Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4755-2018
© Author(s) 2018. 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-11-4755-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
30 Nov 2018
Model description paper |
| 30 Nov 2018
| 30 Nov 2018
GSFLOW–GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems
G.-H. Crystal Ng
CORRESPONDING AUTHOR
Department of Earth Sciences, University of Minnesota, Minneapolis, Minnesota, USA
St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, Minnesota, USA
Andrew D. Wickert
Department of Earth Sciences, University of Minnesota, Minneapolis, Minnesota, USA
St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, Minnesota, USA
Lauren D. Somers
Department of Earth and Planetary Sciences, McGill University, Montreal, Quebec, Canada
Leila Saberi
Department of Earth Sciences, University of Minnesota, Minneapolis, Minnesota, USA
Collin Cronkite-Ratcliff
Geology, Minerals, Energy and Geophysics Science Center, United States Geological Survey, Menlo Park, California USA
Richard G. Niswonger
Earth Systems Modeling Branch, United States Geological Survey, Menlo Park, California, USA
Jeffrey M. McKenzie
Department of Earth and Planetary Sciences, McGill University, Montreal, Quebec, Canada
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Andrew D. Wickert, Chad T. Sandell, Bobby Schulz, and Gene-Hua Crystal Ng
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Pan Wu, Sihai Liang, Xu-Sheng Wang, Yuqing Feng, and Jeffrey M. McKenzie
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-744, https://doi.org/10.5194/hess-2017-744, 2018
Manuscript not accepted for further review
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Andrew D. Wickert
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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
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B. L. Kurylyk, K. T. B. MacQuarrie, D. Caissie, and J. M. McKenzie
Hydrol. Earth Syst. Sci., 19, 2469–2489, https://doi.org/10.5194/hess-19-2469-2015, https://doi.org/10.5194/hess-19-2469-2015, 2015
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We aim to improve mapping of floods and present a new method for hydraulic modelling that uses a combination of novel geospatial analysis and existing hydraulic modelling approaches. This method is wrapped into a modelling software called Blackbird. We compared Blackbird with two other existing options for flood mapping and found that the Blackbird model outperformed both. The Blackbird model has the potential to support real-time and large-scale flood mapping applications in the future.
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Lukas Gudmundsson, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
Geosci. Model Dev., 18, 2409–2425, https://doi.org/10.5194/gmd-18-2409-2025, https://doi.org/10.5194/gmd-18-2409-2025, 2025
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Global water models contribute to the evaluation of important natural and societal issues but are – as all models – simplified representation of reality. So, there are many ways to calculate the water fluxes and storages. This paper presents a visualization of 16 global water models using a standardized visualization and the pathway towards this common understanding. Next to academic education purposes, we envisage that these diagrams will help researchers, model developers, and data users.
Minki Hong, Nathaniel Chaney, Sergey Malyshev, Enrico Zorzetto, Anthony Preucil, and Elena Shevliakova
Geosci. Model Dev., 18, 2275–2301, https://doi.org/10.5194/gmd-18-2275-2025, https://doi.org/10.5194/gmd-18-2275-2025, 2025
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This study shows the significance of groundwater in resolving the coupled terrestrial water–energy cycle. LM4-SHARC (soil–hillslope aquifer–river continuum) describes the hillslope groundwater using its emergent properties, yielding noticeable improvements in soil moisture/temperature and groundwater discharge predictions. The implications of groundwater-mediated hydrologic interactions between hillslopes and streams need further exploration in the Earth system modeling community.
Ryan Bailey, Salam Abbas, Jeffrey Arnold, and Michael White
EGUsphere, https://doi.org/10.5194/egusphere-2025-300, https://doi.org/10.5194/egusphere-2025-300, 2025
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Water managers often make use of computer models to assess a region’s water supply under future conditions and management scenarios. This article introduces a new computer model that combines a land surface model (SWAT+) and a groundwater model (MODFLOW) and shows how it can be applied to managed, irrigated watersheds. This new model can be used for regions that rely on both surface water and groundwater for drinking water, agriculture, and industry.
Damian N. Mingo, Remko Nijzink, Christophe Ley, and Jack S. Hale
Geosci. Model Dev., 18, 1709–1736, https://doi.org/10.5194/gmd-18-1709-2025, https://doi.org/10.5194/gmd-18-1709-2025, 2025
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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. Bayes’ factor is a tool that can be used to compare models; however, it is very difficult to compute Bayes' factor numerically. In our paper, we explore and develop highly efficient algorithms for computing Bayes’ factor of hydrological systems, which will introduce this useful tool for selecting models into everyday hydrological practice.
Kerry L. Callaghan, Andrew D. Wickert, Richard Barnes, and Jacqueline Austermann
Geosci. Model Dev., 18, 1463–1486, https://doi.org/10.5194/gmd-18-1463-2025, https://doi.org/10.5194/gmd-18-1463-2025, 2025
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We present the Water Table Model (WTM), a new model for simulating groundwater and lake levels at continental scales over millennia. The WTM enables long-term evaluations of water-table changes. As a proof of concept, we simulate the North American water table for the present and the Last Glacial Maximum (LGM), showing that North America held more groundwater and lake water during the LGM than it does today – enough to lower sea levels by 14.98 cm. The open-source code is available on GitHub.
Chi-Ling Wei, Pei-Chun Chen, Chien-Yu Tseng, Ting-Yu Dai, Yun-Ting Ho, Ching-Chun Chou, Christian Onof, and Li-Pen Wang
Geosci. Model Dev., 18, 1357–1373, https://doi.org/10.5194/gmd-18-1357-2025, https://doi.org/10.5194/gmd-18-1357-2025, 2025
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pyBL is an open-source package for generating realistic rainfall time series based on the Bartlett–Lewis (BL) model. It can preserve not only standard but also extreme rainfall statistics across various timescales. Notably, compared to traditional frequency analysis methods, the BL model requires only half the record length (or even shorter) to achieve similar consistency in estimating sub-hourly rainfall extremes. This makes it a valuable tool for modelling rainfall extremes with short records.
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., 18, 819–842, https://doi.org/10.5194/gmd-18-819-2025, https://doi.org/10.5194/gmd-18-819-2025, 2025
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Multiple methods for measuring soil moisture beyond the point scale exist. Their validation is generally hindered by not 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 for the rigorous testing of these virtual sensors to understand their effectiveness and limitations.
Zhi Li, Gregor Rickert, Na Zheng, Zhibo Zhang, Ilhan Özgen-Xian, and Daniel Caviedes-Voullième
Geosci. Model Dev., 18, 547–562, https://doi.org/10.5194/gmd-18-547-2025, https://doi.org/10.5194/gmd-18-547-2025, 2025
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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.
Concetta D'Amato, Niccolò Tubini, and Riccardo Rigon
EGUsphere, https://doi.org/10.5194/egusphere-2024-4128, https://doi.org/10.5194/egusphere-2024-4128, 2025
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This paper presents GEOSPACE and its 1D implementation: an open-source tool for simulating soil-plant-atmosphere continuum (SPAC) interactions. Using object-oriented programming, GEOSPACE modularizes SPAC processes, focusing on infiltration, evapotranspiration, and root water uptake. The 1D deployment integrates plant transpiration, soil evaporation, and root growth, providing a flexible and validated framework for ecohydrological modeling and applications.
Hannes Müller Schmied, Tim Trautmann, Sebastian Ackermann, Denise Cáceres, Martina Flörke, Helena Gerdener, Ellen Kynast, Thedini Asali Peiris, Leonie Schiebener, Maike Schumacher, and Petra Döll
Geosci. Model Dev., 17, 8817–8852, https://doi.org/10.5194/gmd-17-8817-2024, https://doi.org/10.5194/gmd-17-8817-2024, 2024
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Assessing water availability and water use at the global scale is challenging but essential for a range of purposes. We describe the newest version of the global hydrological model WaterGAP, which has been used for numerous water resource assessments since 1996. We show the effects of new model features, as well as model evaluations, against water abstraction statistics and observed streamflow and water storage anomalies. The publicly available model output for several variants is described.
Yanchen Zheng, Gemma Coxon, Mostaquimur Rahman, Ross Woods, Saskia Salwey, Youtong Rong, and Doris Wendt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-211, https://doi.org/10.5194/gmd-2024-211, 2024
Revised manuscript accepted for GMD
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Groundwater is vital for people and ecosystems, but most physical models lack surface-groundwater interactions representation, leading to inaccurate streamflow predictions in groundwater-rich areas. This study presents DECIPHeR-GW v1, which links surface and groundwater systems to improve predictions of streamflow and groundwater levels. Tested across England and Wales, DECIPHeR-GW shows high accuracy, especially in south east England, making it a valuable tool for large-scale water management.
João António Martins Careto, Rita Margarida Cardoso, Ana Russo, Daniela Catarina André Lima, and Pedro Miguel Matos Soares
Geosci. Model Dev., 17, 8115–8139, https://doi.org/10.5194/gmd-17-8115-2024, https://doi.org/10.5194/gmd-17-8115-2024, 2024
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This study proposes a new daily drought index, the generalised drought index (GDI). The GDI not only identifies the same events as established indices but is also capable of improving their results. The index is empirically based and easy to compute, not requiring fitting the data to a probability distribution. The GDI can detect flash droughts and longer-term events, making it a versatile tool for drought monitoring.
Laura L. Swatridge, Ryan P. Mulligan, Leon Boegman, and Shiliang Shan
Geosci. Model Dev., 17, 7751–7766, https://doi.org/10.5194/gmd-17-7751-2024, https://doi.org/10.5194/gmd-17-7751-2024, 2024
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We develop an operational forecast system, Coastlines-LO, that can simulate water levels and surface waves in Lake Ontario driven by forecasts of wind speeds and pressure fields from an atmospheric model. The model has relatively low computational requirements, and results compare well with near-real-time observations, as well as with results from other existing forecast systems. Results show that with shorter forecast lengths, storm surge and wave predictions can improve in accuracy.
Dapeng Feng, Hylke Beck, Jens de Bruijn, Reetik Kumar Sahu, Yusuke Satoh, Yoshihide Wada, Jiangtao Liu, Ming Pan, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 17, 7181–7198, https://doi.org/10.5194/gmd-17-7181-2024, https://doi.org/10.5194/gmd-17-7181-2024, 2024
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Accurate hydrologic modeling is vital to characterizing water cycle responses to climate change. For the first time at this scale, we use differentiable physics-informed machine learning hydrologic models to simulate rainfall–runoff processes for 3753 basins around the world and compare them with purely data-driven and traditional modeling approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
Matevž Vremec, Raoul A. Collenteur, and Steffen Birk
Geosci. Model Dev., 17, 7083–7103, https://doi.org/10.5194/gmd-17-7083-2024, https://doi.org/10.5194/gmd-17-7083-2024, 2024
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Geoscientists commonly use various potential evapotranpiration (PET) formulas for environmental studies, which can be prone to errors and sensitive to climate change. PyEt, a tested and open-source Python package, simplifies the application of 20 PET methods for both time series and gridded data, ensuring accurate and consistent PET estimations suitable for a wide range of environmental applications.
Nedal Aqel, Lea Reusser, Stephan Margreth, Andrea Carminati, and Peter Lehmann
Geosci. Model Dev., 17, 6949–6966, https://doi.org/10.5194/gmd-17-6949-2024, https://doi.org/10.5194/gmd-17-6949-2024, 2024
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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.
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Adresen, J., Hilberg, S., and Kunkel, K.: Historical climate and climate
trends in the Midwestern United States, Climate Change in the Midwest: A
Synthesis Report for the National Climate Assessment, 8–36, 2014. a
Ajami, N. K., Gupta, H., Wagener, T., and Sorooshian, S.: Calibration of a
semi-distributed hydrologic model for streamflow estimation along a river
system, J. Hydrol., 298, 112–135, https://doi.org/10.1016/j.jhydrol.2004.03.033,
2004. a
Arge, L., Chase, J. S., Halpin, P., Toma, L., Vitter, J. S., Urban, D., and
Wickremesinghe, R.: Efficient flow computation on massive grid terrain
datasets, GeoInformatica, 7, 283–313, https://doi.org/10.1023/A:1025526421410, 2003. a, b
Arnold, J. G. and Fohrer, N.: SWAT2000: Current capabilities and research
opportunities in applied watershed modelling, Hydrol. Process., 19,
563–572, https://doi.org/10.1002/hyp.5611, 2005. a
Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., and White,
M. W.: SWAT: Model use, calibration, and validation,
ACS Sym. Ser., 55, 1491–1508, 2012. a
Bandaragoda, C., Tarboton, D. G., and Woods, R.: Application of TOPNET in
the distributed model intercomparison project, J. Hydrol., 298, 178–201,
https://doi.org/10.1016/j.jhydrol.2004.03.038, 2004. a
Baraer, M., Mckenzie, J., Mark, B. G., Gordon, R., Bury, J., Condom, T.,
Gomez, J., Knox, S., and Fortner, S. K.: Contribution of groundwater to the
outflow from ungauged glacierized catchments: A multi-site study in the
tropical
Cordillera Blanca, Peru, Hydrol. Process., 29, 2561–2581,
https://doi.org/10.1002/hyp.10386, 2015. a
Barnes, R., Lehman, C., and Mulla, D.: Priority-flood: An optimal
depression-filling and watershed-labeling algorithm for digital elevation
models, Comput. Geosci., 62, 117–127,
https://doi.org/10.1016/j.cageo.2013.04.024, 2014. a
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320,
18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006. a
Bhatt, G., Kumar, M., and Duffy, C. J.: A tightly coupled GIS and
distributed hydrologic modeling framework, Environ. Model. Softw.,
62, 70–84, https://doi.org/10.1016/j.envsoft.2014.08.003, 2014. a, b, c, d
Bhowmik, A. K., Metz, M., and Schäfer, R. B.: An automated, objective
and open source tool for stream threshold selection and upstream riparian
corridor delineation, Environ. Model. Softw., 63, 240–250,
https://doi.org/10.1016/j.envsoft.2014.10.017, 2015. a
Bird, M. I., O'Grady, D., and Ulm, S.: Humans, water, and the colonization
of Australia, P. Natl. Acad. Sci. USA, 113,
11477–11482, https://doi.org/10.1073/pnas.1608470113, 2016. a
Braun, J. and Willett, S. D.: A very efficient O(n), implicit and parallel
method to solve the stream power equation governing fluvial incision and
landscape evolution, Geomorphology, 180–181, 170–179,
https://doi.org/10.1016/j.geomorph.2012.10.008, 2013. a
Butts, M. and Graham, D.: Flexible Integrated Watershed Modeling with MIKE
SHE, in: Watershed Models, CRC Press, 245–271,
https://doi.org/10.1201/9781420037432.ch10, 2005. a
Clark, R. A., Halvorson, W. L., Sawdo, A. A., and Danielsen, K. C.: Plant
communities of Santa Rosa Island, Channel Islands National Park,
University of California, Davis, California, Technical Report 42, 93 pp., 1990. a
Czuba, J. A. and Foufoula-Georgiou, E.: A network-based framework for
identifying potential synchronizations and amplifications of sediment
delivery in river basins, Water Resour. Res., 50, 3826–3851,
https://doi.org/10.1002/2013WR014227, 2014. a, b
Essaid, H. I. and Hill, B. R.: Watershed-scale modeling of streamflow change
in incised montane meadows, Water Resour. Res., 50, 2657–2678,
https://doi.org/10.1002/2013WR014420, 2014. a
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.:
The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004,
https://doi.org/10.1029/2005RG000183, 2007. a, b
Feldman, A. D.: Hydrologic modeling system HEC-HMS: Technical Reference Manual,
U.S. Army Corps of Engineers, Davis, California, 2000. a
Galeone, D. G., Risser, D. W., Eicholtz, L. W., and Hoffman, S. A.: Water
Quality and Quantity and Simulated Surface-Water and Groundwater Flow in the
Laurel Hill Creek Basin, Southwestern Pennsylvania, 1991–2007,
Scientific Investigations Report, U.S. Geological
Survey, https://doi.org/10.3133/sir20165082, 2016. a
Gallagher, M. and Doherty, J.: Parameter estimation and uncertainty analysis
for a watershed model, Environ. Model. Softw., 22,
1000–1020, https://doi.org/10.1016/j.envsoft.2006.06.007, 2007. a
Gannett, M., Lite, K. J., Risley, J., Pischel, E., and La Marche, J.:
Simulation of Groundwater and Surface-Water Flow in the Upper Deschutes
Basin, Oregon, Scientific Investigations Report,
U.S. Geological Survey, 2017-5097, https://doi.org/10.3133/sir20175097, 2017. a
Hassan, S. T., Lubczynski, M. W., Niswonger, R. G., and Su, Z.:
Surface-groundwater interactions in hard rocks in Sardon Catchment of
western Spain: An integrated modeling approach, J. Hydrol., 517, 390–410,
https://doi.org/10.1016/j.jhydrol.2014.05.026, 2014. a
Heckmann, T., Schwanghart, W., and Phillips, J. D.: Graph theory-Recent
developments of its application in geomorphology, Geomorphology, 243,
130–146, https://doi.org/10.1016/j.geomorph.2014.12.024, 2014. a
Hofierka, J., Mitášová, H., and Neteler, M.: Geomorphometry
in GRASS GIS, chap. 17, in: Developments in Soil Science, 33, 387–410,
https://doi.org/10.1016/S0166-2481(08)00017-2, 2009. a
Hsieh, P. A. and Winston, R. B.: User's Guide To Model Viewer, a Program for
Three-Dimensional Visualization of Ground-Water Model Results, U.S.
Geological Survey, Menlo Park, CA, Open-File Report 02-106, 2002. a
Hunt, R. J., Walker, J. F., Selbig, W. R., Westenbroek, S. M., and Regan,
R. S.: Simulation of Climate – Change effects on streamflow, Lake water
budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake
Watershed, Wisconsin, USGS Scientific Investigations Report, 2013–5159,
2013. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9,
99–104, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Jasiewicz, J. and Metz, M.: A new GRASS GIS toolkit for Hortonian analysis
of drainage networks, Comput. Geosci., 37, 1162–1173,
https://doi.org/10.1016/j.cageo.2011.03.003, 2011. a, b, c, d
Jazwa, C. S., Duffy, C. J., Leonard, L., and Kennett, D. J.: Hydrological
Modeling and Prehistoric Settlement on Santa Rosa Island, California, USA,
Geoarchaeology, 31, 101–120, https://doi.org/10.1002/gea.21532, 2016. a, b
Jenson, S. K. and Domingue, J. O.: Extracting topographic structure from
digital elevation data for geographic information system analysis,
Photogramm. Eng. Rem. S., 54, 1593–1600, 1988. a
Kinner, D., Mitasova, H., Stallard, R., Harmon, R. S., and Toma, L.:
GIS-Based Stream Network Analysis for the Upper Río Chagres Basin,
Panama, in: The Río Chagres, Panama: A Multidisciplinary Profile of a
Tropical Watershed, edited by: Harmon, R. S., Springer-Verlag,
Berlin/Heidelberg, 83–95, https://doi.org/10.1007/1-4020-3297-8_6, 2005. a
Kreiling, R. M. and Houser, J. N.: Long-term decreases in phosphorus and
suspended solids, but not nitrogen, in six upper Mississippi River
tributaries, 1991–2014, Environ. Monit. Assess., 188, 454,
https://doi.org/10.1007/s10661-016-5464-3, 2016. a
Leavesley, G. H., Lichty, R., Troutman, B., and Saindon, L.:
Precipitation-Runoff Modeling System: User's Manual, Water-Resources
Investigations Report, U.S. Geological Survey, Denver, Colorado, USA, 1983. a
Leavesley, G. H., Restrepo, P., Markstrom, S., Dixon, M., and Stannard, L.:
The Modular Modeling System (MMS): User's Manual, Version 1.1, USGS
Numbered Series, U.S. Geological Survey, no. 96-151, 1996. a
Leonard, L. and Duffy, C. J.: Essential Terrestrial Variable data workflows
for distributed water resources modeling, Environ. Model. Softw.,
50, 85–96, https://doi.org/10.1016/j.envsoft.2013.09.003, 2013. a
Leopold, L. B. and Maddock, T.: The hydraulic geometry of stream channels
and some physiographic implications, Professional Paper, U.S. Geological
Survey, Washington, DC, 1953. a
LeVeque, R. J.: Finite volume methods for hyperbolic problems, vol. 31,
Cambridge university press, 580 pp., 2002. a
López-Moreno, J., Fontaneda, S., Bazo, J., Revuelto, J., Azorin-Molina,
C., Valero-Garcés, B., Morán-Tejeda, E., Vicente-Serrano, S.,
Zubieta, R., and Alejo-Cochachín, J.: Recent glacier retreat and
climate trends in Cordillera Huaytapallana, Peru, Global Planet. Change,
112, 1–11, https://doi.org/10.1016/j.gloplacha.2013.10.010, 2014. a
Luzio, M. D., Arnold, J. G., and Srinivasan, R.: A GIS Coupled hydrological
model system for the watershed assessment of agricultural nonpoint and point
sources of polution, T. GIS, 8, 113–136,
https://doi.org/10.1111/j.1467-9671.2004.00170.x, 2006. a
Magalhães, S. V. G., Andrade, M. V. A., Franklin, W. R., and Pena,
G. C.: A linear time algorithm to compute the drainage network on grid
terrains, J. Hydroinform., 16, 1227–1234, https://doi.org/10.2166/hydro.2013.068,
2014. a, b
Maidment, D. R. and Morehouse, S.: Arc Hydro: GIS for water resources, 3rd edn., ESRI
Press, Redlands, California, USA, 2002. a
Markstrom, S. L., Niswonger, R. G., Regan, R. S., Prudic, D. E., and Barlow,
P. M.: GSFLOW–Coupled Ground-Water and Surface-Water Flow Model Based on
the Integration of the Precipitation-Runoff Modeling System (PRMS) and the
Modular Ground-Water Flow Model (MODFLOW-2005), U.S. Geological Survey
Techniques and Methods, p. 240, https://doi.org/10.13140/2.1.2741.9202, 2008. a, b, c, d, e, f, g, h, i, j, k
Markstrom, S. L., Regan, R. S., Hay, L. E., Viger, R. J., Webb, R. M. T.,
Payn, R. A., and LaFontaine, J. H.: PRMS-IV , the Precipitation-Runoff
Modeling System, Version 4, U.S. Geological Survey, Reston, Virginia, USA,
https://doi.org/10.3133/tm6B7, 2015. a, b, c
Maxwell, R., Putti, M., Meyerhoff, S., Delfs, J., Ferguson, I. M., Ivanov,
V., Kim, J., Kolditz, O., Kollet, S. J., Kumar, M., Lopez, S., Niu, J.,
Paniconi, C., Park, Y., Phanikumar, M., Shen, C., Sudicky, E. A., and Sulis,
M.: Surface-subsurface model intercomparison: A first set of benchmark
results to diagnose integrated hydrology and feedbacks, Water Resour. Res.,
50, 1531–1549, https://doi.org/10.1002/2013WR013725, 2014. a
Maxwell, R. M., Kollet, S. J., Smith, S. G., Woodward, C. S., Falgout, R. D.,
Ferguson, I. M., Engdahl, N., Condon, L. E., Hector, B., Lopez, S., Bearup,
L., Jefferson, J., Collins, C., Graaf, I. D., Pribulick, C., Baldwin, C.,
Bosl, W. J., Hornung, R., and Ashby, S.: ParFlow User's Manual, Integrated
Ground-Water Modeling Center, Report GWMI 2016-01, 167 pp., 2017. a, b
Metz, M., Mitasova, H., and Harmon, R. S.: Efficient extraction of drainage
networks from massive, radar-based elevation models with least cost path
search, Hydrol. Earth Syst. Sci., 15, 667–678,
https://doi.org/10.5194/hess-15-667-2011, 2011. a, b, c
Miliaresis, G. and Delikaraoglou, D.: Effects of percent tree canopy density
and DEM misregistration on SRTM/NED vegetation height estimates, Remote
Sens., 1, 36–49, https://doi.org/10.3390/rs1020036, 2009. a
Mitasova, H., Mitas, L., Brown, W. M., Gerdes, D. P., Kosinovsky, R., and
Baker, T.: Modelling spatially and temporally distributed phenomena: New
methods and tools for GRASS GIS, Int. J. Geogr. Inf. Syst., 9, 433–446,
https://doi.org/10.1080/02693799508902048, 1995. a
Neitsch, S., Arnold, J., Kiniry, J., Srinivasan, R., and Williams, J.: Soil
and Water Assessment Tool User's Manual, vol. TR-192, Texas Water Resources
Institute, College Station, Texas, USA, available at:
http://swat.tamu.edu/media/1294/swatuserman.pdf (last access: 22 November 2018), 2002. a
Neteler, M. and Mitasova, H.: Open Source GIS: A GRASS GIS Approach,
Springer, New York, New York, USA, 3rd edn., 2008. a
Neteler, M., Beaudette, D., Cavallini, P., Lami, L., and Cepicky, J.: GRASS
GIS, Open Source Approaches in Spatial Data Handling, 2, 171–199,
https://doi.org/10.1007/978-3-540-74831-1_9, 2008. a
Neteler, M., Bowman, M. H., Landa, M., and Metz, M.: GRASS GIS: A
multi-purpose open source GIS, Environ. Model. Softw., 31,
124–130, https://doi.org/10.1016/j.envsoft.2011.11.014, 2012. a, b
Pal, J. S., Giorgi, F., Bi, X., Elguindi, N., Solmon, F., Gao, X., Rauscher,
S. A., Francisco, R., Zakey, A., Winter, J., Ashfaq, M., Syed, F. S., Bell,
J. L., Differbaugh, N. S., Karmacharya, J., Konari, A., Martinez, D.,
Da Rocha, R. P., Sloan, L. C., and Steiner, A. L.: Regional climate modeling
for the developing world: The ICTP RegCM3 and RegCNET, B. Am. Meteorol.
Soc., 88, 1395–1409, https://doi.org/10.1175/BAMS-88-9-1395, 2007. a
Patterson, C. J. and Hobbs, H. C.: Surficial geology, in: County Atlas C-9:
Geologic atlas of Rice County, edited by: Hobbs, H. C., Minnesota Geological
Survey, University of Minnesota Digital Conservancy,
http://hdl.handle.net/11299/58514 (last access: 15 November 2018),
1995. a
Pérez, F. and Granger, B. E.: IPython: A system for interactive
scientific computing, Comput. Sci. Eng., 9, 21–29,
https://doi.org/10.1109/MCSE.2007.53, 2007. a
Poeter, E. P. and Hill, M. C.: UCODE, a computer code for universal inverse
modeling, Comput. Geosci., 25, 457–462,
https://doi.org/10.1016/S0098-3004(98)00149-6, 1999. a, b, c
QGIS Development Team: QGIS Geographic Information System, available
at: http://qgis.org/, last access: 22 November 2018. a
Qu, Y. and Duffy, C. J.: A semidiscrete finite volume formulation for
multiprocess watershed simulation, Water Resour. Res., 43, 1–18,
https://doi.org/10.1029/2006WR005752, 2007. a, b, c
Razavi, S. and Gupta, H. V.: What do we mean by sensitivity analysis? The
need for comprehensive characterization of “global” sensitivity in Earth
and Environmental systems models, Water Resour. Res., 51, 3070–3092,
https://doi.org/10.1002/2014WR016527.Received, 2015. a
Reed, S., Koren, V., Smith, M., Zhang, Z., Moreda, F., and Seo, D. J.:
Overall distributed model intercomparison project results, J. Hydrol., 298,
27–60, https://doi.org/10.1016/j.jhydrol.2004.03.031, 2004. a
Regan, R. S., Niswonger, R. G., Markstrom, S. L., and Barlow, P. M.:
Documentation of a restart option for the U.S. Geological Survey coupled
groundwater and surface-water flow (GSFLOW) model, Techniques and Methods
6-D3, U.S. Geological Survey, Reston, Virginia, USA, 2015. a
Reilly, T. E.: System and Boundary Conceptualization in Ground-Water Flow
Simulation, in: Techniques of Water-Resources Investigations of the United
States Geological Survey, Book 3, Applications of Hydraulics, U.S. Geological
Survey, p. 38, 2001. a
Reilly, T. E. and Harbaugh, A. W.: Guidelines for Evaluating Ground-Water
Flow Models, U.S. Geological Survey, Report no. 2004-5038, 2004. a
Rossi, M. and Reichenbach, P.: LAND-SE: a software for statistically based
landslide susceptibility zonation, version 1.0, Geosci. Model Dev., 9,
3533–3543, https://doi.org/10.5194/gmd-9-3533-2016, 2016. a
Sangireddy, H., Stark, C. P., Kladzyk, A., and Passalacqua, P.: GeoNet: An
open source software for the automatic and objective extraction of channel
heads, channel network, and channel morphology from high resolution
topography data, Environ. Model. Softw., 83, 58–73,
https://doi.org/10.1016/j.envsoft.2016.04.026, 2016. a
Schumann, R. R., Pigati, J. S., and McGeehin, J. P.: Fluvial system response
to late Pleistocene-Holocene sea-level change on Santa Rosa Island, Channel
Islands National Park, California, Geomorphology, 268, 322–340,
https://doi.org/10.1016/j.geomorph.2016.05.033, 2016. a
Schwanghart, W. and Scherler, D.: Short Communication: TopoToolbox 2 –
MATLAB-based software for topographic analysis and modeling in Earth surface
sciences, Earth Surf. Dynam., 2, 1–7,
https://doi.org/10.5194/esurf-2-1-2014, 2014. a
Shapiro, M. and Westervelt, J.: r. mapcalc: An algebra for GIS and image
processing, USACERL-TR, Construction Engineering Research Lab, Champaign,
Illinois, USA, 1994. a
Simunek, J., Sejna, M., Saito, H., Sakai, M., and van Genuchten, M.: The
HYDRUS-1D software package for simulating the one-dimensional movement of
water, heat, and multiple solutes in variably-saturated media, Version 4.08,
HYDRUS Softw. Ser. 3., Technical Report, 2009. a
Somers, L. D., McKenzie, J. M., Zipper, S. C., Mark, B. G., Lagos, P., and
Baraer, M.: Does hillslope trenching enhance groundwater recharge and
baseflow in the Peruvian Andes?, Hydrol. Process., 32, 318–331,
https://doi.org/10.1002/hyp.11423, 2018. a
Song, X., Zhang, J., Zhan, C., Xuan, Y., Ye, M., and Xu, C.: Global
sensitivity analysis in hydrological modeling: Review of concepts, methods,
theoretical framework, and applications, J. Hydrol., 523, 739–757,
https://doi.org/10.1016/j.jhydrol.2015.02.013, 2015. a
Srinivasan, R. and Arnold, J. G.: Integration of a basin-scale water quality
model with GIS, J. Am. Water Resour. As., 30, 453–462,
https://doi.org/10.1111/j.1752-1688.1994.tb03304.x, 1994. a
Steenberg, J. R., Tipping, R. G., and Runkel, A. C.: Geologic controls on
groundwater and surface water flow in southeastern Minnesota and its impact
on nitrate concentrations in streams, Minnesota Geological Survey Open File
Report, p. 154, 2013. a
Surfleet, C. G. and Tullos, D.: Uncertainty in hydrologic modelling for
estimating hydrologic response due to climate change (Santiam River,
Oregon), Hydrol. Process., 27, 3560–3576, https://doi.org/10.1002/hyp.9485, 2013. a
Šúri, M. and Hofierka, J.: A new GIS-based solar radiation model
and its application to photovoltaic assessments, T. GIS, 8, 175–190,
https://doi.org/10.1111/j.1467-9671.2004.00174.x, 2004. a
Tachikawa, T., Kaku, M., Iwasaki, A., Gesch, D., Oimoen, M., Zhang, Z.,
Danielson, J., Krieger, T., Curtis, B., Haase, J., Abrams, M., Crippen, R.,
Carabajal, C., and ASTER GDEM Validation Team: ASTER Global Digital
Elevation Model Version 2 – Summary of Validation Results, Technical
report, NASA Earth Resources Observation and Science (EROS) Center, Sioux
Falls, South Dakota, USA, https://doi.org/10.1017/CBO9781107415324.004, 2011. a
Tejedor, A., Longjas, A., Zaliapin, I., and Foufoula-Georgiou, E.: Delta
channel networks: 1. A graph-theoretic approach for studying connectivity and
steady state transport on deltaic surfaces, Water Resour. Res., 51,
3998–4018, https://doi.org/10.1002/2014WR016577, 2015. a
Tian, Y., Zheng, Y., Wu, B., Wu, X., Liu, J., and Zheng, C.: Modeling
surface water-groundwater interaction in arid and semi-arid regions with
intensive agriculture, Environ. Model. Softw., 63, 170–184,
https://doi.org/10.1016/j.envsoft.2014.10.011, 2015. a
Tian, Y., Zheng, Y., and Zheng, C.: Development of a visualization tool for
integrated surface water-groundwater modeling, Comput. Geosci.,
86, 1–14, https://doi.org/10.1016/j.cageo.2015.09.019, 2016. a
Tipping, R. G.: Subsurface recharge and surface infiltration, in: Geologic
Atlas of Scott County, Minnesota, Minnesota Geological Survey Atlas Series,
2006. a
Vivoni, E. R., Ivanov, V. Y., Bras, R. L., and Entekhabi, D.: Generation of
Triangulated Irregular Networks Based on Hydrological Similarity, J. Hydrol.
Eng., 9, 288–302, https://doi.org/10.1061/(ASCE)1084-0699(2004)9:4(288), 2004. a
Wang, D., Liu, Y., and Kumar, M.: Using nested discretization for a detailed
yet computationally efficient simulation of local hydrology in a distributed
hydrologic model, Sci. Rep., 8, 1–13, https://doi.org/10.1038/s41598-018-24122-7,
2018. a
Waterloo Hydrogeologic Inc.: Visual MODFLOW 2011.1 User's Manual: For
Professional Applications in Three-Dimensional Groundwater Flow and
Contaminant Transport Modeling, Waterloo Hydrologic, Inc., Waterloo,
Ontario, Canada, available at:
http://trials.swstechnology.com/software/Visual_MODFLOW/2011/Manuals_and_Guides/VMOD-2011.1_Manual.pdf (last access: 22 November 2018), 2011. a
Wickert, A. D.: Reconstruction of North American drainage basins and river
discharge since the Last Glacial Maximum, Earth Surf. Dynam., 4, 831–869,
https://doi.org/10.5194/esurf-4-831-2016, 2016. a
Wickert, A. D. and Ng, G.-H. C.: GSFLOW-GRASS version 1.0.0, Zenodo,
https://doi.org/10.5281/zenodo.1487716, 2018. a
Winston, R. B.: Graphical User Interface for MODFLOW, Version 4, Open-File
Report no. 00-315, U.S. Geological Survey, Reston, Virginia, USA, 2000. a
Winston, R. B.: ModelMuse: A Graphical User Interface for MODFLOW-2005 and
PHAST, chap. 29, in: Section A, Ground Water – Book 6, Modeling Techniques,
U.S. Geological Survey, Reston, Virginia, USA, p. 52, available at:
http://pubs.usgs.gov/tm/tm6A29/tm6A29.pdf (last access: 22 November 2018), 2009. a, b, c
Winter, T. C., Harvey, J. W., Franke, O. L., and Alley, W. M.: Ground water
and surface water: A single resource, U.S. Government Printing Office,
Denver, Colorado, USA, 1998. a
Zambelli, P., Gebbert, S., and Ciolli, M.: Pygrass: An Object Oriented
Python Application Programming Interface (API) for Geographic Resources
Analysis Support System (GRASS) Geographic Information System (GIS), ISPRS
Int. Geo.-Inf., 2, 201–219, https://doi.org/10.3390/ijgi2010201, 2013. a
Short summary
The profound importance of water has led to the development of increasingly complex hydrological models. However, implementing these models is usually time-consuming and requires specialized expertise, stymieing their widespread use to support science-driven decision-making. In response, we have developed GSFLOW–GRASS, a robust and comprehensive set of software tools that can be readily used to set up and execute GSFLOW, the U.S. Geological Survey's coupled groundwater–surface-water flow model.
The profound importance of water has led to the development of increasingly complex hydrological...
