All posts by Michel Van Camp

New paper in Journal of Applied Geophysics

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).

Identification as a function of the depth Z and of the length X of the monitoring profile of zones with variable variations in electrical resistivity. These areas depend on the geological characteristics. For example, the brown area represents a faulted zone where water is quickly drained to the caves.

New paper in Water Resources Research

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.

Conceptual model of a 13‐m flood event in the Lorette cave projected on a west-east cross-section (vertical and horizontal scales in [m]). The zone progressively shifting from white to red represents the layer in which the modelled cavities are located. Red indicates a greater number of cavities. LUR and WWT refer to the water level sensor.

Watlet A., Van Camp M., Francis O., Poulain A., Rochez G., Hallet V., Quinif Y., Kaufmann O., Gravity monitoring of underground flash flood events to study their impact on groundwater recharge and the distribution of karst voids, Water Resources Research, doi:10.1029/2019WR026673, 2020.

EGU meeting: about the non-linear interactions in a karst system

Hydrological connectivity from causal analysis of time series in the Lhomme Karst System, Belgium.
Damien Delforge, Michel Van Camp, Marnik Vanclooster, Vincent Hallet, Olivier Kaufmann, Amaël Poulain, and Arnaud Watlet

EGU meeting, Vienna, April 8, 2019

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?

9 November: PhD thesis of Arnaud Watlet

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:
Prof. Olivier Kaufman, Université de Mons
Dr. Michel Van Camp, Observatoire Royal de Belgique
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.
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A new Ph.D. student for KARAG

02 January 2017:

A new Ph.D. student joints the KARAG team: Ir. Damien Delforge. The supervisors are Prof. Marnik Vanclooster (UCL, Earth and Life Institute/Environmental Sciences (ELI-e)) and Dr. Michel Van Camp (Royal Observatory of Belgium, Seismology-Gravimetry). This project is supported by the Fund for Scientific Research FNRS-FRIA.

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.