Utilizing Linear Uncertainty Analysis for Potential Observation Well Locations in the Pwales Aquifer, Malta

In coastal aquifers, a main objective of groundwater management is often to determine sustainable pumping rates that avoid seawater intrusion and well salinization. Models can be used to understand and forecast the behavior of such aquifers. A necessary step for modeling is calibration, and such a process contains uncertainty. Understanding how uncertainties affect water management is crucial for providing water utilities with the necessary information about well salinization risk. Uncertainty in the model can be reduced by new observation types and locations. One of the most common observation types is groundwater head observation in an observation well. However, the number of observation wells is limited by constraints, such as budget. A FOSM approach was chosen for data worth analysis considering parameter and observation uncertainty. It was implemented in a real-world island aquifer in the Pwales CA (Malta). The flow model was developed using MODFLOW6, and Linear Uncertainty analysis was done via PEST. FOSM was conducted, aiming to find optimum groundwater head observation locations to reduce forecast uncertainty. The workflow used scripts for reproductibility and it adapted to high-dimensional model.