Zobrazeno 1 - 10
of 159
pro vyhledávání: '"Niklas Linde"'
Autor:
Alejandro Romero‐Ruiz, Niklas Linde, Ludovic Baron, Santiago Gabriel Solazzi, Thomas Keller, Dani Or
Publikováno v:
Vadose Zone Journal, Vol 20, Iss 4, Pp n/a-n/a (2021)
Abstract A well‐developed soil structure is a key attribute of a productive and functioning soil. Evidence shows that subtle changes in the spatial arrangement and binding of soil constituents impart large changes in soil mechanical and hydraulic p
Externí odkaz:
https://doaj.org/article/e06ed9bd764b40d18f567c8264081822
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
Abstract Existing 3-D density models of the Somma-Vesuvius volcanic complex (SVVC), Italy, largely disagree. Despite the scientific and socioeconomic importance of Vesuvius, there is no reliable 3-D density model of the SVVC. A considerable uncertain
Externí odkaz:
https://doaj.org/article/e0749203f6bc4040ae791cdccaf99b52
Autor:
Lara A. Blazevic, Ludovic Bodet, Sylvain Pasquet, Niklas Linde, Damien Jougnot, Laurent Longuevergne
Publikováno v:
Water, Vol 12, Iss 5, p 1230 (2020)
The vadose zone is the main host of surface and subsurface water exchange and has important implications for ecosystems functioning, climate sciences, geotechnical engineering, and water availability issues. Geophysics provides a means for investigat
Externí odkaz:
https://doaj.org/article/d3bdba39395445ec97104fbdb2eb59d3
We seek to develop a methodology enabling fast geostatistical simulations honoring both geophysical data and a complex prior model. Particularly, we consider a multiple-point statistics (MPS) framework in which a training image (TI) describes the ava
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0182ca005b7131904e373fb5fad22d9e
https://doi.org/10.5194/egusphere-egu23-16088
https://doi.org/10.5194/egusphere-egu23-16088
Autor:
Kaiyan Hu, Hengxin Ren, Qinghua Huang, Ling Zeng, Karl E. Butler, Damien Jougnot, Niklas Linde, Klaus Holliger
Publikováno v:
Journal of Geophysical Research: Solid Earth. 128
Autor:
Thomas Hermans, Pascal Goderniaux, Damien Jougnot, Jan H. Fleckenstein, Philip Brunner, Frédéric Nguyen, Niklas Linde, Johan Alexander Huisman, Olivier Bour, Jorge Lopez Alvis, Richard Hoffmann, Andrea Palacios, Anne-Karin Cooke, Álvaro Pardo-Álvarez, Lara Blazevic, Behzad Pouladi, Peleg Haruzi, Alejandro Fernandez Visentini, Guilherme E. H. Nogueira, Joel Tirado-Conde, Majken C. Looms, Meruyert Kenshilikova, Philippe Davy, Tanguy Le Borgne
Publikováno v:
Hydrology and earth system sciences 27(1), 255-287 (2023). doi:10.5194/hess-27-255-2023
HYDROLOGY AND EARTH SYSTEM SCIENCES
Hermans, T, Goderniaux, P, Jougnot, D, Fleckenstein, J H, Brunner, P, Nguyen, F, Linde, N, Huisman, J A, Bour, O, Lopez Alvis, J, Hoffmann, R, Palacios, A, Cooke, A-K, Pardo-Álvarez, Á, Blazevic, L, Pouladi, B, Haruzi, P, Visentini, A F, Nogueira, G E H, Tirado-Conde, J, Looms, M C, Kenshilikova, M, Davy, P & Le Borgne, T 2023, ' Advancing measurements and representations of subsurface heterogeneity and dynamic processes : towards 4D hydrogeology ', Hydrology and Earth System Sciences, vol. 27, no. 1, pp. 255-287 . https://doi.org/10.5194/hess-27-255-2023
Hydrology and Earth System Sciences, vol. 27, no. 1, pp. 255-287
HYDROLOGY AND EARTH SYSTEM SCIENCES
Hermans, T, Goderniaux, P, Jougnot, D, Fleckenstein, J H, Brunner, P, Nguyen, F, Linde, N, Huisman, J A, Bour, O, Lopez Alvis, J, Hoffmann, R, Palacios, A, Cooke, A-K, Pardo-Álvarez, Á, Blazevic, L, Pouladi, B, Haruzi, P, Visentini, A F, Nogueira, G E H, Tirado-Conde, J, Looms, M C, Kenshilikova, M, Davy, P & Le Borgne, T 2023, ' Advancing measurements and representations of subsurface heterogeneity and dynamic processes : towards 4D hydrogeology ', Hydrology and Earth System Sciences, vol. 27, no. 1, pp. 255-287 . https://doi.org/10.5194/hess-27-255-2023
Hydrology and Earth System Sciences, vol. 27, no. 1, pp. 255-287
Essentially all hydrogeological processes are strongly influenced by the subsurface spatial heterogeneity and the temporal variation of environmental conditions, hydraulic properties, and solute concentrations. This spatial and temporal variability g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d625be75236ed6219e7d8935ea754b5
https://juser.fz-juelich.de/record/917301
https://juser.fz-juelich.de/record/917301
Variational Bayesian inference with complex geostatistical priors using inverse autoregressive flows
Publikováno v:
Computers & Geosciences, vol. 171, pp. 105263
We combine inverse autoregressive flows (IAF) and variational Bayesian inference (variational Bayes) in the context of geophysical inversion parameterized with deep generative models encoding complex priors. Variational Bayes approximates the unnorma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5aac8dddacd5c60ca41464b0462caa00
https://serval.unil.ch/notice/serval:BIB_BB2F0E925B0B
https://serval.unil.ch/notice/serval:BIB_BB2F0E925B0B
Publikováno v:
Advances in Water Resources, vol. 166, pp. 104252
For strongly non-linear and high-dimensional inverse problems, Markov chain Monte Carlo (MCMC) methods may fail to properly explore the posterior probability density function (PDF) given a realistic computational budget and are generally poorly amena
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5c924ba98ba1866efb188502c67b75a
https://serval.unil.ch/notice/serval:BIB_CEEF73E0083E
https://serval.unil.ch/notice/serval:BIB_CEEF73E0083E
Publikováno v:
Geophysical Journal International, vol. 226, no. 2, pp. 1220-1238
Bayesian model selection enables comparison and ranking of conceptual subsurface models described by spatial prior models, according to the support provided by available geophysical data. Deep generative neural networks can efficiently encode such co
Publikováno v:
Water Resources Research, vol. 58, no. 4
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba4b775b31ac5c243176cb328e6829ce
https://serval.unil.ch/resource/serval:BIB_8117907E019A.P001/REF.pdf
https://serval.unil.ch/resource/serval:BIB_8117907E019A.P001/REF.pdf