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Related papers: In-situ soil parametrization from multi-layer mois…

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Soil salinization poses a significant threat to both ecosystems and agriculture because it limits plants' ability to absorb water and, in doing so, reduces crop productivity. This phenomenon alters the soil's spectral properties, creating a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Rupasree Dey , Abdul Matin , Everett Lewark , Tanjim Bin Faruk , Andrei Bachinin , Sam Leuthold , M. Francesca Cotrufo , Shrideep Pallickara , Sangmi Lee Pallickara

Bayesian approaches are one of the primary methodologies to tackle an inverse problem in high dimensions. Such an inverse problem arises in hydrology to infer the permeability field given flow data in a porous media. It is common practice…

Methodology · Statistics 2023-10-02 Navid Shervani-Tabar

Groundwater flow modeling is commonly used to calculate groundwater heads, estimate groundwater flow paths and travel times, and provide insights into solute transport processes within an aquifer. However, the values of input parameters…

Computational Engineering, Finance, and Science · Computer Science 2023-03-15 Emily A. Baker , Sauro Manenti , Alessandro Reali , Giancarlo Sangalli , Lorenzo Tamellini , Sara Todeschini

Observations of the solar surface reveal the presence of flows with length scales of around $35$ Mm, commonly referred to as supergranules. Inferring the sub-surface flow profile of supergranules from measurements of the surface and…

Solar and Stellar Astrophysics · Physics 2016-08-03 Jishnu Bhattacharya , Shravan M. Hanasoge

The use of GNSS signals as a source of opportunity for remote sensing applications, GNSS-R, has been a research area of interest for more than a decade. One of the possible applications of this technique is soil moisture monitoring. The…

Seismic waves are the most sensitive probe of the Earth's interior we have. With the dense data sets available in exploration, images of subsurface structures can be obtained through processes such as migration. Unfortunately, relating…

Geophysics · Physics 2009-05-05 R. B. Schlottmann

Airborne transient electromagnetic (TEM) is a cost-effective method to image the distribution of electrical conductivity in the ground. We consider layered earth inversion to interpret large data sets of hundreds of kilometre. Different…

Geophysics · Physics 2012-07-17 Julien Guillemoteau , Pascal Sailhac , Mickael Behaegel

Structural seismic interpretation and quantitative characterization are historically intertwined processes. The latter provides estimates of properties of the subsurface which can be used to aid structural interpretation alongside the…

Geophysics · Physics 2021-10-13 Matteo Ravasi , Claire Emma Birnie

Electromagnetic induction methods are a common means for geophysical survey. For soil structures that are invariant in one spatial dimension such as trench structures, we propose a fast forward model based on a 2D response function, taking…

Geophysics · Physics 2018-05-17 Hans Dierckx , Katrien De Blauwe , Marc Van Meirvenne , Henri Verschelde

In this general report, experimental systems and procedures of investigating the hydro-mechanical behaviour of unsaturated soils are presented. The water retention properties of unsaturated soils are commented and linked to various physical…

Geophysics · Physics 2008-12-18 Pierre Delage

Aircraft-based surveying to collect airborne electromagnetic data is a key method to image large swaths of the Earth's surface in pursuit of better knowledge of aquifer systems. Despite many years of advancements, 3D inversion still poses…

The frequency dependence of dielectric material properties of water saturated and unsaturated porous materials such as soil is not only disturbing in applications with high frequency electromagnetic (HF-EM) techniques but also contains…

Geophysics · Physics 2024-06-25 Norman Wagner , Frank Daschner , Alexander Scheuermann , Moritz Schwing

The near-surface environment is often too complex to enable inference of hydrological and environmental variables using one geophysical data type alone. Joint inversion and coupled inverse modeling involving numerical flow- and transport…

Geophysics · Physics 2017-01-09 N. Linde , J. Doetsch

The goal of inversion is to estimate the model which generates the data of observations with a specific modeling equation. One general approach to inversion is to use optimization methods which are algebraic in nature to define an objective…

Geophysics · Physics 2015-06-02 August Lau , Chuan Yin

4D seismic inversion is the leading method to quantitatively monitor fluid flow dynamics in the subsurface, with applications ranging from enhanced oil recovery to subsurface CO2 storage. The process of inverting seismic data for reservoir…

Geophysics · Physics 2023-10-25 Juan Romero , Nick Luiken , Matteo Ravasi

Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth. As such, it is widely utilized in the energy and construction…

Geophysics · Physics 2024-11-05 Juan Romero , Wolfgang Heidrich , Nick Luiken , Matteo Ravasi

Nonlinear least squares data-fitting driven by physical process simulation is a classic and widely successful technique for the solution of inverse problems in science and engineering. Known as "Full Waveform Inversion" in application to…

Optimization and Control · Mathematics 2020-10-28 William W. Symes

Accurate prediction of shallow water flows relies on precise bottom topography data, yet direct bathymetric surveys are expensive and time-consuming. In contrast, remote sensing platforms such as radar or satellite altimetry provide…

Numerical Analysis · Mathematics 2026-03-13 Falko Ruppenthal , Dmitri Kuzmin

High fidelity models used in many science and engineering applications couple multiple physical states and parameters. Inverse problems arise when a model parameter cannot be determined directly, but rather is estimated using (typically…

Optimization and Control · Mathematics 2020-12-30 Isaac Sunseri , Joseph Hart , Bart van Bloemen Waanders , Alen Alexanderian

We present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an…

Machine Learning · Computer Science 2024-12-30 Jice Zeng , Yuanzhe Wang , Alexandre M. Tartakovsky , David Barajas-Solano