The Delft Measures Rain Citizen-Science programme has been running for several years in the city of Delft, the Netherlands. Within this programme, interested citizens can apply to receive a low-cost Alecto WS5500 weather station, to measure local meteorological parameters in their own garden. Currently there are over 45 of these citizen-science weather stations spread across neighbourhoods in Delft, capturing rainfall variability in different urban microclimates. However, the scientific quality of these specific stations has never been tested, and from previous work we know that rigorous quality assurance is necessary in order to get meaningful (precipitation) data. Thus we have installed 8 Alecto stations in The Green Village outdoors urban climate field lab at the TU Delft. Stations have been explicitly installed in ways that a citizen might do: slightly tilted, next to a wall (simulating the limited open garden space of a Dutch urban residence), on top of a shed as well as free-standing. These different measurement setups, combined with a row of stations installed in the same way right next to one another, allow us to investigate the bias caused by less-than-ideal station installation, as well as systematic errors related to the tipping bucket mechanism and sensor drifts. Initial results show a general overestimation of the Alecto compared to reference stations and radar observations, and a discernible negative bias caused by sheltering effects of plants and, to a lesser extent by walls.@en

Citizen science (CS) has so far failed to achieve its potential to contribute to water resource management globally despite a significant body of work proclaiming the benefits of such an approach. Also, this work has addressed concerns over precision, accuracy and reliability of methods used. This article presents the findings of a hackathon-type workshop challenge that brought together water quality experts and CS practitioners to explore barriers and possible solutions to mainstream citizen scientist-generated data into national, regional, and global reporting processes, and thereby provide a tangible connection between policy makers and community-based citizen scientists. We present the findings here as a perspective-type summary. This workshop challenge highlighted the breadth and scope of CS activities globally yet recognized that their potential for positive impact is going unrealized. The challenge team proposed that impact could be improved by: developing awareness; applying a simultaneous bottom-up/top-down approach to increase success rates; that local leaders or ‘catalysts' are key to initiate and sustain activities; that generated data need to fulfill a purpose and create required information, and ultimately, lead to actions (data > information > action); recognizing that we are all potential citizen scientists is important; recognizing that “good water quality” is subjective; and lastly that developing a communication gateway that allows bi-directional data and information transfer is essential.

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The Dutch citizen science project Delft Measures (https://bit.ly/DelftMeasures) focuses on the collaboration between citizens, local institutions, and NGOs to map the weather and changing climate in the city of Delft. It has been running for 4 years, during which citizens of Delft measure long-term changes in rainfall patterns, temperature, and now also soil moisture in their private gardens. Currently, there are over 45 of the Alecto WS5500 citizen-science weather stations spread across neighborhoods in Delft, capturing rainfall variability in different urban microclimates. But in the past years, more than 100 different inhabitants have already been engaged and have helped to collect data.

The data is used by a diverse number of organizations like the National Meteorological Institute, the Delft University of Technology and the Delft Municipality, to answer different scientific, engineering, or policy questions. We collaborate with multiple NGOs in project execution. Considering the diverse interests of all stakeholders, the project addresses a variety of goals from education to improving climate adaptation to implementing open science practices.

All in all, the project grew into a successful co-creation between many different partners. Delft Measures has been growing and changing and it managed to reach a consistent base of enthusiastic citizens that support the goals of the project, engaging them in making changes in the city for climate change adaptation. For Delft, as a city below sea level, this means a better drainage network to deal with the larger showers of summer rain, while retaining water during longer periods of drought. By setting up secure collaborations with the municipality and university, the data citizens collect is used as direct input for the (future) efficiency of the municipality’s city-wide sewer and drainage network. For the university, this is valuable for education and research into how city infrastructure influences local weather patterns and the variability of rainfall, to understand better where high-intensity rainfall events will have the highest effect. Currently, such high spatial resolution on rainfall in cities is scarce. Additionally, the project functions as a case study for the university’s Open Science program, aiming to evaluate the implementation of open science practices in local citizen science projects, while NGOs invested in climate change adaptation in the city roll up their sleeves to help citizens make the practical changes needed for our new climate.

We are currently in the process of writing down the ‘recipe’ of Delft Measures, to help other cities implement similar projects and not to have to reinvent the wheel. We would like to share this recipe during this session, where we will answer questions such as how we manage to collect useful information and increase community involvement and awareness, what kind of participatory approaches we implemented to facilitate community involvement, how we tackle legitimate concerns about potential data biases, inaccuracies and how we ensure the long-term sustainability of the project.@en

Representatives from 14 countries worldwide worked together on improving their monitoring and ultimately their water management to reach the Sustainable Development Goal (SDG) 6 goals by 2030, thereby testing the Information Strategy Model (ISM). This model is developed to support identifying the need for information for water management. In a workshop setting, participants were instructed and subsequently developed the ISM for their own situation. The results show that the ISM fulfils its task of structuring the development and improvement of a monitoring network, but can be enhanced by adding detailed information for specific elements and needs explanation and assistance to be of use.

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