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GROW Observatory is a project funded under the European Union's Horizon 2020 research and innovation program. Its aim is to establish a large scale (more than 20,000 participants), resilient and integrated 'Citizen Observatory' (CO) and community for environmental monitoring that is self-sustaining beyond the life of the project. This article describes how the initial framework and tools were developed to evolve, bring together and train such a community; raising interest, engaging participants, and educating to support reliable observations, measurements and documentation, and considerations with a special focus on the reliability of the resulting dataset for scientific purposes. The scientific purposes of GROW observatory are to test the data quality and the spatial representativity of a citizen engagement driven spatial distribution as reliably inputs for soil moisture monitoring and to create timely series of gridded soil moisture products based on citizens' observations using low cost soil moisture (SM) sensors, and to provide an extensive dataset of in situ soil moisture observations which can serve as a reference to validate satellite-based SM products and support the Copernicus in situ component. This article aims to showcase the initial steps of setting up such a monitoring network that has been reached at the mid-way point of the project's funded period, focusing mainly on the design and development of the CO monitoring network. [ABSTRACT FROM AUTHOR]

The involvement of non-experts in scientific work and data collection, namely citizen science, is rapidly increasing. Although the potential of citizen science activities and projects to generate huge amounts of data otherwise not feasible is widely recognized, the obtained data and observations are often treated with caution and skepticism. Their quality and reliability is not fully trusted since they are obtained by non-experts using low-cost instruments and/or simplified methods. In this study, we evaluate the performance of the low-cost soil moisture sensor used within the European citizen science project GROW Observatory (GROW; https://growobservatory.org/). The aim of GROW is to empower hundreds of motivated citizens to monitor soil moisture and other environmental variables within nine high-density clusters around Europe covering different climate and soil conditions. The citizen's contribution is laying the foundation for scientists to validate satellite-based soil moisture products at an unprecedented high spatial resolution. Clearly, to serve as reference dataset, the quality of ground observations is crucial, especially if obtained from low-cost sensors. To investigate the accuracy of such measurements, the low-cost sensors were installed alongside professional soil moisture probes in the Hydrological Open Air Laboratory (HOAL) in Petzenkirchen, Austria, where data has already been collected for more than a year. We assess the skill of the low cost sensors against the professional probes by the means of various methods. Apart from common statistical metrics like correlation, bias and rmsd, we investigate and compare the temporal stability as well as soil moisture memory. We will demonstrate that low-cost sensors can be used to generate a dataset valuable for environmental monitoring and satellite validation and thus provide the basis for citizen-based soil moisture science.This study is funded by the GROW Observatory project of the European Union's Horizon 2020 research and innovation programme (https://growobservatory.org/) and the International Soil Moisture Network under IDEAS+ of the European Space Agency (https://ismn.geo.tuwien.ac.at/). [ABSTRACT FROM AUTHOR]