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• W2794472632 abstract "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." @default.
• W2794472632 created "2018-04-06" @default.
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• W2794472632 date "2018-08-01" @default.
• W2794472632 modified "2023-10-10" @default.
• W2794472632 title "Citizen science pioneers in Kenya – A crowdsourced approach for hydrological monitoring" @default.
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• W2794472632 doi "https://doi.org/10.1016/j.scitotenv.2018.03.130" @default.
• W2794472632 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29727983" @default.
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