The AguAlearn project, funded in the first call for AEI of 2021 by MINCOTUR, is coordinated by CWP and involves Aigües del PratAmphos 21HYDS. The project aims to increase the sustainability of water exploitation and demonstrate the applicability of Machine Learning in other areas of water management. The objective of the project is the development of an innovative platform for early warning of groundwater quality in the Llobregat delta area with a double purpose: to identify the most suitable channel to minimize the entry of contaminants and to predict the presence of specific contaminants based on the results of routine low-cost analysis. In the first phase of the project, Aigües del Prat shared with the other participants, historical data of head and level, as well as laboratory analyses of the water management of Prat de Llobregat, with which a big data analysis was carried out to extract information on temporal patterns, allowing the identification of the most significant variables for the quality of the water supply. Next, algorithms and predictive models were developed to identify relationships between operating conditions and the presence of certain pollutants. Using Machine Learning techniques, a training of the algorithms was carried out and the most suitable ones were selected to relate quality and exploitation as well as to predict the minority pollutants. The resulting models have been integrated in a software platform developed in open code for the management of ponds and early warning with automated alerts, which is currently in the validation phase.

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