PhD Position: Remote monitoring of hydrocarbons in groundwater through sensor data fusion
Various industries might influence groundwater quality around assets or factories. Monitoring of groundwater quality is currently done by manually collected samples which are routinely measured to support risk-based and remediation decision making. The temporal information density of this approach is very low, resulting in slow response and increased cost for remediation. Additionally, the collection of groundwater samples can trigger significant health and safety concerns related to sampling in high-traffic areas, exposure to contaminated groundwater and travel to and from site, especially in areas with offsite security concerns. Water quality sensors and telemetry systems, in combination with reactive transport modelling, may provide a cost-effective alternative to help reduce or eliminate many of these groundwater monitoring issues. In addition, remote, continuous, real-time data collection provides a means for reducing liabilities through rapid identification of groundwater concentration trends (i.e., new product releases) and improving data interpretation (i.e., key factors that affect groundwater concentration trends).
Sensors for continuous and remote monitoring of total dissolved-phase petroleum hydrocarbons have recently become commercially available, but are not a realistic option for routine groundwater monitoring because of high costs and maintenance. Alternatively, less expensive sensors routinely used for groundwater monitoring (e.g., pH, dissolved oxygen, temperature, oxidation-reduction potential, chemical oxygen demand, and electrical conductivity) are available, which do not directly measure dissolved-phase hydrocarbons. This project explores how data collected from these existing, cost-effective sensors can be used (i.e. data fusion), for hydrocarbon concentration monitoring in groundwater, or to trigger sampling based on bulk water quality changes. In addition, innovative spectral sensors, developed in the Wetsus research theme Sensoring previously, will be evaluated. Development of new algorithms is required to realize this new type of robust, remote and continuous sensor systems. Through controlled laboratory experiments and field experiments, the applicability of these sensors for hydrocarbon trends in groundwater will be assessed. This includes: testing long term stability, optimizing groundwater monitoring networks through spatiotemporal modelling, optimizing groundwater monitoring networks through integration of sensors and water sampling.
We are looking for a candidate that holds an MSc degree in the field of hydro(geo)logy, environmental chemistry, chemical engineering or electrical engineering (or similar) and has an interest in developing cutting edge methods for monitoring groundwater quality and who enjoys working at the interface between different disciplines. Experience in performing laboratory experiments, working with sensors or large groundwater quality datasets is helpful but not required. Recommended skills are: (Python) programming; (time trend) statistics; (groundwater) modelling.
The PhD student will be based at Wetsus in Leeuwarden and co-supervised by TU Delft. It is expected that the student will work regularly at Delft.
The research project is part of the Wetsus research theme Sensoring.
The following companies are part of the theme: Shell Global Solutions, Evoqua, Grundfos and Easymeasure
Promotor: prof. dr. ir. L.C. (Luuk) Rietveld (TU Delft, dep. of Water Management)
For more information contact Martijn Wagterveld: firstname.lastname@example.org
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Location: Wetsus, Leeuwarden, The Netherlands