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

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.

Citizen science pioneers in Kenya - A crowdsourced approach for hydrological monitoring.

Although water is involved in many ecosystem services, the absence of monitoring data restricts the development of effective water management strategies especially in remote regions. Traditional monitoring networks can be expensive, with unaffordable costs in many low-income countries. Involving citizens in monitoring through crowdsourcing has the potential to reduce these costs but remains uncommon in hydrology. This study evaluates the quality and quantity of data generated by citizens in a remote Kenyan basin and assesses whether crowdsourcing is a suitable method to overcome data scarcity. We installed thirteen water level gauges equipped with signboards explaining the monitoring process to passers-by. Results were sent via a text-message-based data collection framework that included an immediate feedback to citizens. A public web interface was used to visualize the data. Within the first year, 124 citizens reported 1175 valid measurements. We identified thirteen citizens as active observers providing more than ten measurements, whereas 57% only sent one record. A comparison between the crowdsourced water level data and an automatic gauging station revealed high data quality. The results of this study indicate that citizens can provide water level data of sufficient quality and with high temporal resolution.