Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state of the art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing-based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water, and natural hazard management, are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing, and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined.

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Recent research developments indicate that citizens’ observatories, a novel approach for data collection, management and governance, can provide valuable contributions to strategic delta planning processes. Most citizen observatories are limited in spatial coverage during data collection, according to the citizens’ availability and static locations. However, there are times in which citizens participate as trained volunteers during data collection field campaigns. In this later scenario, an important aspect in organising and maintaining citizen observatories is having a clear plan for data gathering activities, including determination of routes to be followed by these citizens. This article addresses the issue of determining such routes (called pathways) related to the specific problem of gathering data in deltaic areas, which are composed of intricate canals and wetlands. Data collection activities consist of citizens acquiring images and videos with mobile phones at predetermined locations (Points of Interest) that are only accessible by boats. A pathway selection approach is presented, supported by a hydrodynamic model, developed to capture the specific processes of the delta. The aim of the approach is to define: where to send the citizens to fulfil stakeholders’ interest and planning goals, how to reach these points and which pathways should be selected (prioritised based on such interests), considering possible flood patterns. The developed methodology is part of an ongoing H2020 funded research. The proof of concept is carried out in the Sontea-Fortuna area, of the Danube Delta, which, similar to many wetlands, contains a large variety of unique, endemic species. With the developed approach, pathways to be followed by citizens during data collection campaigns were generated and scored considering local interests. Analysis of the boat’s accessibility into the delta during different hydrological scenarios showed that the wetland is more accessible than expected, hence the proposed pathway approach was useful in prioritizing some canals over others. The determined pathways will be applied in field campaigns. The approach can be applied to other delta regions with different environmental problems, such as water quality or ecosystem assessment, contributing to the organisation of effective active citizen data collection.@en

Citizen contributions to science have been successfully implemented in many fields, and water resources is one of them. Through citizens, it is possible to collect data and obtain a more integrated decision-making process. Specifically, data scarcity has always been an issue in flood modelling, which has been addressed in the last decades by remote sensing and is already being discussed in the citizen science context. With this in mind, this article aims to review the literature on the topic and analyse the opportunities and challenges that lie ahead. The literature on monitoring, mapping and modelling, was evaluated according to the flood-related variable citizens contributed to. Pros and cons of the collection/analysis methods were summarised. Then, pertinent publications were mapped into the flood modelling cycle, considering how citizen data properties (spatial and temporal coverage, uncertainty and volume) are related to its integration into modelling. It was clear that the number of studies in the area is rising. There are positive experiences reported in collection and analysis methods, for instance with velocity and land cover, and also when modelling is concerned, for example by using social media mining. However, matching the data properties necessary for each part of the modelling cycle with citizen-generated data is still challenging. Nevertheless, the concept that citizen contributions can be used for simulation and forecasting is proved and further work lies in continuing to develop and improve not only methods for collection and analysis, but certainly for integration into models as well. Finally, in view of recent automated sensors and satellite technologies, it is through studies as the ones analysed in this article that the value of citizen contributions, complementing such technologies, is demonstrated.

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