Testing a citizen science water monitoring approach in Tunisia. Issue 104 (February 2020)

• Record Type: Journal Article
• Authors: Fehri, Raed; Khlifi, Slaheddine; Vanclooster, Marnik
• Is Part Of: Environmental science & policy. Issue 104(2020)
• Page Start: 67
• Page End: 72
• Publication Date: 2020-02
• Subjects: Citizen science -- Rainfall -- Monitoring -- Validation -- Online platform; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2019.11.009
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: A citizen science (CS)-based method was applied to monitor rainfall in a test region. A step-by-step approach was used to engage citizens from different generations. Field training was provided to volunteers to guarantee consistent monitoring. Statistical analysis validated the quality of the CS data compared to reference ones. Abstract: Citizen Science (CS) has been emerging in the last decade as a new field of environmental monitoring involving a direct collaboration between everyday citizens and scientists. In Tunisia, several recent governmental efforts aimed at reinforcing and renovating the existing official water monitoring systems. However, the lack of reliable hydrological data is still an issue, which could be better addressed through integrating a CS approach. The latter approach is tested for rainfall monitoring in the Medjerda catchment in Tunisia using cost-effective and publicly available manual rain gauges. We used a step-by-step approach to target, engage and train citizens on using the monitoring tools and transmitting the data to a user-friendly online platform. The ongoing approach involved 7 citizens from different generations and different educational backgrounds. The collected daily CS data are compared with data from reference stations. Results yield a significant correlation between CS data collected at 3 different sites and the reference stations with r (Pearson Correlation Coefficient (PCC)) ranges between 0.91 and 0.98 for all citizens. Student's t -test was applied to evaluate the significance of the agreement between the CS and reference data. In addition, the variability of the CS data is compared with the variability associated with the official governmental data. The CS approach delivered consistent outcomes to complement existing Tunisian monitoring systems, and also to enhance innovation, adaptation, and local capacity building in the Tunisian water sector.