Ensuring a reliable and safe supply of water is essential for the socioeconomic and environmental sustainability of our society. In the UK, several water companies are responsible for supplying clean water to industrial and domestic users in different parts of the country. Water companies need to estimate what the water demand and the available resource will be in the future (typically over a 25-years ahead period) so to be able to plan infrastructure development (for example, building a new reservoir) or changes in their management (for example, reducing or increasing river abstractions that feed into an existing reservoir) wherever they anticipate a gap between demand and supply.
Making decisions is becoming increasingly complex in the fast-changing world we live in. On the supply side, extreme events such as floods and droughts are becoming more frequent and unpredictable under the combined effect of climate and land-use change. On the demand side, water demand is also becoming more variable due to changes in population density and distribution, changing life-style and socioeconomic conditions, and technological developments (for example, the introduction of smart water meters), which all together may affect water consumption in different ways in different places.
To tackle all these complexities, the water industry needs to adopt innovative, flexible and adaptive planning and management solutions, which will increase the efficiency and resilience of water systems while avoiding raising costs. Mathematical models can provide a vital contribution to this end. By reproducing the behavior of the main components of a water resource system (such as reservoirs, pumping stations, treatment plants, etc.) and their connections among each other and with the natural environment, mathematical models enable water practitioners to predict the key system variables (for example, the future storage levels in a reservoir, the amount of energy consumed for pumping, the supply rate of clean water to a group of domestic users) and to simulate the system response under different infrastructural/management scenarios.
The use of mathematical models in the water industry has increased in recent years, however their adoption is still relatively limited with respect to their potential. A key challenge water resource practitioners face is in recognising the uncertainty and errors that unavoidably affect all model predictions while still extracting useful information from them. A great opportunity that they are offered today, is to extract more and more useful information from fast growing sensing and computing technology, for example satellite data, smart sensors and high-performance computers. In this research project, I aim to tackle the uncertainty challenge and take the IT opportunity to develop the next-generation modelling tools that will support more sustainable water resource management in the UK.
This project will develop mathematical methods and software tools to assist water system managers in their day-to-day decisions (for example, how much water to abstract from a river or a reservoir, how much water to pump to a treatment plant, etc.) as well as long-term decisions (for example, whether to build a new reservoir or connect existing ones) by finding "low-regret" solutions that would prove effective across a range of possible futures. All methods will be developed and tested on case study applications provided by water companies, so to ensure that they are actually valuable to address the most urgent issues they face, and they will be implemented in open-source software packages so that also other water practitioners besides those directly involved in the project will benefit from its findings and outputs.