Application of Artificial Intelligence for the prediction of water resources.


The TERRA project uses machine learning models that are able to predict the evolution of reservoir water or aquifer level up to a year in advance and an error of less than 20%.

These models have been applied in 3 pilots of different nature: in Marbella and Granada, where a joint use is made of the regulated and underground surface water resources of detrital aquifers; and in Torremolinos, where resources from an aquifer of karst nature are exploited. In addition, with the results of the predictions, the scarcity index has been predicted according to the Special Drought Plans and a modified scarcity index has been created, also taking into account the available underground water resource reserves.

All these results are collected in a Water 4.0 visualization tool developed using Power BI that, thanks to its friendly and simple interface, allows you to visualize the main management parameters of water bodies and help when making preventive decisions or drought mitigation and even in the preparation of annual budgets.

Duration: June 2021 - January 2022
Coordinator: Cetaqua Andalucía
Hidralia, EMASAGRA y Aguas de Torremolinos

Related News

Here you will find all the news about This Cetaqua’s project

View all news
  • The European SEMPRE-BIO project will demonstrate new cost- effective ways to produce biomethane

  • A study proves an existing relation between the SARS-CoV-2 in wastewater and the accumulated incidence in the contagion waves during the COVID-19 pandemics

  • Aggregating platform of models for the Integrated management of quality data and status of surface water bodies

  • Computer Vision Center and Cetaqua create a Joint Lab for research and development of projects and Artificial Intelligence

  • EDAR 360, Galician technology and talent for the digitalization of the water sector

  • Studies support the good state of health of the Roquetas coastline

  • The Costa del Sol becomes a hub of innovation for the efficient management of water resources through digitisation