ORCID Profile
0000-0003-1613-353X
Current Organisation
University of Lausanne
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Publisher: Springer Science and Business Media LLC
Date: 07-09-2013
Publisher: Oxford University Press (OUP)
Date: 30-12-2015
DOI: 10.1093/GJI/GGV517
Publisher: Oxford University Press (OUP)
Date: 30-10-2015
DOI: 10.1093/GJI/GGV406
Publisher: Elsevier BV
Date: 10-2015
Publisher: American Geophysical Union (AGU)
Date: 13-02-2007
DOI: 10.1029/2006GL028878
Publisher: Wiley
Date: 04-2017
Publisher: European Association of Geoscientists & Engineers
Date: 2018
Publisher: California Digital Library (CDL)
Date: 09-02-2022
DOI: 10.31223/X5RG7Q
Abstract: Highly simplified approaches continue to underpin hydrological climate change impact assessments across the Earth’s mountainous regions. Fully-integrated surface-subsurface models may hold far greater potential to represent the distinctive regimes of steep, geologically-complex headwater catchments. However, their utility has not yet been tested across a wide range of mountainous settings. Here, an integrated model of two adjacent calcareous Alpine headwaters that accounts for 2D surface flow, 3D variably-saturated groundwater flow, and evapotranspiration is presented. An energy balance-based representation of snow dynamics contributed to the model’s high-resolution forcing data, and a sophisticated 3D geological model helped to define and parameterize the subsurface structure. In the first known attempt to calibrate a catchment-scale integrated model of a mountainous region automatically, numerous uncertain model parameters were estimated. The salient features of the hydrological regime could ultimately be satisfactorily reproduced – over an 11-month evaluation period, the Nash-Sutcliffe efficiency of simulated streamflow at the main gauging station was 0.76. Spatio-temporal visualization of the forcing data and simulated responses further confirmed the model’s broad coherence. Presumably due to unresolved local subsurface heterogeneity, closely replicating the somewhat contrasting groundwater level signals observed near to one another proved more elusive. Finally, we assessed the impacts of various common model simplifications and assumptions on key simulated outputs, finding strongly affected model performance in many cases. Although certain outstanding challenges must be overcome if the global uptake of integrated models in mountain regions is to increase, our work demonstrates the feasibility and benefits of their application in such complex systems.
Publisher: American Geophysical Union (AGU)
Date: 06-2019
DOI: 10.1029/2018JF004921
Publisher: American Geophysical Union (AGU)
Date: 02-2017
DOI: 10.1002/2016WR019347
Abstract: Inversion methods that build on multiple‐point statistics tools offer the possibility to obtain model realizations that are not only in agreement with field data, but also with conceptual geological models that are represented by training images. A recent inversion approach based on patch‐based geostatistical resimulation using graph cuts outperforms state‐of‐the‐art multiple‐point statistics methods when applied to synthetic inversion ex les featuring continuous and discontinuous property fields. Applications of multiple‐point statistics tools to field data are challenging due to inevitable discrepancies between actual subsurface structure and the assumptions made in deriving the training image. We introduce several amendments to the original graph cut inversion algorithm and present a first‐ever field application by addressing porosity estimation at the Boise Hydrogeophysical Research Site, Boise, Idaho. We consider both a classical multi‐Gaussian and an outcrop‐based prior model (training image) that are in agreement with available porosity data. When conditioning to available crosshole ground‐penetrating radar data using Markov chain Monte Carlo, we find that the posterior realizations honor overall both the characteristics of the prior models and the geophysical data. The porosity field is inverted jointly with the measurement error and the petrophysical parameters that link dielectric permittivity to porosity. Even though the multi‐Gaussian prior model leads to posterior realizations with higher likelihoods, the outcrop‐based prior model shows better convergence. In addition, it offers geologically more realistic posterior realizations and it better preserves the full porosity range of the prior.
Publisher: American Geophysical Union (AGU)
Date: 08-2019
DOI: 10.1029/2019WR024840
Publisher: Elsevier BV
Date: 04-2019
Publisher: Copernicus GmbH
Date: 27-06-2014
DOI: 10.5194/HESS-18-2449-2014
Abstract: Abstract. River restoration can enhance river dynamics, environmental heterogeneity and bio ersity, but the underlying processes governing the dynamic changes need to be understood to ensure that restoration projects meet their goals, and adverse effects are prevented. In particular, we need to comprehend how hydromorphological variability quantitatively relates to ecosystem functioning and services, bio ersity as well as ground- and surface water quality in restored river corridors. This involves (i) physical processes and structural properties, determining erosion and sedimentation, as well as solute and heat transport behavior in surface water and within the subsurface (ii) biogeochemical processes and characteristics, including the turnover of nutrients and natural water constituents and (iii) ecological processes and indicators related to bio ersity and ecological functioning. All these aspects are interlinked, requiring an interdisciplinary investigation approach. Here, we present an overview of the recently completed RECORD (REstored CORridor Dynamics) project in which we combined physical, chemical, and biological observations with modeling at a restored river corridor of the perialpine Thur River in Switzerland. Our results show that river restoration, beyond inducing morphologic changes that reshape the river bed and banks, triggered complex spatial patterns of bank infiltration, and affected habitat type, biotic communities and biogeochemical processes. We adopted an interdisciplinary approach of monitoring the continuing changes due to restoration measures to address the following questions: How stable is the morphological variability established by restoration? Does morphological variability guarantee an improvement in bio ersity? How does morphological variability affect biogeochemical transformations in the river corridor? What are some potential adverse effects of river restoration? How is river restoration influenced by catchment-scale hydraulics and which feedbacks exist on the large scale? Beyond summarizing the major results of in idual studies within the project, we show that these overarching questions could only be addressed in an interdisciplinary framework.
Publisher: American Geophysical Union (AGU)
Date: 29-03-2022
DOI: 10.1029/2020WR029390
Abstract: Highly simplified approaches continue to underpin hydrological climate change impact assessments across the Earth's mountainous regions. Fully‐integrated surface‐subsurface models may hold far greater potential to represent the distinctive regimes of steep, geologically‐complex headwater catchments. However, their utility has not yet been tested across a wide range of mountainous settings. Here, an integrated model of two adjacent calcareous Alpine headwaters that accounts for two‐dimensional surface flow, three‐dimensional (3D) variably‐saturated groundwater flow, and evapotranspiration is presented. An energy balance‐based representation of snow dynamics contributed to the model's high‐resolution forcing data, and a sophisticated 3D geological model helped to define and parameterize its subsurface structure. In the first known attempt to calibrate a catchment‐scale integrated model of a mountainous region automatically, numerous uncertain model parameters were estimated. The salient features of the hydrological regime could ultimately be satisfactorily reproduced – over an 11‐month evaluation period, the Nash‐Sutcliffe efficiency of simulated streamflow at the main gauging station was 0.76. Spatio‐temporal visualization of the forcing data and simulated responses further confirmed the model's broad coherence. Presumably due to unresolved local subsurface heterogeneity, closely replicating the somewhat contrasting groundwater level signals observed near to one another proved more elusive. Finally, we assessed the impacts of various simplifications and assumptions that are commonly employed in physically‐based modeling – including the use of spatially uniform forcings, a vertically limited model domain, and global geological data products – on key simulated outputs, finding strongly affected model performance in many cases. Although certain outstanding challenges must be overcome if the uptake of integrated models in mountain regions around the world is to increase, our work demonstrates the feasibility and benefits of their application in such complex systems.
Publisher: American Geophysical Union (AGU)
Date: 08-2016
DOI: 10.1002/2015WR018378
Publisher: Elsevier BV
Date: 09-2007
DOI: 10.1016/J.JCIS.2007.03.037
Abstract: We consider a charged porous material that is saturated by two fluid phases that are immiscible and continuous on the scale of a representative elementary volume. The wetting phase for the grains is water and the nonwetting phase is assumed to be an electrically insulating viscous fluid. We use a volume-averaging approach to derive the linear constitutive equations for the electrical current density as well as the seepage velocities of the wetting and nonwetting phases on the scale of a representative elementary volume. These macroscopic constitutive equations are obtained by volume-averaging Ampère's law together with the Nernst-Planck equation and the Stokes equations. The material properties entering the macroscopic constitutive equations are explicitly described as functions of the saturation of the water phase, the electrical formation factor, and parameters that describe the capillary pressure function, the relative permeability functions, and the variation of electrical conductivity with saturation. New equations are derived for the streaming potential and electro-osmosis coupling coefficients. A primary drainage and imbibition experiment is simulated numerically to demonstrate that the relative streaming potential coupling coefficient depends not only on the water saturation, but also on the material properties of the s le, as well as the saturation history. We also compare the predicted streaming potential coupling coefficients with experimental data from four dolomite core s les. Measurements on these s les include electrical conductivity, capillary pressure, the streaming potential coupling coefficient at various levels of saturation, and the permeability at saturation of the rock s les. We found very good agreement between these experimental data and the model predictions.
Publisher: Oxford University Press (OUP)
Date: 20-04-2019
DOI: 10.1093/GJI/GGZ185
Abstract: Deterministic geophysical inversion approaches yield tomographic images with strong imprints of the regularization terms required to solve otherwise ill-posed inverse problems. While such tomograms enable an adequate assessment of the larger-scale features of the probed subsurface, the finer-scale details tend to be unresolved. Yet, representing these fine-scale structural details is generally desirable and for some applications even mandatory. To address this problem, we have developed a two-step methodology based on area-to-point kriging to generate fine-scale multi-Gaussian realizations from smooth tomographic images. Specifically, we use a co-kriging system in which the smooth, low-resolution tomogram is related to the fine-scale heterogeneity through a linear mapping operation. This mapping is based on the model resolution and the posterior covariance matrices computed using a linearization around the final tomographic model. This, in turn, allows us for analytical computations of covariance and cross-covariance models. The methodology is tested on a heterogeneous synthetic 2-D distribution of electrical conductivity that is probed with a surface-based electrical resistivity tomography (ERT) survey. The results demonstrate the ability of this technique to reproduce a known geostatistical model characterizing the fine-scale structure, while simultaneously preserving the large-scale structures identified by the smoothness-constrained tomographic inversion. Small discrepancies between the geophysical forward responses of the realizations and the reference synthetic data are attributed to the underlying linearization. Overall, the method provides an effective and fast alternative to more comprehensive, but computationally more expensive approaches, such as, for ex le, Markov chain Monte Carlo techniques. Moreover, the proposed method can be used to generate fine-scale multivariate Gaussian realizations from virtually any smoothness-constrained inversion results given the corresponding resolution and posterior covariance matrices.
Publisher: Elsevier BV
Date: 04-2016
Location: Switzerland
Location: France
No related grants have been discovered for Niklas Linde.