Delineation of discrete conduit networks in karst aquifers via combined analysis of tracer tests and geophysical data

Abstract Assessment of the karst network geometry based on field data is an important challenge in the accurate modeling of karst aquifers. In this study, we propose an integrated approach for the identification of effective three-dimensional (3D) discrete karst conduit networks conditioned on tracer tests and geophysical data. The procedure is threefold: (i) tracer breakthrough curves (BTCs) are processed via a regularized inversion procedure to determine the minimum number of distinct tracer flow paths between injection and monitoring points, (ii) available surface-based geophysical data and borehole-logging measurements are aggregated into a 3D proxy model of aquifer hydraulic properties, and (iii) single or multiple tracer flow paths are identified through the application of an alternative shortest path (SP) algorithm to the 3D proxy model. The capability of the proposed approach to adequately capture the geometrical structure of actual karst conduit systems mainly depends on the sensitivity of geophysical signals to karst features, whereas the relative completeness of the identified conduit network depends on the number and spatial configuration of tracer tests. The applicability of the proposed approach is illustrated through a case study at the Hydrogeological Experimental Site (HES) in Poitiers, France.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Delineation of discrete conduit networks in karst aquifers via combined analysis of tracer tests and geophysical data ; volume:26 ; number:6 ; year:2022 ; pages:1713-1726 ; extent:14 ; Hydrology and earth system sciences ; 26, Heft 6 (2022), 1713-1726 (gesamt 14)

Beteiligte, Orts- und Zeitangaben

• Urheber: Bodin, Jacques ; Porel, Gilles ; Nauleau, Benoît ; Paquet, Denis

Weitere Informationen

• DOI: 10.5194/hess-26-1713-2022
• URN: urn:nbn:de:101:1-2022041210290510948163
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:37 MESZ