Citizen science in hydrological monitoring and ecosystem services management: State of the art and future prospects

Last modified: 
August 12, 2019 - 4:28pm
Type: Journal Article
Year of publication: 2019
Date published: 11/2019
Authors: N. Njue, Stenfert Kroese, J. Gräf, S.R. Jacobs, B. Weeser, L. Breuer, M.C. Rufino
Journal title: Science of The Total Environment
Volume: 693
Pages: 133531
ISSN: 00489697

Hydrological monitoring is essential to guide evidence-based decision making necessary for sustainable water resource management and governance. Limited hydrometric datasets and the pressure on long-term hydrological monitoring networks make it paramount to explore alternative methods for data collection. This is particularly the case for low-income countries, where data scarcity is more pronounced, and where conventional monitoring methods are expensive and logistically challenging. Citizen science in hydrological research has recently gained popularity and crowdsourced monitoring is a promising cost-effective approach for data collection. Citizen science also has the potential to enhance knowledge co-creation and science-based evidence that underpins the governance and management of water resources. This paper provides a comprehensive review on citizen science and crowdsourced data collection within the context of hydrology, based on a synthesis of 71 articles from 2001 to 2018. Application of citizen science in hydrology is increasing in number and breadth, generating a plethora of scientific data. Citizen science approaches differ in scale, scope and degree of citizen involvement. Most of the programs are found in North America and Europe. Participation mostly comprises a contributory citizen science model, which engages citizens in data collection. In order to leverage the full potential of citizen science in knowledge co-generation, future citizen science projects in hydrology could benefit from more co-created types of projects that establish strong ties between research and public engagement, thereby enhancing the long-term sustainability of monitoring networks.

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