Data fusion of citizen-generated smartphone discharge measurements in Tunisia

Abstract

Water resources management techniques have been evolving over the years, introducing new ways of monitoring and collecting data that improve both the quality and quantity of water-related information. Among them, Citizen Science (CS) has been introduced in the field of environmental monitoring as a novel approach that involves a direct collaboration between citizens, scientists and local authorities.In Tunisia, the lack of reliable hydrological data about rivers’ discharge remains a major issue, despite the recent governmental efforts to reinforce the existing official monitoring systems. In this study, we show how this problem can be efficiently addressed using a CS methodology. Citizens at two locations in Tunisia (Slouguia and Medjez-N5) have monitored discharge of the Medjerda river (the most important water resource in the country) using a mobile phone application for a series of hydrological events. Using a Best Linear Unbiased Predictor (BLUP) as a data fusion procedure for combining the various CS measurements, the results show that predicted discharge at both locations is in very good agreement with the reference data collected for the same hydrological events. Based on a variance decomposition, this approach allows us as well to properly assess the respective part of the random errors that are related to the citizens and measuring devices.It is concluded that CS-based discharge data collection is a promising cost-effective way for obtaining reliable and numerous measurements. The monitoring approach based on the use of a mobile phone application is thus quite valuable for complementing the existing Tunisian monitoring system, as well as for empowering local communities. Furthermore, this approach can be applied at larger scales in the country by involving more citizens and adding other sites, which should support the national efforts for better and smarter water resources management.