Articles | Volume 14, issue 11
https://doi.org/10.5194/gmd-14-6893-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-6893-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
15 Nov 2021
Model description paper |
| 15 Nov 2021
| 15 Nov 2021
DRYP 1.0: a parsimonious hydrological model of DRYland Partitioning of the water balance
E. Andrés Quichimbo
CORRESPONDING AUTHOR
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, CF10 3AT, UK
Michael Bliss Singer
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, CF10 3AT, UK
Water Research Institute, Cardiff University, Cardiff, CF10 3AX, UK
Earth Research Institute, University of California Santa Barbara,
Santa Barbara, California, USA
Katerina Michaelides
School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
Earth Research Institute, University of California Santa Barbara,
Santa Barbara, California, USA
Cabot Institute for the Environment, University of Bristol, Bristol, BS8 1QU, UK
Daniel E. J. Hobley
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, CF10 3AT, UK
ADAS RSK Ltd, Bristol, BS3 4EB, UK
Rafael Rosolem
Cabot Institute for the Environment, University of Bristol, Bristol, BS8 1QU, UK
Faculty of Engineering, University of Bristol, Clifton, BS8 1TR, UK
Mark O. Cuthbert
School of Earth and Environmental Sciences, Cardiff University,
Cardiff, CF10 3AT, UK
Water Research Institute, Cardiff University, Cardiff, CF10 3AX, UK
School of Civil and Environmental Engineering, The University of New
South Wales, Sydney, New South Wales, Australia
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Mostaquimur Rahman and Rafael Rosolem
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Modelling water flow through chalk (a fine-grained porous medium traversed by fractures) is important for optimizing water resource management practices in the UK. However, efficient simulations of water movement through chalk are difficult due to the porous nature of chalk, creating high-velocity preferential flow paths. This paper describes a novel approach to representing chalk hydrology in land surface modelling for large-scale applications.
Daniel E. J. Hobley, Jordan M. Adams, Sai Siddhartha Nudurupati, Eric W. H. Hutton, Nicole M. Gasparini, Erkan Istanbulluoglu, and Gregory E. Tucker
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Many geoscientists use computer models to understand changes in the Earth's system. However, typically each scientist will build their own model from scratch. This paper describes Landlab, a new piece of open-source software designed to simplify creation and use of models of the Earth's surface. It provides off-the-shelf tools to work with models more efficiently, with less duplication of effort. The paper explains and justifies how Landlab works, and describes some models built with it.
Gregory E. Tucker, Daniel E. J. Hobley, Eric Hutton, Nicole M. Gasparini, Erkan Istanbulluoglu, Jordan M. Adams, and Sai Siddartha Nudurupati
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C. E. M. Lloyd, K. Michaelides, D. R. Chadwick, J. A. J. Dungait, and R. P. Evershed
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A. F. Charteris, T. D. J. Knowles, K. Michaelides, and R. P. Evershed
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Revised manuscript not accepted
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DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
J. Iwema, R. Rosolem, R. Baatz, T. Wagener, and H. R. Bogena
Hydrol. Earth Syst. Sci., 19, 3203–3216, https://doi.org/10.5194/hess-19-3203-2015, https://doi.org/10.5194/hess-19-3203-2015, 2015
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The cosmic-ray neutron sensor can provide soil moisture content averages over areas of roughly half a kilometre by half a kilometre. Although this sensor is usually calibrated using soil samples taken on a single day, we found that multiple sampling days are needed. The calibration results were also affected by the soil wetness conditions of the sampling days. The outcome of this study will help researchers to calibrate/validate new cosmic-ray neutron sensor sites more accurately.
P. T. S. Oliveira, E. Wendland, M. A. Nearing, R. L. Scott, R. Rosolem, and H. R. da Rocha
Hydrol. Earth Syst. Sci., 19, 2899–2910, https://doi.org/10.5194/hess-19-2899-2015, https://doi.org/10.5194/hess-19-2899-2015, 2015
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We determined the main components of the water balance for an undisturbed cerrado.
Evapotranspiration ranged from 1.91 to 2.60mm per day for the dry and wet seasons, respectively. Canopy interception ranged from 4 to 20% and stemflow values were approximately 1% of gross precipitation.
The average runoff coefficient was less than 1%, while cerrado deforestation has the potential to increase that amount up to 20-fold.
The water storage may be estimated by the difference between P and ET.
A. Hartmann, T. Gleeson, R. Rosolem, F. Pianosi, Y. Wada, and T. Wagener
Geosci. Model Dev., 8, 1729–1746, https://doi.org/10.5194/gmd-8-1729-2015, https://doi.org/10.5194/gmd-8-1729-2015, 2015
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We present a new approach to assess karstic groundwater recharge over Europe and the Mediterranean. Cluster analysis is used to subdivide all karst regions into four typical karst landscapes and to simulate karst recharge with a process-based karst model. We estimate its parameters by a combination of a priori information and observations of soil moisture and evapotranspiration. Independent observations of recharge that present large-scale models significantly under-estimate karstic recharge.
X. Han, H.-J. H. Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 615–629, https://doi.org/10.5194/hess-19-615-2015, https://doi.org/10.5194/hess-19-615-2015, 2015
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This paper presents the joint assimilation of cosmic-ray neutron counts and land surface temperature with parameter estimation of leaf area index at an irrigated corn field. The results show that the data assimilation can reduce the systematic input errors due to the lack of irrigation data. The estimations of soil moisture, evapotranspiration and leaf area index can be improved in the joint assimilation framework.
R. Rosolem, T. Hoar, A. Arellano, J. L. Anderson, W. J. Shuttleworth, X. Zeng, and T. E. Franz
Hydrol. Earth Syst. Sci., 18, 4363–4379, https://doi.org/10.5194/hess-18-4363-2014, https://doi.org/10.5194/hess-18-4363-2014, 2014
J. Shuttleworth, R. Rosolem, M. Zreda, and T. Franz
Hydrol. Earth Syst. Sci., 17, 3205–3217, https://doi.org/10.5194/hess-17-3205-2013, https://doi.org/10.5194/hess-17-3205-2013, 2013
T. E. Franz, M. Zreda, R. Rosolem, and T. P. A. Ferre
Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, https://doi.org/10.5194/hess-17-453-2013, 2013
Related subject area
Hydrology
HydroFATE (v1): a high-resolution contaminant fate model for the global river system
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
Modelling water quantity and quality for integrated water cycle management with the WSIMOD software
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
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
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.
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
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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.
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.
Barnaby Dobson, Leyang Liu, and Ana Mijic
EGUsphere, https://doi.org/10.5194/egusphere-2023-1662, https://doi.org/10.5194/egusphere-2023-1662, 2023
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Water management is challenging when models don't capture the entire water cycle. We propose using integrated models facilitates management and improves understanding. Thus, we introduce a software tool designed for this task. We discuss its foundation, how it simulates water system components and their interactions, and its customization. We provide a flexible way to represent water systems, and we hope it will inspire more research and practical applications for sustainable water management.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
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Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
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Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
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NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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.
Cited articles
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and
Rasmussen, J.: An introduction to the European Hydrological System –
Systeme Hydrologique Europeen, “SHE”, 2: Structure of a physically-based,
distributed modelling system, J. Hydrol., 87, 61–77,
https://doi.org/10.1016/0022-1694(86)90115-0, 1986.
Abdulrazzak, M. J.: Losses of flood water from alluvial channels, Arid Soil
Res. Rehab., 9, 15–24, https://doi.org/10.1080/15324989509385870, 1995.
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008.
Albergel, C., Dutra, E., Munier, S., Calvet, J.-C., Munoz-Sabater, J., de Rosnay, P., and Balsamo, G.: ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better?, Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, 2018.
Alfieri, L., Lorini, V., Hirpa, F. A., Harrigan, S., Zsoter, E., Prudhomme,
C., and Salamon, P.: A global streamflow reanalysis for 1980–2018, J.
Hydrol. X, 6, 100049, https://doi.org/10.1016/j.hydroa.2019.100049, 2020.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop
evapotranspiration-Guidelines for computing crop water requirements-FAO
Irrigation and drainage paper 56, FAO Rome, 300, D05109, 1998.
Anderson, M. P., Woessner, W. W., and Hunt, R. J.: Applied Groundwater
Modeling: Simulation of Flow and Advective Transport, Academic Press – Elsevier, the Netherlands, 632 pp., 2015.
Aryal, S. K., Silberstein, R. P., Fu, G., Hodgson, G., Charles, S. P., and
McFarlane, D.: Understanding spatio-temporal rainfall-runoff changes in a
semi-arid region, Hydrol. Process., 34, 2510–2530,
https://doi.org/10.1002/hyp.13744, 2020.
Assouline, S.: Infiltration into soils: Conceptual approaches and solutions,
Water Resour. Res., 49, 1755–1772, https://doi.org/10.1002/wrcr.20155,
2013.
Atmospheric and Geospace Sciences Division of the National Science Foundation: Kendall, available at: http://cosmos.hwr.arizona.edu/Probes/StationDat/010/index.php, last access: 20 June 2021.
Bakker, M., Post, V., Langevin, C. D., Hughes, J. D., White, J., Starn, J.,
and Fienen, M. N.: FloPy: Python package for creating, running, and
post-processing MODFLOW-based models, U.S. Geological Survey,
https://doi.org/10.5066/F7BK19FH, 2016a.
Bakker, M., Post, V., Langevin, C. D., Hughes, J. D., White, J. T., Starn,
J. J., and Fienen, M. N.: Scripting MODFLOW Model Development Using Python
and FloPy, Groundwater, 54, 733–739, https://doi.org/10.1111/gwat.12413,
2016b.
Barnhart, K. R., Hutton, E. W. H., Tucker, G. E., Gasparini, N. M., Istanbulluoglu, E., Hobley, D. E. J., Lyons, N. J., Mouchene, M., Nudurupati, S. S., Adams, J. M., and Bandaragoda, C.: Short communication: Landlab v2.0: a software package for Earth surface dynamics, Earth Surf. Dynam., 8, 379–397, https://doi.org/10.5194/esurf-8-379-2020, 2020.
Batelaan, O. and Smedt, F. D.: SEEPAGE, a New MODFLOW DRAIN Package,
Groundwater, 42, 576–588,
https://doi.org/10.1111/j.1745-6584.2004.tb02626.x, 2004.
Batelis, S.-C., Rahman, M., Kollet, S., Woods, R., and Rosolem, R.: Towards
the representation of groundwater in the Joint UK Land Environment
Simulator, Hydrol. Process., 34, 2843–2863,
https://doi.org/10.1002/hyp.13767, 2020.
Becker, R., Gebremichael, M., and Märker, M.: Impact of soil surface and
subsurface properties on soil saturated hydraulic conductivity in the
semi-arid Walnut Gulch Experimental Watershed, Arizona, USA, Geoderma, 322,
112–120, https://doi.org/10.1016/j.geoderma.2018.02.023, 2018.
Beven, K. and Binley, A.: The future of distributed models: model
calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
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.
Brooks, R. H. and Corey, A. T.: Hydraulic Properties of Porous Media,
Hydrology Paper No. 3, Fort Collins,
Colorado State University, 40 pp., 1964.
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface–Hydrology Model
with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation
and Sensitivity, Mon. Weather Rev., 129, 569–585,
https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001.
Cherlet, M., Hutchinson, C., Reynolds, J., Hill, J., Sommer, S., and von
Maltitz, G.: World atlas of desertification, Publication Office
of the European Union, Luxembourg, 3rd ed., 295 pp., 2018.
Chow, V. T., Maidment, D. R., and Mays, L. W.: Applied Hydrology, McGraw-Hill Companies, Singapore, 588 pp., 1988.
Clapp, R. B. and Hornberger, G. M.: Empirical equations for some soil
hydraulic properties, Water Resour. Res., 14, 601–604,
https://doi.org/10.1029/WR014i004p00601, 1978.
Clark, M. P., Fan, Y., Lawrence, D. M., Adam, J. C., Bolster, D., Gochis, D.
J., Hooper, R. P., Kumar, M., Leung, L. R., Mackay, D. S., Maxwell, R. M.,
Shen, C., Swenson, S. C., and Zeng, X.: Improving the representation of
hydrologic processes in Earth System Models, Water Resour. Res., 51,
5929–5956, https://doi.org/10.1002/2015WR017096, 2015.
Coes, A. L. and Pool, D. R.: Ephemeral-stream channel and basin-floor
infiltration and recharge in the Sierra Vista subwatershed of the Upper San
Pedro Basin, Southeastern Arizona: Chapter J in Ground-water recharge in the
arid and semiarid southwestern United States, Professional Paper 1703, U.S.
Geological Survey, 2007.
Craig, J. R., Liu, G., and Soulis, E. D.: Runoff–infiltration partitioning
using an upscaled Green–Ampt solution, Hydrol. Process., 24, 2328–2334,
https://doi.org/10.1002/hyp.7601, 2010.
Cuthbert, M. O., Acworth, R. I., Andersen, M. S., Larsen, J. R., McCallum,
A. M., Rau, G. C., and Tellam, J. H.: Understanding and quantifying focused,
indirect groundwater recharge from ephemeral streams using water table
fluctuations, Water Resour. Res., 52, 827–840,
https://doi.org/10.1002/2015WR017503, 2016.
Cuthbert, M. O., Gleeson, T., Moosdorf, N., Befus, K. M., Schneider, A.,
Hartmann, J., and Lehner, B.: Global patterns and dynamics of
climate–groundwater interactions, Nat. Clim. Change, 9, 137–141,
https://doi.org/10.1038/s41558-018-0386-4, 2019a.
Cuthbert, M. O., Taylor, R. G., Favreau, G., Todd, M. C., Shamsudduha, M.,
Villholth, K. G., MacDonald, A. M., Scanlon, B. R., Kotchoni, D. O. V.,
Vouillamoz, J.-M., Lawson, F. M. A., Adjomayi, P. A., Kashaigili, J.,
Seddon, D., Sorensen, J. P. R., Ebrahim, G. Y., Owor, M., Nyenje, P. M.,
Nazoumou, Y., Goni, I., Ousmane, B. I., Sibanda, T., Ascott, M. J.,
Macdonald, D. M. J., Agyekum, W., Koussoubé, Y., Wanke, H., Kim, H.,
Wada, Y., Lo, M.-H., Oki, T., and Kukuric, N.: Observed controls on
resilience of groundwater to climate variability in sub-Saharan Africa,
Nature, 572, 230–234, https://doi.org/10.1038/s41586-019-1441-7, 2019b.
Dai, Y., Xin, Q., Wei, N., Zhang, Y., Shangguan, W., Yuan, H., Zhang, S.,
Liu, S., and Lu, X.: A Global High-Resolution Data Set of Soil Hydraulic and
Thermal Properties for Land Surface Modeling, J. Adv. Model. Earth Sy.,
11, 2996–3023, https://doi.org/10.1029/2019MS001784, 2019.
Datry, T., Bonada, N., and Boulton, A. (Eds.): Intermittent Rivers and
Ephemeral Streams, Ecology and Management, Academic Press – Elsevier, the Netherlands,
https://doi.org/10.1016/B978-0-12-803835-2.09997-6, 2017.
de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., and Bierkens, M. F. P.: A high-resolution global-scale groundwater model, Hydrol. Earth Syst. Sci., 19, 823–837, https://doi.org/10.5194/hess-19-823-2015, 2015.
Desilets, D. and Zreda, M.: Footprint diameter for a cosmic-ray soil
moisture probe: Theory and Monte Carlo simulations, Water Resour. Res., 49,
3566–3575, https://doi.org/10.1002/wrcr.20187, 2013.
Desilets, D., Zreda, M., and Ferré, T. P. A.: Nature’s neutron probe: Land surface hydrology at an elusive scale with cosmic rays, Water Resour. Res., 46, W11505, https://doi.org/10.1029/2009WR008726, 2010.
Emmerich, W. E. and Verdugo, C. L.: Long-term carbon dioxide and water flux
database, Walnut Gulch Experimental Watershed, Arizona, United States, Water
Resour. Res., 44, W05S09, https://doi.org/10.1029/2006WR005693, 2008.
European Centre for Medium-Range Weather Forecasts: ERA5 hourly data, ECMWF [data set], available at:
https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form (last access: 20 June 2021), 2018.
Ewen, J., Parkin, G., and O'Connell, P. E.: SHETRAN: Distributed River Basin
Flow and Transport Modeling System, J. Hydrol. Eng., 5, 250–258,
https://doi.org/10.1061/(ASCE)1084-0699(2000)5:3(250), 2000.
Fan, Y., Li, H., and Miguez-Macho, G.: Global Patterns of Groundwater Table
Depth, Science, 339, 940–943, https://doi.org/10.1126/science.1229881,
2013.
Franz, T. E., Zreda, M., Ferre, T. P. A., Rosolem, R., Zweck, C., Stillman,
S., Zeng, X., and Shuttleworth, W. J.: Measurement depth of the cosmic ray
soil moisture probe affected by hydrogen from various sources, Water Resour.
Res., 48, W08515, https://doi.org/10.1029/2012WR011871, 2012.
Franz, T. E., Zreda, M., Rosolem, R., and Ferre, T. P. A.: A universal calibration function for determination of soil moisture with cosmic-ray neutrons, Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, 2013.
Giordano, M.: Global Groundwater? Issues and Solutions, Annu. Rev. Env.
Resour., 34, 153–178,
https://doi.org/10.1146/annurev.environ.030308.100251, 2009.
Goodrich, D. C., Lane, L. J., Shillito, R. M., Miller, S. N., Syed, K. H.,
and Woolhiser, D. A.: Linearity of basin response as a function of scale in
a semiarid watershed, Water Resour. Res., 33, 2951–2965,
https://doi.org/10.1029/97WR01422, 1997.
Goodrich, D. C., Keefer, T. O., Unkrich, C. L., Nichols, M. H., Osborn, H.
B., Stone, J. J., and Smith, J. R.: Long-term precipitation database, Walnut
Gulch Experimental Watershed, Arizona, United States, Water Resour. Res.,
44, W08515, https://doi.org/10.1029/2006WR005782, 2008.
Goodrich, D. C., Williams, D. G., Unkrich, C. L., Hogan, J. F., Scott, R.
L., Hultine, K. R., Pool, D., Goes, A. L., and Miller, S.: Comparison of
Methods to Estimate Ephemeral Channel Recharge, Walnut Gulch, San Pedro
River Basin, Arizona, in: Groundwater Recharge in a Desert Environment: The
Southwestern United States, American Geophysical Union (AGU), 77–99,
2013.
Goodrich, D. C., Kepner, W. G., Levick, L. R., and Wigington, P. J.:
Southwestern Intermittent and Ephemeral Stream Connectivity, JAWRA J. Am.
Water Resour. Assoc., 54, 400–422, https://doi.org/10.1111/1752-1688.12636,
2018.
Harbaugh, A. W.: MODFLOW-2005, The U.S. Geological Survey Modular
Ground-Water Model – the Ground-Water Flow Process, U.S. Geological Survey
Techniques and Methods 6-A16, 2005.
Harbaugh, A. W., Banta, E. R., Hill, M. C., and McDonald, M. G.: MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model – User Guide to Modularization Concepts and the Ground-Water Flow Process, Geological Survey (U.S.), Denver, CO, https://doi.org/10.3133/ofr200092, 2000-92, 121, 2000.
Heilman, P., Nichols, M. H., Goodrich, D. C., Miller, S. N., and Guertin, D.
P.: Geographic information systems database, Walnut Gulch Experimental
Watershed, Arizona, United States, Water Resour. Res., 44, W05S11,
https://doi.org/10.1029/2006WR005777, 2008.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P.
de, Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Hobley, D. E. J., Adams, J. M., Nudurupati, S. S., Hutton, E. W. H., Gasparini, N. M., Istanbulluoglu, E., and Tucker, G. E.: Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics, Earth Surf. Dynam., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, 2017.
Holtan, H. N.: Time-condensation in hydrograph-analysis, EOS T. Am.
Geophys. Union, 26, 407–413, https://doi.org/10.1029/TR026i003p00407, 1945.
Huang, J., Yu, H., Guan, X., Wang, G., and Guo, R.: Accelerated dryland
expansion under climate change, Nat. Clim. Change, 6, nclimate2837,
https://doi.org/10.1038/nclimate2837, 2015.
Huang, J., Li, Y., Fu, C., Chen, F., Fu, Q., Dai, A., Shinoda, M., Ma, Z.,
Guo, W., Li, Z., Zhang, L., Liu, Y., Yu, H., He, Y., Xie, Y., Guan, X., Ji,
M., Lin, L., Wang, S., Yan, H., and Wang, G.: Dryland climate change: Recent
progress and challenges, Rev. Geophys., 55, 719–778,
https://doi.org/10.1002/2016RG000550, 2017.
Hughes, A., Mansour, M., Robins, N., and Peach, D.: Numerical Modelling of
Run-off Recharge in a Catchment in the West Bank, MODFLOW More 2006 Manag.
Ground-Water Syst. Conf. Proc., 1, 385–389, 2006.
Hughes, D. A.: A simple approach to estimating channel transmission losses
in large South African river basins, J. Hydrol., 25, 100619,
https://doi.org/10.1016/j.ejrh.2019.100619, 2019.
Ivanov, V. Y., Vivoni, E. R., Bras, R. L., and Entekhabi, D.: Catchment
hydrologic response with a fully distributed triangulated irregular network
model, Water Resour. Res., 40, W11102, https://doi.org/10.1029/2004WR003218, 2004.
Kampf, S. K. and Burges, S. J.: A framework for classifying and comparing
distributed hillslope and catchment hydrologic models, Water Resour. Res.,
43, W05423, https://doi.org/10.1029/2006WR005370, 2007.
Keefer, T. O., Moran, M. S., and Paige, G. B.: Long-term meteorological and
soil hydrology database, Walnut Gulch, W05S07, https://doi.org/10.1029/2006WR005702,
2008.
Kipkemoi, I., Michaelides, K., Rosolem, R., and Singer, M. B.: Climatic expression of rainfall on soil moisture dynamics in drylands, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2021-48, 2021.
Lahmers, T. M., Gupta, H., Castro, C. L., Gochis, D. J., Yates, D., Dugger,
A., Goodrich, D., and Hazenberg, P.: Enhancing the Structure of the
WRF-Hydro Hydrologic Model for Semiarid Environments, J. Hydrometeorol., 20,
691–714, https://doi.org/10.1175/JHM-D-18-0064.1, 2019.
Leenaars, J. G. B., Claessens, L., Heuvelink, G. B. M., Hengl, T., Ruiperez
González, M., van Bussel, L. G. J., Guilpart, N., Yang, H., and Cassman,
K. G.: Mapping rootable depth and root zone plant-available water holding
capacity of the soil of sub-Saharan Africa, Geoderma, 324, 18–36,
https://doi.org/10.1016/j.geoderma.2018.02.046, 2018.
Marçais, J., de Dreuzy, J.-R., and Erhel, J.: Dynamic coupling of
subsurface and seepage flows solved within a regularized partition
formulation, Adv. Water Resour., 109, 94–105,
https://doi.org/10.1016/j.advwatres.2017.09.008, 2017.
Maxwell, R. M. and Condon, L. E.: Connections between groundwater flow and
transpiration partitioning, Science, 353, 377–380,
https://doi.org/10.1126/science.aaf7891, 2016.
Mayes, M., Caylor, K. K., Singer, M. B., Stella, J. C., Roberts, D., and
Nagler, P.: Climate sensitivity of water use by riparian woodlands at
landscape scales, Hydrol. Process., 34, 4884–4903,
https://doi.org/10.1002/hyp.13942, 2020.
Mein, R. G. and Larson, C. L.: Modeling infiltration during a steady rain,
Water Resour. Res., 9, 384–394, https://doi.org/10.1029/WR009i002p00384,
1973.
Messager, M. L., Lehner, B., Cockburn, C., Lamouroux, N., Pella, H.,
Snelder, T., Tockner, K., Trautmann, T., Watt, C., and Datry, T.: Global
prevalence of non-perennial rivers and streams, Nature, 594, 391–397,
https://doi.org/10.1038/s41586-021-03565-5, 2021.
Michaelides, K. and Wainwright, J.: Modelling the effects of
hillslope–channel coupling on catchment hydrological response, Earth Surf.
Proc. Land., 27, 1441–1457, https://doi.org/10.1002/esp.440, 2002.
Michaelides, K. and Wilson, M. D.: Uncertainty in predicted runoff due to
patterns of spatially variable infiltration, Water Resour. Res., 43, W02415,
https://doi.org/10.1029/2006WR005039, 2007.
Michaelides, K., Hollings, R., Singer, M. B., Nichols, M. H., and Nearing,
M. A.: Spatial and temporal analysis of hillslope–channel coupling and
implications for the longitudinal profile in a dryland basin, Earth Surf.
Proc. Land., 43, 1608–1621, https://doi.org/10.1002/esp.4340, 2018.
Miller, S. N., Youberg, A., Guertin, D. P., and Goodrich, D. C.: Channel morphology investigations using Geographic Information Systems and field research, in: Land Stewardship in the 21st Century: The Contributions of Watershed Management, Tucson, Arizona, 13–16 March 2000, 415–419, 2000.
Mudd, S. M.: Investigation of the hydrodynamics of flash floods in ephemeral
channels: Scaling analysis and simulation using a shock-capturing flow model
incorporating the effects of transmission losses, J. Hydrol., 324, 65–79,
https://doi.org/10.1016/j.jhydrol.2005.09.012, 2006.
Nash, I. E. and Sutcliffe, I. V.: River flow forecasting through conceptual
models, J. Hydrol., 10, 282–290, 1970.
Noorduijn, S. L., Shanafield, M., Trigg, M. A., Harrington, G. A., Cook, P.
G., and Peeters, L.: Estimating seepage flux from ephemeral stream channels
using surface water and groundwater level data, Water Resour. Res., 50,
1474–1489, https://doi.org/10.1002/2012WR013424, 2014.
Pelletier, J. D., Broxton, P. D., Hazenberg, P., Zeng, X., Troch, P. A.,
Niu, G.-Y., Williams, Z., Brunke, M. A., and Gochis, D.: A gridded global
data set of soil, intact regolith, and sedimentary deposit thicknesses for
regional and global land surface modeling, J. Adv. Model. Earth Sy., 8,
41–65, https://doi.org/10.1002/2015MS000526, 2016.
Philip, J. R.: Theory of Infiltration: The infiltration equation and its solutions, Soil Sci., 171, S34–S46, 1957.
Pilgrim, D. H., Chapman, T. G., and Doran, D. G.: Problems of
rainfall-runoff modelling in arid and semiarid regions, Hydrolog. Sci. J., 33,
379–400, https://doi.org/10.1080/02626668809491261, 1988.
Power, D., Rico-Ramirez, M. A., Desilets, S., Desilets, D., and Rosolem, R.: Cosmic-Ray neutron Sensor PYthon tool (crspy): An open-source tool for the processing of cosmic-ray neutron and soil moisture data, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-77, in review, 2021.
Quichimbo, E. A., Singer, M. B., and Cuthbert, M. O.: Characterising
groundwater–surface water interactions in idealised ephemeral stream
systems, Hydrol. Process., 34, 3792–3806,
https://doi.org/10.1002/hyp.13847, 2020.
Quichimbo, E. A., Cuthbert, M. O., Singer, M. B., Michaelides, K., Rosolem, R., and Hobley, D. E. J.: DRYP 1.0: A parsimonious hydrological model of DRYland Partitioning of the water balance, In DRYP 1.0: A parsimonious hydrological model of DRYland Partitioning of the water balance (1.0), Zenodo, https://doi.org/10.5281/zenodo.5061988, 2021.
Rahman, M., Rosolem, R., Kollet, S. J., and Wagener, T.: Towards a
computationally efficient free-surface groundwater flow boundary condition
for large-scale hydrological modelling, Adv. Water Resour., 123, 225–233,
https://doi.org/10.1016/j.advwatres.2018.11.015, 2019.
Rawls, W. J., Brakensiek, D. L., and Saxtonn, K. E.: Estimation of Soil
Water Properties, T. ASAE, 25, 1316–1320,
https://doi.org/10.13031/2013.33720, 1982.
Reinecke, R., Foglia, L., Mehl, S., Trautmann, T., Cáceres, D., and Döll, P.: Challenges in developing a global gradient-based groundwater model (G3M v1.0) for the integration into a global hydrological model, Geosci. Model Dev., 12, 2401–2418, https://doi.org/10.5194/gmd-12-2401-2019, 2019.
Renard, K. G.: The hydrology of semiarid rangeland watersheds, Rep. ARS-41-162, Agricultural Research Service, United States Department of Agriculture, Washington, D.C., 28 pp., 1970.
Renard, K. G., Nichols, M. H., Woolhiser, D. A., and Osborn, H. B.: A brief
background on the U.S. Department of Agriculture Agricultural Research
Service Walnut Gulch Experimental Watershed, Water Resour. Res., 44, W05S02,
https://doi.org/10.1029/2006WR005691, 2008.
Reynolds, J. F., Smith, D. M. S., Lambin, E. F., Turner, B. L., Mortimore,
M., Batterbury, S. P. J., Downing, T. E., Dowlatabadi, H., Fernández, R.
J., Herrick, J. E., Huber-Sannwald, E., Jiang, H., Leemans, R., Lynam, T.,
Maestre, F. T., Ayarza, M., and Walker, B.: Global Desertification: Building
a Science for Dryland Development, Science, 316, 847–851,
https://doi.org/10.1126/science.1131634, 2007.
Richardson, A. D., Hollinger, D. Y., Burba, G. G., Davis, K. J., Flanagan,
L. B., Katul, G. G., William Munger, J., Ricciuto, D. M., Stoy, P. C.,
Suyker, A. E., Verma, S. B., and Wofsy, S. C.: A multi-site analysis of
random error in tower-based measurements of carbon and energy fluxes, Agr.
Forest Meteorol., 136, 1–18, https://doi.org/10.1016/j.agrformet.2006.01.007,
2006.
Rosolem, R., Shuttleworth, W. J., Zreda, M., Franz, T. E., Zeng, X., and
Kurc, S. A.: The Effect of Atmospheric Water Vapor on Neutron Count in the
Cosmic-Ray Soil Moisture Observing System, J. Hydrometeorol., 14,
1659–1671, https://doi.org/10.1175/JHM-D-12-0120.1, 2013.
Schaake, J. C., Koren, V. I., Duan, Q.-Y., Mitchell, K., and Chen, F.:
Simple water balance model for estimating runoff at different spatial and
temporal scales, J. Geophys. Res.-Atmos., 101, 7461–7475,
https://doi.org/10.1029/95JD02892, 1996.
Schmidt, A., Hanson, C., Chan, W. S., and Law, B. E.: Empirical assessment
of uncertainties of meteorological parameters and turbulent fluxes in the
AmeriFlux network, J. Geophys. Res.-Biogeo., 117, G04014,
https://doi.org/10.1029/2012JG002100, 2012.
Schreiner-McGraw, A., Ajami, H., and Vivoni, E. R.: Extreme weather events
and transmission losses in arid streams, Environ. Res. Lett., 14, 084002,
https://doi.org/10.1088/1748-9326/ab2949, 2019.
Schrön, M., Köhli, M., Scheiffele, L., Iwema, J., Bogena, H. R., Lv, L., Martini, E., Baroni, G., Rosolem, R., Weimar, J., Mai, J., Cuntz, M., Rebmann, C., Oswald, S. E., Dietrich, P., Schmidt, U., and Zacharias, S.: Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity, Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, 2017.
Scoging, H. M. and Thornes, J. B.: Infiltration characteristics in a semiarid environment, in: The Hydrology of areas of low precipitation, Canberra Symposium, Paris, 1979, International Association of Hydrological Sciences, 128, 159–168, 1979.
Scott, R. L.: Using watershed water balance to evaluate the accuracy of eddy
covariance evaporation measurements for three semiarid ecosystems, Agr.
Forest Meteorol., 150, 219–225,
https://doi.org/10.1016/j.agrformet.2009.11.002, 2010.
Scott, R.: US-Wkg: Walnut Gulch Kendall Grasslands, (2021), AmeriFlux BASE US-Wkg Walnut Gulch Kendall Grasslands, Ver. 17-5, AmeriFlux AMP [data set], https://doi.org/10.17190/AMF/1246112, 2021.
Scott, R. L., Biederman, J. A., Hamerlynck, E. P., and Barron-Gafford, G.
A.: The carbon balance pivot point of southwestern U.S. semiarid ecosystems:
Insights from the 21st century drought, J. Geophys. Res.-Biogeo.,
120, 2612–2624, https://doi.org/10.1002/2015JG003181, 2015.
Shanafield, M. and Cook, P. G.: Transmission losses, infiltration and
groundwater recharge through ephemeral and intermittent streambeds: A review
of applied methods, J. Hydrol., 511, 518–529,
https://doi.org/10.1016/j.jhydrol.2014.01.068, 2014.
Sherman, L. K.: Comparison f-curves derived by the methods of sharp and
Holtan and of Sherman and Mayer, EOS T. Am. Geophys. Union, 24,
465–467, https://doi.org/10.1029/TR024i002p00465, 1943.
Siebert, S., Burke, J., Faures, J. M., Frenken, K., Hoogeveen, J., Döll, P., and Portmann, F. T.: Groundwater use for irrigation – a global inventory, Hydrol. Earth Syst. Sci., 14, 1863–1880, https://doi.org/10.5194/hess-14-1863-2010, 2010.
Šimunek, J., Van Genuchten, M. T., and Šejna, M.: The HYDRUS
software package for simulating two-and three-dimensional movement of water,
heat, and multiple solutes in variably-saturated media, Tech. Man. Version,
1, 241, 2006.
Singer, M. B. and Michaelides, K.: How is topographic simplicity maintained
in ephemeral dryland channels?, Geology, 42, 1091–1094,
https://doi.org/10.1130/G36267.1, 2014.
Singer, M. B. and Michaelides, K.: Deciphering the expression of climate
change within the Lower Colorado River basin by stochastic simulation of
convective rainfall, Environ. Res. Lett., 12, 104011,
https://doi.org/10.1088/1748-9326/aa8e50, 2017.
Singer, M. B., Michaelides, K., and Hobley, D. E. J.: STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change, Geosci. Model Dev., 11, 3713–3726, https://doi.org/10.5194/gmd-11-3713-2018, 2018.
Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G.,
MacLeod, D., Quichimbo, E. A., and Michaelides, K.: Hourly potential
evapotranspiration at 0.1∘ resolution for the global land surface
from 1981-present, Sci. Data, 8, 224,
https://doi.org/10.1038/s41597-021-01003-9, 2021.
Sivapalan, M. and Milly, P. C. D.: On the relationship between the time
condensation approximation and the flux concentration relation, J. Hydrol.,
105, 357–367, https://doi.org/10.1016/0022-1694(89)90113-3, 1989.
Sourthwest Watershed Research Center: Online Data access, available at: https://www.tucson.ars.ag.gov/dap/runoff_aggregate.asp, last access: 20 June 2021.
Stone, J. J., Nichols, M. H., Goodrich, D. C., and Buono, J.: Long-term
runoff database, Walnut Gulch Experimental Watershed, Arizona, United
States, Water Resour. Res., 44, W05S05, https://doi.org/10.1029/2006WR005733, 2008.
Tarek, M., Brissette, F. P., and Arsenault, R.: Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America, Hydrol. Earth Syst. Sci., 24, 2527–2544, https://doi.org/10.5194/hess-24-2527-2020, 2020.
Taylor, R. G., Scanlon, B., Döll, P., Rodell, M., Beek, R. van, Wada,
Y., Longuevergne, L., Leblanc, M., Famiglietti, J. S., Edmunds, M., Konikow,
L., Green, T. R., Chen, J., Taniguchi, M., Bierkens, M. F. P., MacDonald,
A., Fan, Y., Maxwell, R. M., Yechieli, Y., Gurdak, J. J., Allen, D. M.,
Shamsudduha, M., Hiscock, K., Yeh, P. J.-F., Holman, I., and Treidel, H.:
Ground water and climate change, Nat. Clim. Change, 3, nclimate1744,
https://doi.org/10.1038/nclimate1744, 2012.
Taylor, R. G., Todd, M. C., Kongola, L., Maurice, L., Nahozya, E., Sanga,
H., and MacDonald, A. M.: Evidence of the dependence of groundwater
resources on extreme rainfall in East Africa, Nat. Clim. Change, 3,
374–378, https://doi.org/10.1038/nclimate1731, 2013.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R.,
Meyers, T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting
eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol.,
103, 279–300, https://doi.org/10.1016/S0168-1923(00)00123-4, 2000.
Vergnes, J.-P., Decharme, B., Alkama, R., Martin, E., Habets, F., and
Douville, H.: A Simple Groundwater Scheme for Hydrological and Climate
Applications: Description and Offline Evaluation over France, J.
Hydrometeorol., 13, 1149–1171, https://doi.org/10.1175/JHM-D-11-0149.1,
2012.
Wagner, W., Lemoine, G., and Rott, H.: A Method for Estimating Soil Moisture
from ERS Scatterometer and Soil Data, Remote Sens. Environ., 70, 191–207,
https://doi.org/10.1016/S0034-4257(99)00036-X, 1999.
Walker, W. R.: Guidelines for Designing and Evaluating Surface Irrigation Systems, FAO Irrigation and Drainage Paper No. 45, FAO, Rome, 1989.
Wang, H. F. and Anderson, M. P.: Introduction to Groundwater Modeling:
Finite Difference and Finite Element Methods, W.H.Freeman & Co Ltd, San
Francisco, 237 pp., 1982.
Wang, L., Chen, W., Huang, G., and Zeng, G.: Changes of the transitional
climate zone in East Asia: past and future, Clim. Dynam., 49, 1463–1477,
https://doi.org/10.1007/s00382-016-3400-4, 2017.
Wheater, H., Sorooshian, S., and Sharma, K. D. (Eds.): Hydrological
Modelling in Arid and Semi-Arid Areas, 1 edition, Cambridge University
Press, Cambridge, New York, 222 pp., 2007.
White, R. P. and Nackoney, J.: Drylands, People, and Ecosystem Goods and Services, World Resources Institute, Washington, D.C., 58 pp., 2003.
Wood, E. F., Lettenmaier, D. P., Liang, X., Lohmann, D., Boone, A., Chang,
S., Chen, F., Dai, Y., Dickinson, R. E., Duan, Q., Ek, M., Gusev, Y. M.,
Habets, F., Irannejad, P., Koster, R., Mitchel, K. E., Nasonova, O. N.,
Noilhan, J., Schaake, J., Schlosser, A., Shao, Y., Shmakin, A. B., Verseghy,
D., Warrach, K., Wetzel, P., Xue, Y., Yang, Z. L., and Zeng, Q. C.: The
project for intercomparison of land-surface parameterization schemes (PILPS)
phase 2(c) Red-Arkansas River basin experiment: 1. Experiment description
and summary intercomparisons, Global Planet. Change, 19, 115–135,
https://doi.org/10.1016/S0921-8181(98)00044-7, 1998.
Woodward, C. S. and Dawson, C. N.: Analysis of Expanded Mixed Finite Element
Methods for a Nonlinear Parabolic Equation Modeling Flow into Variably
Saturated Porous Media, SIAM J. Numer. Anal. Phila., 37, 701–724,
https://doi.org/10.1137/S0036142996311040, 2000.
Woolhiser, D. A., Smith, R., and Goodrich, D. C.: KINEROS: a kinematic runoff and erosion model: documentation and user manual, U.S. Department of Agriculture, Washington, D.C., 77 pp., 1990.
Zimmer, M. A., Kaiser, K. E., Blaszczak, J. R., Zipper, S. C., Hammond, J.
C., Fritz, K. M., Costigan, K. H., Hosen, J., Godsey, S. E., Allen, G. H.,
Kampf, S., Burrows, R. M., Krabbenhoft, C. A., Dodds, W., Hale, R., Olden,
J. D., Shanafield, M., DelVecchia, A. G., Ward, A. S., Mims, M. C., Datry,
T., Bogan, M. T., Boersma, K. S., Busch, M. H., Jones, C. N., Burgin, A. J.,
and Allen, D. C.: Zero or not? Causes and consequences of zero-flow stream
gage readings, WIREs Water, 7, e1436, https://doi.org/10.1002/wat2.1436,
2020.
Zoccatelli, D., Marra, F., Armon, M., Rinat, Y., Smith, J. A., and Morin, E.: Contrasting rainfall-runoff characteristics of floods in desert and Mediterranean basins, Hydrol. Earth Syst. Sci., 23, 2665–2678, https://doi.org/10.5194/hess-23-2665-2019, 2019.
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012.
Short summary
Understanding and quantifying water partitioning in dryland regions are of key importance to anticipate the future impacts of climate change in water resources and dryland ecosystems. Here, we have developed a simple hydrological model (DRYP) that incorporates the key processes of water partitioning in drylands. DRYP is a modular, versatile, and parsimonious model that can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland regions.
Understanding and quantifying water partitioning in dryland regions are of key importance to...
