Delforge, D., Watlet, A., Kaufmann, O., Van Camp, M., Vanclooster, M., “Time-series clustering approaches for subsurface zonation and hydrofacies detection using a real time-lapse electrical resistivity dataset”, Journal of Applied Geophysics (2020). 10.1016/j.jappgeo.2020.104203.
This article studies how to analyse automatically the numerous data series resulting from the measurements of the variations in the electrical resistivities of the soil on the site of the Lorette Cave (Rochefort). These variations, which inform us about the modifications of the water content of the subsoil, were described in their hydrogeological context by A. Watlet ( Watlet, A., Kaufmann, O., Triantafyllou, A., Poulain, A., Chambers, J., Meldrum, P., Wilkinson, P., Hallet, V., Quinif, Y., Van Ruymbeke, M., Van Camp, M., Imaging groundwater infiltration dynamics in the karst vadose zone with long-term ERT monitoring, Hydrology and Earth System Sciences (2018). 10.5194/hess-22-1563-2018).
New paper evidencing unknown voids within the Lorette karst system, evidenced by the continuous gravity measurements of flash floods. This was first achieved with a gPhone spring gravimeter in 2013, continued with a superconducting gravimeter since end 2014.
On Friday May, 24, 2019, the Belgian Chapter of the International Association of Hydrogeologists organised its study day at the Rochefort-Lorette site. After an academic session in the morning, the participants visited the Rochefort Laboratory.
The hydrological behaviour of karstic systems is difficult to theorize holistically because of their specific heterogeneities leading to distinctive non-linear processes. Karstified systems present great opportunities for field exploration and hydrogeological monitoring of the vadose zone through its network of caves and conduits. These unique but explorable environments are predisposed to an inductive scientific approach where transfer processes associated with hydrological connections are directly inferred from the data. This is done conventionally using dye tracing from which connections and transfer times are undeniably revealed. However, single tests do not allow appreciating the dynamic character of the hydrological connections. Nowadays,several data analysis methods aim at the detection of causal relationships between time series allowing the investigation of dynamics and interactions. Some are designed for linear systems as the simple cross-correlation method or the Granger causality, while others are suitable for non-linear interactions, such as the Convergent Cross Mapping method. Here, these methods are applied in order to draw up causal maps and compare short-term (up to 2 days) interactions in the Lhomme Karst System in Belgium. The Lhomme Karst System has been monitored since 2013 and many time series are available: meteorological data, soil moisture, drip discharges in the caves, piezometric levels, and local gravimetric time series. In addition, dye tracing experiments revealing connections and characteristic transfer times were conducted. The different causal maps are compared and causal interactions are appreciated through the current knowledge of the system and discussed in relation to the question: can we infer true hydrological connections and processes from the empirical determination of causal relationships between hydrological time series?
On 9 November 2017, Arnaud Watlet will defend his PhD thesis dedicated to the de FNRS KARAG project of Rochefort.
Arnaud will present 4 years of results on the saturated and non-saturated zones of the karst aquifers.
The jury will be composed of the following members: Supervisors: Prof. Olivier Kaufman, Université de Mons Dr. Michel Van Camp, Observatoire Royal de Belgique Jury: Pr Jean-Marc Baele, Université de Mons Pr Thierry Camelbeeck, Observatoire Royal de Belgique Pr Konstantinos Chalikakis, Université d’Avignon Pr Cédric Champollion, Université de Montpellier Pr Olivier Francis, Université de Luxembourg Pr Pascal Goderniaux, Université de Mons The dissertation defense will take place at 15 pm at U. Mons, Salle Académique, Bd Dolez, 31 (2e étage), 7000 Mons. The defense is public.
The data from the iGrav019 superconducting of Rochefort are now available online on the IRIS database (www.iris.edu). The time series are available under the SG.RCHS code.
The superconducting gravimeters excel at measuring the low-frequency waves emitted by major earthquakes.
The objective of the project is to improve gravity signal processing and karst systems modelling through the use of novel data mining techniques, derived from chaos theory, known as convergent cross mapping (CCM). CCM is a statistical method to elucidate cause-effect relationships between multiple time series that seek to resolve the problem that correlation does not imply causation. Regarding the uniqueness and the complex non-linear dynamics of karst systems, the main underlying assumptions are the following: (i) data-driven tools derived from the chaos theory and CCM appears to be relevant to investigate both the relationship between the gravimetric signal and the monitored environmental variables and the hydrological behaviour of a karst system; (ii) using CCM analysis, a framework can be built to assess the realism of a hydrological model structure in complex hydrologic systems such as karst systems; and (iii) the resulting model structure can lead to a better prediction in water storage changes (WSC) and therefore to a better interpretation of the gravity signal.
Based on this assumptions, this research aims at applying advanced causal analysis to characterize the relationships between gravity signals and the locally monitored environmental variables and to assess what are the dominant hydrological processes involved in a complex Lomme karst system.