Host institution: Politecnico di Milano Milan, Italy
Principal supervisor: Prof. Andrea Castelletti
Co-supervisor: Prof. Margreet Zwarteveen
Non-academic co-supervisor: Ms Iris Bijlsma
Application deadline: 15 March 2020
Starting date: Between 1 May and 1 September 2020
Duration: 3 years
Changing water demands in urban centers are considerably raising the stress on finite supplies of available freshwater, as per the combined effect of climate change, population growth, and urbanization. In response to such changes, planners and policy makers need to improve urban water management plans and develop demand management strategies that complement supply-side interventions to enhance the resilience of urban water systems. The need to identify water demand patterns and drivers to inform such management strategies has fostered the development of several recent works and smart metering programs in a number of medium to large cities worldwide, providing new consumption data at high spatial and temporal resolution. The availability of such high-resolution data enables the development of advanced data-driven models of water demand at different scales. The aim of this project is developing data driven models of residential water demand at different spatial scales (e.g., buildings, district, city). We will identify the main patterns of urban water demand, along with their economic, social, climatic, and environmental drivers at different spatial and temporal scales across heterogeneous urban contexts in European countries. Data-driven demand models will be developed to inform regional, national, and European water demand management policies and governance decitions.
This ESR position will:
- Identify the main patterns of urban water demand and use and their economic, social, climatic, and environmental drivers at different spatial and temporal scales across heterogeneous urban contexts in European countries;
- Enhance models describing how water governance decisions propagate across sectors and scales, under diverse social, economic, technological, and climate scenarios;
- Understand how fine-scale urban water use, demand, and management data and projective scenarios can be scaled up and integrated with regional, national, and European models;
- Develop tools ultimately supporting policy formulations, local and regional water management investments, and for discovering which factors most strongly influence water futures of interest.
- Informed description and comparative analysis of the spatial and temporal heterogeneity of urban water demand and use patterns and drivers across the main European urban centres, usually masked by current modelling approaches at coarse scales;
- Descriptive and predictive multi-scale mathematical models of urban water use and management implications that bridge the gap between state/European level modelling and the finer regional/urban/sub-urban scale;
- Scale-flexible assessments that better account for how decisions propagate across spatial scales and short- to long-term time horizons. These innovations are critical for supporting strategic decision making under uncertain futures at local, state, and European levels;
- Release of a set of open-source tools to mine water use data at various spatial and temporal scales and sectors, and ultimately support the design of demand management options.
About Politecnico di Milano
Politecnico di Milano (Polimi) was established in 1863. Polimi is now ranked as one of the most outstanding European universities in Engineering, Architecture and Industrial Design. Polimi has five campuses, 9 Schools (6 of Engineering, 2 of Architecture, Industrial Design) and over 40.000 students. Research is carried out on a wide range of technical and scientific subjects by 16 Departments. Polimi is the first Italian university for projects funded by the EC under the 7th FP. Within the ERC sub-program, Polimi won several Advanced and Consolidator Grants, Proof of Concept Grants and Starting Grants. The Dipartimento di Elettronica, Informazione e Bioingengeria (DEIB) is one of the major ICT university departments in Europe, with over 800 members. DEIB professors Stefano Ceri and Carlo Ghezzi in 2008, Daniele Ielmini in 2015, and Stefano Ceri in 2016 have been awarded the prestigious ERC grants (Advanced Grant for Ceri and Ghezzi and Consolidator Grant for Ielmini). The DEIB has participated to many FP7 projects. Research areas include Systems and Control, Computer Science and Engineering, Telecommunications, Electronics, and Bioenegineering.
The Environmental Intelligence Lab (EI-Lab) develops methods and tools to advance environmental decision-analytics for supporting human decisions in complex engineering systems including multiple actors and exposed to evolving multisectoral demands and global change. EI-Lab approach fuses environmental, climate, and hydrologic disciplines with machine learning, optimal control, and evolutionary computation.
Vrije Universiteit Amsterdam is home to more than 24,500 students.
- Above-average MSc (or equivalent degree) in Computer Science or Engineering, also profile with a degree in Environmental Engineering, Water Resources Management, or related fields will be considered.
- A solid background in either Systems Analysis or Machine Learning/Artifical Intelligence.
- Commitment to academic excellence with a track record of high impact research.
- Proven skills in programming for data analytics (e.g. Python, R, Matlab).
- Capacity to work independently and as part of a team.
- Examples of high-quality written work, such as a journal paper or equivalent.
- Outstanding interpersonal skills to work with multiple stakeholders.
Dr. Andrea Castelletti
Professor at Politecnico di Milano
Environmental Intelligence Lab at Politecnico di Milano, Italy
Dr. Margreet Zwarteveen
Professor of Water Governance at IHE-Delft and the University of Amsterdam
Universiteit van Amsterdam, The Netherlands
Ms Iris Bijlsma
Senior Project Manager
ARCADIS, The Netherlands