Towards flexible groundwater level prediction for adaptive water management: using Facebook’s Prophet forecasting approach

Versión Aceptada There is an increasing need for accurate groundwater level (GWL) prediction to support effective seasonal water management. It is desirable for forecasting tools to be not only accurate but also accessible for decision-makers. We test the Prophet forecasting procedure, an open source code released by Facebook, to address these challenges. It is based on an additive model considering non-periodic changes and periodic components in a Bayesian framework with easily-interpretable parameters. Predictions of daily GWL data in an area affected by pumping near a tourist complex in the Ramsar wetland area of Doñana (Spain) are compared to other forecasting methods. Prophet outperforms most methods in predicting GWL making it a fast and flexible forecasting tool for hydrologists and water managers. Furthermore, it allows gaining insight into the influence of each component of the forecast separately, helping to assess the hydrodynamic response to external drivers such as groundwater pumping. Departamento de Investigación en Recursos Geológicos, Instituto Geológico y Minero de España, España Plan Nacional de I+D+i, España Consejería de Educación, Juventud y Deporte, Comunidad de Madrid, España Iniciativa de Empleo Juvenil, España Fondo Social Europeo, Europa Secretaría de Estado de Investigación, Desarrollo e Innovación, España