Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-277-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-277-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Jan 2019
Research article |
| 17 Jan 2019
| 17 Jan 2019
Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Wolfgang Kurtz
Leibniz Supercomputing Centre, Environmental Computing Group, Boltzmannstr. 1, 85748 Garching, Germany
Carsten Montzka
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Wendy Sharples
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Research Centre Jülich, Jülich Supercomputing Centre, 52425 Jülich, Germany
Klaus Goergen
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Jessica Keune
Laboratory of Hydrology and Water Management, Ghent University, 9000 Ghent, Belgium
Huilin Gao
Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843, USA
Anne Springer
Institute of Geodesy and Geoinformation, Bonn University, Nussallee 17, 53115 Bonn, Germany
Harrie-Jan Hendricks Franssen
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
Stefan Kollet
Research Centre Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52425 Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, 52425 Jülich, Germany
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We propose deriving altimetric rating curves by
bridginggaps between time series from gauge and altimeter measurements using hydrological model simulations. We investigate several stations at the Niger River, which is a challenging region. We show that altimetry reproduces discharge well and enables continuing the gauge time series, albeit at a lower temporal resolution.
Wendy Sharples, Ilya Zhukov, Markus Geimer, Klaus Goergen, Sebastian Luehrs, Thomas Breuer, Bibi Naz, Ketan Kulkarni, Slavko Brdar, and Stefan Kollet
Geosci. Model Dev., 11, 2875–2895, https://doi.org/10.5194/gmd-11-2875-2018, https://doi.org/10.5194/gmd-11-2875-2018, 2018
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Next-generation geoscientific models are based on complex model implementations and workflows. Next-generation HPC systems require new programming paradigms and code optimization. In order to meet the challenge of running complex simulations on new massively parallel HPC systems, we developed a run control framework that facilitates code portability, code profiling, and provenance tracking to reduce both the duration and the cost of code migration and development, while ensuring reproducibility.
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
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This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Hanna Post, Harrie-Jan Hendricks Franssen, Xujun Han, Roland Baatz, Carsten Montzka, Marius Schmidt, and Harry Vereecken
Biogeosciences, 15, 187–208, https://doi.org/10.5194/bg-15-187-2018, https://doi.org/10.5194/bg-15-187-2018, 2018
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Estimated values of selected key CLM4.5-BGC parameters obtained with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) strongly altered catchment-scale NEE predictions in comparison to global default parameter values. The effect of perturbed meteorological input data on the uncertainty of the predicted carbon fluxes was notably higher for C3-grass and C3-crop than for coniferous and deciduous forest. A future distinction of different crop types including management is considered essential.
Dominik Rains, Xujun Han, Hans Lievens, Carsten Montzka, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5929–5951, https://doi.org/10.5194/hess-21-5929-2017, https://doi.org/10.5194/hess-21-5929-2017, 2017
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We have assimilated 6 years of satellite-observed passive microwave data into a state-of-the-art land surface model to improve surface soil moisture as well as root-zone soil moisture simulations. Long-term assimilation effects/biases are identified, and they are especially dependent on model perturbations, applied to simulate model uncertainty. The implications are put into context of using such assimilation-improved data for classifying extremes within hydrological monitoring systems.
Hongjuan Zhang, Harrie-Jan Hendricks Franssen, Xujun Han, Jasper A. Vrugt, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 4927–4958, https://doi.org/10.5194/hess-21-4927-2017, https://doi.org/10.5194/hess-21-4927-2017, 2017
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Applications of data assimilation (DA) arise in many fields of geosciences, perhaps most importantly in weather forecasting and hydrology. We want to investigate the roles of data assimilation methods and land surface models (LSMs) in joint estimation of states and parameters in the assimilation experiments. We find that all DA methods can improve prediction of states, and that differences between DA methods were limited but that the differences between LSMs were much larger.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Carsten Montzka, Michael Herbst, Lutz Weihermüller, Anne Verhoef, and Harry Vereecken
Earth Syst. Sci. Data, 9, 529–543, https://doi.org/10.5194/essd-9-529-2017, https://doi.org/10.5194/essd-9-529-2017, 2017
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Global climate models require adequate parameterization of soil hydraulic properties, but typical resampling to the model grid introduces uncertainties. Here we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the problems. It preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters that enables modellers to perturb hydraulic parameters for model ensemble generation.
Roland Baatz, Harrie-Jan Hendricks Franssen, Xujun Han, Tim Hoar, Heye Reemt Bogena, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, https://doi.org/10.5194/hess-21-2509-2017, 2017
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Soil moisture is a major variable that affects regional climate, weather and hydrologic processes on the Earth's surface. In this study, real-world data of a network of cosmic-ray sensors were assimilated into a regional land surface model to improve model states and soil hydraulic parameters. The results show the potential of these networks for improving model states and parameters. It is suggested to widen the number of observed variables and to increase the number of estimated parameters.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
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In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
Stefan J. Kollet
Hydrol. Earth Syst. Sci., 20, 2801–2809, https://doi.org/10.5194/hess-20-2801-2016, https://doi.org/10.5194/hess-20-2801-2016, 2016
Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, https://doi.org/10.5194/gmd-9-1341-2016, 2016
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This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library.
Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP.
Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
P. Shrestha, M. Sulis, C. Simmer, and S. Kollet
Hydrol. Earth Syst. Sci., 19, 4317–4326, https://doi.org/10.5194/hess-19-4317-2015, https://doi.org/10.5194/hess-19-4317-2015, 2015
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This study highlights the grid resolution dependence of energy and water balance of the 3-D physically based integrated surface-groundwater model. The non-local controls of soil moisture were found to be highly grid resolution dependent, but the local vegetation control strongly modulates the scaling behavior of surface energy fluxes. For coupled runs, variability in patterns of surface fluxes due to this scale dependence can affect the simulated atmospheric boundary layer and local circulation.
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-7395-2015, https://doi.org/10.5194/gmdd-8-7395-2015, 2015
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.
S. Gebler, H.-J. Hendricks Franssen, T. Pütz, H. Post, M. Schmidt, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 2145–2161, https://doi.org/10.5194/hess-19-2145-2015, https://doi.org/10.5194/hess-19-2145-2015, 2015
R. M. Maxwell, L. E. Condon, and S. J. Kollet
Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, https://doi.org/10.5194/gmd-8-923-2015, 2015
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A model that simulates groundwater and surface water flow has been developed for the major river basins of the continental United States. Fundamental data sets provide input to the model resulting in a natural organization of stream networks and groundwater flow that is compared to observations of surface water and groundwater. Model results show relationships between flow and area that are moderated by aridity and represent an important step toward integrated hydrological prediction.
E. Katragkou, M. García-Díez, R. Vautard, S. Sobolowski, P. Zanis, G. Alexandri, R. M. Cardoso, A. Colette, J. Fernandez, A. Gobiet, K. Goergen, T. Karacostas, S. Knist, S. Mayer, P. M. M. Soares, I. Pytharoulis, I. Tegoulias, A. Tsikerdekis, and D. Jacob
Geosci. Model Dev., 8, 603–618, https://doi.org/10.5194/gmd-8-603-2015, https://doi.org/10.5194/gmd-8-603-2015, 2015
H. Post, H. J. Hendricks Franssen, A. Graf, M. Schmidt, and H. Vereecken
Biogeosciences, 12, 1205–1221, https://doi.org/10.5194/bg-12-1205-2015, https://doi.org/10.5194/bg-12-1205-2015, 2015
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This study introduces an extension of the classical two-tower approach for uncertainty estimation of measured net CO2 fluxes (NEE). Because land surface properties cannot be assumed identical at two eddy covariance towers, a correction for systematic flux differences is proposed to be added to the classical weather filter. With this extension, the overestimation of NEE uncertainty due to systematic flux differences (which are assumed to increase with tower distance) can considerably be reduced.
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.
F. Gasper, K. Goergen, P. Shrestha, M. Sulis, J. Rihani, M. Geimer, and S. Kollet
Geosci. Model Dev., 7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, https://doi.org/10.5194/gmd-7-2531-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
W. Kurtz, H.-J. Hendricks Franssen, P. Brunner, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3795–3813, https://doi.org/10.5194/hess-17-3795-2013, https://doi.org/10.5194/hess-17-3795-2013, 2013
V. R. N. Pauwels, G. J. M. De Lannoy, H.-J. Hendricks Franssen, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3499–3521, https://doi.org/10.5194/hess-17-3499-2013, https://doi.org/10.5194/hess-17-3499-2013, 2013
Related subject area
Subject: Global hydrology | Techniques and Approaches: Modelling approaches
Technical note: Comparing three different methods for allocating river points to coarse-resolution hydrological modelling grid cells
Representing farmer irrigated crop area adaptation in a large-scale hydrological model
Combined impacts of climate and land-use change on future water resources in Africa
Deep learning for quality control of surface physiographic fields using satellite Earth observations
Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations
Influence of irrigation on root zone storage capacity estimation
Root zone soil moisture in over 25 % of global land permanently beyond pre-industrial variability as early as 2050 without climate policy
Assessment of pluri-annual and decadal changes in terrestrial water storage predicted by global hydrological models in comparison with the GRACE satellite gravity mission
Improving the quantification of climate change hazards by hydrological models: a simple ensemble approach for considering the uncertain effect of vegetation response to climate change on potential evapotranspiration
Towards reducing the high cost of parameter sensitivity analysis in hydrologic modeling: a regional parameter sensitivity analysis approach
Unveiling Hydrological Dynamics in Data-Scarce Regions: A Comprehensive Integrated Approach
Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables
River flow in the near future: a global perspective in the context of a high-emission climate change scenario
Methodology for constructing a flood-hazard map for a future climate
Diagnosing modeling errors in global terrestrial water storage interannual variability
Hyper-resolution PCR-GLOBWB: opportunities and challenges from refining model spatial resolution to 1 km over the European continent
A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia
Poor correlation between large-scale environmental flow violations and freshwater biodiversity: implications for water resource management and the freshwater planetary boundary
Accuracy of five ground heat flux empirical simulation methods in the surface-energy-balance-based remote-sensing evapotranspiration models
Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff
Revisiting large-scale interception patterns constrained by a synthesis of global experimental data
Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh
Using a long short-term memory (LSTM) neural network to boost river streamflow forecasts over the western United States
Quantifying overlapping and differing information of global precipitation for GCM forecasts and El Niño–Southern Oscillation
Globally widespread and increasing violations of environmental flow envelopes
Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations
Soil moisture estimation in South Asia via assimilation of SMAP retrievals
Toward hyper-resolution global hydrological models including human activities: application to Kyushu island, Japan
Towards hybrid modeling of the global hydrological cycle
The importance of vegetation in understanding terrestrial water storage variations
Large-scale sensitivities of groundwater and surface water to groundwater withdrawal
A hydrography upscaling method for scale-invariant parametrization of distributed hydrological models
A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods
Bright and blind spots of water research in Latin America and the Caribbean
Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters
Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management
Robust historical evapotranspiration trends across climate regimes
A note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modeling
Global scenarios of irrigation water abstractions for bioenergy production: a systematic review
Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling
Uncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble study
Ubiquitous increases in flood magnitude in the Columbia River basin under climate change
Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors
The role of household adaptation measures in reducing vulnerability to flooding: a coupled agent-based and flood modelling approach
Assessing global water mass transfers from continents to oceans over the period 1948–2016
Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface model
The influence of assimilating leaf area index in a land surface model on global water fluxes and storages
Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps
The pantropical response of soil moisture to El Niño
HESS Opinions: Beyond the long-term water balance: evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds
Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
Hydrol. Earth Syst. Sci., 28, 1403–1413, https://doi.org/10.5194/hess-28-1403-2024, https://doi.org/10.5194/hess-28-1403-2024, 2024
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This work was performed in order to precisely address a point that is often neglected by hydrologists: the allocation of points located on a river network to grid cells, which is often a mandatory step for hydrological modelling.
Jim Yoon, Nathalie Voisin, Christian Klassert, Travis Thurber, and Wenwei Xu
Hydrol. Earth Syst. Sci., 28, 899–916, https://doi.org/10.5194/hess-28-899-2024, https://doi.org/10.5194/hess-28-899-2024, 2024
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Global and regional models used to evaluate water shortages typically neglect the possibility that irrigated crop areas may change in response to future hydrological conditions, such as the fallowing of crops in response to drought. Here, we enhance a model used for water shortage analysis with farmer agents that dynamically adapt their irrigated crop areas based on simulated hydrological conditions. Results indicate that such cropping adaptation can strongly alter simulated water shortages.
Celray James Chawanda, Albert Nkwasa, Wim Thiery, and Ann van Griensven
Hydrol. Earth Syst. Sci., 28, 117–138, https://doi.org/10.5194/hess-28-117-2024, https://doi.org/10.5194/hess-28-117-2024, 2024
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Africa's water resources are being negatively impacted by climate change and land-use change. The SWAT+ hydrological model was used to simulate the hydrological cycle in Africa, and results show likely decreases in river flows in the Zambezi and Congo rivers and highest flows in the Niger River basins due to climate change. Land cover change had the biggest impact in the Congo River basin, emphasizing the importance of including land-use change in studies.
Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, and Tim Palmer
Hydrol. Earth Syst. Sci., 27, 4661–4685, https://doi.org/10.5194/hess-27-4661-2023, https://doi.org/10.5194/hess-27-4661-2023, 2023
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Lakes play an important role when we try to explain and predict the weather. More accurate and up-to-date description of lakes all around the world for numerical models is a continuous task. However, it is difficult to assess the impact of updated lake description within a weather prediction system. In this work, we develop a method to quickly and automatically define how, where, and when updated lake description affects weather prediction.
Haiyang Shi, Geping Luo, Olaf Hellwich, Xiufeng He, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 27, 4551–4562, https://doi.org/10.5194/hess-27-4551-2023, https://doi.org/10.5194/hess-27-4551-2023, 2023
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Using evidence from meteorological stations, this study assessed the climatic, hydrological, and ecological aridity changes in global drylands and their associated mechanisms. A decoupling between atmospheric, hydrological, and vegetation aridity was found. This highlights the added value of using station-scale data to assess dryland change as a complement to results based on coarse-resolution reanalysis data and land surface models.
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
EGUsphere, https://doi.org/10.5194/egusphere-2023-2622, https://doi.org/10.5194/egusphere-2023-2622, 2023
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Vegetation plays a crucial role in regulating the water cycle by transporting water from the subsurface to the atmosphere via vegetation roots, which depends on the extent of the vegetation root system. In this study we quantified the effect of irrigation on the vegetation roots globally. Our results emphasize the importance of accounting for irrigation in estimating the root extent of vegetation, which is essential to adequately represent the water cycle in hydrological and climate models.
En Ning Lai, Lan Wang-Erlandsson, Vili Virkki, Miina Porkka, and Ruud J. van der Ent
Hydrol. Earth Syst. Sci., 27, 3999–4018, https://doi.org/10.5194/hess-27-3999-2023, https://doi.org/10.5194/hess-27-3999-2023, 2023
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This research scrutinized predicted changes in root zone soil moisture dynamics across different climate scenarios and different climate regions globally between 2021 and 2100. The Mediterranean and most of South America stood out as regions that will likely experience permanently drier conditions, with greater severity observed in the no-climate-policy scenarios. These findings underscore the impact that possible future climates can have on green water resources.
Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, and Anne Barnoud
Hydrol. Earth Syst. Sci., 27, 3743–3768, https://doi.org/10.5194/hess-27-3743-2023, https://doi.org/10.5194/hess-27-3743-2023, 2023
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The GRACE (Gravity Recovery And Climate Experiment) satellite mission enabled the quantification of water mass redistributions from 2002 to 2017. The analysis of GRACE satellite data shows here that slow changes in terrestrial water storage occurring over a few years to a decade are severely underestimated by global hydrological models. Several sources of errors may explain such biases, likely including the inaccurate representation of groundwater storage changes.
Thedini Asali Peiris and Petra Döll
Hydrol. Earth Syst. Sci., 27, 3663–3686, https://doi.org/10.5194/hess-27-3663-2023, https://doi.org/10.5194/hess-27-3663-2023, 2023
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Hydrological models often overlook vegetation's response to CO2 and climate, impairing their ability to forecast impacts on evapotranspiration and water resources. To address this, we suggest involving two model variants: (1) the standard method and (2) a modified approach (proposed here) based on the Priestley–Taylor equation (PT-MA). While not universally applicable, a dual approach helps consider uncertainties related to vegetation responses to climate change, enhancing model representation.
Samah Larabi, Juliane Mai, Markus Schnorbus, Bryan A. Tolson, and Francis Zwiers
Hydrol. Earth Syst. Sci., 27, 3241–3263, https://doi.org/10.5194/hess-27-3241-2023, https://doi.org/10.5194/hess-27-3241-2023, 2023
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The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.
Ayenew D. Ayalew, Paul D. Wagner, Dejene Sahlu, and Nicola Fohrer
EGUsphere, https://doi.org/10.5194/egusphere-2023-1895, https://doi.org/10.5194/egusphere-2023-1895, 2023
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The study presents a pioneering Comprehensive Integrated Approach to unravel hydrological complexities in data-scarce regions. By integrating diverse data sources and advanced analytics, it offers a holistic understanding of water systems, unveiling hidden patterns and driving factors. This innovative method holds immense promise for informed decision-making and sustainable water resource management, addressing a critical need in hydrological science.
Tanja Denager, Torben O. Sonnenborg, Majken C. Looms, Heye Bogena, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 27, 2827–2845, https://doi.org/10.5194/hess-27-2827-2023, https://doi.org/10.5194/hess-27-2827-2023, 2023
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This study contributes to improvements in the model characterization of water and energy fluxes. The results show that multi-objective autocalibration in combination with mathematical regularization is a powerful tool to improve land surface models. Using the direct measurement of turbulent fluxes as the target variable, parameter optimization matches simulations and observations of latent heat, whereas sensible heat is clearly biased.
Omar Vicente Müller, Patrick McGuire, Pier Luigi Vidale, and Ed Hawkins
EGUsphere, https://doi.org/10.5194/egusphere-2023-1281, https://doi.org/10.5194/egusphere-2023-1281, 2023
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We evaluate how rivers are expected to change in the near future compared to the recent past in the context of a warming world. We show that important rivers of the world will notably change their flows, mainly during peaks, exceeding the variations that rivers used to exhibit. Such a magnitude of changes may produce more frequent floods with severe consequences in metropolitan areas, alter the management of dams affecting hydropower generation, and potentially affect the ocean's circulation.
Yuki Kimura, Yukiko Hirabayashi, Yuki Kita, Xudong Zhou, and Dai Yamazaki
Hydrol. Earth Syst. Sci., 27, 1627–1644, https://doi.org/10.5194/hess-27-1627-2023, https://doi.org/10.5194/hess-27-1627-2023, 2023
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Since both the frequency and magnitude of flood will increase by climate change, information on spatial distributions of potential inundation depths (i.e., flood-hazard map) is required. We developed a method for constructing realistic future flood-hazard maps which addresses issues due to biases in climate models. A larger population is estimated to face risk in the future flood-hazard map, suggesting that only focusing on flood-frequency change could cause underestimation of future risk.
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
Hydrol. Earth Syst. Sci., 27, 1531–1563, https://doi.org/10.5194/hess-27-1531-2023, https://doi.org/10.5194/hess-27-1531-2023, 2023
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We spatially attribute the variance in global terrestrial water storage (TWS) interannual variability (IAV) and its modeling error with two data-driven hydrological models. We find error hotspot regions that show a disproportionately large significance in the global mismatch and the association of the error regions with a smaller-scale lateral convergence of water. Our findings imply that TWS IAV modeling can be efficiently improved by focusing on model representations for the error hotspots.
Jannis M. Hoch, Edwin H. Sutanudjaja, Niko Wanders, Rens L. P. H. van Beek, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 27, 1383–1401, https://doi.org/10.5194/hess-27-1383-2023, https://doi.org/10.5194/hess-27-1383-2023, 2023
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To facilitate locally relevant simulations over large areas, global hydrological models (GHMs) have moved towards ever finer spatial resolutions. After a decade-long quest for hyper-resolution (i.e. equal to or smaller than 1 km), the presented work is a first application of a GHM at 1 km resolution over Europe. This not only shows that hyper-resolution can be achieved but also allows for a thorough evaluation of model results at unprecedented detail and the formulation of future research.
Mugni Hadi Hariadi, Gerard van der Schrier, Gert-Jan Steeneveld, Samuel Sutanto, Edwin Sutanudjaja, Dian Nur Ratri, Ardhasena Sopaheluwakan, and Albert Klein Tank
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-14, https://doi.org/10.5194/hess-2023-14, 2023
Revised manuscript accepted for HESS
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We utilize the high-resolution CMIP6 on extreme rainfall and extreme streamflow projection over Southeast Asia. This region will experience an increase in both dry and wet extremes in near future. We found a more extreme low flow and high flow, respectively along with the increasing probability of low flow and high flow events. We reveal that the changes in low flow events and their probabilities are not only influenced by extreme dry climates but also by the catchment characteristics.
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022, https://doi.org/10.5194/hess-26-6247-2022, 2022
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The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Zhaofei Liu
Hydrol. Earth Syst. Sci., 26, 6207–6226, https://doi.org/10.5194/hess-26-6207-2022, https://doi.org/10.5194/hess-26-6207-2022, 2022
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Ground heat flux (G) accounts for a significant fraction of the surface energy balance (SEB), but there is insufficient research on these models compared with other flux. The accuracy of G simulation methods in the SEB-based remote sensing evapotranspiration models is evaluated. Results show that the accuracy of each method varied significantly at different sites and at half-hour intervals. Further improvement of G simulations is recommended for the remote sensing evapotranspiration modelers.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
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We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, https://doi.org/10.5194/hess-26-5647-2022, 2022
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A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1° spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, https://doi.org/10.5194/hess-26-5473-2022, 2022
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Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Kieran M. R. Hunt, Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 5449–5472, https://doi.org/10.5194/hess-26-5449-2022, https://doi.org/10.5194/hess-26-5449-2022, 2022
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In this study, we use three models to forecast river streamflow operationally for 13 months (September 2020 to October 2021) at 10 gauges in the western US. The first model is a state-of-the-art physics-based streamflow model (GloFAS). The second applies a bias-correction technique to GloFAS. The third is a type of neural network (an LSTM). We find that all three are capable of producing skilful forecasts but that the LSTM performs the best, with skilful 5 d forecasts at nine stations.
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249, https://doi.org/10.5194/hess-26-4233-2022, https://doi.org/10.5194/hess-26-4233-2022, 2022
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This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
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Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar
Hydrol. Earth Syst. Sci., 26, 2221–2243, https://doi.org/10.5194/hess-26-2221-2022, https://doi.org/10.5194/hess-26-2221-2022, 2022
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Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to an unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data-scarce regions.
Naota Hanasaki, Hikari Matsuda, Masashi Fujiwara, Yukiko Hirabayashi, Shinta Seto, Shinjiro Kanae, and Taikan Oki
Hydrol. Earth Syst. Sci., 26, 1953–1975, https://doi.org/10.5194/hess-26-1953-2022, https://doi.org/10.5194/hess-26-1953-2022, 2022
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Global hydrological models (GHMs) are usually applied with a spatial resolution of about 50 km, but this time we applied the H08 model, one of the most advanced GHMs, with a high resolution of 2 km to Kyushu island, Japan. Since the model was not accurate as it was, we incorporated local information and improved the model, which revealed detailed water stress in subregions that were not visible with the previous resolution.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614, https://doi.org/10.5194/hess-26-1579-2022, https://doi.org/10.5194/hess-26-1579-2022, 2022
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We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109, https://doi.org/10.5194/hess-26-1089-2022, https://doi.org/10.5194/hess-26-1089-2022, 2022
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We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878, https://doi.org/10.5194/hess-25-5859-2021, https://doi.org/10.5194/hess-25-5859-2021, 2021
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We introduce a simple analytical framework that allows us to estimate to what extent large-scale groundwater withdrawal affects groundwater levels and streamflow. It also calculates which part of the groundwater withdrawal comes out of groundwater storage and which part from a reduction in streamflow. Global depletion rates obtained with the framework are compared with estimates from satellites, from global- and continental-scale groundwater models, and from in situ datasets.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
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Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Jérôme Kopp, Pauline Rivoire, S. Mubashshir Ali, Yannick Barton, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 5153–5174, https://doi.org/10.5194/hess-25-5153-2021, https://doi.org/10.5194/hess-25-5153-2021, 2021
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Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Alyssa J. DeVincentis, Hervé Guillon, Romina Díaz Gómez, Noelle K. Patterson, Francine van den Brandeler, Arthur Koehl, J. Pablo Ortiz-Partida, Laura E. Garza-Díaz, Jennifer Gamez-Rodríguez, Erfan Goharian, and Samuel Sandoval Solis
Hydrol. Earth Syst. Sci., 25, 4631–4650, https://doi.org/10.5194/hess-25-4631-2021, https://doi.org/10.5194/hess-25-4631-2021, 2021
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Latin America and the Caribbean face many water-related stresses which are expected to worsen with climate change. To assess the vulnerability, we reviewed over 20 000 multilingual research articles using machine learning and an understanding of the regional landscape. Results reveal that the region’s inherent vulnerability is compounded by research blind spots in niche topics (reservoirs and risk assessment) and subregions (Caribbean nations), as well as by its reliance on one country (Brazil).
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125, https://doi.org/10.5194/hess-25-4099-2021, https://doi.org/10.5194/hess-25-4099-2021, 2021
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In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Louise J. Slater, Bailey Anderson, Marcus Buechel, Simon Dadson, Shasha Han, Shaun Harrigan, Timo Kelder, Katie Kowal, Thomas Lees, Tom Matthews, Conor Murphy, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 3897–3935, https://doi.org/10.5194/hess-25-3897-2021, https://doi.org/10.5194/hess-25-3897-2021, 2021
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Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
Sanaa Hobeichi, Gab Abramowitz, and Jason P. Evans
Hydrol. Earth Syst. Sci., 25, 3855–3874, https://doi.org/10.5194/hess-25-3855-2021, https://doi.org/10.5194/hess-25-3855-2021, 2021
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Evapotranspiration (ET) links the water, energy and carbon cycle on land. Reliable ET estimates are key to understand droughts and flooding. We develop a new ET dataset, DOLCE V3, by merging multiple global ET datasets, and we show that it matches ET observations better and hence is more reliable than its parent datasets. Next, we use DOLCE V3 to examine recent changes in ET and find that ET has increased over most of the land, decreased in some regions, and has not changed in some other regions
Frederik Kratzert, Daniel Klotz, Sepp Hochreiter, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 25, 2685–2703, https://doi.org/10.5194/hess-25-2685-2021, https://doi.org/10.5194/hess-25-2685-2021, 2021
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We investigate how deep learning models use different meteorological data sets in the task of (regional) rainfall–runoff modeling. We show that performance can be significantly improved when using different data products as input and further show how the model learns to combine those meteorological input differently across time and space. The results are carefully benchmarked against classical approaches, showing the supremacy of the presented approach.
Fabian Stenzel, Dieter Gerten, and Naota Hanasaki
Hydrol. Earth Syst. Sci., 25, 1711–1726, https://doi.org/10.5194/hess-25-1711-2021, https://doi.org/10.5194/hess-25-1711-2021, 2021
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Ideas to mitigate climate change include the large-scale cultivation of fast-growing plants to capture atmospheric CO2 in biomass. To maximize the productivity of these plants, they will likely be irrigated. However, there is strong disagreement in the literature on how much irrigation water is needed globally, potentially inducing water stress. We provide a comprehensive overview of global irrigation demand studies for biomass production and discuss the diverse underlying study assumptions.
Charles Rougé, Patrick M. Reed, Danielle S. Grogan, Shan Zuidema, Alexander Prusevich, Stanley Glidden, Jonathan R. Lamontagne, and Richard B. Lammers
Hydrol. Earth Syst. Sci., 25, 1365–1388, https://doi.org/10.5194/hess-25-1365-2021, https://doi.org/10.5194/hess-25-1365-2021, 2021
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Amid growing interest in using large-scale hydrological models for flood and drought monitoring and forecasting, it is important to evaluate common assumptions these models make. We investigated the representation of reservoirs as separate (non-coordinated) infrastructure. We found that not appropriately representing coordination and control processes can lead a hydrological model to simulate flood and drought events that would not occur given the coordinated emergency response in the basin.
Robert Reinecke, Hannes Müller Schmied, Tim Trautmann, Lauren Seaby Andersen, Peter Burek, Martina Flörke, Simon N. Gosling, Manolis Grillakis, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Wim Thiery, Yoshihide Wada, Satoh Yusuke, and Petra Döll
Hydrol. Earth Syst. Sci., 25, 787–810, https://doi.org/10.5194/hess-25-787-2021, https://doi.org/10.5194/hess-25-787-2021, 2021
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Billions of people rely on groundwater as an accessible source of drinking water and for irrigation, especially in times of drought. Groundwater recharge is the primary process of regenerating groundwater resources. We find that groundwater recharge will increase in northern Europe by about 19 % and decrease by 10 % in the Amazon with 3 °C global warming. In the Mediterranean, a 2 °C warming has already lead to a reduction in recharge by 38 %. However, these model predictions are uncertain.
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272, https://doi.org/10.5194/hess-25-257-2021, https://doi.org/10.5194/hess-25-257-2021, 2021
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Using a large ensemble of simulated flows throughout the northwestern USA, we compare daily flood statistics in the past (1950–1999) and future (2050–1999) periods and find that nearly all locations will experience an increase in flood magnitudes. The flood season expands significantly in many currently snow-dominant rivers, moving from only spring to both winter and spring. These results, properly extended, may help inform flood risk management and negotiations of the Columbia River Treaty.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Yared Abayneh Abebe, Amineh Ghorbani, Igor Nikolic, Natasa Manojlovic, Angelika Gruhn, and Zoran Vojinovic
Hydrol. Earth Syst. Sci., 24, 5329–5354, https://doi.org/10.5194/hess-24-5329-2020, https://doi.org/10.5194/hess-24-5329-2020, 2020
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The paper presents a coupled agent-based and flood model for Hamburg, Germany. It explores residents’ adaptation behaviour in relation to flood event scenarios, economic incentives and shared and individual strategies. We found that unique trajectories of adaptation behaviour emerge from different flood event series. Providing subsidies improves adaptation behaviour in the long run. The coupled modelling technique allows the role of individual measures in flood risk management to be examined.
Denise Cáceres, Ben Marzeion, Jan Hendrik Malles, Benjamin Daniel Gutknecht, Hannes Müller Schmied, and Petra Döll
Hydrol. Earth Syst. Sci., 24, 4831–4851, https://doi.org/10.5194/hess-24-4831-2020, https://doi.org/10.5194/hess-24-4831-2020, 2020
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We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.
Salma Tafasca, Agnès Ducharne, and Christian Valentin
Hydrol. Earth Syst. Sci., 24, 3753–3774, https://doi.org/10.5194/hess-24-3753-2020, https://doi.org/10.5194/hess-24-3753-2020, 2020
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In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we use different input global soil texture maps from the literature to investigate the impact of soil texture on the simulated water budget in an LSM. The medium loamy textures give the highest evapotranspiration and lowest total runoff rates. However, the different soil texture maps result in similar water budgets because of their inherent similarities, especially when upscaled at the 0.5° resolution.
Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko
Hydrol. Earth Syst. Sci., 24, 3775–3788, https://doi.org/10.5194/hess-24-3775-2020, https://doi.org/10.5194/hess-24-3775-2020, 2020
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This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mark D. Wahl, and Michael L. Follum
Hydrol. Earth Syst. Sci., 24, 2711–2729, https://doi.org/10.5194/hess-24-2711-2020, https://doi.org/10.5194/hess-24-2711-2020, 2020
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Global-scale hydrologic forecasts should account for attenuation through lakes and reservoirs. There is no consensus on the best approach to estimating this attenuation in large-spatial-scale hydrologic forecasts. This article investigates two existing parsimonious approaches to estimating reservoir outflows. We test each method at 60 reservoirs in the United States. We find that a method first developed in 2003 can provide a reasonable approximation of diurnal reservoir outflows.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
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We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
A. Sankarasubramanian, Dingbao Wang, Stacey Archfield, Meredith Reitz, Richard M. Vogel, Amirhossein Mazrooei, and Sudarshana Mukhopadhyay
Hydrol. Earth Syst. Sci., 24, 1975–1984, https://doi.org/10.5194/hess-24-1975-2020, https://doi.org/10.5194/hess-24-1975-2020, 2020
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The Budyko framework which relies on the supply and demand concept could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response. This framework is extended with a few illustrative examples for quantifying the variability in land-surface fluxes for natural and human-altered watersheds. Potential for using observed and remotely sensed datasets in capturing this variability is also discussed.
Cited articles
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Albergel, C., Munier, S., Leroux, D. J., Dewaele, H., Fairbairn, D., Barbu, A.
L., Gelati, E., Dorigo, W., Faroux, S., Meurey, C., Le Moigne, P., Decharme, B.,
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Short summary
This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
This study investigates the value of assimilating coarse-resolution remotely sensed soil...
