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WeSenseIT: Citizen Observatory of Water

Final Report Summary - WESENSEIT (WeSenseIT: Citizen Observatory of Water)

Executive Summary:
The WeSenseIt project defined citizen observatories as “A method, an environment and an infrastructure supporting an information ecosystem for communities and citizens, as well as emergency operators and policymakers, for discussion, monitoring and intervention on situations, places and events”. A collaborative approach has been taken to develop solutions that involve an exchange of information and expertise from all participants and where the focus is on arriving at practical solutions with a clear vision and direction grounded in basic research. This has created a shared ownership scheme, and shifts power to the process itself rather than remaining within authorities, developers or decision-makers. The project’s emphasis was on delivering highly innovative technologies to support citizens, communities and authorities in developing real-time situation awareness while ensuring all stakeholders play their part. Implementation has been through a combination of crowdsourcing, custom applications and dedicated web portals designed to foster collaboration, and which has created a shared knowledge base that facilitates decision-making processes and engages with communities. Data is captured via innovative sensors that are used directly by citizens, crowdsourcing from social networks (or by collective intelligence). Networks and models have been developed able to use heterogeneous information from both sensors and citizens. The project has paid particular attention to the governance implication of citizen observations and their acceptance by governments and decision makers for practical implications in fields such as planning and emergency response.
Project Context and Objectives:
Europe is in the process of meeting social, political and environmental challenges of our time (the economic crisis, the emergence of populism, globalisation, pressure on resources, ageing) (EC 2020). Among these, climate change is expected to significantly affect the environment. Water quality, water availability and flooding will be particularly affected. Predictions indicate that over the next 70 years there will be a doubling in both the number of people affected by flooding each year (to 0.5-0.8 million) and in the annual damages (increasing to 7.7-15 billion €) [Ciscar 2009]. Yet water-related decisions are complex because they affect a variety of interests that are often in conflict, such as the environment, economic development and society. Traditional approaches to observing the water cycle on earth such as earth observations through satellites and in-situ observations through monitoring networks have two major drawbacks. First, the density and resolution of the collected data is still too low to describe the status of the water cycle, even when both spatial and in-situ observations are considered complementary. This is particularly the case during anomalous (critical) events such as floods and continuing droughts. Second, it promotes a passive role for the community with regards to understanding the environment, i.e. citizens are traditionally considered consumers of information services at the very end of the information chain.
In order to harness environmental data and knowledge to effectively and efficiently manage water resources, WeSenseIt developed citizen observatories of water, which allow citizens and communities to take on a new role in the information chain about water management: a shift from the traditional one-way communication paradigm towards a two-way communication model in which citizens become active stakeholders in information capturing, evaluation and communication. An interdisciplinary concept was developed on the basis of three different aspects of community participation in water governance: (i) environmental non-structured data collection via optimized networks of sensors as well as information provided directly by citizens (measurements, images, messages) and via mining of social media portals; (ii) development of descriptive and predictive models (both physical/natural and social) and decision-making tools that are able to optimally assimilate both social and physical data; (iii) two-way feedback and exchange of environmental knowledge/experience between citizens and authorities for decision-making, planning and governance. From a technical point of view, the project created and deployed a method, an environment and an infrastructure supporting an information ecosystem for communities and citizens, as well as emergency operators and policymakers, for discussion, monitoring and intervention on water bodies and services. Data capture is based on: (i) innovative sensor devices which can be used directly by the citizens and (ii) exploitation of the citizens’ collective intelligence through monitoring social networks communications (e.g. Twitter, Facebook, etc.) and allowing citizens and communities to upload data to the observatory. The predictive models and decision support tools are integrated and able to continuously assimilate data originating from citizens, Web/text mining and sensors in an optimal and adaptive way. Through the involvement of social scientists who worked with the citizen and stakeholder groups throughout the project, theoretical and conceptual social models were developed to better understand citizen motivation and engagement, their needs, abilities, preferences and potential for input into decision-making processes. Exchange of experience and feedback ensured innovative continuing user involvement and community creation and maintenance. In order to enable and facilitate participation in decision-making, data management strategies enabling sharing of environmental data and information within an e-collaboration environment covered important phases of social interaction.
The citizen water observatories concept was tested and validated in three case studies in water management, which were proposed by decision makers in the UK, the Netherlands and Italy. The case studies covered the entire hydrologic cycle with a major focus on variables responsible for floods occurrences. Floods carry enormous economic and social costs and their frequency and impact is likely to increase in the future, due to climate change and to the increasing number of communities and industries located in flood and drought-prone areas. In addition, changes in water quality can also have important impacts (both positive and negative) upon the natural environment, society and the economy.
WeSenseIt had a strong focus on economic opportunities for SMEs. Eight SMEs were involved in the project; they developed cutting edge technologies and methodologies, which have, in some cases, been developed into commercial products. In general, the observatory provided a solid infrastructure to create and test applications and services at low cost using large data banks and with a potentially large audience and high visibility.
Finally, we evaluated the extent to which WeSenseIt enables the direct transfer of environmental (water-related) knowledge for use by policy makers, industry and research as well as society to effectively and efficiently manage water resources.
WeSenseIt provide exceptional contributions in terms of both the development of the concept of citizen observatories and the necessary surrounding governance, as well as in technological terms, studying, defining, evaluating and exploiting technologies that have been used in real world scenarios such as the support to the evacuation of 30,000 people from the city of Vicenza in Italy and the support to emergency control rooms during events involving over a million people.
Project Results:
WeSenseIt addressed the whole lifecycle of citizen observatories of water, considering ways that citizens and decision makers can cooperate to collect data, to make sense of the data and act on the basis of the collected data. The project has focussed on the following areas of research:
* Sensing water variables via professional and citizens sensors; collecting data via participatory and opportunistic sensing (WP1)
* Integrated Social and Physical Sensors Networks connecting the data collected in WP1;
* Adaptive risk based models (WP3)
* Methods for participatory decision support (WP4)
* Infrastructure for citizen observatories (WP5)
* Analysis of governance around citizen observatories of water (WP6)
Application of the methods and technologies was tested in real life in 3 case studies in Italy, UK and The Netherland (WP7) as well as in collaboration with emergency control rooms UK-wide.

WP1: Social and Physical Sensors

The advent of low-cost computing and hardware to interface a variety of inexpensive sensors, such as the RaspberryPi and Arduino, and the increasing ubiquity of smartphones has provided the ability to engage with citizens to monitor the environment at spatial and temporal scales that were previously impossible or requiring considerable resources. WeSenseIt (WSI) has developed, tested, deployed and evaluated a number of physical and social sensors specifically suited and intended as components of a diverse CO. The technical evaluation and functionality of these sensors and peripheral hardware, and sensor-citizen combinations for data acquisition are presented in the above sections.

Moreover, WSI has examined a number of citizen sensing paradigms, from passive sensors (such as the use of social media or Wifi signals) to acquire environmental information with little or no user involvement, to participatory sensing where the user is engaged to varying degrees in the monitoring process. These methods and technologies are presented in more detail in other corresponding project deliverables. The key to participatory sensing is motivation and the use of mobile devices offers the potential of mass engagement. The technologies developed in WSI have shown how mobile devices can be used to monitor the activity of large populations of citizens with little engagement on their part, or enable them to engage in complex interactions using text, audio and video. As mobile devices become more powerful, contain an increasing number of on-board sensors, and communication networks become faster and more robust, the possibilities for citizen sensing will continue to expand.
The technical evaluation of developed and implemented sensing equipment in the three use cases of the WSI project, (IT, NL, UK) has provided valuable information on the performance (and acceptance) of the proposed and provided technologies. It is evident that such real-world tests and deployments are indispensable for assessing the suitability and reliability of a sensing algorithm or sensing system. The evaluation has shown by many examples the success and the added value of CO compatible sensing equipment, as well as the potential of producing larger numbers of sensors and hardware components at acceptable cost in an attempt to increase spatial and temporal coverage significantly if not by orders of magnitude. At the same time the field deployments revealed some weaknesses and problems associated with the measurement and observation systems. These may be of technical nature or related to incorrect manipulation, lack of maintenance, inappropriate installation, or a result of insufficient power supply. Also the selected location for an observation itself can be the cause of problems. The evaluation of our systems has shown such existing or potential shortcomings, and also identifies the limitation of such technology.
The various physical and social environmental sensing technologies described and evaluated may be considered as individual tools in a large container (toolbox): the citizen observatories. These tools are available and at the service of the community to contribute to the citizen observatory database, help creating environmental awareness and responsibility. The citizens get empowered to contribute in creating a base for decisions and thus directly participate in decision-making processes.

The following sections provide the main science and technological results (summarised in the list below) for each of the project partners and gives the main related publications (for the scientific results) for further information.

● Sensible heat flux for wireless sensor networks - EPFL
● Stream flow velocity from smartphone video clips - EPFL
● Integration of social feedback as model parameters - IHE
● Various sensor interfaces and sensor nodes - ADV
● Disdrometers – connected acoustic rain gauges - DSD
● Urban umbrella rain gauge (prototype) - DSD
● Citizen reporting - IHE
● Wireless multi-sensor hydro-meteorological sensor stations - EPFL/SSS
● SmartCam for long-term water monitoring - SSS
● Wireless soil moisture and temperature measurement - STAR
● Satellite derived soil moisture maps - STAR
● Platform for smart irrigation planning - STAR
● River discharge estimation with mobile phone - USFD
● Citizen Video Communication - USFD
● Crowd activity monitoring - USFD
● Social Media Monitoring - USFD
● Augmented Reality - USFD

Sensible heat flux sensor (EPFL)
Sensible heat flux is an essential quantity in the surface energy budget. Information about it is crucial for the derivation of models of air-surface interaction which in turn are needed for larger scale climate models. Sensible heat flux varies greatly across short distances and thus many sensors are required in order to obtain measurements of sufficient spatial density. The standard measurement method however requires expensive equipment which constrains the deployment of a large number of sensors. Our work implements a method relying only on the variance of the measured temperature to compute the sensible heat flux. We first verify the validity of this method and then modify SENSORSCOPE, a commercially available weather station, to capture the required data. The resulting setup is able to provide sensible heat flux measurements with high spatial density in near real time at negligible additional cost.
A printed circuit board (PCB) has been designed and produced according to the requirements for measuring a fast response thermistor and for on-board processing and interfacing it with existing remote sensing technologies. A major effort was to establish communication protocols and to develop proper programming of the PCB enabling user defined data acquisition. These developments have been done with a focus on optimizing power consumption. Some apparent issues regarding the manufacturer's specifications of the sensing element require further investigation.
In general, the new low-cost sensible heat flux sensor shows promising results. The sensor itself is sensitive enough to measure fast temperature changes. The thermal inertia is negligible and the power consumption remains acceptable. In addition, the experiment carried out in real outdoor conditions has proved the robustness of the fine-wire thermocouple. Even though the sensible heat flux is hard to measure accurately, the new low-cost sensor performs fairly well. The detailed comparison with a benchmark shows a small positive bias. This error seems to be due to the method and not to the sensor itself. Further investigations are needed to determine the exact reasons of this general overestimation.

Related Publications
Huwald, Hendrik, Tristan Jonas Brauchli, Michael Lehning, and Chad W. Higgins. "Distributed Sensible Heat Flux Measurement for Wireless Sensor Networks." In American Geophysical Union (AGU) Fall Meeting 2015, no. EPFL-POSTER-215092. 2015.
Brauchli, Tristan Jonas, Nicolas Bigler, Alexander Bahr, Steven Vincent Weijs, Chad Higgins, and Hendrik Huwald. "A low-cost sensible heat flux sensor for potential use in wireless sensor networks and citizen observatories." In 12th Swiss Geoscience Meeting, no. EPFL-POSTER-206741. 2014.
Bahr, Alexander, Chris Evans, Alcherio Martinoli, Hendrik Huwald, Chad Higgins, and Marc Parlange. "Measuring sensible heat flux with high spatial density." In Sensors Applications Symposium (SAS), 2012 IEEE, pp. 1-6. IEEE, 2012.

Flowcam algorithm
Stream flow velocity may be used for estimating discharge. Given the relative scarcity of direct stream flow and discharge measurements, surface velocity measurements can provide useful information for flood warning, hydropower production, hydrological science in general and water resource management. Some recent research efforts attempt involving the population in environmental sensing to complement existing static monitoring networks with alternative, spatially dense environmental information. Given the availability of sensing and the advances in image processing techniques (smartphones), there is a large potential to obtain hydrologically relevant data through motivated citizens. WSI investigated the feasibility of stream flow surface velocity measurements from movie clips taken by (smartphone) cameras based on specifically adapted image processing techniques. Results from movie clip derived velocity information are compared to reference measurements from standard flow meters in various field experiments.
Work on deriving surface flow velocities from video clips has continued, with the main aim of testing robustness in different conditions and to solve the issue of a reference length. Under the right conditions, we are now able to use videos from a non-stable viewpoint (no tripod) and still obtain reasonable velocity estimates. Also for the reference length, we have a solution using lasers, which enables automatic processing of the videos into real-world unit velocities (not pixels).
Note that the development of this tool/algorithm has undergone a lot of changes during the course of the project as the subject is evolving rapidly and required various adjustments and inclusion of features. The development of the algorithm and potential mobile phone app is still ongoing.

Related Publications
Huwald, Hendrik, Tristan Jonas Brauchli, Zichong Chen, and Steven Weijs. "Stream flow velocity measurement with smartphones: a technique for citizen observatories, decision-making, and water management." In 26th General Assembly International Union of Geodesy and Geophysics (IUGG), no. EPFL-POSTER-215091. 2015.
Weijs, Steven V., Zichong Chen, Tristan Brauchli, and Hendrik Huwald. "Measuring surface flow velocity with smartphones: potential for citizen observatories." In EGU General Assembly Conference Abstracts, vol. 16, p. 15882. 2014.
Weijs, S. V., T. Brauchli, Z. Chen, and H. Huwald. "Estimating Stream Surface Flow Velocities from Video Clips." In AGU Fall Meeting Abstracts, vol. 1, p. 1197. 2014.

WSN+ Concordia: Flexible and adaptive sensor interfacing and data collection (ADV - Advanticsys)
ADV’s has developed communication devices for sensor networks, in particular improving their DM-124 RF (Radio Frequency) devices to allow the expansion of measurement points at a lower cost. This requires the design of a wireless RF module at lower frequencies than traditional 2.4 GHz transmission for dealing with harsh environmental conditions for radio waves transmissions. DM-124 firmware has been changed in order to cope with sensor network requirements. It is foreseen that point-to-point connections can go between 1 and 2 km.
In addition ADV have developed the Concordia platform; this infrastructure has an internal scheduling procedure to synchronously poll information from all Advanticsys’ devices and also detect failures in communications and devices themselves. Data collected by each monitoring station was sent through a GPRS link (SIM card included) on a VPN (Virtual Private Network) to the ADV Concordia® platform which can deliver edge services for end users such as visualization and management tools and also APIs for the sharing of data with public authorities and networks. Water-related service APIs have been implemented into ADV’s network in order to share information with the WeSenseIt platform using WaterML standard. This not only enables the interoperability with other EU initiatives that work towards the implementation of earth observation standards and applications but also the adoption of these standards by the industry and therefore fostering new business models.

Acoustic disdrometer (DSD - Distrometrics)
The key outcome of Disdrometrics is a low cost acoustic disdrometer, which is being developed jointly with Delft University of Technology. The acoustic rain gauges of Disdrometrics simply ‘listen’ to the rain, do not have any moving parts and are, therefore, very low maintenance. The Disdro gives information about the drop size distribution and the time of a rain event, from which the rain depth and rain intensity can be derived. In the project DSD have developed and updated version of their sensor (Distro 2.0) and a proof of concept for an umbrella that measured rainfall intensity and communicated the information through a Bluetooth device to an iPhone app.

Related Publications
R. Hut, S. de Jong, and N. van de Giesen. Using umbrellas as mobile rain gauges: Prototype demonstration. European Geosciences Union General Assembly 2014. April 28, 2014. Vienna, Austria. Geophysical Research Abstracts, Vol. 16, EGU2014-16418, 2014.
Hut, Rolf, Stijn de Jong, Nick van de Giesen, Hidde Leijnse, and Marijn de Haij. "Design and field test of a robust acoustic disdrometer for distributed rainfall observations." In EGU General Assembly Conference Abstracts, vol. 15, p. 12388. 2013.

Smartflow water-velocity meter (SensorScope)
In collaboration with EPFL Sensorscope have developed a water-velocity meter based on the video analysis and tested at three sites. The initial camera selected for this project proved to be inadequate, and there were also difficulties providing enough solar power and keeping the free from algae growth. In final analysis the current solution is not commercially practical, in its tested form. Further work might consider the use of smartphone video (see above) or different installation locations (e.g. with mains power).

Starlab Sensors
Worked on the validation of both soil moisture retrieval methods. We analyzed the surface of averaging of the soil moisture to obtain the most correlated estimations between both methods. And then we analyse the results of both methods in three fields of experiment where both probes and satellite imagery are estimating soil moisture. Results are good and provide robust methods to estimate soil moisture in fields for multiple applications such as agriculture, flood prevention monitoring.

Starlab has developed a new version of the soil moisture probes, making them more resilient and sustainable (inclusion of solar panels), more competitive (improved probes with more measuring points per probe) and with enhanced compatibility (more sensors can be connected to the probes). Also, Starlab has adapted its soil moisture retrieval algorithm to the recently launched SAR satellite Sentinel-1A. All its processing chain has been adapted to read and process the new SAR products. Soil moisture estimation systems work together to provide a high accurate soil moisture measurement, both locally through single measurements by probes, and full coverage of fields/areas from satellite maps. Additionally, the whole service that has been deployed, offers a GUI (Graphical User Interface) named AQUA that acts as a visualization tool to display to the end users the information received and processed in SmartIrrigation system: in situ sensor measurements, soil moisture maps from satellite, and additional information about weather conditions from local meteorological stations

Activity Monitor (University of Sheffield)
Understanding the behaviour of citizens and volunteers is important in order to provide services that can be badly needed in case of emergency. USFD has developed a mobile technology able to track the activities of people 24/7. The technology can either work in isolation as an independent app or be integrated into another app and work as a virtual sensor.
The app uses the internal physical and virtual sensors of an Android or iOS phone to identify geolocated physical activities (walking, running, cycling, using a vehicle, still). The system collects data at sub-minute level using the accelerometer, the gyro, the fused location sensor, the step counter and the fused activity sensor. The data is integrated classified and a precise activity (with history) will be derived. The app provides real time data to the control room at population level or as individuals (in the case of usage by volunteer or emergency personnel). The app is open and allows combination with external sensors, activated in specific geo-locations or when specific activities are carried out. For example it could be used in combination with other tools to invite people to provide readings from a river gauge board when they are walking in its surrounding area or to invite a cyclist to make a small deviation to provide data or pictures of a nearby location
The activity tracker was evaluated as part of the MoveMore initiative in Sheffield involving over 4,000 citizens which aims to make Sheffield the city in the UK that physically moves more. The importance of physical activity (e.g. walking for at least 30 minutes every day or taking at least 10,000 steps a day) cannot be underestimated as it could save thousands of lives in the UK (600 annually in Sheffield alone) and reduce the bill for the National Health System by millions by reducing the incidence of behavioural illnesses like diabetes B, a wide range of heart and circulatory diseases and osteoporosis. We have developed a collaboration with MoveMore, The National Centre for Sports, Exercise and Medicine (a city wide initiative that involves the NHS, the two Sheffield University, the City Council and several businesses) and the Centre for Sports and Exercise Research at Sheffield Hallam University, as well as Ollie Hart a local doctor who is the real force behind the MoveMore initiative. The Activity tracker is being used as a way to assess progress towards the MoveMore challenge. The technology has now been adopted by the Department of Health as part of a wider campaign potentially involving up to 1 million UK citizens to bring the benefits experimented in MoveMore nation-wide. This is made possible by the technology developed within WeSenseIt.

Social Sensors (USFD)
USFD has developed and evaluated techniques and tools to monitor social media over large scale during large events involving hundreds of thousands of people. The technology extracts a number of entity types (locations, person, organisations), where it is necessary to identify entities from millions of possibilities, and where each entity can have multiple name variation (including language related variation) and there can be a high level of ambiguity (i.e. different entities having the same names). The WSI approach parses and matches the terms in the message with those from a knowledge-base (KB) (i.e. lexicon or ontology), either derived from background resources or extracted from the data, those terms identified in the message form entity mentions. Such approaches are not sensitive to grammatical patterns and are computationally efficient, and therefore applicable to real-time processing of high volume social media message streams. The two main processes involved are the selection of candidate entities (i.e. the identification of name variants in the messages, from millions of potentially possibilities) and the disambiguation of those candidates, with a consideration of the efficiency and effectiveness of applying these processes in real-time when dealing with thousands of messages per second.

Candidate selection involved the implementation of two efficient, character-based pattern matching techniques, which have the performance and flexible to deal with the volume and variation of social media text. A pattern matching approach compiles a number of regular expressions into a set of Deterministic Finite Automaton (DFA). The implementation expands on previous work primarily in terms of efficiency and parallelisation of the DFA creation, the OpenSource code is publicly available ( A fuzzy string matching approach, based on an efficient exact matching algorithm (Aho-Corasick), was developed which can handle millions of entity names. The code is publicly available (

Extracting organisation and person information, in real-time. This approach is now being applied and constantly evaluated and improved within a real-world, commercial environment. The Information Extraction technology was adopted by a start-up organisation, FootballWhispers ( which provided a real-world, real-time, use case to evaluate the technology on extraction of organisation and person names. The initial aim of FootballWhispers (FW) is to identify the likelihood of players and managers transferring into and out of teams. Although not yet subject to a strict evaluation the use of the IE technology in FW has been seen as a success by the domain experts, who are using the system in a live, commercial setting. While less than 1% of the whispers generated have been considered as false positives this figure should be viewed with extreme caution given the impossibility of manual validation of all the whispers generated.

Related Publications
Ireson Neil; Lanfranchi, Vitaveska; Mazumdar Suvodeep; Ciravegna Fabio: “TRIDS: Real-time Incident Monitoring with Social Media”. Proceedings of Semantics and Analytics for Emergency Response (SAFE) workshop at ISCRAM, 2015

WP2: Integrated Social and Physical Sensors Networks


The objective of this work package is to integrate social and physical sensors into a heterogeneous dynamic network and develop methods to optimize this network for environmental management. Specific objectives include the integration of models for human and physical sensors, as suppliers of information and the development of multi-objective optimisation methods and software for the design of dynamic, heterogeneous and uncertain monitoring networks.


Dynamic multi-objective optimisation for dynamic heterogeneous networks
Three algorithmic frameworks were development and applied to identify the best spatial and temporal locations in a region where extra information about rainfall is needed. These frameworks were developed to optimally guide citizens, which are part of a citizen observatory, in time and space in such a way that their contribution can efficiently complement the information coming from traditional rainfall stations. The existing procedures for multi-objective optimisation, reviewed and improved in deliverable 2.21 were applied.

In order to identify the knowledge gaps in the current state of the art of monitoring network design, an extensive literature review was carried out. It was found that majority of the existing mathematical formulations and algorithms are developed for designing networks composed by static, high quality sensors and that the idea of designing dynamic monitoring networks for environmental studies is limited. In addition, approaches to design complex monitoring networks (i.e. with heterogeneous quality, time span, dynamic components, such as those envisaged by WeSenseIt), are quite reduced. A new classification of design methods was proposed, in which measurements-free and measurements-based methods are recognised. The latter can subsequently be classified as model-free and model-based methods. A general framework for design of monitoring network design was presented.

The three mathematical algorithmic formulations developed for designing heterogeneous dynamic monitoring networks are non-stationary kriging, model ensemble variations and Information-Theory-based. These formulations and algorithms use the classification of approaches for network design presented in deliverable D2.11 and the algorithmic basis for optimisation developed in D2.21.

Kriging-based methods drive the measurements towards areas of high uncertainty. In the conventional Kriging-based methods, the description of the interpolation uncertainty is determined by the covariance structure of the process. In the conventional posing of the problem, it is assumed that the covariance function is unique and isotropic, thus making the interpolation variance only function of the sensor position, leaving no space for dynamic sensors. Considering these limitations, we developed a generalisation of the Kriging method, in which the covariance structure adapts locally to the precipitation patterns (NS-Kriging).

In contrast, the model ensemble variation method aims to minimise the discrepancies of equifinal interpolation models at ungauged locations. This idea is rooted in the idea that there is no proof of that a model is more accurate than other, at ungauged locations, when its accuracy is similar at testing points. Consequently, the process is not guided by the estimates of the precipitation intensity, but instead by the relative differences between observations and the distance between these observations.

Finally, the Information Theory-based method shows that the sensor location is determined by the entropy of the region (or areas with higher uncertainty), and that these areas do not necessarily correspond with the areas with the highest mean average precipitation. Value of Information is an alternative method that was explored for the case floodplain planning, in which the consequences of the potential decisions and the capacity of the collected data to describe the true state of the system are taken into account.

Numerical results do not offer insights of the superiority of a single method, considering that the objectives functions are rather incomparable. These apparent disconnections arise due to the use of a different mathematical apparatus for posing of the optimisation problem. However, accuracy of the resulting sensor networks using any of the methods is comparable.

In general, the proposed algorithms are mainly based on statistical properties of the time series, existing or generated, in all the case studies. In this regard, two main directions for future research are recommended: 1) for early warning systems, establish the best location of sensors, using as objective function the performance of hydrological models. The results from deliverable D3.1.3 can be used as starting point; 2) develop a framework to decide in which cases to select a particular algorithm or a combination of algorithms, depending on the characteristics of the catchment and the use of the information. The results of this work can easily be connected with the algorithms developed in WP3, in which citizen data is assimilated into hydraulic and hydrological models. The proposed algorithms must be tested with real observations coming from citizen observatories.

Related Publications
Chacon-Hurtado, J. C., L. Alfonso, and D. Solomatine (2016), Rainfall and streamflow sensor network design: a review of applications, classification, and a proposed framework, Hydrol. Earth Syst. Sci. Discuss., 2016, 1-33,10.5194/hess-2016-368.
Chacon-Hurtado, J. C., L. Alfonso, and D. Solomatine (in preparation) Comparison of geostatistical, information theory and hydrological model performance metrics for the design of precipitation sensor networks. Case study: Brue catchment.
Chacon-Hurtado, J. C., L. Alfonso, and D. Solomatine (in preparation) NS-Kriging: a method to evaluate and interpolate spacio-temporal non stationarity fields.
Chacon-Hurtado, J. C., L. Alfonso, and D. Solomatine (in preparation) Integrated design of partially dynamic precipitation sensor networks.
Chacon-Hurtado, J. C., L. Alfonso, and D. Solomatine (in preparation) Optimal scheduling of dynamic precipitation sensor networks.
Alfonso, L., M. M. Mukolwe, and G. Di Baldasssarre (2016), Probabilistic flood maps to support decision-making: Mapping the Value of Information, Water Resources Research, n/a-n/a,10.1002/2015WR017378.
Alfonso, L., Chacón-Hurtado, J.C. Mazzoleni, M., Solomatine, D.P. (2016) Optimal Design of Hydrometric Monitoring Networks with Dynamic Components Based on Information Theory. 12th International Conference on Hydroinformatics, HIC 2016
Alfonso, L., Chacon-Hurtado, J., Solomatine, D. P. (2016) Optimal design of hydrometric monitoring networks with dynamic components based on Information Theory”, EGU 2016 conference, Geophysical Research Abstract, Vienna, Austria
Chacon-Hurtado, Juan Carlos, Leonardo Alfonso, and Dimitri P. Solomatine. "Precipitation Sensor Network Optimal Design Using Time-Space Varying Correlation Structure." (2014). 11th International Conference on Hydroinformatics, HIC 2014.
Alfonso, L., Chacon-Hurtado, J., (2016) “Experiences of citizen-based reporting of rainfall events using lab-generated videos”, EGU 2016 conference, Geophysical Research Abstract, Vienna, Austria.
Chacon-Hurtado, J., Mazzoleni, M., Alfonso, L., Solomatine, D. P. (2016) “Comparison between passive and active social sensors of precipitation for flood forecasting”, COWM2016 - International Conference on Citizen Observatories for Water Management, Venice.
Alfonso, L., Chacon-Hurtado, J., and Peña-Castellanos, G. "Allowing citizens to effortlessly become rainfall sensors." In E-proceedings of the 36th IAHR World Congress, vol. 28. 2015.

WP3: Adaptive risk-based models for social and natural processes


This work package aims to develop innovative approaches to integrate crowdsourced data coming from heterogeneous network of sensors, with varying life-span and space-time coverage, into predictive models. In addition, one of the objectives of this work package is to better understand and model citizen behaviour as well as the potential change of this behaviour when citizens are better informed via an observatory.


Optimal integration of heterogeneous uncertain data into models
Standard data assimilation approaches, such as Kalman filtering, ensemble Kalman filtering, nudging, etc. are applied to assimilate crowdsourced observations of variable accuracy and random life-span. For the Bacchiglione catchment, IHE developed a data assimilation procedure to incorporate crowdsourced observations of water level within hydrological and hydraulic models. The results of this work package demonstrate that crowdsourced observations can significantly improve flood prediction if they are properly integrated in hydrological and hydraulic models.
In particular, the WSI proved that assimilation of streamflow observations from static physical sensors provides improvements in model performance, the magnitude of which depends on the observation locations and model structure. However, the varying spatial distribution of precipitation generating flood events affects which sensor locations produce the best model performance at the catchment outlet. Overall, assimilation of crowdsourced streamflow observations at interior points of the catchment can improve model performances, dependent upon the particular location of the static social sensors and the hydrological model structures. In this case, lower accuracy, variable in time and space, is assumed for crowdsourced data from social sensors than for physical sensors. Interestingly, it is demonstrated that hydrological models can perform better with appropriately distributed social sensors than with inappropriately distributed physical sensors. For this reason, a non-optimal distribution of static physical sensors can be integrated with a network of static social sensors, providing intermittent crowdsourced observations in order to improve model performance.
Citizen-based crowdsourced observations are generally characterised by random accuracy and are derived at random (asynchronous) moments, which may not coincide with the model time step. The results we obtained show that, for a given sensor location, there is a limit to the number of assimilated crowdsourced asynchronous observations, after which only marginal model improvements are obtained. Accuracy of the crowdsourced observations influences the model results more than the time of arrival of the data. Model performance drops when the intervals between the assimilated observations are too large (intermittent observations). In this case, the abundance of crowdsourced data is no longer able to compensate their intermittency. In experiments with the Bacchiglione catchment it is proved that a single physical sensor can be complemented with distributed static social sensors providing asynchronous observations, even with a limited number of intermittent asynchronous crowdsourced measurements.
Regarding hydraulic modelling, different data assimilation approaches (such as direct insertion, nudging, Kalman filtering, ensemble Kalman filtering and asynchronous ensemble Kalman filtering) are implemented to integrate streamflow and water depth observations from static social and physical sensors at different locations. In general, assimilation of streamflow observations in both lumped and distributed structures of a 3-parameter Muskingum model increases model performance. Furthermore, it is found that direct insertion works better for lumped models, while ensemble Kalman filtering approaches are more reliable for distributed models. This can be due to the fact that using direct insertion model states are updated only at the assimilation location, while using Kalman filtering approaches the update is performed along the whole river reach because of the distributed nature of the Kalman gain and covariance matrix. Increasing the number of past observations in the asynchronous ensemble Kalman filter improves model performance expressed in terms of Nash-Sutcliffe, correlation and Bias indexes. Nonetheless, Kalman filtering methods are noticeably sensitive to the degree of model error and sensor locations.
Considering assimilation of distributed water depth observations in a linear hydraulic model, such as a Muskingum-Cunge model, it is found that the Kalman filter is noticeably sensitive to the degree of model error and sensor location. When the largest error is found in the boundary condition, the optimal sensor location is close to the boundary condition point, while if the error in the model exceeds the boundary condition error, the optimal sensor location is close to the reach outlet. In the Bacchiglione River it is shown that assimilating water depth observations from reaches close to the river outlet rather than from upstream reaches tends to provide larger improvement. However, downstream reaches tend to lose the assimilation effects faster than the upstream ones, in the case of flood prediction, due to their shorter travel time. In consequence, the optimal location of static physical and social sensors should be considered as a compromise between the largest model improvement and the prediction capability of the model itself.
The WSI Project demonstrates that networks of low-cost static and dynamic social sensors can complement traditional networks of static physical sensors, for the purpose of improving flood forecasting accuracy. This can be a potential application of recent efforts to build citizen observatories of water, in which citizens not only can play an active role in information capturing, evaluation and communication, but can also help to improve models and thus increase flood resilience.

Related Publications
Mazzoleni M., Chacon-Hurtado J., Noh S.J. Seo D.J. Alfonso L., and Solomatine D.P. (2016) Data assimilation in hydrologic routing: impact of sensor placement on flood prediction, under review
Mazzoleni M., Noh S.J. Lee H., Liu Y., Seo D.J. and Solomatine D.P. (2016) Real-time assimilation of streamflow observations into a hydrologic routing model: Effects of different model structures and updating methods, under review
Chacon-Hurtado, J. C., Mazzoleni, M., Corzo, G., Solomatine, D. P. (2016) On the use of surrogate inverse models for hydrological data assimilation. 12th International Conference on Hydroinformatics, HIC 2016. Incheon, South Korea.
Mazzoleni M., Veerlan M., Alfonso L., Monego M., Norbiato D., Ferri M., and Solomatine D.P. (2015) Can assimilation of crowdsourced streamflow observations in hydrological modelling improve flood prediction?, Hydrology and Earth System Sciences, under review
Mazzoleni M., Alfonso L. and Solomatine D.P. (2015) Effect of spatial distribution and quality of sensors on the assimilation of distributed streamflow observations in hydrological modelling, Hydrological Sciences Journal, accepted
Mazzoleni M., Alfonso L., Chacon-Hurtado J.C. and Solomatine D.P. (2015) Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models'', Advances in Water Resources, 83, 323-339.

PriceXD model performance boost and integration of social feedback as model parameters
The Price2D model is currently a model developed by professor Roland Price for surface water runoff over short periods of time. The PriceXD model is a port of this code to C# to allow it to become more flexible not only on choice of core engine (for use of experimental new features, like sub area gridding) but also input/output and use as a service. During the WeSenseIt project, a new core will be developed in C++ and CUDA to harness the power of the high capacity for mathematical operations and parallelization of current generation graphical cards, in an effort to optimize the model run time. Also, as part of the WeSenseIt project, the model will be altered to include social feedback (like tweets and other public information) as model parameters for data assimilation. The showcase is part of the Dutch case (Digital Polder / CityFlood), where users will have the possibility to access and order model runs through the web portal (HydroNET), or view results on their mobile devices (see next technology).

Modelling perception, engagement and behaviour of citizens
The ABM frame development was based on the interviews of a few highly engaged citizens and key professionals from the case studies. The social research is limited by sample size to a qualitative approach which supports flexibility in understanding decision-making behaviour. The frame is then revised as the project progressed based on observed behaviour on the citizen observatory developed through the project. However, due to delays in the development of the citizen observatory, the absence of flood warning event over the research period and no sustained use of the observatory on the two case studies (Doncaster and Vicenza), the development of the framework have been limited to the early stakeholder analysis. The Bacchiglione and Doncaster case studies provide two contrasting examples due to differences in the development of the citizen observatory, in governance, in the flood risk and its management as well as the socio-economic, cultural and geographical context; yet similarities enable building the same modelling framework for both cases.
The role of Information and Communication Technology such as the Citizen Observatory developed in this project can play a major role as they provide a platform to observe the activities of real citizens and professionals. Long-term surveys will also permit to gather evidences on a greater number of flood warning situations. Validation could be done either by a group of experts or by comparing the results of the model with the observed behavior during an event. Calibration will require in-depth analysis of the evidences to better understand the decision process but also to anticipate change in the decision process as a result of the new experienced flood warning and events.
Future developments of the framework may consist of better consideration of the potential failure of the measures, a variable response rate per agent and, finally, a better representation of the flooding and its consequences by integrating flood hazard maps and loss assessment modules.

Related Publication
McCarthy, S., Tapsell, S., McDonagh,R., Lanfranchi, V., Anema, K., When de Montalvo,U. (2013) Report on Requirements analysis for citizen observatories. Deliverable D6.21 European FP7 WeSenseIt project.

Physical and social modelling integration
WSI Project aims to explore the potential integration between physical and social modelling in the context of flood risk management and citizens observatory to improve flood forecast and represent emergency protocols to simulate citizen behaviour in case of flood event. The work developed in this deliverable is one of the first attempts to integrate physical and social models which have different characteristic. Three potential integrations have been considered based on the results of the project.
A first integration has the objective to assess the behaviour of citizens and professionals following a flood warning, focusing on modelling emergency protocols using agent-based model with different river level scenarios inputted from hydraulic modelling. Whereas most of the mitigation actions are identified for social models and some of the inputs parameters could be estimated for physical models, the required information obtained to run both models is still insufficient for the Doncaster case study. For the Bacchiglione catchment, a well-developed protocol and hydrologic model providing validated synthetic scenarios have been inputted in the agent-based model to assess the protocol in different conditions of events and resources (number of volunteers and location). However, this prototype is still at an early-stage and will require further calibration and validation in collaboration with the authorities complemented by a long-term survey of the observatory.
The second integration consists in coupling synthetic river level produced by hydraulic modelling with travel demand model to feed forecast modelling with observed water level. The aim is to better understand how citizens may improve forecast modelling by reporting water level observations. For the Bacchiglione catchment, integrating water depth observations provided by citizen can improve model results even for a small number of citizen-based observations. In fact, higher model performances can be expected increasing the number of such citizen data.
In the last integration, a simplified social model is used to estimate the citizen engagement level to share hydrological observations based on their proximity to the river. The outputs of this model are used to constrain the arrival time of the flow observations assimilated within the hydraulic model. In this case, no travelling between locations is considered. This work package shows that sharing crowdsourced observations motivated by a feeling of belonging to a community helps in improving flood predictions. In particular, the model results can benefit from the additional observations provided by weather enthusiasts.
The most important finding is that flood forecasting can be significantly improved assimilating crowdsourced observations within hydraulic models coming at moment simulated by ABM. In addition, citizen behaviour can be properly represented by ABM in case of different flood event water level provided by the physical model. However, validation of these approaches using real-life flood event has to be performed. Unfortunately, during the period of the WSI Project, no relevant flood events occurred in the case study in order to validate our methodologies.

Related Publication
Mazzoleni M., Cortes Arevalo V.J. Wehn U., Alfonso L., and Solomatine D.P. (2016) Assimilation of crowdsourced observations into a cascade of hydrological and hydraulic models: The flood event of May 2013 in the Bacchiglione basin, under review
Mazzoleni, M. (2016) Improving flood prediction assimilating uncertain crowdsourced data into hydrologic and hydraulic models, PhD Thesis, UNESCO-IHE, TU-Delft, Delft, The Netherlands.

WP4: Participatory Decision Support and Feedback


● Design and implement citizen observatories by establishing an e-collaboration environment for participation, feedback and decision-making
● Development of new methodologies for enabling access, understanding and decision-making based on highly complex, large-scale heterogeneous data.


The project developed an e-collaboration environment for citizens and one for decision makers. The e-collaboration environment supported citizen participation in water governance by providing access through a mobile app or a web browser to the WeSenseIt Citizens Observatory, a platform that contains information and services for citizens. The e-collaboration environment supported decision-makers by providing access through a mobile app or a web browser to a platform for monitoring information about water resources, and organise reactions to emergencies as needed. The e-collaboration environment communicated with the different services providing and accepting information (sensors, models, etc.) via the WP5 platform.

Citizens Observatory
This platform provided means for citizens to communicate and receive information about water resources and contextualising the information (e.g. providing maps, detailed information, warnings related to a specific emergency situation as it unfolds).
The platform was developed by Quinary SPA as an extension and customisation of Ushahidi, an open source web platform that has been used worldwide to share crowd-sourced information and increase situation awareness during crisis.
The original Ushahidi software has been customized, developing a set of plug-ins that implement specific functionalities and can be easily personalized, activated or de-activated, depending on the needs of the community of users. An android application was also developed, for providing mobile access to available data and enabling citizens to share information. The platform has been customized for Alto Adriatico and Doncaster case studies, accordingly to the requirements that emerged from WP6 and WP7.
“Sharing and Collaboration” plug-ins enable citizens to actively contribute to the observatory, by submitting contributions from the fields: posts, reports and social sensor readings about emergencies, flood incidents and water related phenomena, but also about community life. Citizens using the Android app can also be informed if a report is submitted by the authority or in given area or if they enter a dangerous area. “Information Contextualization” plug-ins act as content aggregators from different information sources and allow us to contextualize the information collected by the citizens. Different type of data can be aggregated and integrated with the information provided by citizens: water related news collected from relevant web sites, hydrological data and measurements coming both from WeSenseIt sensors and available open data initiatives (data provided by ARPAV, Environmental Protection Agency of the Veneto region, and by UK Environment Agency), tide times available in specialized web sites ( flood warnings raised by provisional models (AMICO early warning system, by the regional authority Autorità di Bacino), information streams from social networks (Facebook and Twitter), and other publicly available useful data (e.g. points of interests or weather forecasts).
“Exploration and Focus” plug-ins: all the information is visualized to the citizens in searchable lists, maps, charts, and can be browsed and filtered according to different dimensions: geographical, to see, e.g. all the reports sent in a given area, by time interval, to focus on more recent or historical data, or by metadata, such as water level. The observatory can be easily customized using an administration interface to tailor functionalities to roles and users’ needs. Open web base API provides external access to the collected data.

Related Publications
C. Bagnasco, M. Ferraro “Implementing a citizen observatory of water in the WeSenseIt project”, convegno COWM, Citizen Observatories for Water Management, Venezia, Giugno 2016.

Mobile app for citizens
HydroLogic Research (HR) has created several mobile applications in the WeSenseIt project. One set of applications intends to transform citizens into active participating “Water Detectives”. This set of applications has been created with input of UNESCO-IHE and a Dutch water board named Delfland.
The idea behind WaterDetective is to have an easy to use mobile application that can be used as tool to create citizen observatories, as a communication channel for decision makers and as a tool for community involvement.
As part of the WeSenseIt project, Hydrologic Research has developed two mobile applications for mobile devices (cross platform) to be made available on mobile application distribution markets. The first one, RainWatch, is aimed at making precipitation information available to any audience on the globe for free, using Satellite data and Radar data (when available). Premium services, like historical data, may be accessed for a fee. This application should also allow for the viewing of model results (like the PriceXD model), forecasting and service subscription. The second application is aimed at providing augmented reality/3D model result viewing on mobile devices. Currently the functionality for this novel mobile application is under research, but both of them should be showcased during the Dutch study case with the same target audience in mind (anyone that has a smartphone running iOS, Android or Windows Mobile 7 or 8). For the entire area of Delfland, in particular polders and storage basin we developed a basic application on basis of RainWatch. This application uses real-time rainfall, evaporation data (satellite and in-situ) and monitoring data of structures (TA Delfland). Up to 10 days ahead a forecast is made of the wetness of the region, as predictor for pluvial floods and regional droughts.

Related Publications
Jonoski, Andreja, Leonardo Alfonso, Adrian Almoradie, Ioana Popescu, Schalk Jan van Andel, and Zoran Vojinovic. "Mobile phone applications in the water domain." Environmental Engineering and Management Journal 11, no. 5 (2012): 919-930.

Decision-makers platform
To satisfy the needs of decision-makers the following technologies (more details in the following sections) were developed and implemented:
- a web app to monitor information about water resources (K-Now and USFD)
- a low-cost command and control system to organise reactions to emergencies as needed (K-Now)
- a video-communication system (USFD)
- a social media monitoring tool to keep decision-makers up-to-date with any information shared on social media channels (K-Now and USFD)

Related Publications
Lanfranchi, Vitaveska, N. Ireson, U. Wehn, S. N. Wrigley, and F. Ciravegna. "Citizens’ observatories for situation awareness in flooding." In Proceedings of the 11th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2014): 18-21 May 2014, pp. 145-154. 2014.

Web portal and Low-cost command and control system
A web portal was developed to collect information from citizens, sensors and model prediction and visualise the. The dashboard is separated into a set of small widget panels, each showing information ranging from previously reported water levels, to twitter feeds and weather forecasts. StaffSense is a service for crowdsourcing data from members of staff using a set of mobile apps (iOS, Android) and a web interface, creating a low cost command and control solution. The mobile applications (iOS and Android) allow staff on the ground to submit information (using customisable forms), attach pictures and videos as evidence, geolocate submissions, view tasks assigned by the control room, mark the status of the tasks, send/receive message with co-workers and the control room. The app tracks the users’ location in real-time, providing the control room with complete situation awareness over the position of the staff on the ground (historic and real-time). Using the web app, control room personnel can view immediately any information submitted by staff on the ground, assign tasks to the staff, and monitor their progress.

Related Publications
Suvodeep Mazumdar, Vita Lanfranchi, Neil Ireson, Stuart Wrigley, Clara Bagnasco, Uta Wehn, Rosalind McDonagh, Michele Ferri, Simon McCarthy, Hendrik Huwald and Fabio Ciravegna. Citizens observatories for effective Earth observations: the WeSenseIt Approach. Environmental Scientist journal, 2016

On 25th of April 2014, the system was used by the City Council in Vicenza, Italy in evacuating 30,000 people to facilitate the defusal of a 4,000-pound War World II bomb (#bombaday).
The local authorities (Vicenza City Council, Emergency Services and Civil Protection), needed technologies for efficiently managing the event.
Moreover the system was used in a simulation exercise on 10th October 2015, affecting the municipalities of Caldogno, Vicenza, Longare, Montegalda and Montegaldella. These municipalities are members of the Local District of Risk, involved in the hydraulic risk management of the Bacchiglione river.
The exercise represented also the final event of the "Achelous" Project ( another initiative funded by the European Commission in order to identify the best practices of Civil Protection to be activated in situations of hydrogeological and hydraulic crisis.
StaffSense has been tested by Doncaster Emergency Planning Team during the duration of the project and has been adopted to support the Emergency planning Team during a major event, the Tour de Yorkshire.

Video Communication between Citizens and Emergency Control Room
The ‘Eyes on the Ground’ system is a cross-platform application that turns a citizen’s camera into a street camera for the Emergency control room. The system facilitates connecting with citizens via Android, iOS devices and personal computers running a web-browser. Control Room operators can see through the camera of the citizens while simultaneously communicating with them via audio and on-screen messages (e.g. to give instructions or ask questions). Control room operators can take notes, screenshots and record videos, as well as fully control the citizen camera (displaying alternatively front or back camera), hide themselves to reduce bandwidth or show themselves to clarify instructions with body language.
The technology was evaluated in collaboration with the Northern General Hospital in Sheffield with Occupational Therapist providing a proxy domain to Emergency Response, where accurate remote observations of homes is essential to allow patients to return to a safe environment. Since then there has been ongoing interest in further adoption of the technology in the healthcare domain to allow more effective remote interaction between healthcare professionals and their recuperating patients and their relatives. We are also continuing to look at opportunities for the use and exploitation of this technology in emergency response situations.

Related Publications
Ciravegna, Fabio, Suvodeep Mazumdar, Neil Ireson, and Peter Cudd. "Seeing through the Eyes of the Citizens during Emergencies." In The 12th International Conference on Information Systems for Crisis Response and Management. International Association for Information Systems for Crisis Response and Management, 2016.

Augmented Reality
The first augmented reality (AR) smart phone app is meant to visualise potential flood levels of known flood zones in real time. The interactive provides in situ modelling of simple prototype 3D building models (cuboids) along a riverbank, which are then used to “occlude” an augmented flood plain within the scene.
In our first prototype app cuboids were manually scaled and translated to overlay existing buildings within a scene. A key problem of this approach was the ad hoc nature of in situ geometry modelling. A second prototype was subsequently developed where natural / augmented point correspondence were determined using interactive point triangulation and occlusion geometry was added to the scene by selecting two such points to which the two top front facing vertices of the cuboid are fixed.
The current app uses homography based NFT, where a target image is captured and processed in real-time to track the environment. Tracking permits limited site navigation, the extent of which is a function of parallax content, and target image visibility and feature richness.
The main challenge here is to effectively recognize and/or create a 3D model of the surrounding buildings in a given flood zone for correct flood visualisation. Models should be built on-site and in real-time using the app. Once created, models can be uploaded for reuse by all users.

Related Publications
Haynes, P. & E. Lange (2016): “In-situ Flood Visualisation Using Mobile AR”. IEEE Symposium on 3D User Interfaces 2016 (3DUI), 19–23 March, Greenville, SC, USA, 243-244.
Lange, E., and P. Haynes. "Mobile Augmented Reality for Flood Visualisation in Urban Riverside Landscapes." JoDLA–Journal of Digital Landscape Architecture (2016).

WP5: Technological infrastructure


As citizen observatories can scale up to very large scale (as we have seen we have been involved in the emergency control rooms of events involving a total of over a million people), a robust architecture was needed to support the large scale flow of information and data and to provide security and protection.


The core of WeSenseIt architecture is the Software Mind Sensor Platform - a scalable, cloud-based Sensor/IoT platform, which enables flexible integration of modules and elements: physical and social sensors, models, e-collaboration applications, Decision Support tools as well as integration with external systems. The Software Mind Sensor Platform provides the following modules, capabilities and technologies:
● Large scale sensor data collection and integration (Sensor Integration Layer): designed to handle billions of sensor readings and petabytes of data, supporting common formats. Provides sensor management, Web Service API, visualization of sensor data and uniform access to sensor data for applications, user tracking and social sensors at huge scale
● Management of geospatial data at large scale: Data Storage Layer and API based on Apache HBase cluster, effective management of geospatial data (PostGIS, geohash).
● GeoNotifications - high performance geo-located event processing engine: Complex Event Processing engine for high velocity geo-located event streams, allowing real time response at large scale, integrated with e-collaboration/crowdsourcing tools and mobile applications (SensorNotification, Notifi mobile app).
● SensorNotifications – sensor-based event system, including Sensor Integration Layer tools, customer-facing interfaces and Web Service API for integration with external applications.
● Scalable backend for mobile applications: service-based smart backend for mobile applications supporting mobile apps with millions of users.
The Software Mind Sensor Platform integrates and manages all sensors and is integrated with solutions, systems and mobile applications in WeSenseIt (Citizen Portal, Decision Makers Portal, StaffSense, Water Detective, Sensor Notifications etc.). Existing sensor networks and early warning systems can be easily integrated in with social sensors, mobile applications and external data, enabling new approaches to data capturing, integration methods, cross-validation, data assimilation techniques and updated adaptive water models.
All sensors can be viewed and managed in one place, with easy registering of new sensors, monitoring status, visualisation of measurements and notifying of failures or invalid values. Citizens can subscribe to warnings based on selected sensors. External applications can connect to data from all sensors by unified, well-documented API – all data are accessed the same way, regardless of the source and technologies/protocols used by various sensors (including social sensors). The platform provides also unified OAuth authentication in Sensor Integration Layer for all registered applications.
The platform can be easily scaled out for a big number of sensors and can support mobile applications with huge number of users. The use of computer resources and the load are monitored through specialised tools. Scalability and high availability provided by the Platform is a must for emergency applications. During an emergency event popularity of such an application can grow very fast (much faster than for example a running or banking app), and stability of the system has to be preserved at all times.

WP6: Governance and social innovation


This work package developed social scientific frameworks to analyse i) the governance and stakeholder context within which the development and implementation of citizen observatories took place and to trace changes to governance processes arising from the implementation of the innovative citizen observatories; ii) the motivations (incentives & barriers) of citizens to participate in ICT-enabled citizen observatories, and iii) the different dimensions of citizen observatories.


These objectives were met by the development and successful application of the following frameworks.
i) Governance analysis framework
The implementation of the European Flood Directive 2007/60/EC requires the establishment of public participation mechanisms to ensure citizens’ involvement in the flood management cycle. WeSenseIt developed a framework for analysing the potential for participation via ICT-enabled citizen observatories and undertake a comparative analysis of the UK, the Netherlands and Italy. Expository and qualitative research was undertaken in the three case study areas, with the aim of identifying and comparing the transposition of the EU Flood directive and the mechanisms in place for citizens’ participation during different phases of the disaster cycle (prevention, preparedness, response, and recovery). Our base line analysis of the transposition of legal obligations for citizen participation shows that implementation is limited when examining both the respective roles and types of interactions between citizen and authorities and the impact of citizen participation on decision-making. Different authorities have differing perceptions of citizen participation in flood risk management in terms of their roles and influence. Our results also indicate that these perceptions are related to the importance that the authorities place on the different stages of the disaster cycle.
The subsequent analysis showed that all three WeSenseIt cases demonstrate changes to citizen participation as measured by our conceptualisation, albeit to varying degrees. Beyond involving citizens in data collection, in all three cases, the authorities appear hesitant to transfer their interactions with citizens into the online environment of the observatory, owing to fears of interrupting already establish procedures and the need of having to respond. Liability and accountability concerns are particularly salient in the preparation, impact and response phases of flood risk management (e.g. having to respond quickly to online posts about flooding, creating an additional channel for the emergency response team, separate from their existing decision support systems). Overall, our findings indicate that governance changes towards fundamentally more involved citizens with high impact (i.e. have a direct say) in flood risk management are not (yet) detectable nor envisaged by the involved authorities. In line with a nuanced (i.e. non-normative) understanding of water governance that conceives governance goals as locally-defined rather than universally applicable, the changes resulting from the introduction of citizen observatories are equally location-specific and locally-shaped, presenting relative changes in all three cases. Yet these changes are limited in absolute terms regarding greater participation. The conceptual framework developed for this governance analysis (i.e. relating the range, role and authority of citizens involved in flood risk management) was successfully operationalised and can be applied to trace changes to the governance processes triggered by the implementation of citizen observatories.
ii) Incentives and barriers framework
In order for citizen observatories initiatives to pan out well, various actors need to be willing to engage in these activities, such as decision makers from various local or national authorities, policy makers, scientists in academic, educational and applied professional environments, and of course citizens, often stemming from distinct interest or contributor groups. These actors are subject to (distinct) incentives and drivers. The particular interest of this research effort lied with the latter – the citizens – and their motivations to participate in ICT-enabled citizen observatories since, arguably, without citizen participation, there is no citizen observatory. Moreover, their involvement in citizen observatories typically required and desired not once, but on a continuous basis. To better understand what determines citizens’ interest to participate in citizen observatories, the lens of a decision making theory was used. The analysis and findings are based on qualitative empirical research carried out in the WeSenseIt case study locations in the Netherlands, United Kingdom and Italy. Subsequently, a model was developed that depicts the main drivers and barriers for citizen participation in weather observatories. The resulting model can be utilized as a tool to develop strategies for further enhancing ICT-enabled citizen participation in climatic observations and, consequently, in environmental management.
iii) Dimensions of citizen observatories
The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public and has resulted in the formation of various online environmental citizen observatory networks. The objective of this research was to introduce a conceptual framework that enables a systematic review of different dimensions of citizen observatories. These dimensions include the geographic scope and types of participants, the network's establishment mechanism, revenue stream(s), existing communication paradigm, efforts required by participants, support offered by platform providers, and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run the networks, and their sustainability. This framework is then utilized to perform a critical review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) there are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks; (2) the revenue stream(s) of online amateur weather networks is one of the least discussed but most important dimensions that is crucial for the sustainability of these networks; and (3) all of the networks included in this study have one or more explicit pattern of bi-directional communication, however, this is limited to the feedback mechanisms that are mainly designed to educate the data-sharers.
The framework introduced in this study enables a systematic review of a particular type of mature citizen observatory, namely online amateur weather networks as hubs for one of the oldest and most widely practiced citizen science activities. This was facilitated by breaking down the complexities of these initiatives into unequivocal elements that are comparable across different cases. This systematic review is highly valuable for benchmarking purposes by researchers, platform operators and also citizens to compare and contrast different citizen observatories. Such evaluations can also generate valuable insights about the features and functioning of different observatories that may consequently help enhance citizen participation. Furthermore, the framework developed in this research can also be utilized by researchers and platform operators as a tool to monitor the changes of the observatory over time.

Related Publications
Wehn, Uta, Maria Rusca, Jaap Evers, and Vitaveska Lanfranchi. "Participation in flood risk management and the potential of citizen observatories: A governance analysis." Environmental Science & Policy 48 (2015): 225-236.
Wehn, U., McCarty, S., Lanfranchi, V. and Tapsell, S. (2015) Citizen observatories as facilitators of change in water governance? Experiences from three European cases, Special Issue on ICTs and Water, Journal of Environmental Engineering and Management, Vol. 14, no. 9, pp. 2073-2086.
Wehn, U. and Evers, J. (2015) The social innovation potential of ICT-enabled citizen observatories to increase eParticipation in local flood risk management, Technology in Society, August, pp.187-198 doi:10.1016/j.techsoc.2015.05.002.
Gharesifard, M. and Wehn, U. (2016) To share or not to share: drivers and barriers for sharing data via online amateur weather networks, Journal of Hydrology, Vol. 535, April, pp.181-190 doi:10.1016/j.jhydrol.2016.01.036.
Gharesifard, M. and Wehn, U. (2016) What Drives Citizens to Engage in ICT-enabled Citizen Science? Case Study of Online Amateur Weather Networks, in Ceccaroni, L. and Piera, J. (eds) Analyzing the Role of Citizen Science in Modern Research, IGI Global, pp. 62-88.
Gharesifard, M. and Wehn, U. (2015) Participation in citizen science: Drivers and barriers for sharing personally-collected weather data via web-platforms, presented at the 8th International Conference on ICT, Society and Human Beings (ICT2015),21-23 July, Las Palmas de Gran Canaria, Spain.
Lanfranchi, V., Wrigley, S., Ireson, N., Ciravegna, F., Wehn, U. (2014) Citizens' Observatories for Situation Awareness in Flooding, in S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih (eds) Proceedings of the 11th International ISCRAM Conference (Information Systems for Crisis and Response Management), 18-21 May, Pennsylvania, USA: University Park; 145–154.
Gharesifard, M., Wehn, U. and van der Zaag, P., Dimensions of Citizen Observatories: The case of online weather networks, Environmental Management, under review.

Deliverable D6.1 and D6.3

WP7: Case studies


WeSenseIt validated the envisaged citizen observatory of water and demonstrated the applicability of its outcome through three case studies in distinctly different European areas (UK, Netherlands, Italy). Given the differences not only in topography and climate but also in land use and social context, the water challenges that arise are equally distinct: water quantity and quality management in the Dutch case, river flooding and dam management/failure in the UK and problems of floods and water shortage in Italy. As such, the three cases were complementary and all benefitted significantly from the technology developed within WeSenseIt.

Alto Adriatico Case Study
The Alto Adriatico Water Authority (AAWA) is responsible for the river basin plans for the Hydrographic District of the Eastern Alps in Italy, and promotes planning that includes remedial measures to reduce hydraulic and geological risks, supporting at the same time water-related Authorities and Civil Protection Agencies in case of emergencies caused by floods with an Early warning system for water risk management.
The goal of WSI in the Alto Adriatico Case Study was to develop a Citizens Observatory (CO) on Water, in order to integrate data acquired by physical sensors, then processed by the already existing predictive mathematical models, with the data and knowledge coming from the community of citizens, making the entire water management process more effective.
AAWA focused on the set-up of a group of stakeholders (Municipalities, Regional Civil Protection Agency, Environmental Agencies, Irrigation Authorities) concerned with the management and use of the water resources, and with water related hazards in the Bacchiglione river basin, establishing a cooperation that has been the foundation for the identification of the citizen-based observatory composition and the hub for WSI technology transfer on the territory. The created Observatory of Citizens is composed not only by technicians of the main agencies involved in the defence of territory but also by the citizens, such as Civil Protection volunteers and school students of various levels. The purpose of involving both communities and emergency services was to increase situational awareness and community engagement.
The research areas covered in the Alto Adriatico case study concerned in particular the development of social and physical sensors, the integration of heterogeneous sensor networks with models and the improvement of hydrological predictive models.
The improvement of the monitoring and alert system in real time by integrating in the predictive models and in the DSS information from:
1) the use of cheap and innovative measuring sensors which may also be used directly by the citizens; the entire set of sensors developed by the project was installed on the river Bacchiglione and its related water courses.
2) the exploitation of collective intelligence by monitoring social networks (e.g. Facebook and Twitter) and the use of tools such as properly designed web and smartphone apps, used both by experienced and trained staff (e.g. Civil Protection volunteers) and by citizens.
The case study gave the opportunity of testing the effectiveness, the viability and the benefits of using the WSI technology, methodology and tools for increasing citizens’ awareness, enabling a more timely and effective reaction to adverse events and for improving the short term forecasts of existing water related models.
As part of the improvement of predictive hydrological models, in WSI project research activities were planned to improve the performance of AMICO (Alto Adriatico Hydrological-Hydraulic Model) forecasting platform, developed by AAWA as a result of the November 2010 flood event that caused damage for more than a billion euro in Vicenza territories. WSI planned to increase AMICO's reliability by assimilation of data coming from the CO and consequently not homogeneous in space and time.
Three major evaluation events were carried out in the Alto Adriatico region:
● WeSenseIt technologies were used to support the exercise Aquadike in Vicenza in March 2014 involving the Civil Protection and the City Council of Vicenza where hundreds of citizens and volunteers were involved in the use of the WeSenseIt command and control technology, as well as the large scale social media analysis
● WeSenseIt command and control technologies were used to support the coordination of the Civil Protection teams during the evacuation of 30,000 citizens from the City of Vicenza during the defuse of a World War II bomb in April 2014. During the same exercise, the large scale social media technologies were used to monitor the process of evacuation through the eyes of the citizens.
● A final evaluation was carried out in October 2015 involving the civil protection of Veneto, the City of Vicenza and a delegation of civil protections bodies from the Balkan states.
The Alto Adriatico case study was very successful: Citizen Observatories have been accepted by the Italian Government as a key measure for the European Flood Directive (2007/60) and Water Framework Directive (2000/60) in the Italian Eastern Alps District. These will be heavily based on the WeSenseIt core. The measure has been already included as a measure in the civil protection plan of the Vicenza municipality, where teams of volunteers are dedicated to carry out civil protection actions supported by the technologies developed in WeSenseIt Project.

Doncaster Case Study
The South Yorkshire county has a history of significant flooding events, where the flood risk arises from distinct aspects of the topography and its network of river catchments. In its western half, parts of the district rise to 500 meters above sea level. On the east, very low lying areas exist with an extensive area of floodplain and tidal influences. In addition, valleys to the north and west of the county contain 17 major reservoir dams, which feed into the major watercourse of the River Don. This makes the county liable to fluvial (river), pluvial (rain induced) and marine (sea) flooding caused by heavy rainfall in the catchment and tidal fluctuations and potential floods from dam failure.
The town of Doncaster has the highest flood risk of all the communities in South Yorkshire, with records of flood events dating back to 1536. Currently 25,000 properties in Doncaster are at risk from River Don flooding. This flood risk has had a large economic, social, physical and psychological impact on citizens, especially following a large-scale flood event in 2007. For example, in 2007, 5171 buildings were flooded in Doncaster. While flood waters receded quickly in most cases, Bentley and Toll Bar in Doncaster still had several hundred properties submerged for several days, largely due to flood defences being overtopped by increased river heights . The Doncaster case study area is in between two catchments: the River Don and River Trent catchments. In addition to this geographical complexity, it is managed by two Environment Agency regions: the Yorkshire and the Midlands region. The management by the formal institutions is further divided between three Water Authorities, namely Yorkshire, Severn Trent and Anglian water authorities. It should be noted that the Anglian Water Authority only serves a very small area. The Doncaster area is further broken down into two Regional Flood and Coastal Committees (RFCC), which are Yorkshire RFCC and Midlands RFCC and eleven internal drainage boards.
The Environment Agency manages water resources and enforces water quality standards at the national level. The Environment Agency is mandated to develop and coordinate the implementation of the national flood and coastal erosion risk management strategy while Doncaster Metropolitan Borough Council is charged with the responsibility of developing and coordinating implementation of the local flood and coastal erosion risk management strategy as stipulated in the Floods and Water Management Act 2010 (FWMA). Doncaster Metropolitan Borough Council is the largest metropolitan borough in England and covers the area of approximately 56,000 hectares.
WeSenseIt carried out extensive user and stakeholder analysis through a number of community meetings organised in the different boroughs of Doncaster with both citizens and decision makers, as well as emergency operators. The whole spectrum of physical sensors developed by the project were installed on the river Don, providing an efficient and effective alert system, complemented by citizen observations via the citizen apps developed by both Quinary and K-Now. Different evaluations were performed at different points during the project and culminating with a city wide evaluation where communities and decision makers were involved in using the technology.
Associated to the Doncaster case study was a UK-wide support of emergency control rooms carried out by The University of Sheffield and K-Now. The support was provided during real life events involving over a million people. They were:
● Glastonbury: Largest Music Festival in the World, June 2013 and 2014 200,000 participants per event
• Users: Organisers and Silver Command
● Tour de France (UK), July 2014
• User: Sheffield CC control room
● Tour de Yorkshire, April 2016
• User: Doncaster CC control room
● Bristol Harbour Festival, July 2013 and 2014, 250,000 participants
• User: Emergency Services
● Leeds Music Festival, August 2013, 80,000 participants
• User: Security Company
● Bristol St Paul’s Carnival 2013, 70-150,000 participants
• User: Bristol Emergency Services (Silver and Bronze Commands)
● Brixton Kerrang Event 2014, 20,000 participants
• User: Kerrang Organisers
The domain of large events was chosen as a proxy for flood emergencies in order to prepare and test the technology in real world.

Delftland Case Study
The objective of the Delfland case study was, first, to test the technologies developed in the other work packages of WeSenseIt and, second, to enhance the collaboration between the Delfland water board (HHD) and its residents by installing a WSI citizen observatory.
In order to test the technologies of the soil moisture sensors and Lizard Boxes developed by StarLab thirty sensors and fifteen boxes were installed, spread homogeneously over the Delfland region. In order to get insight in the retention capacity at the different locations an algorithmic model was developed; using the incoming data of the 30 installed measuring points. In order to test the technologies of the disdrometers developed by Disdrometrics BV we installed nine disdrometers on the roof of interested private parties and people. We first installed four and later five more as the calibration of the sensors proved to be a challenging issue. The sensors needed access to power and an internet connection to collect and send their measurements. Both the guardians (with a disdrometer installed on their roof) and the WeSenseIt researchers we able to monitor the collected data – and the functioning of the sensors, at the website developed by Disdrometrics ( and on the WeSenseIt observatory ( In order to get insight in the reliability of the collected data the disdrometer measurements were compared with rainfall data collected by the Royal Dutch Meteorological Institute (KNMI). The disdrometers network and findings are elaborated on in Section 4.
In order to test the technologies of the mobile application, called WaterDetective, developed by Hydrologic Research, we tested the functionality and user-friendliness of it with small groups of Delfland employees, students and Scouting kids. As there were no real events to report on, these testing rounds (six in total, using varying methods and different categories for the observatories) focussed on whether or not people understood how to operate the different functions and if they think they would use it if the occasion occurred. Users of the application could see their own uploads, and those of others, at the in-app map and on a shielded page at HydroNET. In order to get insight in the usefulness of the reports that could be uploaded we had in-depth interviews with Delfland representatives in different departments and management levels.
Enhancing the collaboration between HHD and its residents was less clean cut. Initially we engaged with a national project that HH Delfland was participating in called Digital Delta. This project and its objectives however focussed mainly on the use of big data. At that stage there was no ‘big’ data being generated by the WeSenseIt observatory - and the engagement with residents required for WeSenseIt was much more laborious than the other Digital Delta projects. Because of this, the incoming data at the observatory was not being used or monitored by Delfland; which made it challenging to create a two-way exchange at the observatory.
Learning from this experience we tried to relate with other departments within HH Delfland; such as the Communications department responsible for the social media accounts of the water board, and the ‘Permits & Maintenance’ department responsible for solving any irregularities that are reported on in the Delfland water system. For each of these departments however the topic of pluvial and especially fluvial flooding provided a problem, because preventing floods is the core task of the HH Delfland and it was felt that this responsibility should not be shared with residents. This is, they saw no clear added value for the waterboard to engage in the observatory, as they felt there was no role for citizens on the issue of flooding.
Evaluating the citizen observatory in Delfland was not straightforward. One of the findings in this case study was that active engagement with the participants is not only needed to get/keep the platform going - but also labour intensive. Normally, the water board engages with residents on a personal, demand-driven level for WSI a more daily and overarching engagement was needed. Delfland did not have the resources available to work with the WSI platform in such an intensive way; which was a main retainer in the development of a full-fledged observatory. At the citizen side of the observatory, virtually all participants and respondents (all three types of sensors) indicated that more feedback from the water board - and a clear purpose for their uploads and input, would have motivated them better to The water board more or less confirms that, as flood risk management is their core task and regarded as something that needs to be handled by experts. HH Delfland already has an extensive network of sensors installed throughout her territory, leaving the WSI platform for them as a ‘nice to have’ but not urgently needed. The WaterDetective app was tested with various topics on different user groups and with different evaluation methods. The urgency or interest for using the app was modest, however the functioning and user-friendliness of the app was rated rather good. All the collected data was integrated with Delflands own monitoring data on the HydroNET portal and apart from the separate online dashboards for each sensor was also visualised on the WSI portal. The generated datasets were successfully used to build models on precipitation and soil moisture.
Potential Impact:
WeSenseIt has been a very successful project from a research and applications point of view, advancing the state of the art in citizen observatories for the environment both from a technical and social point of view.
Its legacy concerns a number of areas:
1. The scientific results that are documented in dozens of publications in different disciplines; this is documented in Deliverable D8.12
2. The innovative products generated by our SMEs and that have now reached or are about to reach the market; these are documented in Deliverable 8.22
3. The innovative technologies and products created by our universities and research centre which have been either taken up by our partner SMEs or have found an independent way to market; these are described above and in more detail in several deliverables from WP1, 2, 3 and 4 and in D8.22.
4. The algorithms to optimally complement the existing monitoring networks with citizen data (D2.2 D2.3) as well as the improvement of water models with data assimilation (D3.2).
5. The citizen and decision makers’ communities gathered around the three case studies and other areas where the project results have been adopted (D7.20 D7.30 D7.40)
6. The technical infrastructure (sensors installed, the architecture supporting data collection and data analytics/visualisation, the apps and systems made available to citizens and stakeholders). See deliverables from WP1, 2, 3, 4 and 5
7. The follow up projects, activities and uptake involving single and multiple partners in areas as different as environment, smart cities, health, etc.
Each of these is successful on their own but WeSenseIt’s legacy goes well beyond the single sum of the parties. The consortium believes that in keeping them coordinated we will enable an impact that will go well beyond the funded timeframe of the project.
It is worth reminding how for example Citizen Observatories have been accepted by the Italian Government as a key measure for the European Flood Directive (2007/60) and Water Framework Directive (2000/60) in the Italian Eastern Alps District. These will be heavily based on the WeSenseIt core. Therefore it is necessary that the organisation provided by WeSenseIt is kept intact and actually evolves over the next few years.


Through a large number (120) of events and presentations, the project consortium attempted to reach a wide range of academic and decision-making audiences. These audiences spanned Europe but also international venues such as the United States and South Korea. The project provided constant dissemination activities via the website ( ), Facebook, ( and Twitter ( @WeSenseIt). The scientific dissemination activities included several publications in international Open Access journals, and numerous publications and presentations at international and national conferences, workshops and public engagement events. Various other video and press attention is listed below with links for further details.
WeSenseIt was also a major contributor to several events organised by the European Commission as part of the Citizen Observatories initiatives.

COWM 2016 Conference
The major dissemination event was the International Conference on “Citizen Observatories for Water Management” (COWM 2016), that was organised in Venice in June 2016 which was not only a wide dissemination event to share with an international panel of experts the experiences, methodologies and problems encountered in WeSenseIt, but also the stage for a fuller understanding of the Citizen Observatories also to other fields of application (which were not only emergency management) and to open these topics to a wider audience to share experiences and discussions. The themes of the Conference focused on the research of new instruments, available under the broad title of "Citizen Science", to be used, together with other traditional instruments, in hydraulic risk mitigation, in the defence of territory, environment, infrastructures and water resources from natural and man-made disasters, by limiting the condition of potential damage, and simultaneously preserving the economic development of the territory. This Conference was an opportunity to generate discussion and debate among specialists of the international academic communities, including professionals, public administrations, businesses and engineering companies engaged in the water resources sector. The response to the invitation and to the debate on the use of "Citizen Science" has been very positive in terms of number of received contributions (over 75 scientific presentations by leading experts coming from all over the world (more than 15 nations)), confirming the importance on an international level of the data engineering processes that exploit the potential of citizens’ collective intelligence, via mining of social media and monitoring of information provided directly by citizens, in order to pursue a common interest.
The main topics presented at COWM 2016 Conference were:
● the role of Citizen Observatories in catchment monitoring and management (including water quality and ecosystems monitoring);
● the Citizen Observatories as support for Crisis Management and Disaster-resilience (enhancing the resilience of communities and emergency services through smart technologies);
● the methods and technologies at the service of Citizens (ICT and Innovative Sensors, Remote Sensing, Crowdsourcing and Sensors data Integration, Data Assimilation Techniques, Modelling);
● the social dimension of Citizen Observatories (engagement strategies to enhance citizen participation in public governance, including leveraging incentives and addressing barriers for citizen participation and data sharing).
The Scientific Committee of the Conference was made up of many members from WSI Consortium, with representatives from UNESCO-IHE, University of Sheffield, AAWA, EPFL, Middlesex University, Software Mind, and other relevant personalities of the Citizen Science area of expertise (GEO, NILU, CSA, ESA, ECSA, etc.).
Many WSI Consortium partners participated in the Conference with relevant contributions:
● Huwald H. et al., Sensing technology for citizen observatories: the WeSenseIt project
● Brauchli T. et al., Low-cost sensors for distributed surface-atmosphere heat exchange monitoring – a novel component of citizen observatories
● Van de Giesen N. et al., Open Hardware Raindrop Arrival Rate Sensor for Citizen Science
● Gharesifard M. et al., A framework for analyzing the impact of ICT-based citizen science initiatives
● Anema K. et al., What you sow is what you reap: a comparison of Citizen Observatories on their implementation and societal results
● Alfonso L. et al., Information Theory-based Design of Optimal Dynamic Rainfall Networks
● Chacon-Hurtado J.C. et al., Comparison between passive and active social sensors of precipitation for flood forecasting
● Mazzoleni M., Assimilation of streamflow observations from an heterogeneous network of distributed sensors in hydrological modelling
● Bagnasco C. et al, Implementation of a Citizen Observatory of Water in the WeSenseIt project
● Mazumdar S. et al., Engaging Citizens and Communities for Emergencies
● Viavattene C. et al., Evaluation of flood emergency protocols using agent-based approach
● Sieprawski M., The value of Internet of Things integration in water governance, decision making and crisis management
● McCarthy S. at al., Co-development of a citizens’ observatory to enhance local citizen decision making: lessons from the WeSenseIt project
all available in Citizen Observatories for Water Management, Conference Proceedings, Venice, 7-10 June, 2016.

During the Conference a technical visit was organized with the aim to showcase to the participants the active and operational example of Citizen Observatory in Vicenza.
During the visit the conference participants were accompanied to discover the observatory of citizens operating in the field of environmental monitoring and emergency management, visiting the control room supported by WSI technology (platform technology (QUI), mobile application (QUI, USFD), forecasting system (AAWA)) and assisting to a demonstration of the technologies, techniques and equipment in support of the CO (action measuring instruments (including SSS and DSD sensors), drones, flood barriers, etc.).
In particular Quinary released for this occasion a new version of the Citizens app adding some requested functionalities.

Thanks to the conference, experts from worldwide have been able to reach out that citizens informed, prepared and properly trained, equipped with hi-tech equipment are able to better address the growing risks arising from extreme weather events and to provide useful information, necessary to the authorities to take the right decisions. And that the increasing of "resilience", i.e. the ability of populations to react and adapt to emergency situations, allow to save lives, reduce economic losses and contain the damage by floods that are becoming more numerous. The COWM2016 conference examined in all its aspects the role and opportunities for active participation of citizens in monitoring and environmental policies, in response to the challenges of the Framework Directive on Water (2000/60 /EC) and the Floods Directive (2007/60/EC). An involvement that goes also through the use of modern technologies able to transmit real-time monitoring data and to make effective a constant feedback change between civilians and control rooms/decision makers. The Conference created an important opportunity in order to promote applied research topics about the potential of Citizen Science in the Water Governance between universities, research institutions, local government and professionals of the water management sector, and it was also an occasion to bring to light and comparing experiences from all over the world: from Australia to the United States, from Scandinavia to South Africa.

Other dissemination events
● PCWorld article on flood monitoring and protection, covering the WeSenseIt Project
● A demonstration video, taken by the River Don, Sheffield, was presented at the GEO international conference in Geneva, Switzerland in January 2015 and at an Internal Seminar at the Politecnico di Milano, 9th–11th March 2015.
● UNESCO-IHE Institute for Water Education produces a biennial magazine called UPDATE, featuring water education, research and capacity development activities. 15,000 free copies per issue are printed, which are sent to UNESCO-IHE counterparts across the world:
● BBC article on EGU 2014, Jonathan Amos Smart umbrellas ‘could collect rain data’:
● article on EGU 2014, ANP, Nederlander bouwt paraplu om tot regenmeter:
● Delta article on EGU 2014, Philip Gangan, Smart umbrellas to collect rainfall data:
● Telegraaf article on EGU 2014, Telegraaf / ANP, Nederlander bouwt paraplu om tot regenmeter:
● Radio interview on RNE (Europa Abierta) discussing citizen observatories:
● Doncaster Council was involved in promotional video discussing the impact of the WeSenseIt Project on the council and its community:
● A leaflet was produced for project:
● An Italian leaflet, a promotional video and other shooting were produced for the activities connected to the Italian case study:

Impact and follow up EU projects
A number of European and national projects as well as industrial ones are currently already benefiting from the WeSenseIt legacy. Here we list the main ones and describe how the legacy has influenced them and how they are going to keep the legacy alive.

GroundTruth2.0 - Environmental knowledge discovery of human sensed data
Ground Truth 2.0 is a 3-year project funded by the European Commission under the H2020 programme. The project aims at demonstrating and validating six scaled up citizen observatories in real operational conditions both in the EU and in Africa. It will strengthen the full feedback-loop in the information chain from citizen based data collection to knowledge sharing for joint decision-making and cooperative planning. WeSenseIt partners involved are UNESCO-IHE (lead), Starlab and HydroLogic Research.

WeSenseIt legacy in GroundTruth2.0
● GroundTruth is mainly based on the social science methods developed in WeSenseIt, in particular approaches for stakeholder identification and user-centred approach for building a citizen observatory.
● GroundTruth will apply and improve the methods for dynamic monitoring design and data assimilation into models developed in WeSenseIt’s WP2 and WP3

SETA: Big Data for Mobility in Smart Cities
SETA creates technologies and methodologies set to change the way mobility is organised, monitored and planned in large metropolitan areas. The solutions are based on large, complex dynamic data from millions of citizens, thousands of connected cars, thousands of city sensors and hundreds of distributed databases.
Seta is a H2020 project involving USFD (Coordinator), K-Now and SoftwareMind. It focuses on the involvement of citizens in monitoring mobility in large metropolitan areas ( The project started in February 2016 and will end in January 2019.

WeSenseIt legacy in SETA
A large part of the WeSenseIt legacy is used in SETA. Key in SETA is the concept of citizen observatories of mobility; these are organised around a concept developed by WeSenseIt with community involvement and participatory sensing. The concept of citizen observatories is evolved from WeSenseIt along the lines already delineated in this project as in creating an infrastructure where citizens are enabled to create their own observatories with very limited resources and start collecting and sharing data through the platform right away. The community involvement strategy developed in WeSenseIt is the basis for requirement analysis and community involvement in the project, with three communities involved in three countries (UK, Spain, Italy).
The large-scale data architecture in SETA is provided by SoftwareMind using the WeSenseIt architecture as shape, blueprint and first version of the code. Similarly the participatory sensing technologies developed in WeSenseIt will be the starting point of SETA: the physical activity tracking app and infrastructure developed by USFD will be used and further developed to monitor non-motorised mobility and public service usage in three large metropolitan areas covering thousands of square miles and millions of people (in Birmingham, Santander and Turin). The visual analytics platform developed by K-NOW will be developed and used to provide services to business, citizens and decision makers. These are key deliverables in SETA and are only possible thanks to the legacy provided by WeSenseIt.

Tracking Health in a Large Population
The project involves the University of Sheffield, as well as K-Now as subcontractor.
Aims and Objectives. The aim of the project is to provide support to healthy living to a million users in the UK. It is funded by a part of the UK government. The project supports the National Health Service (NHS) strategic vision of OneYou, involving a healthier lifestyle in the areas of smoking, drinking, eating, moving, sleeping and stress reduction. Our technology is the key support for moving.

WeSenseIt legacy in Tracking Health
The health organisation have adopted the activity tracking technology developed by USFD in WP1 to track and influence the lifestyle of UK citizens who are in need of a healthier lifestyle, e.g. because they need to move more. The technology is comprised of a mobile tracking technology working for Android and iOS, a scalable server architecture and a visual analytics environment. USFD is the main contractor with K-Now as subcontractor. The role of USFD is to provide a service to the health organisation, scaling up to a million users and to provide PHE with insight of the effects of different aspect of the campaigns (e.g. TV ads, and the messages delivered through the app itself). K-now is providing development capabilities to support USFD’s programmers for both app development and large scale visual analytics (derived from the tools developed in WP4 of WeSenseIt).

Football Whispers
The USFD is collaborating with a company focused on data provision and analysis to exploit the Information Extraction technology developed in WeSenseIt. FootballWhispers ( is the first project which has now been running for 1 year, as provides information to users and some of the main media outlets (e.g. SkySports). The FootballWhispers provides an excellent testbed and showcase for WeSenseIt technologies. In addition to the potential improvements to the system discussed about, future work involves removing the Twitter API limits by using the Gnip ( twitter data provider, and expanding the data to other sources, e.g. blog posts. Extending within the football domain to other countries/languages, and also to other sports. It is also hoped to secure funding to transfer the technology to other domains, e.g. the discussion of health related issue.

WeSenseIt legacy in Football Whispers
The Information Extraction technology and social media processing framework forms the backend to the information presented to the users on the FootballWhispers website.

beAWARE: Enhancing decision support and management services in extreme weather climate events
beAWARE is a H2020 project (in detail H2020-DRS-01-2015: Crisis management topic 1: potential of current and new measures and technologies to respond to extreme weather and climate events and teaching)

WeSenseIt legacy in beAWARE
An important part of the WeSenseIt legacy will be used in beAWARE. In fact the intention is to rely on platforms, theories and methodologies that are already used for disaster forecasting and management and add the elements that are necessary to make them work efficiently under the same objective.

KidronNar - From conflict on wastewater management in the Kidron/Al-Nar basin towards sustainable development by decentralised local solutions for wastewater treatment and reuse
KidronNar is a 3-year project funded by the internal fund of UNESCO-IHE for research at countries in development and in transition, focusing on the topics of improved catchment area management and safe deltas and access to clean drinking water and basic sanitation and the cross-cutting themes of Water governance and Water diplomacy.

WeSenseIt legacy in KidronNar
The project will generate grass-root awareness and support from local Palestinian and Israeli communities for decentralised treatment and reuse by involving communities in monitoring of wastewater related pollution or nuisances (citizen observatories). In addition, it will create an online platform where citizen observations can be mapped in real-time, and provide “what if” scenarios for decentralised treatment. These tasks take as a base the methods developed in WeSenseIt, in particular WP2, WP3 and WP6.

B-Putra - Strategic Basin Assessment of Brahmaputra System in Northeast India
B-Putra is a 1-year project funded by the World Bank and lead by Antea Group, in which UNESCO-IHE is a partner.

WeSenseIt legacy in B-Putra
The project will use the algorithms for data assimilation developed in WP3, in which heterogeneous data is assimilated to improve hydrological models. The assessment of the Brahmaputra basin will rely on the improved hydrological model.

GROW Observatory: citizens’ observatory for family farmers gardeners and growers
The GROW project is one of the four citizens’ observatory within the second round of COs projects funded by the European commission (H2020). Starlab and Hydrologic are involved in the project, Starlab as WP leader of the sensing platform, and Hydrologic as WP leader of the informatics platform.

WeSenseIt legacy in GROW Observatory
GROW is taking advantage of technological development from WeSenseIt such as the probe and the informatics infrastructure, and general background of Citizens observatory.
List of Websites:

Professor Fabio Ciravegna
Department of Computer Science
University of Sheffield
Regent Court, 211 Portobello,
Sheffield, S1 4DP United Kingdom
tel: +44 (0) 114 22 21940
fax: +44 (0) 114 22 21810