Forensic Hydrogeology

Contaminant events disrupt stability and resilience of increasingly vulnerable soil and groundwater.

Identifying where, when and how much contaminant spill is released into aquifers is critical for strengthening the competitiveness of EU in risk-reduction management, and Forensic Hydrogeology, a growing discipline that applies scientific knowledge in legal resolutions.

Existing model solutions estimate the origin and affected area, but numerical challenges impose too restrictive assumptions to properly account for multiple sources or suitable aquifer characterization.

The scientific goal of FORENSHYD is to develop a novel, flexible and reliable ensemble Kalman filter data assimilation method (EnKF) for the optimal identification of contaminant sources and occurrence of reactive pollutants in near-actual conditions. Latest assessed developments of Dr.

Gómez-Hernández set EnKF as an excellent optimization tool for the simultaneous identification of the spatial variability of conductivities, the location, and the release function of polluting sources.

A step toward coupling the algorithm with machine learning techniques may overcome ill-posed solutions, stemmed from nonlinearities between parameters and variables in the state equation, to solve kinetic-controlled reactive transport problems and to optimize data collection in groundwater observation network systems, a topic of renewal interest in administration and industrial sector.

We test spurious effects of aquifer heterogeneity, reactive parameters, and initial/boundary conditions in synthetic scenarios, sandbox experiments and two demonstration sites.

Transfer of this novel technology in well-reported, practical and universal open source packages will reinforce the leadership and employability in the global market of intersectorial and interdisciplinary European stakeholders.

The societal value of FORENSHYD is to improve mitigation strategies, and clarify environmental liability, in liaises with Horizon 2020.