Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7391-2021
© 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-14-7391-2021
© 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
| 
01 Dec 2021
Model description paper |
| 01 Dec 2021
| 01 Dec 2021
POET (v0.1): speedup of many-core parallel reactive transport simulations with fast DHT lookups
GFZ German Research Centre for Geosciences, Fluid Systems Modelling, Telegrafenberg, 14473 Potsdam, Germany
Michael Kühn
GFZ German Research Centre for Geosciences, Fluid Systems Modelling, Telegrafenberg, 14473 Potsdam, Germany
University of Potsdam, Institute of Geosciences, Karl-Liebknecht-Str. 24–25, 14476 Potsdam, Germany
Alexander Lindemann
University of Potsdam, Institute of Computer Science, Operating Systems and Distributed Systems, An der Bahn 2, 14476 Potsdam, Germany
Max Lübke
GFZ German Research Centre for Geosciences, Fluid Systems Modelling, Telegrafenberg, 14473 Potsdam, Germany
University of Potsdam, Institute of Computer Science, Operating Systems and Distributed Systems, An der Bahn 2, 14476 Potsdam, Germany
Bettina Schnor
University of Potsdam, Institute of Computer Science, Operating Systems and Distributed Systems, An der Bahn 2, 14476 Potsdam, Germany
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This paper presents a surrogate modelling approach applied to a geochemical system of uranium sorption on clay, relevant for the safety assessment of nuclear waste repositories. The surrogate uses knowledge about the underlying process to recursively partition the dataset into regions of reduced dimensionality. It achieves high accuracy with a competitive prediction throughput, and is a promising method to speedup computationally demanding coupled reactive transport models.
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Barite formation is an important factor for many use cases of the geological subsurface because it may change the rock.
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The steps that were identified to play a role are celestite dissolution followed by two-step precipitation of barite: spontaneous formation of small crystals and their subsequent growth.
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Marco De Lucia and Michael Kühn
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Geosci. Model Dev., 14, 4713–4730, https://doi.org/10.5194/gmd-14-4713-2021, https://doi.org/10.5194/gmd-14-4713-2021, 2021
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Geosci. Model Dev., 8, 279–294, https://doi.org/10.5194/gmd-8-279-2015, https://doi.org/10.5194/gmd-8-279-2015, 2015
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Adv. Geosci., 65, 113–115, https://doi.org/10.5194/adgeo-65-113-2024, https://doi.org/10.5194/adgeo-65-113-2024, 2024
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Adv. Geosci., 65, 45–54, https://doi.org/10.5194/adgeo-65-45-2024, https://doi.org/10.5194/adgeo-65-45-2024, 2024
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This paper presents a surrogate modelling approach applied to a geochemical system of uranium sorption on clay, relevant for the safety assessment of nuclear waste repositories. The surrogate uses knowledge about the underlying process to recursively partition the dataset into regions of reduced dimensionality. It achieves high accuracy with a competitive prediction throughput, and is a promising method to speedup computationally demanding coupled reactive transport models.
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Adv. Geosci., 65, 1–7, https://doi.org/10.5194/adgeo-65-1-2024, https://doi.org/10.5194/adgeo-65-1-2024, 2024
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Waiwera is a small coastal village located on New Zealand's North Island above a geothermal reservoir. The origin of the warm water is not well understood. An inferred fault zone at the base of the reservoir is thought to channelise the uprising thermal water. The observed characteristic cold and hot water distribution in the system was simulated and the temperature profiles show an improved agreement in the near field around the centre of the reservoir.
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Adv. Geosci., 62, 67–69, https://doi.org/10.5194/adgeo-62-67-2024, https://doi.org/10.5194/adgeo-62-67-2024, 2024
Theresa Hennig and Michael Kühn
Adv. Geosci., 62, 21–30, https://doi.org/10.5194/adgeo-62-21-2023, https://doi.org/10.5194/adgeo-62-21-2023, 2023
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Uranium migration for a close to real case situation is quantified with reactive transport simulations using input data from the deep geothermal borehole Schlattingen, which is near the targeted area in Switzerland, and including the effect of the multi-barrier system on the source term. The hydrogeological system must always be considered in safety assessments since adjacent aquifers have a major impact on the pore water geochemistry, and hence sorption processes.
Theresa Hennig and Michael Kühn
Saf. Nucl. Waste Disposal, 2, 147–147, https://doi.org/10.5194/sand-2-147-2023, https://doi.org/10.5194/sand-2-147-2023, 2023
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Migration of uranium in the potential host rock Opalinus Clay is used as an example to demonstrate the extent to which simulated migration lengths can vary for a million years, depending on the model concept and on the underlying data and parameters. To reduce the uncertainty in this context, the calcite carbonate ion and the hydrogeological system at a potential disposal site need to be known, whereas the quantity of clay minerals plays a subordinate role, as long as it is enough.
Michael Kühn, Dirk Bosbach, Horst Geckeis, Vinzenz Brendler, and Olaf Kolditz
Saf. Nucl. Waste Disposal, 2, 195–195, https://doi.org/10.5194/sand-2-195-2023, https://doi.org/10.5194/sand-2-195-2023, 2023
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The Repository Site Selection Act explicitly emphasises that targeting the disposal of high-level radioactive waste is a so-called learning process. We are of the opinion that the procedure and the available data should be combined with geoscientific knowledge to support the identification of siting regions. We propose this workshop and invite all experts who have dealt with the search for a repository site from a geoscientific perspective.
Viktor J. Bruckman, Gregor Giebel, Christopher Juhlin, Sonja Martens, and Michael Kühn
Adv. Geosci., 58, 87–91, https://doi.org/10.5194/adgeo-58-87-2022, https://doi.org/10.5194/adgeo-58-87-2022, 2022
Elena Chabab, Michael Kühn, and Thomas Kempka
Adv. Geosci., 58, 47–54, https://doi.org/10.5194/adgeo-58-47-2022, https://doi.org/10.5194/adgeo-58-47-2022, 2022
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The present study, uses density-driven flow and transport models to evaluate mechanisms of saline water intrusion from deep aquifers into the freshwater column used for drinking water supply under different boundary conditions and for a specific site in the German Federal State of Brandenburg. Results show that mainly decreasing groundwater recharge leads to increased and earlier salinisation which highlights the need for waterworks to initiate effective countermeasures quickly and in time.
Michael Kühn, Melissa Präg, Ivy Becker, Christoph Hilgers, Andreas Grafe, and Thomas Kempka
Adv. Geosci., 58, 31–39, https://doi.org/10.5194/adgeo-58-31-2022, https://doi.org/10.5194/adgeo-58-31-2022, 2022
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The geothermal hot water reservoir below the small town of Waiwera in New Zealand has been known to the indigenous Maori for many centuries. Overproduction by European immigrants led to a water level decrease and consequently artesian flow from the wells and the seeps on the beach ceased. The Te Kaunihera o Tāmaki Makaurau Auckland Council established the Waiwera Thermal Groundwater Allocation and Management Plan to allow the geothermal system to recover.
Thomas Kempka, Svenja Steding, and Michael Kühn
Adv. Geosci., 58, 19–29, https://doi.org/10.5194/adgeo-58-19-2022, https://doi.org/10.5194/adgeo-58-19-2022, 2022
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Theresa Hennig and Michael Kühn
Adv. Geosci., 58, 11–18, https://doi.org/10.5194/adgeo-58-11-2022, https://doi.org/10.5194/adgeo-58-11-2022, 2022
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Maria Wetzel, Thomas Kempka, and Michael Kühn
Adv. Geosci., 58, 1–10, https://doi.org/10.5194/adgeo-58-1-2022, https://doi.org/10.5194/adgeo-58-1-2022, 2022
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Michael Kühn and Leonard Grabow
Adv. Geosci., 56, 107–116, https://doi.org/10.5194/adgeo-56-107-2021, https://doi.org/10.5194/adgeo-56-107-2021, 2021
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The geothermal reservoir at Waiwera has been subject to active exploitation for a long time. However, the continuous production of geothermal water, to supply hotels and spas, had a negative impact on the reservoir. The aim of this work was to link the influence of the abstraction rates to the measured water level data to derive reservoir properties. For the analysis, a modified deconvolution algorithm was implemented and shown to be applicable and in accordance to results of a pumping test.
Dirk Bosbach, Horst Geckeis, Frank Heberling, Olaf Kolditz, Michael Kühn, Katharina Müller, Thorsten Stumpf, and the iCROSS team
Saf. Nucl. Waste Disposal, 1, 85–87, https://doi.org/10.5194/sand-1-85-2021, https://doi.org/10.5194/sand-1-85-2021, 2021
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The present contribution provides an overview on the collaborative project iCROSS and reports selected results. The impact of considering complex coupled processes in repository subsystems for the assessment of the integrity of a given (generic) repository arrangement will be discussed. The interdisciplinary team combines experimental work in the lab, in the underground rock laboratory and environmental simulations in order to achieve process understanding across variable scales.
Theresa Hennig and Michael Kühn
Adv. Geosci., 56, 97–105, https://doi.org/10.5194/adgeo-56-97-2021, https://doi.org/10.5194/adgeo-56-97-2021, 2021
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Uranium migration in the Swiss Opalinus Clay is used as an example to quantify the influence of varying values of a stability constant in the underlying thermodynamic database within the law of mass action on the migration lengths. The difference of the stability constant of 1.33 log units lead to changed migration lengths of 5 m to 7 m. With a maximum diffusion distance of 22 m the influence of an uncertain stability constant is negligible for the host rock scale.
Morgan Tranter, Maria Wetzel, Marco De Lucia, and Michael Kühn
Adv. Geosci., 56, 57–65, https://doi.org/10.5194/adgeo-56-57-2021, https://doi.org/10.5194/adgeo-56-57-2021, 2021
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Barite formation is an important factor for many use cases of the geological subsurface because it may change the rock.
In this modelling study, the replacement reaction of celestite to barite is investigated.
The steps that were identified to play a role are celestite dissolution followed by two-step precipitation of barite: spontaneous formation of small crystals and their subsequent growth.
Explicitly including the processes improve the usability of the models for quantified prediction.
Marco De Lucia and Michael Kühn
Adv. Geosci., 56, 33–43, https://doi.org/10.5194/adgeo-56-33-2021, https://doi.org/10.5194/adgeo-56-33-2021, 2021
Short summary
Short summary
RedModRphree is an R extension package to leverage the PHREEQC engine for geochemical models, providing convenience functions to efficiently setup computations and program algorithms involving geochemical models. Version 0.3.6 ships with a novel implementation of Pourbaix (potential/pH) diagram computation which considers the full speciation of the solution at each diagram point.
Viktor J. Bruckman, Gregor Giebel, Christopher Juhlin, Sonja Martens, Antonio P. Rinaldi, and Michael Kühn
Adv. Geosci., 56, 13–18, https://doi.org/10.5194/adgeo-56-13-2021, https://doi.org/10.5194/adgeo-56-13-2021, 2021
Marco De Lucia and Michael Kühn
Geosci. Model Dev., 14, 4713–4730, https://doi.org/10.5194/gmd-14-4713-2021, https://doi.org/10.5194/gmd-14-4713-2021, 2021
Short summary
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DecTree evaluates a hierarchical coupling method for reactive transport simulations in which pre-trained surrogate models are used to speed up the geochemical subprocess, and equation-based
full-physicssimulations are called only if the surrogate predictions are implausible. Furthermore, we devise and evaluate a decision tree surrogate approach designed to inject domain knowledge of the surrogate by defining engineered features based on law of mass action or stoichiometric reaction equations.
Melissa Präg, Ivy Becker, Christoph Hilgers, Thomas R. Walter, and Michael Kühn
Adv. Geosci., 54, 165–171, https://doi.org/10.5194/adgeo-54-165-2020, https://doi.org/10.5194/adgeo-54-165-2020, 2020
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Utilization of geothermal reservoirs as alternative energy source is becoming increasingly important worldwide. Here, we studied the surface expression of a warm water reservoir in Waiwera, New Zealand, that has been known for many centuries but remained little explored. Using thermal infrared cameras we were able to show renewed activity of the hot springs on the beachfront and identified faults and fractures as important fluid pathways, as well as individual fluid conducting lithologies.
Michael Kühn, Natalie C. Nakaten, and Thomas Kempka
Adv. Geosci., 54, 173–178, https://doi.org/10.5194/adgeo-54-173-2020, https://doi.org/10.5194/adgeo-54-173-2020, 2020
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Energy supply in Germany is subject to a profound change. The present paper addresses the German potential of storing excess energy from renewable power sources in the geological subsurface. Wind and solar electricity can be transformed into hydrogen, and with carbon dioxide subsequently into methane. The current potential for combined subsurface storage of methane and carbon dioxide allows to store far more than required to date and is estimated to provide the entire coverage in 2050.
Maria Wetzel, Thomas Kempka, and Michael Kühn
Adv. Geosci., 54, 33–39, https://doi.org/10.5194/adgeo-54-33-2020, https://doi.org/10.5194/adgeo-54-33-2020, 2020
Sonja Martens, Maren Brehme, Viktor J. Bruckman, Christopher Juhlin, Johannes Miocic, Antonio P. Rinaldi, and Michael Kühn
Adv. Geosci., 54, 1–5, https://doi.org/10.5194/adgeo-54-1-2020, https://doi.org/10.5194/adgeo-54-1-2020, 2020
Márk Somogyvári, Michael Kühn, and Sebastian Reich
Adv. Geosci., 49, 207–214, https://doi.org/10.5194/adgeo-49-207-2019, https://doi.org/10.5194/adgeo-49-207-2019, 2019
Sonja Martens, Christopher Juhlin, Viktor J. Bruckman, Gregor Giebel, Thomas Nagel, Antonio P. Rinaldi, and Michael Kühn
Adv. Geosci., 49, 31–35, https://doi.org/10.5194/adgeo-49-31-2019, https://doi.org/10.5194/adgeo-49-31-2019, 2019
Michael Kühn and Tim Schöne
Adv. Geosci., 45, 235–241, https://doi.org/10.5194/adgeo-45-235-2018, https://doi.org/10.5194/adgeo-45-235-2018, 2018
Short summary
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The water level of the Waiwera geothermal reservoir increased in the hours and days after the Kaikoura earthquake on 14 November 2016. We determined in a continuous time series consisting of monthly means of water level data and pumping rates starting in 1986 if events above a certain strength alter groundwater dynamics at Waiwera. A clear correlation cannot be proven but none of the recorded earthquakes led to such a high energy density in Waiwera as the Kaikoura event did.
Sonja Martens, Christopher Juhlin, Viktor J. Bruckman, Kristen Mitchell, Luke Griffiths, and Michael Kühn
Adv. Geosci., 45, 163–166, https://doi.org/10.5194/adgeo-45-163-2018, https://doi.org/10.5194/adgeo-45-163-2018, 2018
Elena Tillner, Maria Langer, Thomas Kempka, and Michael Kühn
Hydrol. Earth Syst. Sci., 20, 1049–1067, https://doi.org/10.5194/hess-20-1049-2016, https://doi.org/10.5194/hess-20-1049-2016, 2016
Short summary
Short summary
The degree of shallow aquifer salinisation triggered by fluid injection into deeper brine-bearing aquifers and brine upward migration through hydraulically conductive faults strongly depends on the regional depth of the freshwater-saltwater boundary, since displaced brines originate only from the upper fault damage zones in the study area. The highest local salinity increase in shallow aquifers occurs in case of closed model boundaries and low fault damage zone volumes.
M. De Lucia, T. Kempka, and M. Kühn
Geosci. Model Dev., 8, 279–294, https://doi.org/10.5194/gmd-8-279-2015, https://doi.org/10.5194/gmd-8-279-2015, 2015
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The soil water potential (SWP) determines various soil water processes. Since remote sensing techniques cannot measure it directly, it is often deduced from volumetric water content (VWC) information. However, under dynamic field conditions, the relationship between SWP and VWC is highly ambiguous due to different factors that cannot be modeled with the classical approach. Applying a deep neural network with an autoencoder enables the prediction of the dynamic SWP.
Jenny Kupzig, Nina Kupzig, and Martina Flörke
Geosci. Model Dev., 17, 6819–6846, https://doi.org/10.5194/gmd-17-6819-2024, https://doi.org/10.5194/gmd-17-6819-2024, 2024
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Valid simulation results from global hydrological models (GHMs) are essential, e.g., to studying climate change impacts. Adapting GHMs to ungauged basins requires regionalization, enabling valid simulations. In this study, we highlight the impact of regionalization of GHMs on runoff simulations using an ensemble of regionalization methods for WaterGAP3. We have found that regionalization leads to temporally and spatially varying uncertainty, potentially reaching up to inter-model differences.
Zhi Li, Gregor Rickert, Na Zheng, Zhibo Zhang, Ilhan Özgen-Xian, and Daniel Caviedes-Voullième
EGUsphere, https://doi.org/10.5194/egusphere-2024-2588, https://doi.org/10.5194/egusphere-2024-2588, 2024
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We introduce SERGHEI-RE, a 3D subsurface flow simulator with performance-portable parallel computing capabilities. SERGHEI-RE performs effectively on various computational devices, from personal computers to advanced clusters. It allows users to solve flow equations with multiple numerical schemes, making it adaptable to various hydrological scenarios. Testing results show its accuracy and performance, confirming that SERGHEI-RE is a powerful tool for hydrological research.
Till Francke, Cosimo Brogi, Alby Duarte Rocha, Michael Förster, Maik Heistermann, Markus Köhli, Daniel Rasche, Marvin Reich, Paul Schattan, Lena Scheiffele, and Martin Schrön
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-106, https://doi.org/10.5194/gmd-2024-106, 2024
Revised manuscript accepted for GMD
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Multiple methods for measuring soil moisture beyond the point scale exist. Their validation generally hindered by lack of knowing the truth. We propose a virtual framework, in which this truth is fully known and the sensor observations for Cosmic Ray Neutron Sensing, Remote Sensing, and Hydrogravimetry are simulated. This allows the rigourous testing of these virtual sensors to understand their effectiveness and limitations.
Manuel F. Rios Gaona, Katerina Michaelides, and Michael Bliss Singer
Geosci. Model Dev., 17, 5387–5412, https://doi.org/10.5194/gmd-17-5387-2024, https://doi.org/10.5194/gmd-17-5387-2024, 2024
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STORM v.2 (short for STOchastic Rainfall Model version 2.0) is an open-source and user-friendly modelling framework for simulating rainfall fields over a basin. It also allows simulating the impact of plausible climate change either on the total seasonal rainfall or the storm’s maximum intensity.
Lukas Riedel, Thomas Röösli, Thomas Vogt, and David N. Bresch
Geosci. Model Dev., 17, 5291–5308, https://doi.org/10.5194/gmd-17-5291-2024, https://doi.org/10.5194/gmd-17-5291-2024, 2024
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River floods are among the most devastating natural hazards. We propose a flood model with a statistical approach based on openly available data. The model is integrated in a framework for estimating impacts of physical hazards. Although the model only agrees moderately with satellite-detected flood extents, we show that it can be used for forecasting the magnitude of flood events in terms of socio-economic impacts and for comparing these with past events.
Robin Schwemmle, Hannes Leistert, Andreas Steinbrich, and Markus Weiler
Geosci. Model Dev., 17, 5249–5262, https://doi.org/10.5194/gmd-17-5249-2024, https://doi.org/10.5194/gmd-17-5249-2024, 2024
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The new process-based hydrological toolbox model, RoGeR (https://roger.readthedocs.io/), can be used to estimate the components of the hydrological cycle and the related travel times of pollutants through parts of the hydrological cycle. These estimations may contribute to effective water resources management. This paper presents the toolbox concept and provides a simple example of providing estimations to water resources management.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
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This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
M. Graham Clark and Sean K. Carey
Geosci. Model Dev., 17, 4911–4922, https://doi.org/10.5194/gmd-17-4911-2024, https://doi.org/10.5194/gmd-17-4911-2024, 2024
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This paper provides validation of the Canadian Small Lakes Model (CSLM) for estimating evaporation rates from reservoirs and a refactoring of the original FORTRAN code into MATLAB and Python, which are now stored in GitHub repositories. Here we provide direct observations of the surface energy exchange obtained with an eddy covariance system to validate the CSLM. There was good agreement between observations and estimations except under specific atmospheric conditions when evaporation is low.
Thibault Hallouin, François Bourgin, Charles Perrin, Maria-Helena Ramos, and Vazken Andréassian
Geosci. Model Dev., 17, 4561–4578, https://doi.org/10.5194/gmd-17-4561-2024, https://doi.org/10.5194/gmd-17-4561-2024, 2024
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The evaluation of the quality of hydrological model outputs against streamflow observations is widespread in the hydrological literature. In order to improve on the reproducibility of published studies, a new evaluation tool dedicated to hydrological applications is presented. It is open source and usable in a variety of programming languages to make it as accessible as possible to the community. Thus, authors and readers alike can use the same tool to produce and reproduce the results.
Barnaby Dobson, Leyang Liu, and Ana Mijic
Geosci. Model Dev., 17, 4495–4513, https://doi.org/10.5194/gmd-17-4495-2024, https://doi.org/10.5194/gmd-17-4495-2024, 2024
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Water management is challenging when models don't capture the entire water cycle. We propose that using integrated models facilitates management and improves understanding. We introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customisation. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev., 17, 3559–3578, https://doi.org/10.5194/gmd-17-3559-2024, https://doi.org/10.5194/gmd-17-3559-2024, 2024
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We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model; its large selection of different assimilation algorithms; and its modularity with respect to the combination of different types of observations, states and parameters.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
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We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
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The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
Geosci. Model Dev., 17, 2877–2899, https://doi.org/10.5194/gmd-17-2877-2024, https://doi.org/10.5194/gmd-17-2877-2024, 2024
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Treated and untreated wastewaters are sources of contaminants of emerging concern. HydroFATE, a new global model, estimates their concentrations in surface waters, identifying streams that are most at risk and guiding monitoring/mitigation efforts to safeguard aquatic ecosystems and human health. Model predictions were validated against field measurements of the antibiotic sulfamethoxazole, with predicted concentrations exceeding ecological thresholds in more than 400 000 km of rivers worldwide.
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
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We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
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Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
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We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
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Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
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Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
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This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
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We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Damian N. Mingo, Remko Nijzink, Christophe Ley, and Jack S. Hale
EGUsphere, https://doi.org/10.5194/egusphere-2023-2865, https://doi.org/10.5194/egusphere-2023-2865, 2024
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Hydrologists are often faced with selecting amongst a set of competing models with different numbers of parameters and ability to fit available data. The Bayes’ factor is a tool that can be used to compare models, however it is very difficult to compute the Bayes’ factor numerically. In our paper we explore and develop highly efficient algorithms for computing the Bayes’ factor of hydrological systems, which will bring this useful tool for selecting models to everyday hydrological practice.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
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We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
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Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
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Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
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Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
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NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
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Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
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DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
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Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
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Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
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Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
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In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
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We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
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During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
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It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
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Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
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This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
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Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
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Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
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A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
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Short summary
POET is a parallel reactive transport simulator which implements a mechanism to store and reuse previous results of geochemical simulations through distributed hash tables. POET parallelizes chemistry using a master/worker design with noncontiguous grid partitions to maximize its efficiency and load balance on shared-memory machines and compute clusters.
POET is a parallel reactive transport simulator which implements a mechanism to store and reuse...
