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Citizen science, scientific work and data collection conducted by or with non-experts, is rapidly growing. Although the potential of citizen science activities to generate enormous amounts of data otherwise not feasible is widely recognized, the obtained data 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 or scientifically non-verified methods. In this study, we evaluate the performance of Parrot's Flower Power soil moisture sensor used within the European citizen science project, the GROW Observatory (GROW; https://growobservatory.org). The aim of GROW is to enable scientists to validate satellite-based soil moisture products at an unprecedented high spatial resolution through crowdsourced data. To this end, it has mobilized thousands of citizens across Europe in science and climate actions, including hundreds who have been empowered to monitor soil moisture and other environmental variables within twenty four high-density clusters around Europe covering different climate and soil conditions. 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 Flower Power sensors were evaluated in the lab and field. For the field trials, they were installed alongside professional soil moisture probes in the Hydrological Open Air Laboratory (HOAL) in Petzenkirchen, Austria. We assessed the skill of the low cost sensors against the professional probes using various methods. Apart from common statistical metrics like correlation, bias and root-mean-square difference, we investigated and compared the temporal stability, soil moisture memory, and the flagging statistics based on the International Soil Moisture Network (ISMN) quality indicators. We found a low inter-sensor variation in the lab and a high temporal agreement with the professional sensors in the field. The results of soil moisture memory and the ISMN quality flags analysis are in a comparable range for the low-cost and professional probes, only the temporal stability analysis shows a contrasting outcome. We 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. [ABSTRACT FROM AUTHOR]

Integration techniques are used to combine Earth Observation (EO) datasets to study the Water Cycle (WC). By merging several datasets, they reduce uncertainty and introduce coherency among them. Several EO integration methods are presented and compared: The Optimal Selection (OS) simply choses the best individual datasets. Simple Weighting (SW) is a weighted sum of the datasets to reduce uncertainties. Three other techniques introduce a closure-constraint on the WC budget: (1) The SW plus Post-Filtering (PF) is very efficient but it is applied at the basin-scale only, and lacks in spatial information. (2) By using a spatial interpolation scheme, the INTegration (INT) solution allows obtaining a pixel-scale database, but only for the common period of the all the water components. (3) A simple CALibration (CAL) of the EO datasets is therefore introduced to reproduce the INT results over the longer temporal extent of the EO datasets, but its closure constraint is relaxed. Results are presented over the Mediterranean region, one of the more complex environnements and a hot-spot for climate change. We extended previous techniques to close simultaneously the terrestrial, oceanic and atmospheric WC budgets. We also introduce temporal and spatial multi-scaling constraints. The evaluation is performed for precipitation and evapotranspiration: in addition to better close the WC budget, the integrated database is also closer to in situ measurements. The resulting integrated database provides new estimates for the WC components: stock and flux annual-means are re-evaluated, and we now estimate the Bosporus net-flow mean value at 129 & pm 60 mm.yr-1 for the 2004-2009 period. This new EO-based database describing the terrestrial, oceanic and atmospheric WC over the Mediterranean is now proposed to the scientific community. [ABSTRACT FROM AUTHOR]