Imaging hydrological dynamics in karst unsaturated zones by time-lapse electrical resistivity tomography
SIRIEIX, Colette
Université Sciences et Technologies - Bordeaux 1 [UB]
Université de Bordeaux [UB]
Institut de Mécanique et d'Ingénierie [I2M]
ANTEA GROUP
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Université Sciences et Technologies - Bordeaux 1 [UB]
Université de Bordeaux [UB]
Institut de Mécanique et d'Ingénierie [I2M]
ANTEA GROUP
SIRIEIX, Colette
Université Sciences et Technologies - Bordeaux 1 [UB]
Université de Bordeaux [UB]
Institut de Mécanique et d'Ingénierie [I2M]
ANTEA GROUP
< Réduire
Université Sciences et Technologies - Bordeaux 1 [UB]
Université de Bordeaux [UB]
Institut de Mécanique et d'Ingénierie [I2M]
ANTEA GROUP
Langue
EN
Article de revue
Ce document a été publié dans
The Science of The Total Environment. 2024-01-01, vol. 907, p. 168037
Résumé en anglais
The hydrodynamics of karst terrain are highly complex due to the diverse fractures and reservoirs within limestone formations. The time delay between rainfall events and subsequent flow into reservoirs exhibits significant ...Lire la suite >
The hydrodynamics of karst terrain are highly complex due to the diverse fractures and reservoirs within limestone formations. The time delay between rainfall events and subsequent flow into reservoirs exhibits significant variability. However, these hydrological processes are not easily visualized in karst topography. Subsurface geophysics, specifically 2D time-lapse electrical resistivity tomography (ERT), provides an effective method for studying the relationships between hydrological and geophysical features. In our research, we adopted ERT in the Karst Critical Zone (KCZ) to visualize specific karstic zones, including cave galleries, water storage reservoirs, wetting fronts, soil layers, and potential preferential flow paths down to a depth of 20 m. To capture spatial and seasonal variations in resistivity, we presented a comprehensive approach by combining sixteen inversion models obtained between February 2020 and September 2022 above the Villars Cave in SW-France-a well-known prehistoric cave. We used a multi-dimensional statistical technique called Hierarchical Agglomerative Clustering (HAC) to create a composite model that divided the synthetic ERT image into eight clusters representing different karst critical zones. The ERT image clearly visualized the cave gallery with high resistivity values that remained consistent throughout the seasons. Our analysis revealed a close seasonal relationship between water excess and resistivity variations in most infiltration zones, with time delays increasing with depth. The karst reservoirs, located at significant depths compared to other clusters, displayed sensitivity to changes in water excess but were primarily affected by fluctuations in water conductivity, particularly during summer or dry periods. These findings have significant implications for predicting rainwater infiltration pathways into caves, thereby assisting in the conservation and preservation of prehistoric caves and their cultural heritage.< Réduire
Mots clés en anglais
Drip rate
Electrical resistivity tomography
Hierarchical agglomerative clustering
Infiltration
Karst reservoirs
Unités de recherche