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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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.
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. Discuss., https://doi.org/10.5194/gmd-2023-190, https://doi.org/10.5194/gmd-2023-190, 2023
Revised manuscript accepted for GMD
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Accurate hydrological 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 approaches. This sets a benchmark for hydrologic estimates around the world and builds foundations for improving global hydrologic simulations.
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
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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.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
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The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
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A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Kristina Šarović, Melita Burić, and Zvjezdana B. Klaić
Geosci. Model Dev., 15, 8349–8375, https://doi.org/10.5194/gmd-15-8349-2022, https://doi.org/10.5194/gmd-15-8349-2022, 2022
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We develop a simple 1-D model for the prediction of the vertical temperature profiles in small, warm lakes. The model uses routinely measured meteorological variables as well as UVB radiation and yearly mean temperature data. It can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.
Jason A. Clark, Elchin E. Jafarov, Ken D. Tape, Benjamin M. Jones, and Victor Stepanenko
Geosci. Model Dev., 15, 7421–7448, https://doi.org/10.5194/gmd-15-7421-2022, https://doi.org/10.5194/gmd-15-7421-2022, 2022
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Lakes in the Arctic are important reservoirs of heat. Under climate warming scenarios, we expect Arctic lakes to warm the surrounding frozen ground. We simulate water temperatures in three Arctic lakes in northern Alaska over several years. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season and that more heat storage by lakes would enhance thawing of frozen ground.
Danielle S. Grogan, Shan Zuidema, Alex Prusevich, Wilfred M. Wollheim, Stanley Glidden, and Richard B. Lammers
Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, https://doi.org/10.5194/gmd-15-7287-2022, 2022
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This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
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We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Robert Chlumsky, James R. Craig, Simon G. M. Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown, and Rezgar Arabzadeh
Geosci. Model Dev., 15, 7017–7030, https://doi.org/10.5194/gmd-15-7017-2022, https://doi.org/10.5194/gmd-15-7017-2022, 2022
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We introduce the open-source RavenR package, which has been built to support the use of the hydrologic modelling framework Raven. The R package contains many functions that may be useful in each step of the model-building process, including preparing model input files, running the model, and analyzing the outputs. We present six reproducible use cases of the RavenR package for the Liard River basin in Canada to demonstrate how it may be deployed.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
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Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
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...
