Presentation : “Detection of subsurface water storage dynamics with combined gravity – vertical gravity gradient monitoring and hydrological simulation”

Event: EGU General Assembly 2020 (online)
Presentation by Anne-Karin Cooke, Cédric Champollion, Pierre Vermeulen, Camille Janvier, Bruno Desruelle, Nicolas Le Moigne, Sébastien Merlet


Time-lapse ground-based gravimetry is increasingly applied in subsurface hydrology, providing mass balance constraints on water storage dynamics. For a given water content change as e.g. after a precipitation event, the simplest assumption is that of a homogeneous, infinite slab (Bouguer plate) of water column causing the measurable increase in gravitational attraction. For heterogeneous subsurface environments such as karst aquifers at field scale this assumption may not always hold. The gravity signal is depth-integrated and non-unique, hence indistinguishable from a heterogeneous distribution without further information.

Exploiting the different spatial sensitivities of gravity and vertical gravity gradient (VGG) data can shed light on the following questions:

  • Is the subsurface water content within the gravimeter’s footprint likely to be homogeneous or showing small-scale heterogeneity?
  • If not, at which distance are these mass heterogeneities and how large are they?
  • Which monitoring set-ups (tripod heights, number of and distance between VGG measurement locations) are likely to detect mass heterogeneity of which spatial characteristics?

One year of monthly vertical gravity gradient surveys has been completed in the geodetic observatory in karstic environment on the Larzac plateau in southern France. We interpret the VGG observations obtained in this field study in the context of further available hydraulic and geophysical data and hydro-gravimetrical simulation. Finally, practical applications in view of detecting near-surface voids and reservoirs of different porosities as well as their storage capacity and seasonal dynamics are evaluated.

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Poster: An assessment of the relative information content of ground water flux and pressure data in the context of geostatistical inversion

Event: AGU Fall Meeting 2019, San Francisco (USA)
Poster by Behzad Pouladi, Niklas Linde, Olivier Bour, Laurent Longuevergne


Subsurface characterization often relies on inversion of either pressure or tracer data. Unless data from many pumping and observation wells are available, the inversion process only resolves smooth low-resolution images of subsurface properties, which leads to less accurate subsurface flow and reactive transport predictions. Furthermore, tracer tomography can be very challenging and convergence to a global minimum is difficult. Active-distributed temperature sensing technology opens up the prospect of replacing tracer test data with estimates of subsurface groundwater flux [1].

Here, the value of using estimated subsurface groundwater fluxes as a data source to reconstruct subsurface hydraulic properties is explored using a sequence of synthetic multivariate Gaussian aquifers with different measurement configurations. These results are compared to inversion of pressure data and joint inversion of the two data types with the inversions being based on the Principal Component Geostatistical Approach [2]. Inversion of pressure data resulted in a smoothed reconstruction of aquifer heterogeneity capturing approximately high and low conductivity regions while ground water flux data inversion leads to higher-resolution estimates. This is reflected, for one of the considered examples, by a correlation coefficient that increases from 0.57 for the pressure data to 0.65 for the ground water flux data. The complimentary nature of the data sets is represented by a correlation coefficient that increases to 0.74 for the joint inversion of the two data types.To conclude, inversion of ground water flux whether individually or jointly with pressure data, can provide enhanced information about the heterogeneity of subsurface media compared with using pressure data alone.

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Presentation: Time-Lapse seismic and electrical monitoirng of the vadose zone during a controlled infiltration experiment at the Ploeumeur Hydrological Observatory (Brittany, France)

Event: AGU Fall Meeting 2019, San Francisco (USA)
Presentation by Lara Blazevic, Ludovic Bodet, Niklas Linde, Laurent Longuevergne, Sylvain Pasquet, Thomas Hermans, Damien Jougnot


Geophysical methods provide non-intrusive means to obtain subsurface information of relevance for agriculture, pollutant transport and critical zone processes. Electrical resistivity tomography (ERT) is routinely employed to derive water content and associated fluxes while seismic methods in hydrogeophysics have recently developed with the estimation of Poisson’s ratio from the combined use of P-wave traveltime tomography and surface-wave dispersion inversion. Here, we investigate the complementarity of such time-lapse approaches in a well-known and controlled context.

The Ploemeur Hydrological Observatory, located in Brittany (France), lies on a contact zone between granite and micaschists. The crystalline bedrock aquifer is an important source of drinking water for the nearby population and is monitored with numerous boreholes and experimental campaigns on site.

In September 2018, we carried out a two-day controlled and gradual infiltration experiment in soil overlaying the micaschists and performed eleven repeated electrical resistivity and active seismic acquisitions on two orthogonal lines crossing the 2.2×2.4 m2 infiltration area. In total, 3.3 m3 of water were injected. Adjacent to the infiltration area, time-domain reflectometry (TDR) sensors installed at different depths provided real time water content estimates during the experiment. They reveal that in the upper 0.25 m, the increases in water content may exceed 125%, and may increase by 25-50% even at 2 m depth. Our 2D and 3D time-lapse ERT inversions agree with these findings, in that we observe a decrease of up to 90% in electrical resistivity in the upper 1 m.

For the seismic data, we computed the differences in first arrival times with respect to the first reference acquisition by cross-correlating the traces and observed positive relative changes in traveltimes in the infiltration area going from 30-90%. The 2D time-lapse traveltime inversion shows a similar behavior as the ERT with P-wave velocities decreasing between 50-90% in the upper 1 m.

Our ultimate aim is to combine these results with S-wave velocities from surface-wave analyses and perform joint 3D time-lapse inversion of the dataset to better constrain water content and rock physics models in the vadose zone.

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Presentation: The potential of temperature and dissolved gas as smart tracers for process-based heterogeneity characterization

Event: AGU Fall Meeting 2019, San Francisco (USA) Presentation by Richard Hoffmann, Pascal Goderniaux, Alain Dassargues


Informative reference data for a realistic assessment of aquifer heterogeneity is a prerequisite for robust transport simulations. Structure-based imaging using salt or a dye as tracer with a known concentration and volume to observe transfer times, is a powerful hydrogeological tool in moderate heterogenous media. Solving then the advection-dispersion equation will explain most of the point to point transport behavior. But, once the aquifer heterogeneity is more complex, e.g. in a double porosity medium like chalk, matrix porosity linked to diffusion processes must be taken into consideration to avoid a biased interpretation of the tracer information. Thus, performing additional local process-based imaging using smart tracers as dissolved gas and hot or cold water, assists to explain the late-time tailing behaviors realistically.

Smart tracers were injected in a sub-horizontal fracture connecting two adjacent wells to provide data about the complementary behaviors of each tracer and to focus on matrix diffusion processes. One reference data set is a 70 hours injection of hot water (∆T = + 40 °C) complemented by two 10 minutes uranine pulse injections within an inflatable double packer system isolating the sub-horizontal chalk fracture of interest. The temperature signal arrives at a 7.55 m distance with a delay of 12 hours compared to the first uranine injection and shows a rebound after the injection stopped. Useful reference data for further numerical modelling consists now in (a) local fracture geometry information deduced from interpretation by analytical solutions and, (b) matrix diffusion information.

Numerical modelling of those smart tracer experiments may question deterministic models for predictions and motivates for data-driven prediction tools like Monte-Carlo simulation procedures within a direct predictive framework. Distance based global sensitivity analysis (e.g. simultaneous variation of multiple input variables like diffusion coefficient, aperture and matrix storage) will be considered accounting for temperature related changes of viscosity and density. Key information about the most influencing parameters are main model outcomes, as local process understanding is very useful for possible future upscaling in regional models made of structure-based imaging.

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Presentation: Groundwater – surface water interactions in a lowland stream valley: thermal characterization of groundwater upwelling in a wetland

Event: AGU Fall Meeting 2019, San Francisco (USA)
Presentation by Joel Tirado-Conde, Majken Looms, Peter Engesgaard


Wetlands are extremely dynamical systems and their behavior depends on the characteristics of the surroundings (topography, geology and vegetation, among others) as well as on meteorological and hydrological processes. Wetlands are wet partly because they receive groundwater (or drain water) through diffuse upwelling and through springs. Studying upwelling is of great importance to e.g. evaluate the overall ecology or capacity to remove nitrate of the wetland system. One problem is that diffuse upwelling is difficult locate and measure.

We analyze the temporal dynamics of a groundwater fed wetland in central Jutland (Denmark) by the use of various thermal methods across a lowland stream valley. A monitoring system consisting of Distributed Temperature Sensing (DTS), wells with temperature depth profiles and thermal infrared (TIR) imaging on a UAV, in conjunction with hydrological and atmospheric data, provide a quasi 3D time-lapse characterization of the thermal behavior of the system, both on the ground and in the subsurface, over a period of around two years.

By analyzing the temporal evolution of the temperature in both the wetland surface and the groundwater, we can infer potential locations of groundwater upwelling to the land surface and subsequent overland flow. This is relevant as previous studies have shown that it is a generally overlooked flow component that may have a big impact relative to base flow. Moreover, it serves as a test for the feasibility of using heat as a tracer to study groundwater – surface water exchanges in wetlands.

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