Value of quality controlled citizen science data for rainfall-runoff characterization in a rapidly urbanizing catchment

• Published in: Journal of hydrology (Amsterdam) Vol. 629; p. 130639
• Main Authors: Kebede Mengistie, Getahun, Demissie Wondimagegnehu, Kirubel, Walker, David W., Tamiru Haile, Alemseged
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-02-2024
• Subjects: Citizen Science; Data quality control; Rainfall-runoff; River stage; Urbanization; Rainfall-runoff; Urbanization; Data quality control; River stage; Citizen Science
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2024.130639

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•We set-up a citizen science monitoring program in Akaki catchment which hosts Addis Ababa, and the program has been operational since January 2020.•Citizen science data of river flow at multiple sites were evaluated using multiple quality control methods.•The data quality assessment revealed that the citizen scientists can provide accurate river stage data if they receive regular feedback.•The citizen science data enabled evaluation of the spatial and temporal variation of rainfall-runoff relationship in an urbanizing catchment.
The major concern of applying citizen science in water resources is the quality of the data. However, there are limited scientific studies addressing this concern and showing the data value. In this study, we established a citizen science program in the Akaki catchment which hosts Addis Ababa, Ethiopia. Citizen scientists monitored river stage at multiple gauging sites for multiple years. We evaluated the quality of citizen science data through a systematic quality control. Reference data was obtained from neighboring stations of the citizen science program and professionals while the evaluation involved graphical inspections and statistical methods. The quality-controlled data were applied to evaluate the spatial and temporal variation of rainfall-runoff relationships. Initially, large numbers of suspicious data were detected using single station data but that was significantly reduced when the data of multiple sites were compared. Further comparison against professional data revealed excellent agreement with high correlation coefficient (r >0.95), and low centered root mean square error (RMSE) <0.03–0.08 mm. The citizen science data indicated a large difference in rainfall-runoff relationship over the dominantly urban and rural sub-catchments. The citizen science data allowed comparison of runoff coefficient and base flow index for recent and historical periods where recent streamflow data is unavailable from a formal data source. This study illustrates the immense value of (i) multiple data quality assessment steps for building confidence on the quality of citizen science data, and (ii) citizen science for enhancing our understanding of rainfall-runoff relationships and change in a rapidly urbanizing catchment.