Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-961-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-961-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Feb 2023
Development and technical paper |
| 07 Feb 2023
| 07 Feb 2023
Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN
Piyoosh Jaysaval
CORRESPONDING AUTHOR
Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA
Glenn E. Hammond
Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA
Timothy C. Johnson
Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352, USA
Related authors
Piyooh Jaysaval, Judith L. Robinson, and Timothy C. Johnson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-478, https://doi.org/10.5194/hess-2020-478, 2020
Preprint withdrawn
Short summary
Short summary
As contaminants within groundwater prefer to flow through coarse-grained rocks, a detailed mapping of these rocks in the subsurface is vital for effective monitoring and remediation planning to help minimize risk to human health and the environment at legacy waste sites. This work provides images that are obtained from airborne electromagnetic data to delineate subsurface rocks at the Hanford Site, a nuclear waste site located in southeastern Washington State, USA.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-34, https://doi.org/10.5194/gmd-2024-34, 2024
Preprint under review for GMD
Short summary
Short summary
The newly developed Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate respiration and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow via a Jupyter Notebook interface, that digests raw organic matter chemistry data via FTICR-MS, develops the representative reaction network, and completes a biogeochemical simulation with the open source, parallel reactive flow and transport code PFLOTRAN.
Glenn E. Hammond
Geosci. Model Dev., 15, 1659–1676, https://doi.org/10.5194/gmd-15-1659-2022, https://doi.org/10.5194/gmd-15-1659-2022, 2022
Short summary
Short summary
This paper describes a simplified interface for implementing and testing new chemical reactions within the reactive transport simulator PFLOTRAN. The paper describes the interface, providing example code for the interface. The paper includes several chemical reactions implemented through the interface.
Piyooh Jaysaval, Judith L. Robinson, and Timothy C. Johnson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-478, https://doi.org/10.5194/hess-2020-478, 2020
Preprint withdrawn
Short summary
Short summary
As contaminants within groundwater prefer to flow through coarse-grained rocks, a detailed mapping of these rocks in the subsurface is vital for effective monitoring and remediation planning to help minimize risk to human health and the environment at legacy waste sites. This work provides images that are obtained from airborne electromagnetic data to delineate subsurface rocks at the Hanford Site, a nuclear waste site located in southeastern Washington State, USA.
Yilin Fang, Xingyuan Chen, Jesus Gomez Velez, Xuesong Zhang, Zhuoran Duan, Glenn E. Hammond, Amy E. Goldman, Vanessa A. Garayburu-Caruso, and Emily B. Graham
Geosci. Model Dev., 13, 3553–3569, https://doi.org/10.5194/gmd-13-3553-2020, https://doi.org/10.5194/gmd-13-3553-2020, 2020
Short summary
Short summary
Surface water quality along river corridors can be improved by the area of the stream bed and stream bank in which stream water mixes with shallow groundwater or hyporheic zones (HZs). These zones are ubiquitous and dominated by microorganisms that can process the dissolved nutrients exchanged at this interface of these zones. The modulation of surface water quality can be simulated by connecting the channel water and HZs through hyporheic exchanges using multirate mass transfer representation.
Gautam Bisht, William J. Riley, Glenn E. Hammond, and David M. Lorenzetti
Geosci. Model Dev., 11, 4085–4102, https://doi.org/10.5194/gmd-11-4085-2018, https://doi.org/10.5194/gmd-11-4085-2018, 2018
Short summary
Short summary
Most existing global land surface models used to study impacts of climate change on water resources routinely use different models for near-surface unsaturated soil and the deeper groundwater table. We developed a model that uses a unified treatment of soil hydrologic processes throughout the entire soil column. Using a calibrated drainage parameter, the new model is able to correctly predict deep water table depth as reported in an observationally constrained global dataset.
Related subject area
Numerical methods
A computationally efficient parameterization of aerosol, cloud and precipitation pH for application at global and regional scale (EQSAM4Clim-v12)
Assessing the benefits of approximately exact step sizes for Picard and Newton solver in simulating ice flow (FEniCS-full-Stokes v.1.3.2)
Assessing effects of climate and technology uncertainties in large natural resource allocation problems
VISIR-2: ship weather routing in Python
Incremental analysis update (IAU) in the Model for Prediction Across Scales coupled with the Joint Effort for Data assimilation Integration (MPAS–JEDI 2.0.0)
Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0
Developing meshing workflows in Gmsh v4.11 for the geologic uncertainty assessment of high-temperature aquifer thermal energy storage
Development and preliminary validation of a land surface image assimilation system based on the Common Land Model
NorSand4AI: a comprehensive triaxial test simulation database for NorSand constitutive model materials
ParticleDA.jl v.1.0: a distributed particle-filtering data assimilation package
HETerogeneous vectorized or Parallel (HETPv1.0): an updated inorganic heterogeneous chemistry solver for the metastable-state NH4+–Na+–Ca2+–K+–Mg2+–SO42−–NO3−–Cl−–H2O system based on ISORROPIA II
Three-dimensional geological modelling of igneous intrusions in LoopStructural v1.5.10
Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17)
Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding
An automatic mesh generator for coupled 1D–2D hydrodynamic models
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 2: A semi-discrete error analysis framework for assessing coupling schemes
jsmetrics v0.2.0: a Python package for metrics and algorithms used to identify or characterise atmospheric jet streams
P3D-BRNS v1.0.0: a three-dimensional, multiphase, multicomponent, pore-scale reactive transport modelling package for simulating biogeochemical processes in subsurface environments
MinVoellmy v1: a lightweight model for simulating rapid mass movements based on a modified Voellmy rheology
Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets
Sweep interpolation: a cost-effective semi-Lagrangian scheme in the Global Environmental Multiscale model
CHONK 1.0: landscape evolution framework: cellular automata meets graph theory
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations
Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods
GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
A comparison of Eulerian and Lagrangian methods for vertical particle transport in the water column
AutoQS v1: automatic parametrization of QuickSampling based on training images analysis
Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions
A dynamical core based on a discontinuous Galerkin method for higher-order finite-element sea ice modeling
GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation
Leveraging Google's Tensor Processing Units for tsunami-risk mitigation planning in the Pacific Northwest and beyond
Consistent Point Data Assimilation in Firedrake and Icepack
An improved subgrid channel model with upwind-form artificial diffusion for river hydrodynamics and floodplain inundation simulation
A model instability issue in the National Centers for Environmental Prediction Global Forecast System version 16 and potential solutions
A comparison of 3-D spherical shell thermal convection results at low to moderate Rayleigh number using ASPECT (version 2.2.0) and CitcomS (version 3.3.1)
LISFLOOD-FP 8.1: new GPU-accelerated solvers for faster fluvial/pluvial flood simulations
Fast approximate Barnes interpolation: illustrated by Python-Numba implementation fast-barnes-py v1.0
Strategies for conservative and non-conservative monotone remapping on the sphere
Modeling large‐scale landform evolution with a stream power law for glacial erosion (OpenLEM v37): benchmarking experiments against a more process-based description of ice flow (iSOSIA v3.4.3)
A mixed finite-element discretisation of the shallow-water equations
Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling
Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes
The Intelligent Prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning
ISMIP-HOM benchmark experiments using Underworld
spyro: a Firedrake-based wave propagation and full-waveform-inversion finite-element solver
Spatial filtering in a 6D hybrid-Vlasov scheme to alleviate adaptive mesh refinement artifacts: a case study with Vlasiator (versions 5.0, 5.1, and 5.2.1)
A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
Geosci. Model Dev., 17, 5009–5021, https://doi.org/10.5194/gmd-17-5009-2024, https://doi.org/10.5194/gmd-17-5009-2024, 2024
Short summary
Short summary
EQSAM4Clim has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. It is based on an analytical concept that is sufficiently fast and free of numerical noise, which makes it attractive for air quality forecasting. Version 12 allows the calculation of aerosol composition based on the gas–liquid–solid and the reduced gas–liquid partitioning with the associated water uptake for both cases, including the acidity of the aerosols.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
Geosci. Model Dev., 17, 4943–4959, https://doi.org/10.5194/gmd-17-4943-2024, https://doi.org/10.5194/gmd-17-4943-2024, 2024
Short summary
Short summary
Future sea-level rise is of big significance for coastal regions. The melting and acceleration of glaciers plays a major role in sea-level change. Computer simulation of glaciers costs a lot of computational resources. In this publication, we test a new way of simulating glaciers. This approach produces the same results but has the advantage that it needs much less computation time. As simulations can be obtained with fewer computation resources, higher resolution and physics become affordable.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
Geosci. Model Dev., 17, 4791–4819, https://doi.org/10.5194/gmd-17-4791-2024, https://doi.org/10.5194/gmd-17-4791-2024, 2024
Short summary
Short summary
This paper applies a cutting-edge numerical method, SCEQ, to show how uncertain climate change and technological progress affect the future utilization of the world's scarce land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The study finds the range of outcomes for land use change to be smaller when using this novel method compared to existing deterministic models.
Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović
Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, https://doi.org/10.5194/gmd-17-4355-2024, 2024
Short summary
Short summary
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, https://doi.org/10.5194/gmd-17-4199-2024, 2024
Short summary
Short summary
To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs
Geosci. Model Dev., 17, 4031–4052, https://doi.org/10.5194/gmd-17-4031-2024, https://doi.org/10.5194/gmd-17-4031-2024, 2024
Short summary
Short summary
We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions for optimal aircraft trajectories, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel and uses weather conditions simulated by the EMAC atmospheric model. This paper focuses on the ability of SolFinder to identify eco-efficient trajectories, reducing a flight's climate impact at limited cost penalties.
Ali Dashti, Jens C. Grimmer, Christophe Geuzaine, Florian Bauer, and Thomas Kohl
Geosci. Model Dev., 17, 3467–3485, https://doi.org/10.5194/gmd-17-3467-2024, https://doi.org/10.5194/gmd-17-3467-2024, 2024
Short summary
Short summary
This study developed new meshing workflows to enable the automatic generation of meshes that follow geological models. The workflow allows for importing several geological models as input for Gmsh and later exporting the same number of high-quality meshes. This way, geological uncertainty is directly included in the numerical simulations. This study evaluates the impact of the geological uncertainty on thermohydraulic performance of two reservoirs for high-temperature heat storage applications.
Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
Geosci. Model Dev., 17, 3447–3465, https://doi.org/10.5194/gmd-17-3447-2024, https://doi.org/10.5194/gmd-17-3447-2024, 2024
Short summary
Short summary
In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The findings demonstrate that the assimilation of surface soil moisture observation images effectively and reasonably enhances the spatial structure of soil moisture analysis field.
Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante
Geosci. Model Dev., 17, 3175–3197, https://doi.org/10.5194/gmd-17-3175-2024, https://doi.org/10.5194/gmd-17-3175-2024, 2024
Short summary
Short summary
The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils, providing two datasets: one with 2000 soil types, 40 test conditions each (160 000 triaxial tests), and a second with 2048 soil types, 42 test conditions each (172 032 triaxial tests). Each dataset is a 4000×10 matrix applicable for multivariate forecasting and geotechnical simulations. In addition, a new Python code is introduced, empowering researchers to leverage Python packages for NorSand analyses.
Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas
Geosci. Model Dev., 17, 2427–2445, https://doi.org/10.5194/gmd-17-2427-2024, https://doi.org/10.5194/gmd-17-2427-2024, 2024
Short summary
Short summary
Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. A key challenge is the optimal use of high-performance computing environments. The work presented here focuses on a developed open-source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency, and scalability.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev., 17, 2197–2219, https://doi.org/10.5194/gmd-17-2197-2024, https://doi.org/10.5194/gmd-17-2197-2024, 2024
Short summary
Short summary
This work outlines a new solver written in Fortran to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the forward algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev., 17, 1975–1993, https://doi.org/10.5194/gmd-17-1975-2024, https://doi.org/10.5194/gmd-17-1975-2024, 2024
Short summary
Short summary
Previous work has demonstrated that adding geological knowledge to modelling methods creates more accurate and reliable models. Following this reasoning, we added constraints from magma emplacement mechanisms into existing modelling frameworks to improve the 3D characterisation of igneous intrusions. We tested the method on synthetic and real-world case studies, and the results show that our method can reproduce intrusion morphologies with no manual processing and using realistic datasets.
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024, https://doi.org/10.5194/gmd-17-1957-2024, 2024
Short summary
Short summary
It is vital to know the extent and concentration of volcanic ash in the atmosphere during a volcanic eruption. Whilst satellite imagery may give an estimate of the ash right now (assuming no cloud coverage), we also need to know where it will be in the coming hours. This paper presents a method for estimating parameters for a volcanic eruption based on satellite observations of ash in the atmosphere. The software package is open source and applicable to similar inversion scenarios.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
Short summary
Short summary
Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Younghun Kang and Ethan J. Kubatko
Geosci. Model Dev., 17, 1603–1625, https://doi.org/10.5194/gmd-17-1603-2024, https://doi.org/10.5194/gmd-17-1603-2024, 2024
Short summary
Short summary
Models used to simulate the flow of coastal and riverine waters, including flooding, require a geometric representation (or mesh) of geographic features that exhibit a range of disparate spatial scales from large, open waters to small, narrow channels. Representing these features in an accurate way without excessive computational overhead presents a challenge. Here, we develop an automatic mesh generation tool to help address this challenge. Our results demonstrate the efficacy of our approach.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
Short summary
Short summary
Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
Short summary
Short summary
Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
Short summary
Short summary
Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
Short summary
Short summary
Coupled reaction transport modelling is an established and beneficial method for studying natural and synthetic porous material, with applications ranging from industrial processes to natural decompositions in terrestrial environments. Up to now, a framework that explicitly considers the porous structure (e.g. from µ-CT images) for modelling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
Short summary
Short summary
The Voellmy rheology has been widely used for simulating snow and rock avalanches. Recently, a modified version of this rheology was proposed, which turned out to be able to predict the observed long runout of large rock avalanches theoretically. The software MinVoellmy presented here is the first numerical implementation of the modified rheology. It consists of MATLAB and Python classes, where simplicity and parsimony were the design goals.
Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
Short summary
Short summary
This study introduces a new computational framework called Scalable Feature Extraction and Tracking (SCAFET), designed to extract and track features in climate data. SCAFET stands out by using innovative shape-based metrics to identify features without relying on preconceived assumptions about the climate model or mean state. This approach allows more accurate comparisons between different models and scenarios.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
Short summary
Short summary
The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
Short summary
Short summary
This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
Short summary
Short summary
In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
Short summary
Short summary
This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
Short summary
Short summary
Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
Short summary
Short summary
We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
Short summary
Short summary
Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
Short summary
Short summary
Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
Short summary
Short summary
Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
Short summary
Short summary
Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
Short summary
Short summary
To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
EGUsphere, https://doi.org/10.48550/arXiv.2304.06058, https://doi.org/10.48550/arXiv.2304.06058, 2023
Short summary
Short summary
Scientists often use models to study complex processes, like the movement of ice sheets, and compare them to measurements for estimating hard-to-measure quantities. We highlight an approach that ensures accurate results from point data sources (such as height measurements) by evaluating the numerical solution at true point locations. This method improves accuracy, can aid communication between scientists, and is well suited for integration with specialised software that automates the processes.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
Short summary
Short summary
A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Xiaqiong Zhou and Hann-Ming Henry Juang
Geosci. Model Dev., 16, 3263–3274, https://doi.org/10.5194/gmd-16-3263-2023, https://doi.org/10.5194/gmd-16-3263-2023, 2023
Short summary
Short summary
The National Centers for Environmental Prediction Global Forecast System version 16 experienced model instability failures in real-time runs resolved by increasing the minimum thickness depth parameter. Further investigation revealed that the issue was caused by the advection of geopotential heights at the model's layer interfaces. By replacing high-order boundary conditions with zero-gradient boundary conditions for interface-wind reconstruction, the instability was effectively addressed.
Grant T. Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott D. King
Geosci. Model Dev., 16, 3221–3239, https://doi.org/10.5194/gmd-16-3221-2023, https://doi.org/10.5194/gmd-16-3221-2023, 2023
Short summary
Short summary
Due to the increasing availability of high-performance computing over the past few decades, numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously known information to modern methodologies.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
Short summary
Short summary
This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
Short summary
Short summary
We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
Short summary
Short summary
Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
Short summary
Short summary
In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
Short summary
Short summary
This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
Short summary
Short summary
This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
Short summary
Short summary
We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
Short summary
Short summary
In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
Short summary
Short summary
While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
Short summary
Short summary
A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
Short summary
Short summary
Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
Short summary
Short summary
Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
Short summary
Short summary
Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
Short summary
Short summary
Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Cited articles
Alshehri, F. and Abdelrahman, K.: Groundwater resources exploration of Harrat
Khaybar area, northwest Saudi Arabia, using electrical resistivity
tomography, Journal of King Saud University-Science, 33, 101468, https://doi.org/10.1016/j.jksus.2021.101468, 2021. a
Badmus, B. and Olatinsu, O.: Geoelectric mapping and characterization of
limestone deposits of Ewekoro formation, southwestern Nigeria, Journal of
Geology and Mining Research, 1, 008–018, https://academicjournals.org/journal/JGMR/article-full-text-pdf/5FEFE571242 (last access: 30 January 2023), 2009. a
Balay, S., Abhyankar, S., Adams, M. F., Brown, J., Brune, P., Buschelman, K.,
Dalcin, L., Dener, A., Eijkhout, V., Gropp, W. D., Kaushik, D., Knepley,
M. G., May, D. A., McInnes, L. C., Mills, R. T., Munson, T., Rupp, K., Sanan,
P., Smith, B. F., Zampini, S., Zhang, H., and Zhang, H.: PETSc Users
Manual, Tech. Rep. ANL-95/11 – Revision 3.15, Argonne National Laboratory, https://petsc.org/release/docs/manual/manual.pdf (last access: 27 January 2023),
2021. a
Bery, A. A., Saad, R., Mohamad, E. T., Jinmin, M., Azwin, I., Tan, N. A., and
Nordiana, M.: Electrical resistivity and induced polarization data
correlation with conductivity for iron ore exploration, The Electronic
Journal of Geotechnical Engineering, 17, 3223–3233, 2012. a
Blanchy, G., Saneiyan, S., Boyd, J., McLachlan, P., and Binley, A.: ResIPy, an
intuitive open source software for complex geoelectrical inversion/modeling,
Comput. Geosci., 137, 104423, https://doi.org/10.1016/j.cageo.2020.104423, 2020. a
Camporese, M., Cassiani, G., Deiana, R., Salandin, P., and Binley, A.: Coupled
and uncoupled hydrogeophysical inversions using ensemble K alman filter
assimilation of ERT-monitored tracer test data, Water Resour. Res., 51,
3277–3291, 2015. a
Caputo, R., Piscitelli, S., Oliveto, A., Rizzo, E., and Lapenna, V.: The use of
electrical resistivity tomographies in active tectonics: examples from the
Tyrnavos Basin, Greece, J. Geodyn., 36, 19–35, 2003. a
Cockett, R., Kang, S., Heagy, L. J., Pidlisecky, A., and Oldenburg, D. W.:
SimPEG: An open source framework for simulation and gradient based
parameter estimation in geophysical applications, Comput. Geosci.,
85, 142–154, https://doi.org/10.1016/j.cageo.2015.09.015, 2015. a, b, c
Coggon, J.: Electromagnetic and electrical modeling by the finite element
method, Geophysics, 36, 132–155, 1971. a
Dahlin, T.: 2D resistivity surveying for environmental and engineering
applications, First break, 14, https://doi.org/10.3997/1365-2397.1996014, 1996. a
Dahlin, T.: The development of DC resistivity imaging techniques, Comput.
Geosci., 27, 1019–1029, 2001. a
Dahlin, T. and Zhou, B.: A numerical comparison of 2D resistivity imaging with
10 electrode arrays, Geophys. Prospect., 52, 379–398, 2004. a
Das, U. C.: Direct current electric potential computation in an inhomogeneous
and arbitrarily anisotropic layered earthl, Geophys. Prospect., 43,
417–432, https://doi.org/10.1111/j.1365-2478.1995.tb00260.x, 1995. a
Dey, A. and Morrison, H. F.: Resistivity modeling for arbitrarily shaped
three-dimensional structures, Geophysics, 44, 753–780, 1979. a
Ellis, R. and Oldenburg, D.: The pole-pole 3-D Dc-resistivity inverse problem:
a conjugategradient approach, Geophys. J. Int., 119,
187–194, 1994. a
Gabarrón, M., Martínez-Pagán, P., Martínez-Segura, M. A.,
Bueso, M. C., Martínez-Martínez, S., Faz, Á., and Acosta,
J. A.: Electrical resistivity tomography as a support tool for
physicochemical properties assessment of near-surface waste materials in a
mining tailing pond (El Gorguel, SE Spain), Minerals, 10, 559,
https://doi.org/10.3390/min10060559, 2020. a
González-Quirós, A. and Comte, J.-C.: Hydrogeophysical model
calibration and uncertainty analysis via full integration of PEST/PEST++ and
COMSOL, Environ. Modell. Softw., 145, 105183, https://doi.org/10.1016/j.envsoft.2021.105183, 2021. a
Greggio, N., Giambastiani, B., Balugani, E., Amaini, C., and Antonellini, M.:
High-resolution electrical resistivity tomography (ERT) to characterize the
spatial extension of freshwater lenses in a salinized coastal aquifer, Water,
10, 1067, https://doi.org/10.3390/w10081067, 2018. a
Hammond, G. E.: PFLOTRAN, Bitbucket Repository [code], https://bitbucket.org/pflotran/pflotran, last access 27 January 2023. a
Hammond, G. E., Lichtner, P. C., Lu, C., and Mills, R. T.: PFLOTRAN: Reactive
flow & transport code for use on laptops to leadership-class supercomputers,
in: Groundwater Reactive Transport Models, edited by: Zhang, F., Yeh,
G.-T. G., and Parker, J. C., Bentham Science Publishers, 141–159,
https://doi.org/10.2174/978160805306311201010141, 2012. a, b, c
Hammond, G. E., Lichtner, P. C., and Mills, R. T.: Evaluating the performance
of parallel subsurface simulators: An illustrative example with PFLOTRAN,
Water Resour. Res., 50, 208–228, https://doi.org/10.1002/2012WR013483, 2014. a, b, c, d
Hestenes, M. and Stiefel, E.: Methods of conjugate gradients for solving linear
systems, J. Res. Nat. Bur. Stand., 49, 409–436,
https://doi.org/10.6028/jres.049.044, 1952. a
Jahandari, H. and Farquharson, C. G.: A finite-volume solution to the
geophysical electromagnetic forward problem using unstructured grids,
Geophysics, 79, E287–E302, 2014. a
Jaysaval, P., Shantsev, D., and de la Kethulle de Ryhove, S.: Fast multimodel
finite-difference controlled-source electromagnetic simulations based on a
Schur complement approach, Geophysics, 79, E315–E327,
https://doi.org/10.1190/geo2014-0043.1, 2014. a
Jaysaval, P., Hammond, G. E., and Johnson, T. C.: ERT modeling and inversion
using PFLOTRAN v4.0, Zenodo [code and data set], https://doi.org/10.5281/zenodo.6191926, 2022. a
Johnson, T. C., Versteeg, R. J., Ward, A., Day-Lewis, F. D., and Revil, A.:
Improved hydrogeophysical characterization and monitoring through parallel
modeling and inversion of time-domain resistivity andinduced-polarization
data, Geophysics, 75, WA27–WA41, https://doi.org/10.1190/1.3475513, 2010. a, b, c, d, e, f, g, h, i, j
Johnson, T. C., Slater, L. D., Ntarlagiannis, D., Day-Lewis, F. D., and
Elwaseif, M.: Monitoring groundwater-surface water interaction using
time-series and time-frequency analysis of transient three-dimensional
electrical resistivity changes, Water Resour. Res., 48, W07506, https://doi.org/10.1029/2012WR011893, 2012. a
Johnson, T. C., Hammond, G. E., and Chen, X.: PFLOTRAN-E4D: A parallel open
source PFLOTRAN module for simulating time-lapse electrical resistivity
data, Comput. Geosci., 99, 72–80,
https://doi.org/10.1016/j.cageo.2016.09.006, 2017. a
Karypis, G. and Schloegel, K.: ParMetis: Parallel Graph Partitioning and Sparse Matrix Ordering Library, Version 4.0, Tech. Rep., http://glaros.dtc.umn.edu/gkhome/fetch/sw/parmetis/manual.pdf (last access: 27 January 2023), 2013. a
Kessouri, P., Johnson, T., Day-Lewis, F. D., Wang, C., Ntarlagiannis, D., and
Slater, L. D.: Post-remediation geophysical assessment: Investigating
long-term electrical geophysical signatures resulting from bioremediation at
a chlorinated solvent contaminated site, J. Environ. Manage.,
302, 113944, https://doi.org/10.1016/j.jenvman.2021.113944, 2022. a
Lee, T.: An integral equation and its solution for some two-and
three-dimensional problems in resistivity and induced polarization,
Geophys. J. Int., 42, 81–95, 1975. a
Li, Y. and Spitzer, K.: Three-dimensional DC resistivity forward modelling
using finite elements in comparison with finite-difference solutions,
Geophys. J. Int., 151, 924–934, 2002. a
Loke, M., Chambers, J., Rucker, D., Kuras, O., and Wilkinson, P.: Recent
developments in the direct-current geoelectrical imaging method, J.
Appl. Geophys., 95, 135–156, 2013. a
Lysdahl, A. K., Bazin, S., Christensen, C., Ahrens, S., Günther, T., and
Pfaffhuber, A. A.: Comparison between 2D and 3D ERT inversion for engineering
site investigations – a case study from Oslo Harbour, Near Surf. Geophys.,
15, 201–209, 2017. a
Martínez, J., Rey, J., Sandoval, S., Hidalgo, M., and Mendoza, R.:
Geophysical prospecting using ERT and IP techniques to locate Galena veins,
Remote Sensing, 11, 2923, https://doi.org/10.3390/rs11242923, 2019. a
Mboh, C., Huisman, J., Van Gaelen, N., Rings, J., and Vereecken, H.: Coupled
hydrogeophysical inversion of electrical resistances and inflow measurements
for topsoil hydraulic properties under constant head infiltration, Near
Surf. Geophys., 10, 413–426, 2012. a
Méndez-Delgado, S., Gómez-Treviño, E., and Pérez-Flores, M.:
Forward modelling of direct current and low-frequency electromagnetic fields
using integral equations, Geophys. J. Int., 137, 336–352,
1999. a
Meyerhoff, S. B., Maxwell, R. M., Revil, A., Martin, J. B., Karaoulis, M., and
Graham, W. D.: Characterization of groundwater and surface water mixing in a
semiconfined karst aquifer using time-lapse electrical resistivity
tomography, Water Resour. Res., 50, 2566–2585, 2014. a
Mills, R. T., Hammond, G. E., Lichtner, P. C., Sripathi, V., Mahinthakumar, G.,
and Smith, B. F.: Modeling Subsurface Reactive Flows Using Leadership-Class
Computing, in: 5th Annual Conference of Scientific Discovery through Advanced
Computing (SciDAC 2009), J. Phys. Conf.
Ser., 180, 012062, https://doi.org/10.1088/1742-6596/180/1/012062, 2009. a
Nocedal, J. and Wright, S.: Numerical optimization, 2nd edn., Springer Science &
Business Media, 664 pp., ISBN 978-0-387-30303-1, https://doi.org/10.1007/978-0-387-40065-5, 2006. a, b, c
Park, S., Yi, M.-J., Kim, J.-H., and Shin, S. W.: Electrical resistivity
imaging (ERI) monitoring for groundwater contamination in an uncontrolled
landfill, South Korea, J. Appl. Geophys., 135, 1–7, https://doi.org/10.1016/j.jappgeo.2016.07.004, 2016. a
Park, S. K. and Van, G. P.: Inversion of pole-pole data for 3-D resistivity
structure beneath arrays of electrodes, GEOPHYSICS, 56, 951–960,
https://doi.org/10.1190/1.1443128, 1991. a
Penz, S., Chauris, H., Donno, D., and Mehl, C.: Resistivity modelling with
topography, Geophys. J. Int., 194, 1486–1497, 2013. a
Pervago, E., Mousatov, A., and Shevnin, V.: Analytical solution for the
electric potential in arbitrary anisotropic layered media applying the set of
Hankel transforms of integer order, Geophys. Prospect., 54, 651–661,
https://doi.org/10.1111/j.1365-2478.2006.00555.x, 2006. a
Pleasants, M., Neves, F. d. A., Parsekian, A., Befus, K., and Kelleners, T.:
Hydrogeophysical Inversion of Time-Lapse ERT Data to Determine Hillslope
Subsurface Hydraulic Properties, Water Resour. Res., 58,
e2021WR031073, https://doi.org/10.1029/2021WR031073, 2022. a
Revil, A., Karaoulis, M., Johnson, T., and Kemna, A.: Some low-frequency
electrical methods for subsurface characterization and monitoring in
hydrogeology, Hydrogeol. J., 20, 617–658, 2012. a
Richards, K., Revil, A., Jardani, A., Henderson, F., Batzle, M., and Haas, A.:
Pattern of shallow ground water flow at Mount Princeton Hot Springs,
Colorado, using geoelectrical methods, J. Volcanol. Geoth.
Res., 198, 217–232, 2010. a
Rizzo, E., Colella, A., Lapenna, V., and Piscitelli, S.: High-resolution images
of the fault-controlled High Agri Valley basin (Southern Italy) with deep and
shallow electrical resistivity tomographies, Physics and Chemistry of the Earth, Parts A/B/C, 29, 321–327, https://doi.org/10.1016/j.pce.2003.12.002, 2004.
a
Rockhold, M. L., Robinson, J. L., Parajuli, K., Song, X., Zhang, Z., and
Johnson, T. C.: Groundwater characterization and monitoring at a complex
industrial waste site using electrical resistivity imaging, Hydrogeol.
J., 28, 2115–2127, 2020. a
Rosales, R. M., Martínez-Pagan, P., Faz, A., and Moreno-Cornejo, J.:
Environmental monitoring using electrical resistivity tomography (ERT) in the
subsoil of three former petrol stations in SE of Spain, Water Air Soil
Poll., 223, 3757–3773, 2012. a
Rucker, D. F., Myers, D. A., Cubbage, B., Levitt, M. T., Noonan, G. E.,
McNeill, M., Henderson, C., and Lober, R. W.: Surface geophysical
exploration: developing noninvasive tools to monitor past leaks around
Hanford’s tank farms, Environ. Monit. Assess., 185,
995–1010, 2013. a
Schulz, R.: The method of integral equation in the direct current resistivity
method and its accuracy, Journal of Geophysics, 56, 192–200, 1985. a
Singha, K., Johnson, T. C., Day-Lewis, F. D., and Slater, L. D.: Electrical
Imaging for Hydrogeology, The Groundwater Project, Guelph, Ontario, Canada, 74 pp., ISBN 978-1-77470-011-2,
2022. a
Spitzer, K.: A 3-D finite-difference algorithm for DC resistivity modelling
using conjugate gradient methods, Geophys. J. Int., 123,
903–914, 1995. a
Storz, H., Storz, W., and Jacobs, F.: Electrical resistivity tomography to
investigate geological structures of the earth's upper crust, Geophys.
Prospect., 48, 455–472, 2000. a
The HDF Group: Hierarchical Data Format Version 5, The HDF Group [code],
http://www.hdfgroup.org/HDF5 (last access: 27 January 2023), 2022. a
Uhlemann, S., Chambers, J., Falck, W. E., Tirado Alonso, A.,
Fernández González, J. L., and Espín de Gea, A.: Applying
electrical resistivity tomography in ornamental stone mining: challenges and
solutions, Minerals, 8, 491, https://doi.org/10.3390/min8110491, 2018. a
Zhang, J., Mackie, R. L., and Madden, T. R.: 3-D resistivity forward modeling
and inversion using conjugate gradients, Geophysics, 60, 1313–1325, 1995. a
Zhdanov, M. S. and Keller, G. V.: The geoelectrical methods in geophysical
exploration, 2nd edn., in: Methods in geochemistry and geophysics, volume 31, Elsevier, 873 pp., ISBN 978-0444896780, 1994. a
Short summary
We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
We present a robust and highly scalable implementation of numerical forward modeling and...
