Quantum Sensing - Ground, and Aquifer Monitoring for Environmental Sciences (QS-GAMES)

A secure and safe supply of potable water is crucial to the health and well-being of the population, yet this is hampered by limited knowledge of the hydrological process including groundwater changes. Not only having a better understanding of the source of our water supply is crucial, but also ensuring no precious water is lost or wasted on route to consumers. Worldwide though, leakage rates are between 20-30% wasting a precious resource. Recent climate change has led to more droughts in temperate zones while at the same time increasing the risk of flooding making the understanding of these factors even more vital. Invisible water storage such as in aquifers is the main source of uncertainty in future prediction capabilities of hydrological and climate models. Also, understanding water changes in peatland areas can help us restore and maintain these precious natural sites thereby ensuring the embedded carbon remains trapped and is not exposed to the atmosphere. Peatland restoration can significantly contribute to our ability to store carbon in the future.

QS-GAMES will develop a transformative approach using novel quantum technology (QT) gravity gradiometer sensors for the detection of "invisible" water in soils such as monitoring of groundwater and aquifer levels and leak detection in buried water pipes. QS-GAMES will create a scientific evidence base for the use of cold atom gravity gradiometer sensors for these applications, trialling them alongside other sensing and data processing techniques to create more accurate mapping of subsurface water with a higher spatial resolution, transforming our understanding of the hydrological process and ensuring a robust supply of potable water in the future.

To achieve these goals, the project utilises a wide ranging and diverse group of researchers who will work collaboratively, with expertise in QT sensor development, geophysics, buried utilities, hydrology, environmental monitoring, data processing and machine learning. The project has five main work packages:

1. Management and dissemination: This will provide steer to the project through the both the researchers on the project and a steering committee of industrial advisors, as well as engage with industrial stakeholders, end users and wider academic communities. It will review risks, dissemination activities and monitor progress.

2. Sensor optimisation and validation trials: This will evaluate the use of QT gravity gradient and MEMS gravimeter sensors using controlled scaled experiments in the National Buried Infrastructure facility and determine the optimum parameters for measurement of water in the ground using these sensors for both aquifers and leaking pipes.

3. Application Trials: This will test both the novel and existing sensors on well characterised test sites with extensive arrays of sensors providing benchmarking data and methodologies for the QT sensors. This will help identify additional survey challenges associated with significant variations in the ground as well as additional noise sources from environmental conditions and assess how the QT sensors can operate at optimised performance in this environment.

4. Data, hydrological and water flow through soil modelling: This will look to exploit the benefits of novel and existing sensor data by fusing multiple datasets to infer ground conditions more accurately, improving groundwater modelling and developing real time creation of gravity maps. The additional data will significantly enhance our groundwater models thereby providing more confidence in the temporal and spatial variability of the water flow.

5. Survey Methodologies and Guidelines: This will focus on developing methodologies suitable for the collection of time lapse gravity for the different survey applications. It will establish a quality control framework for gravity data and produce guidelines for practitioners to ensure rapid uptake of the technology in the application areas addressed.