedures
are not. New policies are also needed that recognize citizen science as a cross-cutting
priority, to support and regulate opportunistic sensing and unstructured information
gathering, sharing and use (Palsson et al., 2013, Weber et al., 2019, Wehn et al., 2015).
Conceptual transdisciplinary frameworks that integrate technical, administrative,
and societal aspects to support the development of citizen science projects are lacking in
the hydrological sciences. Some investigations developed such frameworks for citizen
science methods, but, even if general, they lacked some aspects (e.g. administrative and
policy assessment in Kieslinger et al, 2018), or referred just to data quality (Antelio et
al., 2012) or were limited to specific disciplines and scopes and lacked generality and
flexibility (Chase and Levine, 2016). This hinders the progress of transdisciplinary
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research, limits the accumulation of knowledge, hampers a consistent implementation of
the research results, and also makes the development of comparative assessments and
evaluations of different citizen science projects challenging and inconsistent.
1.6 Outlook
In this study, we identify and introduce a conceptual framework that integrates
crowdsourcing and behavioural mechanisms, to enable transdisciplinary interlinkages
and assessments. The proposed framework aims to support the development of
accumulated knowledge, avoid pitfalls and maximize the effectiveness of joint efforts
between citizen science projects. Such a conceptual scheme, therefore, intends to foster
advancements of the hydrological sciences by supporting the merging of outcomes from
various citizen science initiatives and by allowing synergies amongst different sectors
dealing with water challenges.
2 The topology of a transdisciplinary framework for citizen science in
hydrology
2.1 Conceptualizing the topological framework
The diversity of concepts, definitions, data, models, tools and procedures poses a
challenge to designing a conceptual framework for citizen science in hydrology.
Nonetheless, we propose a topological space to aid in the definition of such framework
and to initialize the discussions with the hydrological community. Four main elements,
that are commonly shared by citizen science efforts addressing water issues were
identified: (a) citizens, (b) the hydrological sciences (hydrology, for simplicity), (c)
technology, and (d) society. These four elements include different components whose
interplay governs the development of citizen science projects in hydrology. The
proposed elements and components are therefore topological properties shared by
citizen science analysis, modelling and assessment efforts for hydrological applications.
The proposed citizen science topological space is schematically depicted in Figure 2.
[Figure 2]
2.2 The dual value of citizens’ involvement: human sensors and human
behaviour
Two new major components emerge, together with education and innovation, in the
proposed topological space as representative of the main facets of the citizens–
hydrology–technology–society interface: human sensors and human behaviour
(definitions in Table 1).
In the data-information-knowledge creation and sharing process, citizens are both
data producers while participating as observers, and data receivers while working as
nodes of a distributed network (Paul et al., 2018). The term ‘human sensor’ may,
unintentionally, dehumanize the citizen; however, we advocate for this term because in
many studies, the human component of citizen observations is largely neglected. It
should be noted that, although we choose to use the ‘human sensors’ terminology, we
acknowledge that citizens can be engaged in citizen science to varying degrees (see
Section 2.3). Nonetheless, to provide a schematic organization of the ‘human sensors’
component, we identify two main categories:
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- Direct citizen observations: Information produced by involved citizens that utilize
custom-made applications for the observation of predetermined phenomena or
landscape features to develop specific modelling or monitoring activities. An
increasing number of web and smartphone applications were recently established,
falling within this category, as in the case of citizens collecting images and videos to
monitor water parameters, land cover or other geophysical parameters (Assumpção
et al., 2018, Seibert et al., 2019, Zheng et al., 2018);
- Indirect citizen observations: The gathering and processing of information shared by
citizens for other purposes, such as citizens spontaneously posting videos and images
in online social networks of unusual river conditions (floods, droughts, pollutants,
debris, etc.). These pieces of information may then be, instantaneously or
subsequently, used by scientists for real-time water monitoring or post-event fluvial
studies (Mazzoleni et al. 2017, Tkachenko et al. 2017, Annis and Nardi 2019).
This classification was also introduced by Craglia et al., 2012, as implicitly and
explicitly contributed data, and by See et al., 2016 as active and passive crowdsourced
geographic information. Thus, the human sensors concept implies that in hydrology,
citizen science data are not always generated for a scientific purpose, in opposition to
traditional monitoring practices. The human sensors component, representing a human-
machine-environment interface, provides qualitative and quantitative observations that
can be used within quantitative hydrological studies, with careful attention to the
accuracy and scale of these observations (Buytaert et al., 2014, Kosmala et al., 2016,
Mazzoleni et al., 2019, Seibert and Vis, 2016). See Table 1 for the definition of ‘human
sensors’.
Citizens’ behaviour (i.e., human conduct related to technical and social norms) and
actions (i.e. activities performed in developing a task or accomplishing a goal) are a
function of social, cultural, educational, psychological and economic conditions. The
‘human behaviour’ component refers, thus, to the subjectivity of human habits,
motivation, perceptions, and dynamics concerning the input citizens receive or
concerning the output (or actions) citizens produce. In particular, ‘human behaviour’
refers to how citizens subjectively extract knowledge from the data, modify their
actions, or change their behaviour as a result of the gathered knowledge. See the Table 1
for the definition of ‘human behaviour’.
The ‘human sensors’ component is widely explored in citizen science projects for the
hydrological sciences (Zheng et al., 2018). On the other hand, the ‘human behaviour’
component represents an unexplored potential for hydrology. The interaction of
hydrological sciences with social sciences, cognitive sciences, psychology, among other
disciplines investigating human behaviour, represents a pivotal asset of transdisciplinary
citizen science projects. Hydrological models, supported by citizen science, should
consider the quantitative integration of human behaviour for understanding and
simulating water processes influenced by humans. The ‘human sensors’ and ‘human
behaviour’ components are both essential for better understanding and forecasting
hydrological dynamics in river basins, where human–water interactions govern water
cycle variables and affect short- to long-term hydrological change (Di Baldassarre et al.,
2013, Di Baldassarre et al., 2016, 2019, Pande and Sivapalan, 2017).
The proposed characterization of the ‘human sensors’ and ‘human behaviour’
components suggests the depiction of an iterative cycle associated with citizens’
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engagement: Data-Information-Knowledge-Behaviour-Action. This concept is derived
from the Data-Information-Knowledge-Wisdom framework (Bernstein, 2011).
Considering that actions also support data production, this looping iteration applies
whenever citizens’ behavioural mechanisms are triggered by citizen science (i.e.
observation) methods, supporting information and knowledge production and exchange.
We posit that this iterative cycle is involved for all citizen science-driven workflows,
and therefore also includes hydrological studies (Figure 3).
[Figure 3]
2.3 Thematic areas of a transdisciplinary framework for advancing
hydrological sciences
In this section, we explore the most relevant research prospects and gaps that shall be
addressed for advancing and connecting the hydrological sciences with academic and
non-academic disciplines. Seven thematic areas are proposed and the related
transdisciplinary interlinkages are identified in Figure 4 and described below.
[Figure 4]
Theme 1. Crowdsourced data and collaborative monitoring/mapping tools
This theme is discussed in terms of: (a) the tools and methods used by citizens for
crowdsourced data gathering and processing; and (b) the crowdsourced data accuracy,
quality and specifications (e.g. spatial and temporal scale, resolution).
The first factor deals with existing or novel technologies used for monitoring
that are available to citizens. While it is still possible to use analogue tools (Breuer et
al., 2015) (e.g. interviews performed by volunteers, notes taken during field surveys,
etc.), crowdsourcing tools are now mainly related to the use of mobile devices and web-
based applications. In particular, significant advancements in the field of data collection
and processing, involving the exploitation of information derived from crowdsourced
data, are rapidly progressing in computer sciences. These also include methods for
crawling indirect citizen observation data from online sources or methods for
transforming qualitative or indirect data into quantitative hydrologically relevant
information (Le Boursicaud et al., 2016, Michelsen et al., 2016, Restrepo-Estrada et al.,
2018). Both tools and methods are gaining momentum provided by artificial
intelligence (AI), and, in general, the rapidly advancing field of big data science, mining
and analytics (Jeschke et al., 2018, Kamar et al., 2012, Sermet et al., 2019).
The second factor pertains to the accuracy, quality and technical specifications
associated with crowdsourced data. The technical specifications associated with
crowdsourced data define the reliability, robustness, flexibility, and scalability of the
data. All these properties need to be considered and evaluated (Jollymore et al., 2017,
Kieslinger et al., 2018). The spatial and temporal scales, the resolution and several other
parameters should also be defined before using such informal datasets. The main trade-
off is having increasing volumes and frequency of data, but having to characterize
crowdsourced data, vs using standard monitoring stations that can lead to limited
discrete records (Davids et al., 2017). The data gathering, processing, production, and
dissemination chain of crowdsourced data should follow quality standards and these
should be analysed and reported (Antelio et al. 2012). Standardization procedures that
actually characterize traditional monitoring networks require innovations to include and
exploit the opportunity offered by such data. Standard metadata structures are required
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to accommodate the heterogeneity of specifications associated with crowdsourced data.
Finally, the design of online platforms to share and visualize crowdsourced data,
implemented independently or jointly with traditional monitoring networks, should
include optimal procedures for combining and/or assimilating each specific dataset
taking into account its quality and properties (see Theme 3).
Theme 2. Human sensors and behaviour analytics
Effective implementation of the ‘human sensors’ and ‘human behaviour’ components,
to be jointly considered, represents the main value, but also the major challenge of
citizen science in hydrology. Citizens’ observations are influenced by diverse non-
technical (e.g. social, cultural, psychological) conditions pertaining to the ‘human
behaviour’ component. Analogously, research aiming to examine or influence human
behaviour should always consider environmental factors, as perceived and observed by
citizens, and thus, interface with the ‘human sensors’ component.
As a result, the joint ‘human sensors-behaviour’ characterize the multiple and
diverse instances of citizens’ participation and the varying influence of citizens’
behaviour on the data collection or on the participation process itself. At the same time,
a change of human behaviour as a reaction to the gathered observation or knowledge
shall be analysed as well. It is, thus, crucial to analyse interactions between the ‘human
sensors’ and ‘human behaviour’ components to understand their combined effects on
the Data-Information-Knowledge-Behaviour-Action workflow.
Nonetheless, while the randomness and subjectivity of human-derived
observations and actions are valuable for citizen science projects in hydrology,
obtaining different information from the same crowdsourcing methodology also
represents a challenge, as hydrological data requires consistency over space and time
(Strobl et al., 2019a). This thematic area is, thus, also suitable to investigate how the
hydrological sciences shall connect with knowledge, expertise and scientific reasoning
from other disciplines. For example, transdisciplinary studies are needed to understand
how conditions of observations vary with changing climatic and demographic settings
such as country, education, gender, age, income and migration status or with fatigue
conditions and other biases linked to diverse socio-cultural conditions. This theme also
promotes research on cognitive and psychological sciences, to analyse individual life
conditions especially related to people at risk, under stress and in critical situations,
which is the case for both water security and hydrological risk management challenges
(Resch et al., 2015, Sheth, 2009).
The interface between ‘human sensors-behaviour’ and hydrology represents a
cross-cutting topic that requires transdisciplinarity, where natural, social and computer
science experts should join efforts. In particular, we see the behavioural and cognitive
sciences, focusing on motivation, learning and communications, as relevant to this
theme (Oliveira et al., 2017). Moreover, gaming technologies, which can integrate
advanced hydrodynamic simulations (Zadick et al., 2016, Jeschke et al., 2018), are also
expected to provide transdisciplinary testing environments and favour the engagement
of non-traditional audiences (Newman et al., 2012, Morschheuser et al., 2016, Radchuk
et al., 2017, Aubert et al., 2018, 2019, Haan and Voort, 2018).
Citizen science faces several challenges related to the integration of the human
sensors and human behaviour. Theme 2 inherits the issues identified in Theme 1 and, in
particular, those affecting the operational use of crowdsourced data. Additionally, the
confidentiality and the heterogeneity of data related to behavioural mechanisms provide
further complications. Privacy and security concerns become more relevant and
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impactful in establishing long-lasting, consistent, generalized and scalable citizens’
engagement processes (Anhalt-Depies et al., 2019, Quinn, 2018).
Theme 3. Integration and exchange of hydrological data, models, and tools
Although on-ground and remote sensing monitoring contribute to an increasing volume
of hydrological data (Tomsett and Leyland, 2019), large parts of the world suffer from
water data scarcity, e.g. due to the degradation of traditional gauge networks and lack of
resources and commitment (Dixon et al., 2020, Manfreda et al., 2018, McCabe et al.,
2017, Tauro et al., 2018, World Bank Group, 2018). The usefulness of this scarce
amount of data, if any, strongly relies on the accessibility, organization, and distribution
of derived information for supporting research and innovations.
The availability and performances of water information systems have flourished
in recent times (Demir and Krajewski, 2013, Shukla et al., 2019, Swain et al., 2015,
Vitolo et al., 2015). Water information systems are generally equipped with GIS and
web-GIS interfaces implementing geospatial data models representing morphometric,
environmental, hydrological, and socio-economic parameters associated with river
basins and networks (Maguire et al., 2005, Silberbauer, 2019, Singh and Fiorentino,
1996, Whiteaker et al., 2006).
A number of regional and local water management agencies are investing
relevant economic resources to extend their monitoring networks and develop ad hoc
hardware and software for data gathering and sharing (e.g. webGIS, dashboards).
Notably, examples exist of hydrological information systems covering large spatial
scales and a wide variety of data sources (Addor et al., 2020), such as WMO-WHOS,
USGS-Nwis, CUAHSI- HydroShare, EU-Wise, UNESCO-Wins, WRI-Aqueduct,
GRDC database. However, these systems rely solely on existing institutionalized data
collection, and therefore reflect the uneven global distribution of observations, with
significant gaps especially in low- and middle-income countries (de Bruijn et al., 2019,
Crochemore et al., 2020, World Bank Group, 2018). Moreover, satellite-based earth
observation (EO) systems are also improving considerably, capturing high resolution
spatial and temporal coverages of major earth and water dynamics, with major efforts
from governmental agencies (e.g. ESA, NASA). EO services also provide readily
available expert-use solution-oriented data and models for managing, monitoring and
mapping floods, droughts, land use and urban change, among others (Hewitt et al.,
2012, Demeritt et al., 2013). EO platforms could also benefit from the integration of
citizens’ observations (Fritz et al., 2017), from global to local crowdsourcing projects.
Nonetheless, major obstacles and issues still impact the integration of unconventional
citizen-driven information and tools with standard hydrological and EO information
systems.
This theme describes the role of citizen science in the integration and exchange
of heterogeneous data sources and in the development of software for hydrological
sciences and across the wide spectra of disciplines interested in water issues.
Theme 4. Technological, institutional, psychological/cultural barriers for the uptake of
citizen science projects
Implementing citizen science projects for innovation in hydrological sciences is a
scientific challenge, but psychological and cultural barriers also need to be considered
(Elliott and Rosenberg, 2019). The water resource and risk management sector is bound
by diverse laws and norms developed by international, national, regional and local
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authorities. They are designed to make the different parties (e.g. managers,
professionals, scientists, governments, etc.) cooperate consistently and efficiently to
monitor, protect and allocate water resources while guaranteeing sustainable and safe
human activities (Bubeck et al., 2017, Kallis and Butler, 2001). However, such rules
often do not include citizen science activities explicitly. The use of informal data and
community engagement in policy and decision-making may even contrast with some of
the current approaches, where government authorities are not used to cooperating and
interacting with laypeople. As a result, in existing highly hierarchical top-down
approaches, a psychological and cultural shift is needed to overcome and move towards
greater collaboration and participation (see also Theme 6). It is also needed to
investigate how benefit from existing local participatory methods that are not related to
citizen science.
This theme investigates regulatory frameworks that support the effective
integration of new technical and administrative specifications, including citizen science.
Adaptive and flexible, yet consistent and robust, regulations are needed to support the
transfer of hydrological science innovations in operational water information, policy
and decision-making systems empowered by citizen science. Three major factors shall
be investigated in this theme: (a) regulations and norms about the tools and methods for
collecting, sharing, using and validating hydrological data from informal sources; (b)
evaluation of participatory approaches as mechanisms for more inclusive decision-
making; and (c) cost-benefit analyses of citizen science projects.
The first factor deals with the issue that specifications of crowdsourced data and
crowdsourcing platforms for hydrological monitoring and modelling are not consistent
with existing standards. Pictures taken from cell phones as compared to water level
measurements gathered from standard flow gauges is a good example of the lack of
consistency that hampers the impacts of citizen science on fostering technological
innovations for hydrological sciences. For example, evacuation decision-making during
flooding conditions only considers validated data from official standard flow
monitoring gauges. Crowdsourced data may complement standard data used for disaster
risk management, especially if supported by proper legal frameworks, norms and
quality control.
The second factor pertains to research on the impacts of including public
participation in decision-making. Some studies indicate positive correlations between
participation, awareness, compliance with the law, and improved management (Von
Korff et al., 2012, Buchecker et al. 2013); therefore, European directives (e.g. Water
Framework Directive, Floods Directive) incentivize participatory approaches.
Nevertheless, most national and regional regulations do not consider participatory
approaches, and significant political and cultural barriers impact citizen science uptake
for more inclusive water governance and decision-making. To overcome these barriers,
official authorities may benefit, by means of citizen science projects, from increased
and wider involvement of citizens and stakeholders.
The third factor is linked to studies that address other reasons hindering the
uptake of regulations supporting citizen science. These reasons are rooted not only on
the reliability of the data but also in the lack of understanding by authorities of the costs
of citizen science projects and how to adapt existing practices. Understanding the
technologies used by scientists and citizens is fundamental, but not sufficient. Indeed,
cost-benefit analyses that consider the entire technological and administrative burden
associated with citizen science projects are needed. This theme, thus, also includes
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research on how to create locally-adapted citizen science projects, to facilitate adoption,
paving the way for parsimonious citizen science project implementation (Assumpcao et
al., 2019).
Theme 5. Communicating water science and societal feedbacks
Scientific communication (definition in Table 1) has moved from the sole dissemination
of scientific knowledge and research outcomes to the general public to public
awareness, scientific literacy, and culture (Burns et al., 2003). This new purpose may
stimulate behaviour change and actions from affected citizens and stakeholders. The
scientific communication workflow includes multi-directional feedback between
scientists and society, which can be further enhanced by citizen science (Bonney et al.,
2009, Le Coz et al., 2016, Montargil and Santos, 2017).
Communication and dissemination has become an integral part of research
projects addressing hydrological issues. Citizen science constitutes a valid method for
testing novel ways to exchange information between scientists and communities,
particularly those affected by societal, climatic and hydrological challenges. Citizen
science projects represent a testbed for processing and conveying, to both experts and
the general public, the transdisciplinary value of water as a resource and disaster risk
management.
This theme extends the proposed transdisciplinary framework to include studies
on communication strategies for knowledge exchange and public feedback. It seeks to
investigate, test and discover new forms of visualisation, infographics, and mapping, as
well as new engagement models (e.g. demographics-targeted communication
campaigns, online communities and social networks, gaming technologies) that are
explored and tested by scientists to reach a wider audience, from children to senior
citizens (Schwabish, 2020).
Theme 6. Collaborative and participatory efforts supporting decision- and policy-
making
Citizen science can help decision-making in many forms, most obviously by providing
relevant data to authorities or by increasing participation levels in addressing societal
challenges linked to water issues. The level and scale of citizens’ participation (Haklay,
2013) determine the effectiveness and impact of citizen science projects in supporting
or prompting a change in water governance (Buytaert et al., 2016), but are not the only
ones. Challenges due to the segmentation and diversity of participatory approaches, are
identified. These have various implications on the uptake of citizen science for decision-
and policy-making. Four major factors to be investigated include: (a) diversity of
approaches and scales; (b) diversity of participants; (c) the working conditions
(behaviour, safety, productivity, etc.) characterizing citizens when deploying data as
human sensors; and (d) trustworthiness and authoritativeness of citizen science data and
projects.
The first factor relates to the collaborative process. Differences in citizen science
approaches depend on the spatial and temporal scale of the phenomenon of interest. For
example, different scales apply to participatory projects aiming to manage extreme
events, that usually require high frequency and low data latency (i.e. real-time
conditions), like in disaster risk management and emergency response (Eilander et al.,
2016, Ernst et al., 2017, Sy et al., 2019). This last example contrasts with urban and
regional monitoring activities that are characterized by low frequency and long term
response times (Albano et al., 2015, Lisjak et al., 2017). The dynamics of the
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phenomena of interest also affect the behaviour component, since different citizen
science approaches are implemented for emergency management, such as extreme river
flows versus water sampling of regular river flows.
The second factor is linked to the diversity and often random unpredictable
behaviour of the participants. In this regard, we emphasize that human sensors–
behaviour interactions not only vary from citizen to citizen but also vary in time and
depend on the specific context. The same citizen in the same time frame may behave
and operate differently depending on motivation, availability, and the technical and
engagement methods used for prompting and implementing its involvement. In this
regard, uncertainty analyses in crowdsourcing benefit from transdisciplinarity. In
particular, the hydrological sciences are linking with statistical and demographic
studies, as well as with social and psychological sciences, to deal with the randomness
and bias associated with observations of natural and human phenomena (Seibert et al.,
2019, Strobl et al., 2019b).
The third factor refers to the working conditions of humans “working as
sensors”. In particular, there are diverse sensing conditions and processes that affect the
quality and quantity of crowdsourcing records. The behaviour, safety and productivity
that impact the ‘human sensors’ component need to be appropriately managed and
designed. Research investigations shall also consider the behaviour related to the use of
dedicated tools for crowdsourced data production (e.g. the different effectiveness
information generated by citizens previously properly trained on purpose or by the
volunteering data gathering from untrained participants) (Strobl et al., 2019a). Further
working conditions are represented by the analysis of potentially hazardous situations
affecting citizens when sensing extreme phenomena and the potential risks of
implementing citizen networks that may improperly use mobile devices in dangerous
conditions.
The fourth factor deals with the operational use of crowdsourced data and
programs for policy and decision-making in water resource and disaster risk
management. The previous factors, once addressed, may support the inclusion of
crowdsourced data for integrating (or surrogating) traditional monitoring data.
Nevertheless, policy and decision-makers may still be impacted by bounding conditions
linked to actual standardized procedures that often avoid the full exploitation of the
value of crowdsourcing. This bounding factor generally relies on the trustworthiness
and authoritativeness of data gathering using citizen science methods. As an example,
data gathered from a citizen science project supporting hydrological observations using
a mobile application (e.g. Crowdwater (Strobl et al., 2019b) or Scent project (Tserstou
et al., 2017)), even if consistent with standard river flow observations, may be
disregarded for policy and decision-making. In the context of flooding, direct
observations, even if transmitted in a timely manner, cannot be used for evacuation
planning (with some exceptions, e.g. Naik 2016, Pandey and Natarajan 2016, Yadav
and Rahman 2016, Anbalagan and Valliyammai 2017).
It is expected that policy and decision-makers will increasingly integrate citizen
science in their decision-making, but how exactly this will happen is still unclear. This
theme explores how hydrological scientists will collaborate with jurisdictional and
policy experts, as well as with communication experts, psychologists and other non-
hydrologists, to support the operational use of crowdsourced data. It is therefore crucial
to test shared procedures (i.e. shared among the plethora of heterogeneous components
discussed earlier) and, consequently, identify and test novel guidelines allowing trans-
sectorial participatory decision- and policy-making.
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Theme 7. Procedures and guidelines for citizen science integration into hydrological
research
New procedures and guidelines are needed for valuing citizen science in hydrology.
Citizen science projects are lacking comparable data gathering, modelling and
integrated assessment schemes (Burgess et al., 2017, Haywood and Besley, 2014). The
many examples of diverse citizen science projects confirm that they are hard to find. It
is difficult to even analyse and compare different methodologies within similar projects
sharing the same goal (e.g. water level monitoring) in hydrological sciences. The
integration of the full range of heterogeneous and diverse water-related citizen science
data in a robust assessment framework is challenging, but essential to achieve. From a
technical point of view, comparative considerations on the quality and quantity of data,
plus the quality assurance should be made to support transdisciplinary research
programs that aim to use such diverse data and tools. Also, it is necessary to evaluate
data models and fuzzy methods that can incorporate multiple datasets into modelling
frameworks (Malczewski, 2006). Comparative assessments are fundamental to building
knowledge from diverse citizen science models and outcomes. Additionally,
heterogeneity, gaps, flexibility, interoperability, scalability, and data assimilation should
be evaluated. Investigations on model calibration and validation procedures are also
needed in order to accommodate the varying formats, uncertainties and availability of
crowdsourcing data. In turn, models optimized for crowdsourced data can be compared
with models built with expert-sourced observed data, standard observation or previously
validated simulated variables.
This theme seeks to define and develop procedures and guidelines – as set out in
the proposed conceptual transdisciplinary framework – and establish synergies, as well
as take into account, the opportunities and caveats characterized in the previous six
themes. It constitutes a synthesis of the technical and non-technical, methodological,
and procedural challenges and solutions introduced in this section. It aims to develop
consistent assessments of citizen science projects and frameworks and accumulated
knowledge towards the maturing of transdisciplinary citizen science projects in the
context of finding integrative solutions to water challenges.
3 The CANDHY Working Group at the International Association of
Hydrological Sciences (IAHS)
The Citizens and Hydrology (CANDHY; logo in Figure 5) working group (WG) was
established in July 2017 by the IAHS. The principal aim of the CANDHY WG is to
support the use of citizen science in hydrology and harmonize research in this context,
promoting the value of citizen science for advancing the hydrological sciences and
finding answers to the most pressing open scientific, technical, and societal challenges
in this field of expertise. This paper identifies the fundamental components, thematic
areas, and specifications of citizen science projects giving them structure and direction
to advance research and achieve scientific breakthroughs in hydrology.
[Figure 5]
The citizens and hydrology topic is aligned with major programs and efforts of
the IAHS. IAHS launched and catalysed the Predictions in Ungauged Basins (PUB)
Decade (2003–2012) (Blöschl et al., 2013, Hrachowitz et al., 2013) and the ongoing
Panta Rhei Decade (2013–2022) (McMillan et al., 2016, Montanari et al., 2013) for
promoting and coordinating scientific efforts for achieving improved hydrological data
and models. CANDHY WG cooperates with the IAHS Measurements and Observations
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in the XXI century (MOXXI) WG, of which its mission and goals are to address Panta
Rhei science questions 1 and 5 that focus respectively on the identification of key gaps
in the understanding of hydrological change, and on advancing monitoring and data
analysis capabilities, also through opportunistic sensing, to predict and better manage
hydrological change (Tauro et al., 2018). The CANDHY WG contributed to the
Unsolved Problems in Hydrology (UPH) initiative defining the UPHs of the
Measurement and Data” section (UPHs 16, 17, 18) as well as the questions about the
Interfaces with society” (UPHs 21, 22, 23) (Blöschl et al., 2019).
The CANDHY WG aims to promote the development of citizen science projects
linking earth, environmental, atmospheric and hydro-sciences as well as humanities,
social and computer sciences, to synergistically define methods, procedures and
guidelines for the effective use of informal data and fostering participatory solutions for
water challenges.
4 Citizen science in hydrological sciences: the way forward
While citizen science initiatives show promising results, there are still several
challenges to be addressed. Evaluations of effective costs and benefits of citizen science
projects need to be critically debated. Technology becomes obsolete very quickly and
data infrastructure needs to be maintained. Short-term financing schemes and
fragmentation affect the sustainability and long-term achievements of citizen science
projects. Intellectual property, licensing, and data protection are serious challenges that
need to be managed (Quinn, 2018). Relevant opportunities offered by citizens’
distributed monitoring networks and affordable opportunistic sensing, require
government and financial support, multi-sectoral coordination and long-term vision
(Dixon et al., 2020).
The impact of citizen science in hydrology depends on drivers and involvement
from actors and stakeholders of participatory outcomes. It is not only a matter of
extending the participation. It is a commitment to co-generate citizen science programs
so that stronger links, mutual trust and shared beliefs among researchers, citizens and
policy-makers are developed (Njue et al., 2019, Stahl et al., 2017).
Citizen science is expected to reinforce the value and mission of socio-
hydrology in understanding and addressing sustainable development and environmental
issues (Pande and Sivapalan, 2017; Di Baldassarre et al., 2019, Fritz et al., 2019).
Approaches for connecting citizen science and socio-hydrology are still not well
defined, but initial investigations on this topic are emerging (Sarmento Buarque et al.,
2020).
The next steps needed to allow citizen science to reach its full potential for
hydrological sciences are through the following major research lines of action:
- Understand how crowdsourced data and actions generate hydrological knowledge
and how this should be formalized in models and hydrological studies. Research
and standardization efforts are needed to address data quality, data validation and
data interoperability.
- To date, most of the hydrologic information systems seem to be developed as top-
down programs (e.g. USGS Hydrosheds, Australian Water Observations from
Space, WOfS; EU Global Surface Water Explored, GSWD) and do not allow for
the integration of informal data processing methods resulting from citizen science.
It is necessary to learn from successful examples, such as collaborative mapping
projects like OpenStreetMap, involving thousands of volunteer mappers daily
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updating street/urban features. Hydrologists shall seek a common, inclusive and
open platform fostering the integration of crowdsourcing with standard hydrologic
monitoring and geospatial mapping data.
- A growing number of hydrological studies use data from social networks, but
most of the crowdsourced data used in research are still indirect citizens’
observations. Hydrological scientists may need to focus on creating efficient tools
and resources (e.g. smartphone apps, web platforms, training, awareness, and
communication campaigns) to incorporate the data collected through social
networks. Novel paradigms and disciplines may be needed to support an
increasing volume and effectiveness of social media content for hydrological
sciences.
- Gaming technologies have successfully integrated numerical algorithms
developed by hydrologists. Advanced hydrodynamic simulations of water
dynamics are, in fact, now embedded in commercial gaming console applications
and used daily by millions of users of any nationality and age. Hydrologists
should take advantage of the growing interest, audience and skills raised by the
gaming industry, big data, artificial intelligence, machine learning and augmented
reality technologies. Collaborative virtual gaming and big data environments
represent a great opportunity for citizen science in support of hydrological
sciences.
- Citizen science represents an opportunity for discovery and testing novel
educational programs to be proposed at different levels (from doctoral research to
elementary schools). Hydrological sciences shall focus on the opportunities
offered by citizen science for innovating and proposing transdisciplinary multi-
level education methods and programs.
- Engaged, informed and concerned citizens are essential for managing the crucial
natural resource that is water. Eventually, in this era of increased risk of
disinformation, citizen science also represents a way to rebuild trust between
citizens, science, and authorities. Trustworthiness and authoritativeness issues are,
and will continue to be, a critical topic where scientific knowledge and methods
shall play a governing role in support of well informed decision- and policy-
making.
- There are close analogies between the diversity, heterogeneity and complexity of
human beings and hydrologic phenomena. Human and water systems will
continue to shape each other and inter-play. The knowledge, studies and solutions
that have separately emerged from social and hydrological sciences will need to
merge. Disciplinary boundaries of any further discipline able to understand,
monitor and influence the coupled human-water sensors and behaviour shall
permeate. Novel water governance solutions and strategies can be investigated
through citizen science projects and this represents an opportunity for scientists,
stakeholders, decision- and policy-makers to develop and learn together.
We think that the proposed transdisciplinary framework may pave the way for a
conceptualization and assessment model for citizen science projects addressing water
challenges. The proposed CANDHY framework, with its elements, components and
interfaces may be used to evaluate and compare the completeness, effectiveness,
scalability and replicability of citizen science projects. The CANDHY transdisciplinary
framework is a first step towards new knowledge and the integration of crowdsourced
data, tools, procedures and policies produced in diverse academic and non-academic
settings. We posit that the CANDHY transdisciplinary framework is a suitable means
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for valuing citizen science projects in hydrological sciences, with even broader
applicability across many natural and social sciences.
Acknowledgements
Two anonymous reviewers provided ideas and comments that greatly helped improving
this paper. The IAHS CANDHY Working Group is continuously welcoming new
members, citizens and hydrologists, interested in joining efforts and contributing to the
CANDHY mission. To become a CANDHY friend, a member of the working group,
and stay tuned, please visit the webpage https://iahs.info/Commissions--W-
Groups/Working-Groups/Candhy.do.
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Table 1. Definitions of major concepts used or newly introduced (in bold) in this manuscript.
Name Definition
Crowdsourcing
“A sourcing strategy in which resources (goods, data, information) are produced
or made available through the cooperative effort of several individuals” (Estellés-
Arolas and González-Ladrón-De-Guevara, 2012).
“Online, distributed problem-solving and production model that leverages the
collective intelligence of online communities for specific purposes” (Brabham et
al., 2014).
“Crowdsourcing represents the act of a company or institution taking a function
once performed by employees and outsourcing it to an undefined (and generally
large) network of people in the form of an open call. This can take the form of
peer-production (when the job is performed collaboratively), but is also often
undertaken by sole individuals. The crucial prerequisite is the use of the open call
format and the large network of potential laborers”. (Howe 2006, Brabham 2008).
Crowdsourced data Any data (e.g. measurements, photos, videos, etc.) produced by crowdsourcing
Online communities
(OC)
“A persistent group of people that share common or complementary interests and
use internet-based digital technologies to communicate and coordinate their
actions” (Preece, 2000)
Volunteered
Geographic
Information (VGI)
“A remarkable phenomenon ... has become evident in recent months: the
widespread engagement of large numbers of private citizens, often with little in
the way of formal qualifications, in the creation of geographic information, a
function that for centuries has been reserved to official agencies. They are largely
untrained and their actions are almost always voluntary, and the results may or
may not be accurate. But, collectively, they represent a dramatic innovation that
will certainly have profound impacts on geographic information systems (GIS)
and more generally on the discipline of geography and its relationship to the
general public. I term this volunteered geographic information (VGI), a special
case of the more general Web phenomenon of user-generated content”
(Goodchild, 2007)
Opportunistic
sensing
“The concept of utilizing signals from often unrelated measurements to inform
upon hydrological processes. Inferring hydrological properties by making use of
signals of opportunity (e.g. cellular network signals)” (McCabe et al., 2017) or
“unconventional sources” (Jiang et al., 2019)
Transdisciplinary
research
“The development of transdisciplinarity studies including the following
principles: cross-disciplinarity, shared goal setting, integration of diverse
disciplines and non-academic participants, and development of integrated
knowledge and theory among science and society” (Tress et al., 2005)
Scientific
communication
“The use of appropriate skills, media, activities, and dialogue to produce one or
more of the following personal responses to science: Awareness, Enjoyment,
Interest, Opinion-forming, and Understanding” (Burns et al. 2003)
Human sensors Citizens empowered by digital technologies with bidirectional capacity of
producing and receiving data, information and knowledge about the environment.
Human behaviour
The individual or collective physical and non-physical actions (e.g. emotions,
rules of conduct) performed by citizens when processing information or reacting
to forcing stimuli, conditions or events (Strickland, 2011)
“A function of compatible intentions and perceptions of behavioural control in
that perceived behavioural control is expected to moderate the effect of intention
on behaviour, such that a favorable intention produces the behaviour only when
perceived behavioural control is strong” (Ajzen, 1991)
Citizen science for
hydrological
sciences
The scientific organization of citizens’ actions that produce knowledge about the
water cycle from collecting to processing data on both natural and anthropogenic
features and phenomena, as well as living or non-living entities.
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... The protocol may be employed to produce user-friendly summary data or databases without overcomplicated analysis [62][63][64]. Users can conduct quality checks on the data to make sure that it accurately reflects the current conditions [65][66][67] and matches on-ground observations and experiences of community, particularly during floods [68][69][70]. ...
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... • i2s (Integration and Implementation science) Framework: Focuses on complex societal and environmental research through Synthesizing Knowledge, Managing Knowledge, and Supporting Improvement [146]. • CANDHY (Citizen and Hydrology) Framework: Integrates traditional Aboriginal Australian knowledge with modern hydrology and policy through collaboration among hydrologists, public servants, and researchers [151]. • ANU Framework: Emphasizes a transdisciplinary approach with characteristics like being Change-oriented, Systemic, Context-based, Pluralistic, Interactive, and Integrative [152]. ...
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... Citizen science initiatives have been at the forefront of most informational campaigns regarding either the development of an infrastructure project or the application of a new policy involving the public in scientific research, given its ability to overcome social resistance and advance social acceptance towards innovation. In terms of socio-hydrology, citizen science initiatives provide an understanding of how to leverage subjective decision-making and communicate scientific (often probabilistic) information, through continuous communication with the public (Alexander et al., 2020;Nardi et al., 2022). ...
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... Bringing the long-established prevalence of top-down management and communication (from experts to the public) into constructive tension with participatory governance to allow a diversity of stakeholders to contribute to decisions [8,43,44]. • Applying transdisciplinary thinking [21,[45][46][47] to guide flood scholarship. Conventional disciplines become barriers to investigating multi-level interactions and the study of sustainability in a multi-level world [48]. ...
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... • i2s (Integration and Implementation science) Framework: Focuses on complex societal and environmental research through Synthesizing Knowledge, Managing Knowledge, and Supporting Improvement [146]. • CANDHY (Citizen and Hydrology) Framework: Integrates traditional Aboriginal Australian knowledge with modern hydrology and policy through collaboration among hydrologists, public servants, and researchers [151]. • ANU Framework: Emphasizes a transdisciplinary approach with characteristics like being Change-oriented, Systemic, Context-based, Pluralistic, Interactive, and Integrative [152]. ...
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The Hindu Kush Himalayan (HKH) region, known as the "water tower of the world," is experiencing severe water scarcity due to declining spring discharge. This decline is driven by climate change, unsustainable human activities, and rising water demand, leading to significant impacts on rural agriculture, urban migration, and socio-economic stability.This review investigates the factors behind reduced spring discharge and advocates for a transdisciplinary approach to address the issue. It stresses integrating scientific knowledge with community-based interventions, recognizing that water management involves not just technical solutions but also human values, behaviors, and political considerations. The paper explores the benefits of public-private partnerships (PPP) and participatory approaches for large-scale spring rejuvenation. By combining the strengths of both sectors and engaging local communities, sustainable spring management can be achieved through collaborative and inclusive strategies. It also highlights the need for capacity development and knowledge transfer, including training local hydrogeologists, mapping recharge areas, and implementing sustainable land-use practices. In summary, the review offers insights and recommendations for tackling declining spring discharge in the HKH region. By promoting a transdisciplinary, community-centric approach, it aims to support policymakers, researchers, and practitioners in ensuring the sustainable management of water resources and contributing to the United Nations Sustainable Development Goals (SDGs).
... Engaging the public in data collection and classification not only increases data coverage but also promotes public awareness and participation in water resources management (e.g. Sermet et al. 2020, Nardi et al. 2022. ...
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