Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3421-2021
© Author(s) 2021. 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-14-3421-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
08 Jun 2021
Model description paper |
| 08 Jun 2021
| 08 Jun 2021
Sub3DNet1.0: a deep-learning model for regional-scale 3D subsurface structure mapping
Zhenjiao Jiang
CORRESPONDING AUTHOR
Key Laboratory of Groundwater Resources and Environment, Ministry of
Education, College of Environment and Resources, Jilin University, Changchun, 130021, China
CSIRO Land & Water, Locked Bag 2, Glen Osmond,
SA 5064, Australia
Dirk Mallants
CSIRO Land & Water, Locked Bag 2, Glen Osmond,
SA 5064, Australia
CSIRO Land & Water, Locked Bag 2, Glen Osmond,
SA 5064, Australia
Tim Munday
CSIRO Mineral Resources, Locked Bag 2, Glen Osmond,
SA 5064, Australia
Gregoire Mariethoz
University of Lausanne, Faculty of Geosciences and
Environment, Institute of Earth Surface Dynamics, Lausanne, Switzerland
Luk Peeters
CSIRO Mineral Resources, Locked Bag 2, Glen Osmond,
SA 5064, Australia
Related authors
Zhenjiao Jiang, Dirk Mallants, Luk Peeters, Lei Gao, Camilla Soerensen, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 23, 2561–2580, https://doi.org/10.5194/hess-23-2561-2019, https://doi.org/10.5194/hess-23-2561-2019, 2019
Short summary
Short summary
Paleovalleys often form productive aquifers in the semiarid and arid areas. A methodology based on deep learning is introduced to automatically generate high-resolution 3-D paleovalley maps from low-resolution electrical conductivity data derived from airborne geophysical surveys. It is validated by borehole logs and the surface valley indices that the proposed method in this study provides an effective tool for regional-scale paleovalley mapping and groundwater exploration.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Proc. IAHS, 385, 121–127, https://doi.org/10.5194/piahs-385-121-2024, https://doi.org/10.5194/piahs-385-121-2024, 2024
Short summary
Short summary
This study assesses the impact of climate change on the timing, seasonality and magnitude of mean annual minimum (MAM) flows and annual maximum flows (AMF) in the Volta River basin (VRB). Several climate change projection data are use to simulate river flow under multiple greenhouse gas emission scenarios. Future projections show that AMF could increase with various magnitude but negligible shift in time across the VRB, while MAM could decrease with up to 14 days of delay in occurrence.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data, 16, 731–742, https://doi.org/10.5194/essd-16-731-2024, https://doi.org/10.5194/essd-16-731-2024, 2024
Short summary
Short summary
Modern and fossil pollen data contain precious information for reconstructing the climate and environment of the past. However, these data are only achieved for single locations with no continuity in space. We present here a systematic atlas of 194 digital maps containing the spatial estimation of contemporary pollen presence over Europe. This dataset constitutes a free and ready-to-use tool to study climate, biodiversity, and environment in time and space.
Mathieu Vrac, Denis Allard, Grégoire Mariéthoz, Soulivanh Thao, and Lucas Schmutz
EGUsphere, https://doi.org/10.5194/egusphere-2023-3004, https://doi.org/10.5194/egusphere-2023-3004, 2024
Short summary
Short summary
We aim to combine multiple Global Climate Models (GCMs) to enhance the robustness of future projections. We introduce a novel approach, called "α-pooling", aggregating the Cumulative Distribution Functions (CDFs) of the models into a CDF more aligned with historical data. The new CDFs allow us to perform bias adjustment of all the raw climate simulations at once. Experiments on European temperature and precipitation demonstrate the superiority of this approach over conventional techniques.
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.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
Short summary
Short summary
Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
Short summary
Short summary
Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
Dirk Mallants, John Phalen, and Hef Griffiths
Saf. Nucl. Waste Disposal, 1, 263–264, https://doi.org/10.5194/sand-1-263-2021, https://doi.org/10.5194/sand-1-263-2021, 2021
Short summary
Short summary
In Australia, long-lived ILW from research reactors and radiopharmaceutical production represents the principal waste stream that requires deep geologic disposal. CSIRO and its partners aim to demonstrate the technical feasibility of the long-term safety of borehole disposal in deep geological formations. We will highlight the main findings from the RD&D undertaken so far.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
Short summary
Short summary
This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Jason Bula, Marc-Henri Derron, and Gregoire Mariethoz
Geosci. Instrum. Method. Data Syst., 9, 385–396, https://doi.org/10.5194/gi-9-385-2020, https://doi.org/10.5194/gi-9-385-2020, 2020
Short summary
Short summary
We developed a method to acquire dense point clouds with a low-cost Velodyne Puck lidar system, without using expensive Global Navigation Satellite System (GNSS) positioning or IMU. We mounted the lidar on a motor to continuously change the scan direction, leading to a significant increase in the point cloud density. The system was compared with a more expensive system based on IMU registration and a SLAM algorithm. The alignment between acquisitions with those two systems is within 2 m.
Brady A. Flinchum, Eddie Banks, Michael Hatch, Okke Batelaan, Luk J. M. Peeters, and Sylvain Pasquet
Hydrol. Earth Syst. Sci., 24, 4353–4368, https://doi.org/10.5194/hess-24-4353-2020, https://doi.org/10.5194/hess-24-4353-2020, 2020
Short summary
Short summary
Identifying and quantifying recharge processes linked to ephemeral surface water features is challenging due to their episodic nature. We use a unique combination of well-established near-surface geophysical methods to provide evidence of a surface and groundwater connection in a flat, semi-arid region north of Adelaide, Australia. We show that a combined geophysical approach can provide a unique perspective that can help shape the hydrogeological conceptualization.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 13, 2611–2630, https://doi.org/10.5194/gmd-13-2611-2020, https://doi.org/10.5194/gmd-13-2611-2020, 2020
Short summary
Short summary
Stochastic simulations are key tools to generate complex spatial structures uses as input in geoscientific models. In this paper, we present a new open-source tool that enables to simulate complex structures in a straightforward and efficient manner, based on analogues. The method is tested on a variety of use cases to demonstrate the generality of the framework.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 24, 2841–2854, https://doi.org/10.5194/hess-24-2841-2020, https://doi.org/10.5194/hess-24-2841-2020, 2020
Short summary
Short summary
At subdaily resolution, rain intensity exhibits a strong variability in space and time due to the diversity of processes that produce rain (e.g., frontal storms, mesoscale convective systems and local convection). In this paper we explore a new method to simulate rain type time series conditional to meteorological covariates. Afterwards, we apply stochastic rain type simulation to the downscaling of precipitation of a regional climate model.
Shaoqing Dai, Xiaoman Zheng, Lei Gao, Chengdong Xu, Shudi Zuo, Qi Chen, Xiaohua Wei, and Yin Ren
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-36, https://doi.org/10.5194/bg-2020-36, 2020
Preprint withdrawn
Short summary
Short summary
This paper proposes a method to integrate the advantages of machine learning and spatial statistics, different datasets, and multiple environmental covariates to improve the accuracy of aboveground biomass estimation models, which provides a useful reference for climate change mitigation. This combined method can make full use of data from different sources, and realize the complementary advantages of machine learning and spatial statistics, which has important implications for other fields.
James M. Thornton, Gregoire Mariethoz, Tristan J. Brauchli, and Philip Brunner
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-181, https://doi.org/10.5194/tc-2019-181, 2019
Manuscript not accepted for further review
Short summary
Short summary
Meltwater runoff from steep mountainous terrain holds great societal and ecological importance. Predicting snow dynamics in unmonitored areas and/or under changed climate requires computer simulations. Yet variability in alpine snow patterns poses a considerable challenge. Here we combine existing tools with high-resolution observations to both constrain and quantify the uncertainty in historical simulations. Snowpack evolution was satisfactorily reproduced and uncertainty substantially reduced.
Zhenjiao Jiang, Dirk Mallants, Luk Peeters, Lei Gao, Camilla Soerensen, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 23, 2561–2580, https://doi.org/10.5194/hess-23-2561-2019, https://doi.org/10.5194/hess-23-2561-2019, 2019
Short summary
Short summary
Paleovalleys often form productive aquifers in the semiarid and arid areas. A methodology based on deep learning is introduced to automatically generate high-resolution 3-D paleovalley maps from low-resolution electrical conductivity data derived from airborne geophysical surveys. It is validated by borehole logs and the surface valley indices that the proposed method in this study provides an effective tool for regional-scale paleovalley mapping and groundwater exploration.
Shaoqing Dai, Xiaoman Zheng, Lei Gao, Shudi Zuo, Qi Chen, Xiaohua Wei, and Yin Ren
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-202, https://doi.org/10.5194/bg-2019-202, 2019
Preprint withdrawn
Short summary
Short summary
We propose a low-cost approach that combines machine learning with spatial statistics to construct a regional forest C sequestration map from non-representative sample units. The experimental results demonstrate that the combined methods can improve the accuracy of the C sequestration map. This work provides a useful reference for climate change mitigation and other cases that used non-representative sample units.
Lionel Benoit, Aurelie Gourdon, Raphaël Vallat, Inigo Irarrazaval, Mathieu Gravey, Benjamin Lehmann, Günther Prasicek, Dominik Gräff, Frederic Herman, and Gregoire Mariethoz
Earth Syst. Sci. Data, 11, 579–588, https://doi.org/10.5194/essd-11-579-2019, https://doi.org/10.5194/essd-11-579-2019, 2019
Short summary
Short summary
This dataset provides a collection of 10 cm resolution orthomosaics and digital elevation models of the Gornergletscher glacial system (Switzerland). Raw data have been acquired every 2 weeks by intensive UAV surveys and cover the summer 2017. A careful photogrammetric processing ensures the geometrical coherence of the whole dataset.
Pierre-Olivier Bruna, Julien Straubhaar, Rahul Prabhakaran, Giovanni Bertotti, Kevin Bisdom, Grégoire Mariethoz, and Marco Meda
Solid Earth, 10, 537–559, https://doi.org/10.5194/se-10-537-2019, https://doi.org/10.5194/se-10-537-2019, 2019
Short summary
Short summary
Natural fractures influence fluid flow in subsurface reservoirs. Our research presents a new methodology to predict the arrangement of these fractures in rocks. Contrary to the commonly used statistical models, our approach integrates more geology into the simulation process. The method is simply based on the drawing of images, can be applied to any type of rocks in various geological contexts, and is suited for fracture network prediction in water, geothermal, or hydrocarbon reservoirs.
Qiyu Chen, Gregoire Mariethoz, Gang Liu, Alessandro Comunian, and Xiaogang Ma
Hydrol. Earth Syst. Sci., 22, 6547–6566, https://doi.org/10.5194/hess-22-6547-2018, https://doi.org/10.5194/hess-22-6547-2018, 2018
Short summary
Short summary
One of the critical issues in MPS simulation is the difficulty in obtaining a credible 3-D training image. We propose an MPS-based 3-D reconstruction method on the basis of 2-D cross sections, making 3-D training images unnecessary. The main advantages of this approach are the high computational efficiency and a relaxation of the stationarity assumption. The results, in comparison with previous MPS methods, show better performance in portraying anisotropy characteristics and in CPU cost.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 22, 5919–5933, https://doi.org/10.5194/hess-22-5919-2018, https://doi.org/10.5194/hess-22-5919-2018, 2018
Short summary
Short summary
We propose a method for unsupervised classification of the space–time–intensity structure of weather radar images. The resulting classes are interpreted as rain types, i.e. pools of rain fields with homogeneous statistical properties. Rain types can in turn be used to define stationary periods for further stochastic rainfall modelling. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm.
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
Short summary
Short summary
This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Kashif Mahmud, Gregoire Mariethoz, Andy Baker, and Pauline C. Treble
Hydrol. Earth Syst. Sci., 22, 977–988, https://doi.org/10.5194/hess-22-977-2018, https://doi.org/10.5194/hess-22-977-2018, 2018
Short summary
Short summary
This study explores the relationship between drip water and rainfall in a SW Australian karst, where both intra- and interannual hydrological variations are strongly controlled by seasonal variations in recharge. The hydrological behavior of cave drips is examined at daily resolution with respect to mean discharge and the flow variation. We demonstrate that the analysis of the time series produced by cave drip loggers generates useful hydrogeological information that can be applied generally.
K. Mahmud, G. Mariethoz, A. Baker, P. C. Treble, M. Markowska, and E. McGuire
Hydrol. Earth Syst. Sci., 20, 359–373, https://doi.org/10.5194/hess-20-359-2016, https://doi.org/10.5194/hess-20-359-2016, 2016
Short summary
Short summary
Caves offer a natural inception point to observe both the long-term groundwater recharge and the preferential movement of water through the unsaturated zone of such limestone. In this study, we develop a method that combines automated drip rate logging systems and remote sensing techniques to quantify the infiltration processes within a cave.
L. J. M. Peeters, G. M. Podger, T. Smith, T. Pickett, R. H. Bark, and S. M. Cuddy
Hydrol. Earth Syst. Sci., 18, 3777–3785, https://doi.org/10.5194/hess-18-3777-2014, https://doi.org/10.5194/hess-18-3777-2014, 2014
B. Rogiers, K. Beerten, T. Smeekens, D. Mallants, M. Gedeon, M. Huysmans, O. Batelaan, and A. Dassargues
Hydrol. Earth Syst. Sci., 17, 5155–5166, https://doi.org/10.5194/hess-17-5155-2013, https://doi.org/10.5194/hess-17-5155-2013, 2013
Related subject area
Solid Earth
REHEATFUNQ (REgional HEAT-Flow Uncertainty and aNomaly Quantification) 2.0.1: a model for regional aggregate heat flow distributions and anomaly quantification
A new temperature–photoperiod coupled phenology module in LPJ-GUESS model v4.1: optimizing estimation of terrestrial carbon and water processes
High-precision 1′ × 1′ bathymetric model of Philippine Sea inversed from marine gravity anomalies
Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)
Benchmarking the accuracy of higher order particle methods in geodynamic models of transient flow
Modelling detrital cosmogenic nuclide concentrations during landscape evolution in Cidre v2.0
IMEX_SfloW2D v2: a depth-averaged numerical flow model for volcanic gas–particle flows over complex topographies and water
Simulation of a fully coupled 3D glacial isostatic adjustment – ice sheet model for the Antarctic ice sheet over a glacial cycle
AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling
PySubdiv 1.0: open-source geological modeling and reconstruction by non-manifold subdivision surfaces
Reconstructing tephra fall deposits via ensemble-based data assimilation techniques
ClinoformNet-1.0: stratigraphic forward modeling and deep learning for seismic clinoform delineation
Addressing challenges in uncertainty quantification: the case of geohazard assessments
DeepISMNet: three-dimensional implicit structural modeling with convolutional neural network
Towards automatic finite-element methods for geodynamics via Firedrake
MagmaFOAM-1.0: a modular framework for the simulation of magmatic systems
A global, spherical finite-element model for post-seismic deformation using Abaqus
SMAUG v1.0 – a user-friendly muon simulator for the imaging of geological objects in 3-D
CliffDelineaTool v1.2.0: an algorithm for identifying coastal cliff base and top positions
Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
Structural, petrophysical, and geological constraints in potential field inversion using the Tomofast-x v1.0 open-source code
Spatial agents for geological surface modelling
RHEA v1.0: Enabling fully coupled simulations with hydro-geomechanical heterogeneity
Modelling of faults in LoopStructural 1.0
PALEOSTRIPv1.0 – a user-friendly 3D backtracking software to reconstruct paleo-bathymetries
LoopStructural 1.0: time-aware geological modelling
Analytical solutions for mantle flow in cylindrical and spherical shells
Towards a model for structured mass movements: the OpenLISEM hazard model 2.0a
GO_3D_OBS: the multi-parameter benchmark geomodel for seismic imaging method assessment and next-generation 3D survey design (version 1.0)
PLUME-MoM-TSM 1.0.0: a volcanic column and umbrella cloud spreading model
HydrothermalFoam v1.0: a 3-D hydrothermal transport model for natural submarine hydrothermal systems
Synthetic seismicity distribution in Guerrero–Oaxaca subduction zone, Mexico, and its implications on the role of asperities in Gutenberg–Richter law
A new open-source viscoelastic solid earth deformation module implemented in Elmer (v8.4)
CobWeb 1.0: machine learning toolbox for tomographic imaging
pygeodyn 1.1.0: a Python package for geomagnetic data assimilation
IMEX_SfloW2D 1.0: a depth-averaged numerical flow model for pyroclastic avalanches
A multilayer approach and its application to model a local gravimetric quasi-geoid model over the North Sea: QGNSea V1.0
Development of an automatic delineation of cliff top and toe on very irregular planform coastlines (CliffMetrics v1.0)
Bayesian inference of earthquake rupture models using polynomial chaos expansion
Geodynamic diagnostics, scientific visualisation and StagLab 3.0
SaLEM (v1.0) – the Soil and Landscape Evolution Model (SaLEM) for simulation of regolith depth in periglacial environments
SILLi 1.0: a 1-D numerical tool quantifying the thermal effects of sill intrusions
The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution
Ellipsoids (v1.0): 3-D magnetic modelling of ellipsoidal bodies
Global-scale modelling of melting and isotopic evolution of Earth's mantle: melting modules for TERRA
pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling
Open-source modular solutions for flexural isostasy: gFlex v1.0
FPLUME-1.0: An integral volcanic plume model accounting for ash aggregation
PyXRD v0.6.7: a free and open-source program to quantify disordered phyllosilicates using multi-specimen X-ray diffraction profile fitting
r.randomwalk v1, a multi-functional conceptual tool for mass movement routing
Malte Jörn Ziebarth and Sebastian von Specht
Geosci. Model Dev., 17, 2783–2828, https://doi.org/10.5194/gmd-17-2783-2024, https://doi.org/10.5194/gmd-17-2783-2024, 2024
Short summary
Short summary
Thermal energy from Earth’s active interior constantly dissipates through Earth’s surface. This heat flow is not spatially uniform, and its exact pattern is hard to predict since it depends on crustal and mantle properties, both varying across scales. Our new model REHEATFUNQ addresses this difficulty by treating the fluctuations of heat flow within a region statistically. REHEATFUNQ estimates the regional distribution of heat flow and quantifies known structural signals therein.
Shouzhi Chen, Yongshuo H. Fu, Mingwei Li, Zitong Jia, Yishuo Cui, and Jing Tang
Geosci. Model Dev., 17, 2509–2523, https://doi.org/10.5194/gmd-17-2509-2024, https://doi.org/10.5194/gmd-17-2509-2024, 2024
Short summary
Short summary
It is still a challenge to achieve an accurate simulation of vegetation phenology in the dynamic global vegetation models (DGVMs). We implemented and coupled the spring and autumn phenology models into one of the DGVMs, LPJ-GUESS, and substantially improved the accuracy in capturing the start and end dates of growing seasons. Our study highlights the importance of getting accurate phenology estimations to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.
Dechao An, Jinyun Guo, Xiaotao Chang, Zhenming Wang, Yongjun Jia, Xin Liu, Valery Bondur, and Heping Sun
Geosci. Model Dev., 17, 2039–2052, https://doi.org/10.5194/gmd-17-2039-2024, https://doi.org/10.5194/gmd-17-2039-2024, 2024
Short summary
Short summary
Seafloor topography, as fundamental geoinformation in marine surveying and mapping, plays a crucial role in numerous scientific studies. In this paper, we focus on constructing a high-precision seafloor topography and bathymetry model for the Philippine Sea (5° N–35° N, 120° E–150° E), based on shipborne bathymetric data and marine gravity anomalies, and evaluate the reliability of the model's accuracy.
Octavi Gómez-Novell, Bruno Pace, Francesco Visini, Joanna Faure Walker, and Oona Scotti
Geosci. Model Dev., 16, 7339–7355, https://doi.org/10.5194/gmd-16-7339-2023, https://doi.org/10.5194/gmd-16-7339-2023, 2023
Short summary
Short summary
Knowing the rate at which earthquakes happen along active faults is crucial to characterize the hazard that they pose. We present an approach (Paleoseismic EArthquake CHronologies, PEACH) to correlate and compute seismic histories using paleoseismic data, a type of data that characterizes past seismic activity from the geological record. Our approach reduces the uncertainties of the seismic histories and overall can improve the knowledge on fault rupture behavior for the seismic hazard.
Rene Gassmöller, Juliane Dannberg, Wolfgang Bangerth, Elbridge Gerry Puckett, and Cedric Thieulot
EGUsphere, https://doi.org/10.5194/egusphere-2023-2765, https://doi.org/10.5194/egusphere-2023-2765, 2023
Short summary
Short summary
Numerical models that use simulated particles are a powerful tool for investigating flow in the interior of the Earth, but the accuracy of these models is not fully understood. We here present two new benchmarks, that allow to measure the model accuracy. We then document that better accuracy matters for applications like convection beneath an oceanic plate. Our benchmarks and methods are freely available to help the community develop better models.
Sébastien Carretier, Vincent Regard, Youssouf Abdelhafiz, and Bastien Plazolles
Geosci. Model Dev., 16, 6741–6755, https://doi.org/10.5194/gmd-16-6741-2023, https://doi.org/10.5194/gmd-16-6741-2023, 2023
Short summary
Short summary
We present the development of a code to simulate simultaneously the dynamics of landscapes over geological time and the evolution of the concentration of cosmogenic isotopes in grains throughout their transport from the slopes to the river outlets. This new model makes it possible to study the relationship between the detrital signal of cosmogenic isotope concentration measured in sediment and the erosion--deposition processes in watersheds.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Samantha Engwell
Geosci. Model Dev., 16, 6309–6336, https://doi.org/10.5194/gmd-16-6309-2023, https://doi.org/10.5194/gmd-16-6309-2023, 2023
Short summary
Short summary
We present version 2 of the numerical code IMEX-SfloW2D. With this version it is possible to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). A simulation of the 1883 Krakatau eruption demonstrates the capability of the numerical model to face a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles.
Caroline J. van Calcar, Roderik S. W. van de Wal, Bas Blank, Bas de Boer, and Wouter van der Wal
Geosci. Model Dev., 16, 5473–5492, https://doi.org/10.5194/gmd-16-5473-2023, https://doi.org/10.5194/gmd-16-5473-2023, 2023
Short summary
Short summary
The waxing and waning of the Antarctic ice sheet caused the Earth’s surface to deform, which is stabilizing the ice sheet and mainly determined by the spatially variable viscosity of the mantle. Including this feedback in model simulations led to significant differences in ice sheet extent and ice thickness over the last glacial cycle. The results underline and quantify the importance of including this local feedback effect in ice sheet models when simulating the Antarctic ice sheet evolution.
Baoyi Zhang, Linze Du, Umair Khan, Yongqiang Tong, Lifang Wang, and Hao Deng
Geosci. Model Dev., 16, 3651–3674, https://doi.org/10.5194/gmd-16-3651-2023, https://doi.org/10.5194/gmd-16-3651-2023, 2023
Short summary
Short summary
We propose a Hermite–Birkhoff radial basis function (HRBF) formulation, AdaHRBF, with an adaptive gradient magnitude for continuous 3D stratigraphic potential field (SPF) modeling of multiple stratigraphic interfaces. In the linear system of HRBF interpolants constrained by the scattered on-contact attribute points and off-contact attitude points of a set of strata in 3D space, we add a novel optimization term to iteratively obtain the true gradient magnitude.
Mohammad Moulaeifard, Simon Bernard, and Florian Wellmann
Geosci. Model Dev., 16, 3565–3579, https://doi.org/10.5194/gmd-16-3565-2023, https://doi.org/10.5194/gmd-16-3565-2023, 2023
Short summary
Short summary
In this work, we propose a flexible framework to generate and interact with geological models using explicit surface representations. The essence of the work lies in the determination of the flexible control mesh, topologically similar to the main geological structure, watertight and controllable with few control points, to manage the geological structures. We exploited the subdivision surface method in our work, which is commonly used in the animation and gaming industry.
Leonardo Mingari, Antonio Costa, Giovanni Macedonio, and Arnau Folch
Geosci. Model Dev., 16, 3459–3478, https://doi.org/10.5194/gmd-16-3459-2023, https://doi.org/10.5194/gmd-16-3459-2023, 2023
Short summary
Short summary
Two novel techniques for ensemble-based data assimilation, suitable for semi-positive-definite variables with highly skewed uncertainty distributions such as tephra deposit mass loading, are applied to reconstruct the tephra fallout deposit resulting from the 2015 Calbuco eruption in Chile. The deposit spatial distribution and the ashfall volume according to the analyses are in good agreement with estimations based on field measurements and isopach maps reported in previous studies.
Hui Gao, Xinming Wu, Jinyu Zhang, Xiaoming Sun, and Zhengfa Bi
Geosci. Model Dev., 16, 2495–2513, https://doi.org/10.5194/gmd-16-2495-2023, https://doi.org/10.5194/gmd-16-2495-2023, 2023
Short summary
Short summary
We propose a workflow to automatically generate synthetic seismic data and corresponding stratigraphic labels (e.g., clinoform facies, relative geologic time, and synchronous horizons) by geological and geophysical forward modeling. Trained with only synthetic datasets, our network works well to accurately and efficiently predict clinoform facies in 2D and 3D field seismic data. Such a workflow can be easily extended for other geological and geophysical scenarios in the future.
Ibsen Chivata Cardenas, Terje Aven, and Roger Flage
Geosci. Model Dev., 16, 1601–1615, https://doi.org/10.5194/gmd-16-1601-2023, https://doi.org/10.5194/gmd-16-1601-2023, 2023
Short summary
Short summary
We discuss challenges in uncertainty quantification for geohazard assessments. The challenges arise from limited data and the one-off nature of geohazard features. The challenges include the credibility of predictions, input uncertainty, and assumptions’ impact. Considerations to increase credibility of the quantification are provided. Crucial tasks in the quantification are the exhaustive scrutiny of the background knowledge coupled with the assessment of deviations of assumptions made.
Zhengfa Bi, Xinming Wu, Zhaoliang Li, Dekuan Chang, and Xueshan Yong
Geosci. Model Dev., 15, 6841–6861, https://doi.org/10.5194/gmd-15-6841-2022, https://doi.org/10.5194/gmd-15-6841-2022, 2022
Short summary
Short summary
We present an implicit modeling method based on deep learning to produce a geologically valid and structurally compatible model from unevenly sampled structural data. Trained with automatically generated synthetic data with realistic features, our network can efficiently model geological structures without the need to solve large systems of mathematical equations, opening new opportunities for further leveraging deep learning to improve modeling capacity in many Earth science applications.
D. Rhodri Davies, Stephan C. Kramer, Sia Ghelichkhan, and Angus Gibson
Geosci. Model Dev., 15, 5127–5166, https://doi.org/10.5194/gmd-15-5127-2022, https://doi.org/10.5194/gmd-15-5127-2022, 2022
Short summary
Short summary
Firedrake is a state-of-the-art system that automatically generates highly optimised code for simulating finite-element (FE) problems in geophysical fluid dynamics. It creates a separation of concerns between employing the FE method and implementing it. Here, we demonstrate the applicability and benefits of Firedrake for simulating geodynamical flows, with a focus on the slow creeping motion of Earth's mantle over geological timescales, which is ultimately the engine driving our dynamic Earth.
Federico Brogi, Simone Colucci, Jacopo Matrone, Chiara Paola Montagna, Mattia De' Michieli Vitturi, and Paolo Papale
Geosci. Model Dev., 15, 3773–3796, https://doi.org/10.5194/gmd-15-3773-2022, https://doi.org/10.5194/gmd-15-3773-2022, 2022
Short summary
Short summary
Computer simulations play a fundamental role in understanding volcanic phenomena. The growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques as well as optimizations. MagmaFOAM is a newly developed library that allows for maximum flexibility for solving multiphase volcanic flows and promotes collaborative work for in-house and community model development, testing, and comparison.
Grace A. Nield, Matt A. King, Rebekka Steffen, and Bas Blank
Geosci. Model Dev., 15, 2489–2503, https://doi.org/10.5194/gmd-15-2489-2022, https://doi.org/10.5194/gmd-15-2489-2022, 2022
Short summary
Short summary
We present a finite-element model of post-seismic solid Earth deformation built in the software package Abaqus for the purpose of calculating post-seismic deformation in the far field of major earthquakes. The model is benchmarked against an existing open-source post-seismic model demonstrating good agreement. The advantage over existing models is the potential for simple modification to include 3-D Earth structure, non-linear rheologies and alternative or multiple sources of stress change.
Alessandro Lechmann, David Mair, Akitaka Ariga, Tomoko Ariga, Antonio Ereditato, Ryuichi Nishiyama, Ciro Pistillo, Paola Scampoli, Mykhailo Vladymyrov, and Fritz Schlunegger
Geosci. Model Dev., 15, 2441–2473, https://doi.org/10.5194/gmd-15-2441-2022, https://doi.org/10.5194/gmd-15-2441-2022, 2022
Short summary
Short summary
Muon tomography is a technology that is used often in geoscientific research. The know-how of data analysis is, however, still possessed by physicists who developed this technology. This article aims at providing geoscientists with the necessary tools to perform their own analyses. We hope that a lower threshold to enter the field of muon tomography will allow more geoscientists to engage with muon tomography. SMAUG is set up in a modular way to allow for its own modules to work in between.
Zuzanna M. Swirad and Adam P. Young
Geosci. Model Dev., 15, 1499–1512, https://doi.org/10.5194/gmd-15-1499-2022, https://doi.org/10.5194/gmd-15-1499-2022, 2022
Short summary
Short summary
Cliff base and top lines that delimit coastal cliff faces are usually manually digitized based on maps, aerial photographs, terrain models, etc. However, manual mapping is time consuming and depends on the mapper's decisions and skills. To increase the objectivity and efficiency of cliff mapping, we developed CliffDelineaTool, an algorithm that identifies cliff base and top positions along cross-shore transects using elevation and slope characteristics.
Holly Kyeore Han, Natalya Gomez, and Jeannette Xiu Wen Wan
Geosci. Model Dev., 15, 1355–1373, https://doi.org/10.5194/gmd-15-1355-2022, https://doi.org/10.5194/gmd-15-1355-2022, 2022
Short summary
Short summary
Interactions between ice sheets, sea level and the solid Earth occur over a range of timescales from years to tens of thousands of years. This requires coupled ice-sheet–sea-level models to exchange information frequently, leading to a quadratic increase in computation time with the number of model timesteps. We present a new sea-level model algorithm that allows coupled models to improve the computational feasibility and precisely capture short-term interactions within longer simulations.
Jérémie Giraud, Vitaliy Ogarko, Roland Martin, Mark Jessell, and Mark Lindsay
Geosci. Model Dev., 14, 6681–6709, https://doi.org/10.5194/gmd-14-6681-2021, https://doi.org/10.5194/gmd-14-6681-2021, 2021
Short summary
Short summary
We review different techniques to model the Earth's subsurface from geophysical data (gravity field anomaly, magnetic field anomaly) using geological models and measurements of the rocks' properties. We show examples of application using idealised examples reproducing realistic features and provide theoretical details of the open-source algorithm we use.
Eric A. de Kemp
Geosci. Model Dev., 14, 6661–6680, https://doi.org/10.5194/gmd-14-6661-2021, https://doi.org/10.5194/gmd-14-6661-2021, 2021
Short summary
Short summary
This is a proof of concept and review paper of spatial agents, with initial research focusing on geomodelling. The results may be of interest to others working on complex regional geological modelling with sparse data. Structural agent-based swarming behaviour is key to advancing this field. The study provides groundwork for research in structural geology 3D modelling with spatial agents. This work was done with NetLogo, a free agent modelling platform used mostly for teaching complex systems.
José M. Bastías Espejo, Andy Wilkins, Gabriel C. Rau, and Philipp Blum
Geosci. Model Dev., 14, 6257–6272, https://doi.org/10.5194/gmd-14-6257-2021, https://doi.org/10.5194/gmd-14-6257-2021, 2021
Short summary
Short summary
The hydraulic and mechanical properties of the subsurface are inherently heterogeneous. RHEA is a simulator that can perform couple hydro-geomechanical processes in heterogeneous porous media with steep gradients. RHEA is able to fully integrate spatial heterogeneity, allowing allocation of distributed hydraulic and geomechanical properties at mesh element level. RHEA is a valuable tool that can simulate problems considering realistic heterogeneity inherent to geologic formations.
Lachlan Grose, Laurent Ailleres, Gautier Laurent, Guillaume Caumon, Mark Jessell, and Robin Armit
Geosci. Model Dev., 14, 6197–6213, https://doi.org/10.5194/gmd-14-6197-2021, https://doi.org/10.5194/gmd-14-6197-2021, 2021
Short summary
Short summary
Fault discontinuities in rock packages represent the plane where two blocks of rock have moved. They are challenging to incorporate into geological models because the geometry of the faulted rock units are defined by not only the location of the discontinuity but also the kinematics of the fault. In this paper, we outline a structural geology framework for incorporating faults into geological models by directly incorporating kinematics into the mathematical framework of the model.
Florence Colleoni, Laura De Santis, Enrico Pochini, Edy Forlin, Riccardo Geletti, Giuseppe Brancatelli, Magdala Tesauro, Martina Busetti, and Carla Braitenberg
Geosci. Model Dev., 14, 5285–5305, https://doi.org/10.5194/gmd-14-5285-2021, https://doi.org/10.5194/gmd-14-5285-2021, 2021
Short summary
Short summary
PALEOSTRIP has been developed in the framework of past Antarctic ice sheet reconstructions for periods when bathymetry around Antarctica differed substantially from today. It has been designed for users with no knowledge of numerical modelling and allows users to switch on and off the processes involved in backtracking and backstripping. Applications are broad, and it can be used to restore any continental margin bathymetry or sediment thickness and to perform basin analysis.
Lachlan Grose, Laurent Ailleres, Gautier Laurent, and Mark Jessell
Geosci. Model Dev., 14, 3915–3937, https://doi.org/10.5194/gmd-14-3915-2021, https://doi.org/10.5194/gmd-14-3915-2021, 2021
Short summary
Short summary
LoopStructural is an open-source 3D geological modelling library with a model design allowing for multiple different algorithms to be used for comparison for the same geology. Geological structures are modelled using structural geology concepts and techniques, allowing for complex structures such as overprinted folds and faults to be modelled. In the paper, we demonstrate automatically generating a 3-D model from map2loop-processed geological survey data of the Flinders Ranges, South Australia.
Stephan C. Kramer, D. Rhodri Davies, and Cian R. Wilson
Geosci. Model Dev., 14, 1899–1919, https://doi.org/10.5194/gmd-14-1899-2021, https://doi.org/10.5194/gmd-14-1899-2021, 2021
Short summary
Short summary
Computational models of Earth's mantle require rigorous verification and validation. Analytical solutions of the underlying Stokes equations provide a method to verify that these equations are accurately solved for. However, their derivation in spherical and cylindrical shell domains with physically relevant boundary conditions is involved. This paper provides a number of solutions. They are provided in a Python package (Assess) and their use is demonstrated in a convergence study with Fluidity.
Bastian van den Bout, Theo van Asch, Wei Hu, Chenxiao X. Tang, Olga Mavrouli, Victor G. Jetten, and Cees J. van Westen
Geosci. Model Dev., 14, 1841–1864, https://doi.org/10.5194/gmd-14-1841-2021, https://doi.org/10.5194/gmd-14-1841-2021, 2021
Short summary
Short summary
Landslides, debris flows and other types of dense gravity-driven flows threaten livelihoods around the globe. Understanding the mechanics of these flows can be crucial for predicting their behaviour and reducing disaster risk. Numerical models assume that the solids and fluids of the flow are unstructured. The newly presented model captures the internal structure during movement. This important step can lead to more accurate predictions of landslide movement.
Andrzej Górszczyk and Stéphane Operto
Geosci. Model Dev., 14, 1773–1799, https://doi.org/10.5194/gmd-14-1773-2021, https://doi.org/10.5194/gmd-14-1773-2021, 2021
Short summary
Short summary
We present the 3D multi-parameter synthetic geomodel of the subduction zone, as well as the workflow designed to implement all of its components. The model contains different geological structures of various scales and complexities. It is intended to serve as a tool for the geophysical community to validate imaging approaches, design acquisition techniques, estimate uncertainties, benchmark computing approaches, etc.
Mattia de' Michieli Vitturi and Federica Pardini
Geosci. Model Dev., 14, 1345–1377, https://doi.org/10.5194/gmd-14-1345-2021, https://doi.org/10.5194/gmd-14-1345-2021, 2021
Short summary
Short summary
Here, we present PLUME-MoM-TSM, a volcanic plume model that allows us to quantify the formation of aggregates during the rise of the plume, model the phase change of water, and include the possibility to simulate the initial spreading of the tephra umbrella cloud intruding from the volcanic column into the atmosphere. The model is first applied to the 2015 Calbuco eruption (Chile) and provides an analytical relationship between the upwind spreading and some characteristic of the volcanic column.
Zhikui Guo, Lars Rüpke, and Chunhui Tao
Geosci. Model Dev., 13, 6547–6565, https://doi.org/10.5194/gmd-13-6547-2020, https://doi.org/10.5194/gmd-13-6547-2020, 2020
Short summary
Short summary
We present the 3-D hydro-thermo-transport model HydrothermalFoam v1.0, which we designed to provide the marine geosciences community with an easy-to-use and state-of-the-art tool for simulating mass and energy transport in submarine hydrothermal systems. HydrothermalFoam is based on the popular open-source platform OpenFOAM, comes with a number of tutorials, and is published under the GNU General Public License v3.0.
Marisol Monterrubio-Velasco, F. Ramón Zúñiga, Quetzalcoatl Rodríguez-Pérez, Otilio Rojas, Armando Aguilar-Meléndez, and Josep de la Puente
Geosci. Model Dev., 13, 6361–6381, https://doi.org/10.5194/gmd-13-6361-2020, https://doi.org/10.5194/gmd-13-6361-2020, 2020
Short summary
Short summary
The Mexican subduction zone along the Pacific coast is one of the most active seismic zones in the world, where every year larger-magnitude earthquakes shake huge inland cities such as Mexico City. In this work, we use TREMOL (sThochastic Rupture Earthquake ModeL) to simulate the seismicity observed in this zone. Our numerical results reinforce the hypothesis that in some subduction regions single asperities are responsible for producing the observed seismicity.
Thomas Zwinger, Grace A. Nield, Juha Ruokolainen, and Matt A. King
Geosci. Model Dev., 13, 1155–1164, https://doi.org/10.5194/gmd-13-1155-2020, https://doi.org/10.5194/gmd-13-1155-2020, 2020
Short summary
Short summary
We present a newly developed flat-earth model, Elmer/Earth, for viscoelastic treatment of solid earth deformation under ice loads. Unlike many previous approaches with proprietary software, this model is based on the open-source FEM code Elmer, with the advantage for scientists to apply and alter the model without license constraints. The new-generation full-stress ice-sheet model Elmer/Ice shares the same code base, enabling future coupled ice-sheet–glacial-isostatic-adjustment simulations.
Swarup Chauhan, Kathleen Sell, Wolfram Rühaak, Thorsten Wille, and Ingo Sass
Geosci. Model Dev., 13, 315–334, https://doi.org/10.5194/gmd-13-315-2020, https://doi.org/10.5194/gmd-13-315-2020, 2020
Short summary
Short summary
We present CobWeb 1.0, a graphical user interface for analysing tomographic images of geomaterials. CobWeb offers different machine learning techniques for accurate multiphase image segmentation and visualizing material specific parameters such as pore size distribution, relative porosity and volume fraction. We demonstrate a novel approach of dual filtration and dual segmentation to eliminate edge enhancement artefact in synchrotron-tomographic datasets and provide the computational code.
Loïc Huder, Nicolas Gillet, and Franck Thollard
Geosci. Model Dev., 12, 3795–3803, https://doi.org/10.5194/gmd-12-3795-2019, https://doi.org/10.5194/gmd-12-3795-2019, 2019
Short summary
Short summary
The pygeodyn package is a geomagnetic data assimilation tool written in Python. It gives access to the Earth's core flow dynamics, controlled by geomagnetic observations, by means of a reduced numerical model anchored to geodynamo simulation statistics. It aims to provide the community with a user-friendly and tunable data assimilation algorithm. It can be used for education, geomagnetic model production or tests in conjunction with webgeodyn, a set of visualization tools for geomagnetic models.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Giacomo Lari, and Alvaro Aravena
Geosci. Model Dev., 12, 581–595, https://doi.org/10.5194/gmd-12-581-2019, https://doi.org/10.5194/gmd-12-581-2019, 2019
Short summary
Short summary
Pyroclastic avalanches are a type of granular flow generated at active volcanoes by different mechanisms, including the collapse of steep pyroclastic deposits (e.g., scoria and ash cones) and fountaining during moderately explosive eruptions. We present IMEX_SfloW2D, a depth-averaged flow model describing the granular mixture as a single-phase granular fluid. Benchmark cases and preliminary application to the simulation of the 11 February pyroclastic avalanche at Mt. Etna (Italy) are shown.
Yihao Wu, Zhicai Luo, Bo Zhong, and Chuang Xu
Geosci. Model Dev., 11, 4797–4815, https://doi.org/10.5194/gmd-11-4797-2018, https://doi.org/10.5194/gmd-11-4797-2018, 2018
Short summary
Short summary
A multilayer approach is parameterized for model development, and the multiple layers are located at different depths beneath the Earth’s surface. This method may be beneficial for gravity/manget field modeling, which may outperform the traditional single-layer approach.
Andres Payo, Bismarck Jigena Antelo, Martin Hurst, Monica Palaseanu-Lovejoy, Chris Williams, Gareth Jenkins, Kathryn Lee, David Favis-Mortlock, Andrew Barkwith, and Michael A. Ellis
Geosci. Model Dev., 11, 4317–4337, https://doi.org/10.5194/gmd-11-4317-2018, https://doi.org/10.5194/gmd-11-4317-2018, 2018
Short summary
Short summary
We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a digital elevation model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain.
Hugo Cruz-Jiménez, Guotu Li, Paul Martin Mai, Ibrahim Hoteit, and Omar M. Knio
Geosci. Model Dev., 11, 3071–3088, https://doi.org/10.5194/gmd-11-3071-2018, https://doi.org/10.5194/gmd-11-3071-2018, 2018
Short summary
Short summary
One of the most important challenges seismologists and earthquake engineers face is reliably estimating ground motion in an area prone to large damaging earthquakes. This study aimed at better understanding the relationship between characteristics of geological faults (e.g., hypocenter location, rupture size/location, etc.) and resulting ground motion, via statistical analysis of a rupture simulation model. This study provides important insight on ground-motion responses to geological faults.
Fabio Crameri
Geosci. Model Dev., 11, 2541–2562, https://doi.org/10.5194/gmd-11-2541-2018, https://doi.org/10.5194/gmd-11-2541-2018, 2018
Short summary
Short summary
Firstly, this study acts as a compilation of key geodynamic diagnostics and describes how to automatise them for a more efficient scientific procedure. Secondly, it outlines today's key pitfalls of scientific visualisation and provides means to circumvent them with, for example, a novel set of fully scientific colour maps. Thirdly, it introduces StagLab 3.0, a software that applies such fully automated diagnostics and state-of-the-art visualisation in the blink of an eye.
Michael Bock, Olaf Conrad, Andreas Günther, Ernst Gehrt, Rainer Baritz, and Jürgen Böhner
Geosci. Model Dev., 11, 1641–1652, https://doi.org/10.5194/gmd-11-1641-2018, https://doi.org/10.5194/gmd-11-1641-2018, 2018
Short summary
Short summary
We introduce the Soil and
Landscape Evolution Model (SaLEM) for the prediction of soil parent material evolution following a lithologically differentiated approach. The GIS tool is working within the software framework SAGA GIS. Weathering, erosion and transport functions are calibrated using extrinsic and intrinsic parameter data. First results indicate that our approach shows evidence for the spatiotemporal prediction of soil parental material properties.
Karthik Iyer, Henrik Svensen, and Daniel W. Schmid
Geosci. Model Dev., 11, 43–60, https://doi.org/10.5194/gmd-11-43-2018, https://doi.org/10.5194/gmd-11-43-2018, 2018
Short summary
Short summary
Igneous intrusions in sedimentary basins have a profound effect on the thermal structure of the hosting sedimentary rocks. In this paper, we present a user-friendly 1-D FEM-based tool, SILLi, that calculates the thermal effects of sill intrusions on the enclosing sedimentary stratigraphy. The motivation is to make a standardized numerical toolkit openly available that can be widely used by scientists with different backgrounds to test the effects of magmatic bodies in a wide variety of settings.
Charles M. Shobe, Gregory E. Tucker, and Katherine R. Barnhart
Geosci. Model Dev., 10, 4577–4604, https://doi.org/10.5194/gmd-10-4577-2017, https://doi.org/10.5194/gmd-10-4577-2017, 2017
Short summary
Short summary
Rivers control the movement of sediment and nutrients across Earth's surface. Understanding how rivers change through time is important for mitigating natural hazards and predicting Earth's response to climate change. We develop a new computer model for predicting how rivers cut through sediment and rock. Our model is designed to be joined with models of flooding, landslides, vegetation change, and other factors to provide a comprehensive toolbox for predicting changes to the landscape.
Diego Takahashi and Vanderlei C. Oliveira Jr.
Geosci. Model Dev., 10, 3591–3608, https://doi.org/10.5194/gmd-10-3591-2017, https://doi.org/10.5194/gmd-10-3591-2017, 2017
Short summary
Short summary
Ellipsoids are the only bodies for which the self-demagnetization can be treated analytically. This property is useful for modelling compact orebodies having high susceptibility. We present a review of the magnetic modelling of ellipsoids, propose a way of determining the isotropic susceptibility above which the self-demagnetization must be considered, and discuss the ambiguity between confocal ellipsoids, as well as provide a set of routines to model the magnetic field produced by ellipsoids.
Hein J. van Heck, J. Huw Davies, Tim Elliott, and Don Porcelli
Geosci. Model Dev., 9, 1399–1411, https://doi.org/10.5194/gmd-9-1399-2016, https://doi.org/10.5194/gmd-9-1399-2016, 2016
Short summary
Short summary
Currently, extensive geochemical databases of surface observations exist, but satisfying explanations of underlying mantle processes are lacking. We have implemented a new way to track both bulk compositions and concentrations of trace elements in a mantle convection code. In our model, chemical fractionation happens at evolving melting zones. We compare our results to a semi-analytical theory relating observed arrays of correlated Pb isotope compositions to melting age distributions.
J. Florian Wellmann, Sam T. Thiele, Mark D. Lindsay, and Mark W. Jessell
Geosci. Model Dev., 9, 1019–1035, https://doi.org/10.5194/gmd-9-1019-2016, https://doi.org/10.5194/gmd-9-1019-2016, 2016
Short summary
Short summary
We often obtain knowledge about the subsurface in the form of structural geological models, as a basis for subsurface usage or resource extraction. Here, we provide a modelling code to construct such models on the basis of significant deformational events in geological history, encapsulated in kinematic equations. Our methods simplify complex dynamic processes, but enable us to evaluate how events interact, and finally how certain we are about predictions of structures in the subsurface.
A. D. Wickert
Geosci. Model Dev., 9, 997–1017, https://doi.org/10.5194/gmd-9-997-2016, https://doi.org/10.5194/gmd-9-997-2016, 2016
Short summary
Short summary
Earth's lithosphere bends beneath surface loads, such as ice, sediments, and mountain belts. The pattern of this bending, or flexural isostatic response, is a function of both the loads and the spatially variable strength of the lithosphere. gFlex is an easy-to-use program to calculate flexural isostastic response, and may be used to better understand how ice sheets, glaciers, large lakes, sedimentary basins, volcanoes, and other surface loads interact with the solid Earth.
A. Folch, A. Costa, and G. Macedonio
Geosci. Model Dev., 9, 431–450, https://doi.org/10.5194/gmd-9-431-2016, https://doi.org/10.5194/gmd-9-431-2016, 2016
Short summary
Short summary
We present FPLUME-1.0, a steady-state 1-D cross-section-averaged eruption column model based on the buoyant plume theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in presence of liquid water or ice.
M. Dumon and E. Van Ranst
Geosci. Model Dev., 9, 41–57, https://doi.org/10.5194/gmd-9-41-2016, https://doi.org/10.5194/gmd-9-41-2016, 2016
Short summary
Short summary
This paper presents a FOSS model called PyXRD used to improve the quantification of complex mixed-layer phyllosilicate assemblages using X-ray diffraction. The novelty of this model is the ab initio incorporation of the multi-specimen method, making it possible to share phases and their parameters across multiple specimens. We present results from a comparison of PyXRD with Sybilla v2.2.2 and a number of theoretical experiments illustrating the use of the multi-specimen set-up.
M. Mergili, J. Krenn, and H.-J. Chu
Geosci. Model Dev., 8, 4027–4043, https://doi.org/10.5194/gmd-8-4027-2015, https://doi.org/10.5194/gmd-8-4027-2015, 2015
Short summary
Short summary
r.randomwalk is a flexible and multi-functional open-source GIS tool for simulating the propagation of mass movements. Mass points are routed from given release pixels through a digital elevation model until a defined break criterion is reached. In contrast to existing tools, r.randomwalk includes functionalities to account for parameter uncertainties, and it offers built-in functions for validation and visualization. We show the key functionalities of r.randomwalk for three test areas.
Cited articles
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M.,
Ghemawat, S., Irving, G., and Isard, M.: Tensorflow: a system for large-scale
machine learning, 12th USENIX Symposium on Operating Systems Design and Implementation, 265–283, 2016.
Alley, N., Ckarjet, T., Macphail, M., and Truswell, E.: Sedimentary infillings
and development of major Tertiary palaeodrainage systems of south-central
Australia, in: Palaeoweathering, palaeosurfaces and related continental
deposits, John Wiley and Sons, Hoboken, US, 73, 337, 2009.
Amit, S. N. K. B., Shiraishi, S., Inoshita, T., and Aoki, Y.: Analysis of
satellite images for disaster detection, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 5189–5192, 2016.
Davis, A., Macaulay, S., Munday, T., Sorensen, C., Shudra, J., and
Ibrahimi, T.: Uncovering the groundwater resource potential of Murchison
Region in Western Australia through targeted application of airborne
electromagnetics, ASEG Extended Abstracts, 2016, 1–6, 2016.
de Marsily, G., Delay, F., Gonçalvès, J., Renard, P., Teles, V., and Violette, S.: Dealing with spatial heterogeneity, Hydrogeol. J., 13, 161–183, 2005.
Dodds, S. and Sampson, L.: The Sustainability of Water Resources in the Anangu Pitjantjatjara Lands, South Australia, Department for Water Resources, Adelaide, 2000.
Felletti, F., Bersezio, R., and Giudici, M.: Geostatistical simulation and numerical upscaling, to model ground-water flow in a sandy-gravel, braided river, aquifer analogue, J. Sediment. Res., 76, 1215–1229, 2006.
Gallant, J., Dowling, T., and Austin, J.: Multi-resolution Valley Bottom Flatness (MrVBF), v3, CSIRO, Data Collection, https://doi.org/10.4225/08/5701C885AB4FE, 2012.
Gallant, J. C. and Dowling, T. I.: A multiresolution index of valley bottom
flatness for mapping depositional areas, Water Resour. Res., 39, 1347, https://doi.org/10.1029/2002WR001426,
2003.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D.,
Ozair, S., Courville, A., and Bengio, Y.: Generative adversarial nets, arXiv preprint,
2672–2680, 2014.
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., and Cai, J.: Recent advances in convolutional neural networks, Pattern Recogn., 77, 354–377, 2018.
Hinton, G. E. and Salakhutdinov, R. R.: Reducing the dimensionality of data with neural networks, 313, Science,
504–507, 2006.
Hou, B. and Mauger, A.: How well does remote sensing aid palaeochannel identification?-an example from the Harris Greenstone Belt, SA, MESA J., 38, 46–52, 2005.
Hou, B., Frakes, L., Alley, N., Stamoulis, V., and Rowett, A.: Geoscientific
signatures of Tertiary palaeochannels and their significance for mineral
exploration in the Gawler Craton region, MESA J., 19, 36–39, 2000.
Hou, B., Frakes, L., Sandiford, M., Worrall, L., Keeling, J., and Alley, N.: Cenozoic Eucla Basin and associated palaeovalleys, southern Australia – climatic and tectonic influences on landscape evolution, sedimentation and heavy mineral accumulation, Sediment. Geol., 203, 112–130, 2008.
Høyer, A.-S., Jørgensen, F., Sandersen, P., Viezzoli, A., and Møller, I.: 3D geological modelling of a complex buried-valley network delineated from borehole and AEM data, J. Appl. Geophys., 122, 94–102, 2015.
Hu, L. and Chugunova, T.: Multiple-point geostatistics for modeling subsurface
heterogeneity: A comprehensive review, Water Resour. Res., 44, W11413, https://doi.org/10.1029/2008WR006993,
2008.
Jiang, Z.: A deep learning model for regional-scale 3D subsurface structure mapping, Harvard Dataverse, V1, https://doi.org/10.7910/DVN/DDEIUV, 2020.
Jiang, Z., Mallants, D., Peeters, L., Gao, L., Soerensen, C., and Mariethoz, G.: High-resolution paleovalley classification from airborne electromagnetic imaging and deep neural network training using digital elevation model data, Hydrol. Earth Syst. Sci., 23, 2561–2580, https://doi.org/10.5194/hess-23-2561-2019, 2019.
Jørgensen, F., Lykke-Andersen, H., Sandersen, P. B., Auken, E., and Nørmark, E.: Geophysical investigations of buried Quaternary valleys in Denmark: an integrated application of transient electromagnetic soundings, reflection seismic surveys and exploratory drillings, J. Appl. Geophys., 53, 215–228, 2003.
Kingma, D. P. and Ba, J.: Adam: A method for stochastic optimization, arXiv preprint, arXiv:1412.6980, 2014.
Kingma, D. P. and Welling, M.: Auto-encoding variational bayes, arXiv preprint, arXiv:1312.6114, 2013.
Kitanidis, P. K.: Introduction to Geostatistics: Applications in Hydrogeology,
Cambridge University Press, Cambridge, UK, 1997.
Korus, J. T., Joeckel, R. M., Divine, D. P., and Abraham, J. D.: Three-dimensional architecture and hydrostratigraphy of cross-cutting buried valleys using airborne electromagnetics, glaciated Central Lowlands, Nebraska, USA, Sedimentology, 64, 553–581, 2017.
Krapf, C., Costar, A., Stoian, L., Keppel, M., Gordon, G., Inverarity, L., Love, A., and Munday, T.: A sniff of the ocean in the Miocene at the foothills of the Musgrave Ranges–unravelling the evolution of the Lindsay East Palaeovalley, MESA J., 90, 4–22, 2019.
Kullback, S. and Leibler, R. A.: On information and sufficiency, Ann. Math. Stat., 22, 79–86, 1951.
Laloy, E., Hérault, R., Jacques, D., and Linde, N.: Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network, Water Resour. Res., 54, 381–406, 2018.
Längkvist, M., Kiselev, A., Alirezaie, M., and Loutfi, A.: Classification
and segmentation of satellite orthoimagery using convolutional neural
networks, Remote Sens., 8, 329, https://doi.org/10.3390/rs8040329, 2016.
Lee, S.-Y., Carle, S. F., and Fogg, G. E.: Geologic heterogeneity and a comparison of two geostatistical models: Sequential Gaussian and transition probability-based geostatistical simulation, Adv. Water Resour., 30, 1914–1932, 2007.
Magee, J. W.: Palaeovalley groundwater resources in arid and
semi-arid Australia: A literature review, Geoscience Australia, Record 2009/03, Commonwealth of Australia,
2009.
Marcais, J. and de Dreuzy, J. R.: Prospective Interest of Deep Learning for Hydrological Inference, Groundwater, 55, 688–692, 2017.
Mariethoz, G. and Caers, J.: Multiple-point geostatistics: stochastic modeling
with training images, John Wiley and Sons, Hoboken, US, 2014.
Mey, J., Scherler, D., Zeilinger, G., and Strecker, M. R.: Estimating the fill
thickness and bedrock topography in intermontane valleys using artificial
neural networks, J. Geophys. Res.-Earth, 120, 1301–1320, https://doi.org/10.1002/2014JF003270, 2015.
Mousavi, S. M. and Beroza, G. C.: A Machine-Learning Approach for Earthquake
Magnitude Estimation, Geophys. Res. Lett., 47, e2019GL085976, https://doi.org/10.1029/2019GL085976, 2019.
Munday, T.: Musgrave Province Airborne Electromagnetic Conductivity Grids, v1, CSIRO [data collection], https://doi.org/10.25919/5d0868d48591e, 2019.
Munday, T., Abdat, T., Ley-Cooper, Y., and Gilfedder, M.: Facilitating
Long-term Outback Water Solutions (G-FLOWS Stage-1: Hydrogeological Framework, Technical Report Series,
Goyder Institute for Water Research, Adelaide, Australia,
2013.
Munday, T., Gilfedder, M Costar, A., Blaikie, T., Cahill, K., Cui, T., Davis, A., Deng, Z., Flinchum, B., Gao, L., Gogoll, M., Gordon, G., Ibrahimi, T., Inverarity, K., Irvine, J., Janardhanan, S., Jiang, Z., Keppel, M., Krapf, C., Lane, T., Love, A., Macnae, J., Mallants, D., Mariethoz, G., Martinez, J., Pagendam, D., Peeters, L., Pickett, T., Raiber, M., Ren, X., Robinson, N., Siade, A., Smolanko, N., Soerensen, C., Stoian, L., Taylor, A., Visser, G., Wallis, I., and Xie, Y.: Facilitating Long-term Outback Water Solutions (G-FLOWS Stage 3): Final Summary Report, Goyder Institute for Water Research, Adelaide, Australia, 2020a.
Munday, T., Taylor, A., Raiber, M., Soerensen, C., Peeters, L., Krapf, C., Cui, T., Cahill, K., Flinchum, B., Smolanko, N., Martinez, J., Ibrahimi, T. and Gilfedder, M: Integrated regional hydrogeophysical conceptualisation of the Musgrave Province, South Australia, Technical Report, Goyder Institute for Water Research, Adelaide, Australia, 2020b.
Munday, T. J., Macnae, J., Bishop, J., and Sattel, D.: A geological interpretation of observed electrical structures in the regolith: Lawlers, Western Australia, Explor. Geophys., 32, 36–47, 2001.
Munday, T. J., Cahill, K., Sorensen, C., Davis, A., and Ibrahimi, T.:
Uncovering the Musgraves – a different perspective on an old landscape, Goyder Institute for Water Research,
Adelaide, December, 2016.
Niu, C., Li, J., and Xu, K.: Im2Struct: Recovering 3D Shape Structure from a
Single RGB Image, Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit., 80, 4096, 2018.
Oldenborger, G. A., Pugin, A. J. M., and Pullan, S. E.: Airborne time-domain electromagnetics, electrical resistivity and seismic reflection for regional three-dimensional mapping and characterization of the Spiritwood Valley Aquifer, Manitoba, Canada, Near Surf. Geophys., 11, 63–74, 2013.
Pawley, M. J., Dutch, R. A., Werner, M., and Krapf, C. B.: Repeated failure: long-lived faults in the eastern Musgrave Province, MESA J., 75, 45–55, 2014.
Perol, T., Gharbi, M., and Denolle, M.: Convolutional neural network for
earthquake detection and location, Sci. Adv., 4, e1700578, https://doi.org/10.1126/sciadv.1700578,
2018.
Roach, I., Jaireth, S., and Costelloe, M.: Applying regional airborne electromagnetic (AEM) surveying to understand the architecture of sandstone-hosted uranium mineral systems in the Callabonna Sub-basin, Lake Frome region, South Australia, Aust. J. Earth Sci., 61, 659–688, 2014.
Siemon, B., Eberle, D., Rehli, H.-J., Voß, W., and Pielawa, J.: Airborne geophysical investigation of buried valleys – survey area Ellerbeker Rinne, Germany, BGR Report, Hannover, 2006.
Sinha, A., Unmesh, A., Huang, Q., and Ramani, K.: SurfNet: Generating 3D shape surfaces using deep residual networks, Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit., 1, 6040, 2017.
Soerensen, C. C., Munday, T. J., Ibrahimi, T., Cahill, K., and Gilfedder, M.:
Musgrave Province, South Australia: processing and inversion of airborne
electromagnetic (AEM) data: Preliminary results, Technical Report Series,
1839-2725, Goyder Institute for Water Research, Adelaide, Australia, 2016.
Strebelle, S.: Conditional simulation of complex geological structures using multiple-point statistics, Math. Geol., 34, 1–21, 2002.
Taylor, A., Pichler, M., Olifent, V., Thompson, J., Bestland, E., Davies, P., Lamontagne, S., Suckow, A., Robinson, N., and Love, A.: Groundwater Flow Systems of North-eastern Eyre Peninsula (G-FLOWS Stage-2): Hydrogeology, geophysics and environmental tracers, Technical Report Series, Goyder Institute for Water Research, Adelaide, Australia, 2015.
Weissmann, G. S. and Fogg, G. E.: Multi-scale alluvial fan heterogeneity modeled with transition probability geostatistics in a sequence stratigraphic framework, J. Hydrol., 226, 48–65, 1999.
Wu, J., Zhang, C., Xue, T., Freeman, B., and Tenenbaum, J.: Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling, arXiv [preprint], arXiv:1610.07584, 2016.
Yi, L., Shao, L., Savva, M., Huang, H., Zhou, Y., Wang, Q., Graham, B., Engelcke, M., Klokov, R., and Lempitsky, V.: Large-scale 3d shape reconstruction and segmentation from shapenet core55, arXiv [preprint], arXiv:1710.06104, 2017.
Short summary
Fast and reliable tools are required to extract hidden information from big geophysical and remote sensing data. A deep-learning model in 3D image construction from 2D image(s) is here developed for paleovalley mapping from globally available digital elevation data. The outstanding performance for 3D subsurface imaging gives confidence that this generic novel tool will make better use of existing geophysical and remote sensing data for improved management of limited earth resources.
Fast and reliable tools are required to extract hidden information from big geophysical and...
