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.
Quantum Sensor uses atom interferometry, to place individual freely falling atoms into a quantum superposition, manipulating the atoms with a series of light pulses that coherently transfer momentum and energy to the atoms. Through precise tailoring of an initial pulse, the atomic wave function is split into a superposition of two momentum states, causing them to spatially separate over time. After some time, another pulse is used to invert the momentum states, causing the states to converge – before a final pulse overlaps the trajectories such that they interfere. This is analogous to an optical interferometer, with the output interference pattern of the atom interferometer depending upon the gravitational potential difference between the two trajectories, allowing measurement of local gravity.
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.
