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Updated: Jan 26, 2026

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
Published on: October 6, 2023
Adaptive observation-based subsurface conceptual site modeling framework combining interdisciplinary methodologies: a
Ahamefula U Utom1, Ulrike Werban2, Carsten Leven3
1Department of Monitoring and Exploration Technologies (MET), Helmholtz Center for Environmental Research - UFZ, Permoserstraße 15, 04318, Leipzig, Germany. ahamefula.utom@ufz.de.
Abstract:
Traditional site characterization and laboratory testing methods are insufficient to quantify and conceptualize subsurface contaminant source-pathway-receptor heterogeneity issues, as they hamper groundwater risk assessment and water resource management using mathematical modeling. To address these issues, we propose an adaptive observation-based conceptual site modeling framework, which emphasizes the need for the iterative testing of hypotheses centered on specific questions with clearly defined objectives using interdisciplinary tools (including, but not limited to, geology, microbiology, hydrogeology, geophysics, and the chemistry of solute fate and transport). Under this framework, we present a case study aimed at a goal-oriented investigation of the source and occurrence of a groundwater nitrate plume previously identified using chemical concentration data from sparsely distributed, conventional, and regional groundwater monitoring wells. These investigations occurred in stages, with the first comprehensive outcome of cost-efficient, non-invasive surface geophysical surveys localizing subsurface heterogeneities laying the groundwork for collaborative, minimally invasive, direct push-based investigations followed by groundwater chemical and stable isotope analyses for source fingerprinting and bioprocess evaluation. Despite the obvious need for further refinement of the conceptual site model as new data become available, we illustrate that the step-by-step integrative framework was useful for systematic maximization of the strengths of different investigation methodologies. Such frameworks and approaches should be encouraged for successful environmental site characterization, monitoring, and modeling.
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