PhD Thesis: Towards a Digital Twin for Water Resource Management

PhD Description

Water resource management poses a critical challenge in the era of climate change and population growth. To adequately address the diverse needs of end-users, it becomes imperative to develop advanced management tools. This thesis focuses on the design and development of a digital twin of the water production system ; an innovative tool that will effectively address various prospective scenarios related to water resource availability.

The main objective of this thesis is to design and develop a digital twin of the water production system capable of seamlessly integrating different simulation models to meet the needs of end-users. This digital twin will facilitate co-construction with various stakeholders of prospective scenarios and provide clear representations of simulation results.

The scientific challenges identified for this PhD thesis are the following:

• Integration of Scientific Models: This thesis aims to develop a flexible platform enabling the easy integration of different scientific models within the digital twin of the water production system. This allows for the consideration of various variables and aspects of the system.
• Coupling of Scientific Models: Another crucial challenge is the coupling of scientific models representing different perspectives on the water production system. This multidisciplinary approach will foster a more comprehensive understanding of issues related to water resource management.
• Adaptability to Scenarios: The thesis will also explore how to choose the most appropriate scientific models and configure their use based on specific scenarios proposed by end-users. This ensures that the digital twin can adapt to the needs of different water management stakeholders.
• Results Visualization: Finally, an important challenge will be translating raw model results into comprehensible representations for end-users. The ability to provide clear and actionable information will be crucial for informed decision-making.

This thesis resides at the intersection of scientific modeling, water management, digital technologies, and humanities. It will make significant contributions to how we approach water resource management in a constantly evolving context. It will also contribute to the development of more effective tools for decision-makers and water managers to ensure sustainable use of this precious resource.

This work will be realized in the context of the local pluridisciplinary project IRIS-E ANIME-WATER. The project involves researchers in the field of computer science, but also in the fields of Hydrogeophysics, Hydrology and Sociology. The project involves another PhD student in sociology. Hence, the work on the representation of the simulation results will be realized in collaboration with the second PhD student.

Environment

The candidate will be involved in the DiverSE team, joint to the CNRS (IRISA) and Inria. The DiverSE team is located in Rennes. DiverSE’s research is in the area of software engineering. The team is actively involved in European, French and industrial projects and is composed of 13 faculty members, 20 PhD students, 4 post-docs and 3 engineers. The main advisors of the PhD thesis will be Prof. Benoit Combemale (University of Rennes 1, DiverSE team), Prof. Johann Bourcier (University of Rennes 1, DiverSE team), and Jean-Raynald de Dreuzy (Géosciences, Rennes). The candidate will register to the doctoral school in computer science of the University of Rennes.

References

• June Sallou, Alexandre Gauvain, Johann Bourcier, Benoît Combemale, Jean-Raynald de Dreuzy: Loop Aggregation for Approximate Scientific Computing. ICCS (2) 2020: 141-155
• Romina Eramo, Francis Bordeleau, Benoît Combemale, Mark van den Brand, Manuel Wimmer, Andreas Wortmann: Conceptualizing Digital Twins. IEEE Softw. 39(2): 39-46 (2022)
• Gordon S. Blair et al.: The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere Accord. Patterns 2(1): 100156 (2021)
• Gordon S. Blair: Digital twins of the natural environment. Patterns 2(10): 100359 (2021)

Prerequisites

• A degree (and strong background) in computer science, and more specifically in software engineering
• skills on numerical analysis and scientific computing
• interests in programming and modeling languages, and supporting envirionments
• interests in program transformation, comprehension and analysis
• background or additional skills in environmental sciences is a plus
• professional proficiency in english
• skills for presenting and writting
• autonomly, rigor and hard worker

How to apply

Send your CV, motivation letter, and grades of your bachelor and master with the diplomas to Benoit Combemale and Johann Bourcier.