intelligent, innovative, integrative Water Systems
AI-driven solutions for intelligent, resilient and sustainable water systems
i3WaterS brings together universities, research centers, technology developers
and water utilities across Europe to support the digital transformation of
critical water infrastructures.
Development of Water Supply Quality Index for an optimal management of distribution network
| Code | i3WaterSDC14 |
|---|---|
| Host Institution | UNIVERSITAT DE GIRONA Laboratory of Chemical and Environmental Engineering (LEQUIA). The Laboratory of Chemical and Environmental Engineering (LEQUIA) is a research group at UdG dedicated to the development of eco-innovative solutions in the environmental field. Founded in 1993, LEQUIA is renowned for its work in the water sector. We have a multidisciplinary team of 40 people, including chemists, biologists, biotechnologists, environmentalists, engineers, computer scientists, and political scientists. Current research lines include: 1) innovative bioprocesses for treatment, resource recovery, and synthesis of new products; 2) advanced physico-chemical processes for the treatment and/or reuse of liquid and gaseous effluents; and 3) planning, control, and evaluation of complex environmental systems. |
| Location | GIRONA Postcode 17003 Spain |
| Supervisor(s) | Main Supervisor: Dr Hèctor Monclús (UDG, Spain) Co-supervisor: Dr Alba Cabrera-Codony (UDG, Spain) Industrial Mentor – Experts: Dr Fernando Valero Cervera (ATL, Spain) |
| Research Field | Artificial Intelligence and water science and technology |
| Contract type | Fixed term contract (permanent contract linked to i3WaterS project duration) |
| Application Deadline | September 15th, 2026 |
Description
Research Objectives
The main research goal of iWaterS is to provide, for the first time, rational analyses and explainable intelligent decision support of WDS to increase resilience to day-to-day incidents and to extreme events in the context of climate change such as floods or droughts, through new interdisciplinary and integral approaches for exploiting datasets (on-line, off-line), intelligent models (data-driven, numerical) and simulation results (digital twins, multiagent systems).
The specific research objective of this offer is To develop Artificial Intelligence methodologies that integrate Digital Twins with advanced water quality and contaminant management models to support resilient and sustainable operation of drinking water distribution systems.
The candidate will contribute with the following subobjectives:
Objectives: 1) To generate a matrix of quality indicators for risk quantification and prediction by collecting data from multiple water sources, including desalination, surface water, reservoirs and groundwater. 2) To design and develop a SQI to quantify and evaluate risks, as well as to forecast potential risk scenarios in WDSs. 3) To implement and validate the SQI in real-world systems to improve the water supply management using multiple waters sources.
This tool will identify potential risk scenarios, such as during extreme drought or storms.
Expected Results: 1) A new tool for assessing risks in large water distribution systems that combine multiple water sources. 2) A scenario analysis tool to recommend the most effective management strategy for risk mitigation.
Requirements
Education level
Master Degree
Skills / Qualifications
- Machine Learning and Data Mining
- Knowledge-Based Systems
- Data-driven models
- Explainable Artificial Intelligence (XAI)
- Multi-Agent Systems
- Decision Support Systems
- Python, R, Java or related programming languages
- Data integration and interoperability
- Documenting in Latex
- Teamwork
- Water science and technology
Required languages
English – C1
i3WaterS is a doctoral network project funded by the European Union under the HORIZON.1.2 – Marie Skłodowska-Curie Actions (MSCA) ( HORIZON_MSCA-101227354-i3WaterS).
For more information cordis.europa.eu.
i3WaterS contact: i3waters.management@upc.edu