An overview of multimethod imaging approaches in environmental geophysics

Wagner, F.; Uhlemann, Sebastian

doi:10.1016/bs.agph.2021.06.001

Cited by 25 publications

(11 citation statements)

References 171 publications

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“…The smoothness regularization was imposed to stabilize or constrain the inversion. In the CZ, the structural variation in the vertical direction is usually much larger than that in the horizontal direction; to account for this, an anisotropic smoothness regularization was imposed (Jiang et al., 2020; Wagner & Uhlemann, 2021). In the inversion, the velocity model was updated iteratively using the Gauss‐Newton method until the data misfit reached a predefined value.…”

Section: Extracting Cz Structures From Seismic Resultsmentioning

confidence: 99%

Geophysics‐Informed Hydrologic Modeling of a Mountain Headwater Catchment for Studying Hydrological Partitioning in the Critical Zone

Chen,

Niu,

Mendieta

et al. 2023

Water Resources Research

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Hydrologic modeling has been a useful approach for analyzing water partitioning in catchment systems. It will play an essential role in studying the responses of watersheds under projected climate changes. Numerous studies have shown it is critical to include subsurface heterogeneity in the hydrologic modeling to correctly simulate various water fluxes and processes in the hydrologic system. In this study, we test the idea of incorporating geophysics‐obtained subsurface critical zone (CZ) structures in the hydrologic modeling of a mountainous headwater catchment. The CZ structure is extracted from a three‐dimensional seismic velocity model developed from a series of two‐dimensional velocity sections inverted from seismic travel time measurements. Comparing different subsurface models shows that geophysics‐informed hydrologic modeling better fits the field observations, including streamflow discharge and soil moisture measurements. The results also show that this new hydrologic modeling approach could quantify many key hydrologic fluxes in the catchment, including streamflow, deep infiltration, and subsurface water storage. Estimations of these fluxes from numerical simulations generally have low uncertainties and are consistent with estimations from other methods. In particular, it is straightforward to calculate many hydraulic fluxes or states that may not be measured directly in the field or separated from field observations. Examples include quickflow/subsurface lateral flow, soil/rock moisture, and deep infiltration. Thus, this study provides a useful approach for studying the hydraulic fluxes and processes in the deep subsurface (e.g., weathered bedrock), which needs to be better represented in many earth system models.

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Section: Extracting Cz Structures From Seismic Resultsmentioning

confidence: 99%

Geophysics‐Informed Hydrologic Modeling of a Mountain Headwater Catchment for Studying Hydrological Partitioning in the Critical Zone

Chen,

Niu,

Mendieta

et al. 2023

Water Resources Research

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“…The goal of the present study is to incorporate structural constraints as derived from GPR data into the formulated inverse problem. For such a grid-based inversion procedure, a common approach 90 is to implement a smooth inversion, in which the weight of the smoothness constraints is decreased for model areas where a sharp interface is expected (e.g., Brown et al 2012;Doetsch et al 2012;Yan et al 2017;Wagner & Uhlemann 2021). For such a structurally-constrained smooth inversion approach (C-S), the model regularization function can be defined as…”

Section: Theory 70mentioning

confidence: 99%

“…the final result (e.g.,Wagner & Uhlemann 2021). A common implementation for incorporating structural a priori information in such structurally-constrained inversion approaches is to down-weight or completely remove the smoothness constraints around expected interfaces.…”

mentioning

confidence: 99%

Structurally constrained inversion by means of a Minimum Gradient Support regularizer: examples of FD-EMI data inversion constrained by GPR reflection data

Klose

Guillemoteau

Vignoli

et al. 2023

Geophysical Journal International

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Summary Many geophysical inverse problems are known to be ill-posed and, thus, requiring some kind of regularization in order to provide a unique and stable solution. A possible approach to overcome the inversion ill-posedness consists in constraining the position of the model interfaces. For a grid-based parameterization, such a structurally-constrained inversion can be implemented by adopting the usual smooth regularization scheme in which the local weight of the regularization is reduced where an interface is expected. By doing so, sharp contrasts are promoted at interface locations while standard smoothness constraints keep affecting the other regions of the model. In this work, we present a structurally-constrained approach and test it on the inversion of frequency-domain electromagnetic induction (FD-EMI) data using a regularization approach based on the Minimum Gradient Support (MGS) stabilizer, which is capable to promote sharp transitions everywhere in the model, i.e., also in areas where no structural a priori information is available. Using 1D and 2D synthetic data examples, we compare the proposed approach to a structurally-constrained smooth inversion as well as to more standard (i.e., not structurally-constrained) smooth and sharp inversions. Our results demonstrate that the proposed approach helps in finding a better and more reliable reconstruction of the subsurface electrical conductivity distribution, including its structural characteristics. Furthermore, we demonstrate that it allows to promote sharp parameter variations in areas where no structural information are available. Lastly, we apply our structurally-constrained scheme to FD-EMI field data collected at a field site in Eastern Germany to image the thickness of peat deposits along two selected profiles. In this field example, we use collocated constant offset ground-penetrating radar (GPR) data to derive structural a priori information to constrain the inversion of the FD-EMI data. The results of this case study demonstrate the effectiveness and flexibility of the proposed approach.

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“…To fully exploit the sensitivities of the P-and S-wave seismic refraction and electrical resistivity tomographic data, we used a structurally coupled cooperative joint inversion approach (Skibbe et al, 2021;Wagner and Uhlemann, 2021), which was implemented in PyGIMLi (Rücker et al, 2017). In this approach, the structural similarity is achieved by smoothness constraints in the regularization operator that are locally decreased based on the roughness of the model, and updated between iterations.…”

Section: Characterizationmentioning

confidence: 99%

Understanding Slow-moving Landslide Triggering Processes Using Low-cost Passive Seismic and Inclinometer Monitoring

Fiolleau¹,

Dafflon²,

Wielandt³

et al. 2022

Preprint

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Landslides are a major natural hazard, threatening communities and infrastructures worldwide. Mitigation of these hazards relies on understanding their causes and triggering processes, which critically depend on subsurface characteristics and their variations over time. In this study, we present a novel approach combining passive seismic and low-cost inclinometer monitoring methods to improve the understanding of landslide activation mechanisms and their controls. We evaluate the efficiency of this approach on a shallow, slow-moving landslide directly endangering a road bridge, a bridge that is part of an important emergency response route. Results show the value of combining the two approaches for observing and monitoring landslide hazards. Passive seismic monitoring captures the variation in soil properties (rigidity and density) over time by sensing the variations of the seismic wave velocity (dV/V and its associated correlation coefficient). At the same time, novel low-cost inclinometers are monitoring subsurface deformation (from millimetric to pluricentimetric scale) and temperature. Seismic precursors detected at the bottom sensor a few hours prior to the reactivation are followed by the reactivation of the landslide toe, releasing stresses in the top part that lead to the reactivation of the whole landslide. This reactivation occurs during an episode of heavy rainfall following a 7-month drought. Meanwhile, temperature monitoring enables us to track water infiltration and to highlight its role in the landslide mechanisms. Overall, the combination of the two monitoring methods shows promise for quantifying the sliding mechanisms of landslide reactivations and for designing landslide early warning systems.

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An overview of multimethod imaging approaches in environmental geophysics

Cited by 25 publications

References 171 publications

Geophysics‐Informed Hydrologic Modeling of a Mountain Headwater Catchment for Studying Hydrological Partitioning in the Critical Zone

Geophysics‐Informed Hydrologic Modeling of a Mountain Headwater Catchment for Studying Hydrological Partitioning in the Critical Zone

Structurally constrained inversion by means of a Minimum Gradient Support regularizer: examples of FD-EMI data inversion constrained by GPR reflection data

Understanding Slow-moving Landslide Triggering Processes Using Low-cost Passive Seismic and Inclinometer Monitoring

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