Articles | Volume 11, issue 4
https://doi.org/10.5194/gmd-11-1627-2018
© 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-11-1627-2018
© 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
| 
25 Apr 2018
Model description paper |
| 25 Apr 2018
| 25 Apr 2018
tran-SAS v1.0: a numerical model to compute catchment-scale hydrologic transport using StorAge Selection functions
Laboratory of Ecohydrology ENAC/IIE/ECHO, École
Polytechinque Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Enrico Bertuzzo
Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy
Related authors
Izabela Bujak-Ozga, Jana von Freyberg, Margaret Zimmer, Andrea Rinaldo, Paolo Benettin, and Ilja van Meerveld
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-67, https://doi.org/10.5194/hess-2024-67, 2024
Preprint under review for HESS
Short summary
Short summary
Stream networks expand and contract affecting the amount and quality of water in perennial streams. This study presents measurements of changes in water chemistry and the flowing portion of the drainage network during rainfall events in two neighboring catchments. Despite the proximity, similar size, soil and bedrock, water chemistry and stream network dynamics differed substantially for the two catchments. These differences are attributed to the differences in slope and channel network.
Matthias Sprenger, Pilar Llorens, Francesc Gallart, Paolo Benettin, Scott T. Allen, and Jérôme Latron
Hydrol. Earth Syst. Sci., 26, 4093–4107, https://doi.org/10.5194/hess-26-4093-2022, https://doi.org/10.5194/hess-26-4093-2022, 2022
Short summary
Short summary
Our catchment-scale transit time modeling study shows that including stable isotope data on evapotranspiration in addition to the commonly used stream water isotopes helps constrain the model parametrization and reveals that the water taken up by plants has resided longer in the catchment storage than the water leaving the catchment as stream discharge. This finding is important for our understanding of how water is stored and released, which impacts the water availability for plants and humans.
Magali F. Nehemy, Paolo Benettin, Mitra Asadollahi, Dyan Pratt, Andrea Rinaldo, and Jeffrey J. McDonnell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-528, https://doi.org/10.5194/hess-2019-528, 2019
Preprint withdrawn
Daniele Penna, Luisa Hopp, Francesca Scandellari, Scott T. Allen, Paolo Benettin, Matthias Beyer, Josie Geris, Julian Klaus, John D. Marshall, Luitgard Schwendenmann, Till H. M. Volkmann, Jana von Freyberg, Anam Amin, Natalie Ceperley, Michael Engel, Jay Frentress, Yamuna Giambastiani, Jeff J. McDonnell, Giulia Zuecco, Pilar Llorens, Rolf T. W. Siegwolf, Todd E. Dawson, and James W. Kirchner
Biogeosciences, 15, 6399–6415, https://doi.org/10.5194/bg-15-6399-2018, https://doi.org/10.5194/bg-15-6399-2018, 2018
Short summary
Short summary
Understanding how water flows through ecosystems is needed to provide society and policymakers with the scientific background to manage water resources sustainably. Stable isotopes of hydrogen and oxygen in water are a powerful tool for tracking water fluxes, although the heterogeneity of natural systems and practical methodological issues still limit their full application. Here, we examine the challenges in this research field and highlight new perspectives based on interdisciplinary research.
Paolo Benettin, Till H. M. Volkmann, Jana von Freyberg, Jay Frentress, Daniele Penna, Todd E. Dawson, and James W. Kirchner
Hydrol. Earth Syst. Sci., 22, 2881–2890, https://doi.org/10.5194/hess-22-2881-2018, https://doi.org/10.5194/hess-22-2881-2018, 2018
Short summary
Short summary
Evaporation causes the isotopic composition of soil water to become different from that of the original precipitation source. If multiple samples originating from the same source are available, they can be used to reconstruct the original source composition. However, soil water is influenced by seasonal variability in both precipitation sources and evaporation patterns. We show that this variability, if not accounted for, can lead to biased estimates of the precipitation source water.
Izabela Bujak-Ozga, Jana von Freyberg, Margaret Zimmer, Andrea Rinaldo, Paolo Benettin, and Ilja van Meerveld
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-67, https://doi.org/10.5194/hess-2024-67, 2024
Preprint under review for HESS
Short summary
Short summary
Stream networks expand and contract affecting the amount and quality of water in perennial streams. This study presents measurements of changes in water chemistry and the flowing portion of the drainage network during rainfall events in two neighboring catchments. Despite the proximity, similar size, soil and bedrock, water chemistry and stream network dynamics differed substantially for the two catchments. These differences are attributed to the differences in slope and channel network.
Matthias Sprenger, Pilar Llorens, Francesc Gallart, Paolo Benettin, Scott T. Allen, and Jérôme Latron
Hydrol. Earth Syst. Sci., 26, 4093–4107, https://doi.org/10.5194/hess-26-4093-2022, https://doi.org/10.5194/hess-26-4093-2022, 2022
Short summary
Short summary
Our catchment-scale transit time modeling study shows that including stable isotope data on evapotranspiration in addition to the commonly used stream water isotopes helps constrain the model parametrization and reveals that the water taken up by plants has resided longer in the catchment storage than the water leaving the catchment as stream discharge. This finding is important for our understanding of how water is stored and released, which impacts the water availability for plants and humans.
Magali F. Nehemy, Paolo Benettin, Mitra Asadollahi, Dyan Pratt, Andrea Rinaldo, and Jeffrey J. McDonnell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-528, https://doi.org/10.5194/hess-2019-528, 2019
Preprint withdrawn
Tristan Salles, Patrice Rey, and Enrico Bertuzzo
Earth Surf. Dynam., 7, 895–910, https://doi.org/10.5194/esurf-7-895-2019, https://doi.org/10.5194/esurf-7-895-2019, 2019
Short summary
Short summary
Mountainous landscapes have long been recognized as potential drivers for genetic drift, speciation, and ecological resilience. We present a novel approach that can be used to assess and quantify drivers of biodiversity, speciation, and endemism over geological time. Using coupled climate–landscape models, we show that biodiversity under tectonic and climatic forcing relates to landscape dynamics and that landscape complexity drives species richness through orogenic history.
Daniele Penna, Luisa Hopp, Francesca Scandellari, Scott T. Allen, Paolo Benettin, Matthias Beyer, Josie Geris, Julian Klaus, John D. Marshall, Luitgard Schwendenmann, Till H. M. Volkmann, Jana von Freyberg, Anam Amin, Natalie Ceperley, Michael Engel, Jay Frentress, Yamuna Giambastiani, Jeff J. McDonnell, Giulia Zuecco, Pilar Llorens, Rolf T. W. Siegwolf, Todd E. Dawson, and James W. Kirchner
Biogeosciences, 15, 6399–6415, https://doi.org/10.5194/bg-15-6399-2018, https://doi.org/10.5194/bg-15-6399-2018, 2018
Short summary
Short summary
Understanding how water flows through ecosystems is needed to provide society and policymakers with the scientific background to manage water resources sustainably. Stable isotopes of hydrogen and oxygen in water are a powerful tool for tracking water fluxes, although the heterogeneity of natural systems and practical methodological issues still limit their full application. Here, we examine the challenges in this research field and highlight new perspectives based on interdisciplinary research.
Paolo Benettin, Till H. M. Volkmann, Jana von Freyberg, Jay Frentress, Daniele Penna, Todd E. Dawson, and James W. Kirchner
Hydrol. Earth Syst. Sci., 22, 2881–2890, https://doi.org/10.5194/hess-22-2881-2018, https://doi.org/10.5194/hess-22-2881-2018, 2018
Short summary
Short summary
Evaporation causes the isotopic composition of soil water to become different from that of the original precipitation source. If multiple samples originating from the same source are available, they can be used to reconstruct the original source composition. However, soil water is influenced by seasonal variability in both precipitation sources and evaporation patterns. We show that this variability, if not accounted for, can lead to biased estimates of the precipitation source water.
B. Schaefli, L. Nicótina, C. Imfeld, P. Da Ronco, E. Bertuzzo, and A. Rinaldo
Geosci. Model Dev., 7, 2733–2746, https://doi.org/10.5194/gmd-7-2733-2014, https://doi.org/10.5194/gmd-7-2733-2014, 2014
Short summary
Short summary
This paper presents the Spatially Explicit Hydrologic Response of the Laboratory of Ecohydrology of the Ecole Polytechnique Fédérale de Lausanne for hydrologic simulation at the catchment scale. It simulates the mobilization of water at the subcatchment scale and the transport to the outlet through a convolution with the river network. We discuss the parameter estimation and model performance for discharge simulation in the high Alpine Dischmabach catchment (Switzerland).
Related subject area
Hydrology
Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Reservoir Assessment Tool Version 3.0: A Scalable and User-Friendly Software Platform to Mobilize the Global Water Management Community
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
HydroFATE (v1): A high-resolution contaminant fate model for the global river system
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
SIMO v1.0: simplified model of the vertical temperature profile in a small, warm, monomictic lake
Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling
Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation
A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
Wflow_sbm v0.6.1, a spatially distributed hydrologic model: from global data to local applications
Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains
The eWaterCycle platform for open and FAIR hydrological collaboration
Evaluating the Atibaia River hydrology using JULES6.1
A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-229, https://doi.org/10.5194/gmd-2023-229, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-130, https://doi.org/10.5194/gmd-2023-130, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
The Reservoir Assessment Tool (RAT) version 3.0 represents a scalable and customizable software based on hydrologic modeling and satellite remote sensing to monitor the reservoir's dynamic state. The architecture of RAT 3.0 has been designed in such a way that it requires minimal user input with additional flexibility added for the more advanced users. It is more robust and less susceptible to data gaps or instability that satellite remote sensing systems can sometimes experience.
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
Short summary
Short summary
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.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
EGUsphere, https://doi.org/10.5194/egusphere-2023-1590, https://doi.org/10.5194/egusphere-2023-1590, 2023
Short summary
Short summary
Pharmaceuticals and household chemicals released into surface waters through wastewater pose risks to aquatic ecosystems and human health. HydroFATE, a new global model, estimates contaminant concentrations in rivers, helping identify areas of elevated exposure. It predicted concentrations above ecological thresholds of the antibiotic sulfamethoxazole in 390,000 km of rivers worldwide. HydroFATE can guide monitoring and mitigation efforts to safeguard water systems and human well-being.
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
Short summary
Short summary
This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Ji Li, Daoxian Yuan, Fuxi Zhang, Jiao Liu, and Mingguo Ma
Geosci. Model Dev., 15, 6581–6600, https://doi.org/10.5194/gmd-15-6581-2022, https://doi.org/10.5194/gmd-15-6581-2022, 2022
Short summary
Short summary
A new karst hydrological model (the QMG model) is developed to simulate and predict the floods in karst trough valley basins. Unlike the complex structure and parameters of current karst groundwater models, this model has a simple double-layered structure with few parameters and decreases the demand for modeling data in karst areas. The flood simulation results based on the QMG model of the Qingmuguan karst trough valley basin are satisfactory, indicating the suitability of the model simulation.
Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
Geosci. Model Dev., 15, 6359–6369, https://doi.org/10.5194/gmd-15-6359-2022, https://doi.org/10.5194/gmd-15-6359-2022, 2022
Short summary
Short summary
MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
Short summary
Short summary
Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
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. Discuss., https://doi.org/10.5194/gmd-2022-182, https://doi.org/10.5194/gmd-2022-182, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
We present the wflow_sbm distributed hydrologic 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 run-time 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.
Suyeon Choi and Yeonjoo Kim
Geosci. Model Dev., 15, 5967–5985, https://doi.org/10.5194/gmd-15-5967-2022, https://doi.org/10.5194/gmd-15-5967-2022, 2022
Short summary
Short summary
Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
Short summary
Short summary
With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
Short summary
Short summary
Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Cited articles
Benettin, P., Rinaldo, A., and Botter, G.: Kinematics of age mixing in
advection-dispersion models, Water Resour. Res., 49, 8539–8551,
https://doi.org/10.1002/2013WR014708, 2013. a
Benettin, P., Bailey, S. W., Campbell, J. L., Green, M. B., Rinaldo, A.,
Likens, G. E., McGuire, K. J., and Botter, G.: Linking water age and solute
dynamics in streamflow at the Hubbard Brook Experimental Forest, NH, USA,
Water Resour. Res., 51, 9256–9272, https://doi.org/10.1002/2015WR017552, 2015a. a, b
Benettin, P., Rinaldo, A., and Botter, G.: Tracking residence times in
hydrological systems: forward and backward formulations, Hydrol. Proc.,
29, 5203–5213, https://doi.org/10.1002/hyp.10513, 2015b. a, b
Benettin, P., Bailey, S. W., Rinaldo, A., Likens, G. E., McGuire, K. J., and
Botter, G.: Young runoff fractions control streamwater age and solute
concentration dynamics, Hydrol. Proc., 31, 2982–2986,
https://doi.org/10.1002/hyp.11243, 2017a. a
Benettin, P., Soulsby, C., Birkel, C., Tetzlaff, D., Botter, G., and Rinaldo,
A.: Using SAS functions and high resolution isotope data to unravel travel
time distributions in headwater catchments, Water Resour. Res., 53,
1864–1878, https://doi.org/10.1002/2016WR020117, 2017b. a, b, c, d
Bertuzzo, E., Thomet, M., Botter, G., and Rinaldo, A.: Catchment-scale
herbicides transport: Theory and application, Adv. Water Resour., 52,
232–242, https://doi.org/10.1016/j.advwatres.2012.11.007, 2013. a, b
Botter, G.: Catchment mixing processes and travel time distributions,
Water Resour. Res., 48, W05545, https://doi.org/10.1029/2011WR011160, 2012. a
Botter, G., Settin, T., Marani, M., and Rinaldo, A.: A stochastic model of
nitrate transport and cycling at basin scale, Water Resour. Res., 42, W04415,
https://doi.org/10.1029/2005WR004599, 2006. a
Botter, G., Bertuzzo, E., Bellin, A., and Rinaldo, A.: On the Lagrangian
formulations of reactive solute transport in the hydrologic response, Water
Resour. Res., 41, W04008, https://doi.org/10.1029/2004WR003544, 2005. a
Calabrese, S. and Porporato, A.: Linking age, survival, and transit time
distributions, Water Resour. Res., 51, 8316–8330,
https://doi.org/10.1002/2015WR017785, 2015. a
Cvetkovic, V. and Dagan, G.: Transport of kinetically sorbing solute by
steady random velocity in heterogeneous porous formations, J. Fluid Mech.,
265, 189–215, https://doi.org/10.1017/S0022112094000807, 1994. a
Danesh-Yazdi, M., Foufoula-Georgiou, E., Karwan, D. L., and Botter, G.:
Inferring changes in water cycle dynamics of intensively managed landscapes
via the theory of time-variant travel time distributions, Water Resour. Res.,
52, 7593–7614, https://doi.org/10.1002/2016WR019091, 2016. a, b
Danesh-Yazdi, M., Botter, G., and Foufoula-Georgiou, E.: Time-variant
Lagrangian transport formulation reduces aggregation bias of water and solute
mean travel time in heterogeneous catchments, Geophys. Res. Lett., 44,
4880–4888, https://doi.org/10.1002/2017GL073827, 2017. a
Destouni, G., Persson, K., Prieto, C., and Jarsjö, J.: General
Quantification of Catchment-Scale Nutrient and Pollutant Transport through
the Subsurface to Surface and Coastal Waters, Environ. Sci. Technol., 44,
2048–2055, https://doi.org/10.1021/es902338y, 2010. a
Drever, M. C. and Hrachowitz, M.: Migration as flow: using hydrological
concepts to estimate the residence time of migrating birds from the daily
counts, Methods Ecol. Evol., 8, 1146–1157, https://doi.org/10.1111/2041-210X.12727,
2017. a, b
Harman, C. J., Ward, A. S., and Ball, A.: How does reach-scale
stream-hyporheic transport vary with discharge? Insights from rSAS analysis
of sequential tracer injections in a headwater mountain stream, Water Resour.
Res., 52, 7130–7150, https://doi.org/10.1002/2016WR018832, 2016. a
Hrachowitz, M., Fovet, O., Ruiz, L., and Savenije, H. H. G.: Transit time
distributions, legacy contamination and variability in biogeochemical
1∕fα scaling: how are hydrological response dynamics linked to water
quality at the catchment scale?, Hydrol. Proc., 29, 5241–5256,
https://doi.org/10.1002/hyp.10546, 2015. a
Hrachowitz, M., Benettin, P., Breukelen, B. M. V., Fovet, O., Howden, N.
J. K., Ruiz, L., Velde, Y. V. D., and Wade, A. J.: Transit times –the link
between hydrology and water quality at the catchment scale, WIRES Water, 3,
629–657, https://doi.org/10.1002/wat2.1155, 2016. a
Jackson, B., Wheater, H., Wade, A., Butterfield, D., Mathias, S., Ireson, A.,
Butler, A., McIntyre, N., and Whitehead, P.: Catchment-scale modelling of
flow and nutrient transport in the Chalk unsaturated zone, Ecol. Model., 209,
41–52, https://doi.org/10.1016/j.ecolmodel.2007.07.005, 2007. a
Kauffman, S. J., Royer, D. L., Chang, S., and Berner, R. A.: Export of
chloride after clear-cutting in the Hubbard Brook sandbox experiment,
Biogeochemistry, 63, 23–33, https://doi.org/10.1023/A:1023335002926, 2003. a
Kim, M., Pangle, L. A., Cardoso, C., Lora, M., Volkmann, T. H. M., Wang, Y.,
Harman, C. J., and Troch, P. A.: Transit time distributions and StorAge
Selection functions in a sloping soil lysimeter with time-varying flow paths:
Direct observation of internal and external transport variability, Water
Resour. Res., 52, 7105–7129, https://doi.org/10.1002/2016WR018620, 2016. a, b
Lutz, S. R., Velde, Y. V. D., Elsayed, O. F., Imfeld, G., Lefrancq, M.,
Payraudeau, S., and van Breukelen, B. M.: Pesticide fate on catchment scale:
conceptual modelling of stream CSIA data, Hydrol. Earth Syst. Sci., 21,
5243–5261, https://doi.org/10.5194/hess-21-5243-2017, 2017. a
Maher, K.: The role of fluid residence time and topographic scales in
determining chemical fluxes from landscapes, Earth Planet. Sc. Lett., 312,
48–58, https://doi.org/10.1016/j.epsl.2011.09.040, 2011. a
Maloszewski, P. and Zuber, A.: Principles and practice of calibration and
validation of mathematical models for the interpretation of environmental
tracer data in aquifers, Adv. Water Resour., 16, 173–190,
https://doi.org/10.1016/0309-1708(93)90036-F, 1993. a
Martin, C., Aquilina, L., Gascuel-Odoux, C., Molénat, J., Faucheux, M.,
and Ruiz, L.: Seasonal and interannual variations of nitrate and chloride in
stream waters related to spatial and temporal patterns of groundwater
concentrations in agricultural catchments, Hydrol. Proc., 18, 1237–1254,
https://doi.org/10.1002/hyp.1395, 2004. a
McGuire, K. J. and McDonnell, J. J.: A review and evaluation of catchment
transit time modeling, J. Hydrol., 330, 543–563,
https://doi.org/10.1016/j.jhydrol.2006.04.020, 2006. a
McGuire, K. J. and McDonnell, J. J.: Hydrological connectivity of hillslopes
and streams: Characteristic time scales and nonlinearities, Water Resour.
Res., 46, W10543,https://doi.org/10.1029/2010WR009341, 2010. a
McMillan, H., Tetzlaff, D., Clark, M., and Soulsby, C.: Do time-variable
tracers aid the evaluation of hydrological model structure? A multimodel
approach, Water Resour. Res., 48, W05501, https://doi.org/10.1029/2011WR011688, 2012. a
Oda, T., Asano, Y., and Suzuki, M.: Transit time evaluation using a chloride
concentration input step shift after forest cutting in a Japanese headwater
catchment, Hydrol. Proc., 23, 2705–2713, https://doi.org/10.1002/hyp.7361, 2009. a
Pangle, L. A., Kim, M., Cardoso, C., Lora, M., Meira Neto, A. A., Volkmann,
T. H. M., Wang, Y., Troch, P. A., and Harman, C. J.: The mechanistic basis
for storage-dependent age distributions of water discharged from an
experimental hillslope, Water Resour. Res., 53, 2733–2754,
https://doi.org/10.1002/2016WR019901, 2017. a
Queloz, P., Bertuzzo, E., Carraro, L., Botter, G., Miglietta, F., Rao, P.,
and Rinaldo, A.: Transport of fluorobenzoate tracers in a vegetated
hydrologic control volume: 1. Experimental results, Water Resour. Res., 51,
2773–2792, https://doi.org/10.1002/2014WR016433, 2015a. a
Rigon, R., Bancheri, M., and Green, T. R.: Age-ranked hydrological budgets
and a travel time description of catchment hydrology, Hydrol. Earth Syst.
Sci., 20, 4929–4947, https://doi.org/10.5194/hess-20-4929-2016, 2016. a
Rinaldo, A. and Marani, A.: Basin scale-model of solute transport, Water
Resour. Res., 23, 2107–2118, https://doi.org/10.1029/WR023i011p02107, 1987. a, b
Shampine, L. F. and Reichelt, M. W.: The MATLAB ODE Suite, SIAM J. Sci.
Comput., 18, 1–22, https://doi.org/10.1137/S1064827594276424, 1997. a
Soulsby, C., Birkel, C., Geris, J., and Tetzlaff, D.: Spatial aggregation of
time-variant stream water ages in urbanizing catchments, Hydrol. Proc., 29,
3038–3050, https://doi.org/10.1002/hyp.10500, 2015. a
ter Braak, C. J. F. and Vrugt, J. A.: Differential Evolution Markov Chain
with snooker updater and fewer chains, Stat. Comput., 18, 435–446,
https://doi.org/10.1007/s11222-008-9104-9, 2008. a
van der Velde, Y., Heidbüchel, I., Lyon, S. W., Nyberg, L., Rodhe, A.,
Bishop, K., and Troch, P. A.: Consequences of mixing assumptions for
time-variable travel time distributions, Hydrol. Proc., 29, 3460–3474,
https://doi.org/10.1002/hyp.10372, 2015. a, b, c
van der Velde, Y., de Rooij, G. H., Rozemeijer, J. C., van Geer, F. C., and
Broers, H. P.: Nitrate response of a lowland catchment: On the relation
between stream concentration and travel time distribution dynamics, Water
Resour. Res., 46, W11534, https://doi.org/10.1029/2010WR009105, 2010. a
Vrugt, J., Braak, C. T., Diks, C., Robinson, B., Hyman, J., and Higdon, D.:
Accelerating Markov chain Monte Carlo simulation by differential evolution
with self-adaptive randomized subspace sampling, Int. J. Nonlin. Sci. Num.,
10, 271–288, https://doi.org/10.1515/IJNSNS.2009.10.3.273, 2009. a
Weiler, M., McGlynn, B. L., McGuire, K. J., and McDonnell, J. J.: How does
rainfall become runoff? A combined tracer and runoff transfer function
approach, Water Resour. Res., 39, 1315, https://doi.org/10.1029/2003WR002331, 2003. a
Wilusz, D. C., Harman, C. J., and Ball, W. P.: Sensitivity of Catchment
Transit Times to Rainfall Variability Under Present and Future Climates,
Water Resour. Res., 53, 10231–10256, https://doi.org/10.1002/2017WR020894, 2017. a, b, c, d
Short summary
Solutes introduced in the environment are transported by water to streams and lakes. The tran-SAS package includes a set of codes to model this process for entire watersheds by using the concept of water residence times, i.e. the time that water takes to move through the landscape. Results show that the model is implemented efficiently and it can be used to simulate solute transport in a number of different conditions.
Solutes introduced in the environment are transported by water to streams and lakes. The...
