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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Large-scale profile soil moisture (SM) is important for water resource management, but its estimation is a challenge. Thus, based on in situ SM observations in a cold mountain, a strong relationship between the surface SM and subsurface SM is found. Both the subsurface SM of 10–30 cm and the profile SM of 0–70 cm can be estimated from the surface SM of 0–10 cm accurately. By combing with the satellite product, we improve the large-scale profile SM estimation in the cold mountains finally.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Benjamin N. O. Kuffour, Nicholas B. Engdahl, Carol S. Woodward, Laura E. Condon, Stefan Kollet, and Reed M. Maxwell
Geosci. Model Dev., 13, 1373–1397, https://doi.org/10.5194/gmd-13-1373-2020, https://doi.org/10.5194/gmd-13-1373-2020, 2020
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Integrated hydrologic models (IHMs) were developed in order to allow for more accurate simulations of real-world ecohydrologic conditions. Many IHMs exist, and the literature can be dense, so it is often difficult to understand what a specific model can and cannot do. We provide a review of the current core capabilities, solution techniques, communication structure with other models, some limitations, and potential future improvements of one such open-source integrated model called ParFlow.
Stefan Schröder, Anne Springer, Jürgen Kusche, Bernd Uebbing, Luciana Fenoglio-Marc, Bernd Diekkrüger, and Thomas Poméon
Hydrol. Earth Syst. Sci., 23, 4113–4128, https://doi.org/10.5194/hess-23-4113-2019, https://doi.org/10.5194/hess-23-4113-2019, 2019
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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
Changes in mean evapotranspiration dominate groundwater recharge in semi-arid regions
Merging modelled and reported flood impacts in Europe in a combined flood event catalogue for 1950–2020
Global-scale evaluation of precipitation datasets for hydrological modelling
Influence of irrigation on root zone storage capacity estimation
River flow in the near future: a global perspective in the context of a high-emission climate change scenario
A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia
Unveiling hydrological dynamics in data-scarce regions: experiences from the Ethiopian Rift Valley Lakes Basin
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
The effect of climate change on the simulated streamflow of six Canadian rivers based on the CanRCM4 regional climate 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
Drivers of global irrigation expansion: the role of discrete global grid choice
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
Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables
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
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
Tuvia Turkeltaub and Golan Bel
Hydrol. Earth Syst. Sci., 28, 4263–4274, https://doi.org/10.5194/hess-28-4263-2024, https://doi.org/10.5194/hess-28-4263-2024, 2024
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Future climate projections suggest that climate change will impact groundwater recharge, with its exact effects being uncertain due to incomplete understanding of rainfall, evapotranspiration, and recharge relations. We studied the effects of changes in the average, spread, and frequency of extreme events of rainfall and evapotranspiration on groundwater recharge. We found that increasing or decreasing the potential evaporation has the most dominant effect on groundwater recharge.
Dominik Paprotny, Belinda Rhein, Michalis I. Vousdoukas, Paweł Terefenko, Francesco Dottori, Simon Treu, Jakub Śledziowski, Luc Feyen, and Heidi Kreibich
Hydrol. Earth Syst. Sci., 28, 3983–4010, https://doi.org/10.5194/hess-28-3983-2024, https://doi.org/10.5194/hess-28-3983-2024, 2024
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Long-term trends in flood losses are regulated by multiple factors, including climate variation, population and economic growth, land-use transitions, reservoir construction, and flood risk reduction measures. Here, we reconstruct the factual circumstances in which almost 15 000 potential riverine, coastal and compound floods in Europe occurred between 1950 and 2020. About 10 % of those events are reported to have caused significant socioeconomic impacts.
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024, https://doi.org/10.5194/hess-28-2313-2024, 2024
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Vegetation plays a crucial role in regulating the water cycle by transporting water from the subsurface to the atmosphere via roots; this transport depends on the extent of the root system. In this study, we quantified the effect of irrigation on roots at a global scale. Our results emphasize the importance of accounting for irrigation in estimating the vegetation root extent, which is essential to adequately represent the water cycle in hydrological and climate models.
Omar V. Müller, Patrick C. McGuire, Pier Luigi Vidale, and Ed Hawkins
Hydrol. Earth Syst. Sci., 28, 2179–2201, https://doi.org/10.5194/hess-28-2179-2024, https://doi.org/10.5194/hess-28-2179-2024, 2024
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This work evaluates how rivers are projected 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 large changes may produce more frequent floods, alter hydropower generation, and potentially affect the ocean's circulation.
Mugni Hadi Hariadi, Gerard van der Schrier, Gert-Jan Steeneveld, Samuel J. Sutanto, Edwin Sutanudjaja, Dian Nur Ratri, Ardhasena Sopaheluwakan, and Albert Klein Tank
Hydrol. Earth Syst. Sci., 28, 1935–1956, https://doi.org/10.5194/hess-28-1935-2024, https://doi.org/10.5194/hess-28-1935-2024, 2024
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We utilize the high-resolution CMIP6 for extreme rainfall and streamflow projection over Southeast Asia. This region will experience an increase in both dry and wet extremes in the near future. We found a more extreme low flow and high flow, along with an 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 extremely dry climates but also by the catchment characteristics.
Ayenew D. Ayalew, Paul D. Wagner, Dejene Sahlu, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 28, 1853–1872, https://doi.org/10.5194/hess-28-1853-2024, https://doi.org/10.5194/hess-28-1853-2024, 2024
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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, we offer 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.
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.
Vivek K. Arora, Aranildo Lima, and Rajesh Shrestha
EGUsphere, https://doi.org/10.5194/egusphere-2024-182, https://doi.org/10.5194/egusphere-2024-182, 2024
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This study is likely the first Canada-wide assessment of climate change impact on the hydro-climatology of its major river basins. It finds that the precipitation, runoff, and temperature are all expected to increase over Canada in the future. The northerly Mackenzie and Yukon Rivers are relatively less affected by climate change compared to the southerly Fraser and Columbia Rivers which are located in the milder Pacific north-western region.
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.
Sophie Wagner, Fabian Stenzel, Tobias Krüger, and Jana de Wiljes
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-273, https://doi.org/10.5194/hess-2023-273, 2023
Revised manuscript accepted for HESS
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Statistical models that explain global irrigation rely on location-referenced data. Traditionally, a system based on longitude and latitude lines is chosen. However, this introduces bias to the analysis due to the Earth’s curvature. We propose using a system based on hexagonal grid cells that allows for distortion-free representation of the data. We show that this increases the model’s accuracy by 29 % and identify biophysical and socioeconomic drivers of historical global irrigation expansion.
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.
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.
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.
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
Short summary
Short summary
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.
Cited articles
Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay, P.,
Isaksen, L., Brocca, L., de Jeu, R., and Wagner, W.: Monitoring multi-decadal
satellite earth observation of soil moisture products through land surface
reanalyses, Remote Sens. Environ., 138, 77–89, https://doi.org/10.1016/j.rse.2013.07.009, 2013.
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.,
Mahfouf, J.-F., and Calvet, J.-C.: Sequential assimilation of satellite-derived
vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment
over the Euro-Mediterranean area, Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, 2017.
Andreasen, M., Andreasen, L. A., Jensen, K. H., Sonnenborg, T. O., and Bircher,
S.: Estimation of regional groundwater recharge using data from a distributed
soil moisture network, Vadose Zone J., 12, 3, https://doi.org/10.2136/vzj2013.01.0035, 2013.
Bartalis, Z., Wagner, W., Naeimi, V., Hasenauer, S., Scipal, K., Bonekamp, H.,
Figa, J., and Anderson, C.: Initial soil moisture retrievals from the METOP-A
Advanced Scatterometer (ASCAT), Geophys. Res. Lett., 34, L20401, https://doi.org/10.1029/2007gl031088, 2007.
Batjes, N. H.: A world dataset of derived soil properties by FAO–UNESCO soil
unit for global modelling, Soil Use Manage., 13, 9–16, 1997.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard,
C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M.,
Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding,
R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1:
Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bierkens, M. F., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David, C.
H., de Roo, A., Döll, P., Drost, N., and Famiglietti, J. S.: Hyper-resolution
global hydrological modelling: what is next? “Everywhere and locally relevant”,
Hydrol. Process., 29, 310–320, 2015.
Bollmeyer, C., Keller, J. D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs,
P., Hense, A., Keune, J., Kneifel, S., and Pscheidt, I.: Towards a high-resolution
regional reanalysis for the European CORDEX domain, Q. J. Roy. Meteorol. Soc.,
141, 1–15, 2015.
Bolten, J. D., Crow, W. T., Zhan, X., Jackson, T. J., and Reynolds, C. A.:
Evaluating the utility of remotely sensed soil moisture retrievals for
operational agricultural drought monitoring, IEEE J. Select. Top. Appl. Earth
Obs. Remote Sens., 3, 57–66, 2010.
Bonan, G. B., Oleson, K. W., Vertenstein, M., Levis, S., Zeng, X., Dai, Y.,
Dickinson, R. E., and Yang, Z.-L.: The land surface climatology of the Community
Land Model coupled to the NCAR Community Climate Model, J. Climate, 15, 3123–3149, 2002.
Brocca, L., Melone, F., Moramarco, T., and Morbidelli, R.: Spatial-temporal
variability of soil moisture and its estimation across scales, Water Resour.
Res., 46, W02516, https://doi.org/10.1029/2009wr008016, 2010.
Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S.:
Assimilation of surface-and root-zone ASCAT soil moisture products into
rainfall–runoff modeling, IEEE T. Geosci. Remote, 50, 2542–2555, 2012.
Burgers, G., van Leeuwen, J. P., and Evensen, G.: Analysis scheme in the ensemble
Kalman filter, Mon. Weather Rev., 126, 1719–1724, 1998.
Cammalleri, C. and Ciraolo, G.: State and parameter update in a coupled
energy/hydrologic balance model using ensemble Kalman filtering, J. Hydrol.,
416, 171–181, 2012.
Chen, H., Yang, D., Hong, Y., Gourley, J. J., and Zhang, Y.: Hydrological data
assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations
to update model states for real-time flash flood forecasting, Adv. Water Resour.,
59, 209–220, https://doi.org/10.1016/j.advwatres.2013.06.010, 2013.
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model
projections of changes in European climate by the end of this century, Climatic
Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J.,
Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R.
J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES),
model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci.
Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A statistical
exploration of the relationships of soil moisture characteristics to the
physical properties of soils, Water Resour. Res., 20, 682–690, 1984.
Crow, W. T. and Ryu, D.: A new data assimilation approach for improving runoff
prediction using remotely-sensed soil moisture retrievals, Hydrol. Earth Syst.
Sci., 13, 1–16, https://doi.org/10.5194/hess-13-1-2009, 2009.
Crow, W. T., Chen, F., Reichle, R. H., and Liu, Q.: L band microwave remote
sensing and land data assimilation improve the representation of prestorm soil
moisture conditions for hydrologic forecasting, Geophys. Res. Lett., 44, 5495–5503, 2017.
Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich, M.
G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., and Niu, G.: The common
land model, B. Am. Meteorol. Soc., 84, 1013–1024, 2003.
Danielson, J. J. and Gesch, D. B.: Global multi-resolution terrain elevation
data 2010 (GMTED2010), US Geological Survey, https://doi.org/10.3133/ofr20111073, 2011.
DeChant, C. M. and Moradkhani, H.: Examining the effectiveness and robustness
of sequential data assimilation methods for quantification of uncertainty in
hydrologic forecasting, Water Resour. Res., 48, 1–15, https://doi.org/10.1029/2011wr011011, 2012.
Dee, D. P., Uppala, S. M., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S.,
Andrae, U., Balmaseda, M., Balsamo, G., Bauer, D. P, Bechtold, P., Beljaars, A.
C., van de Berg, M. L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes,
M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V.,
Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P.,
Monge-Sanz, B. M., Morcrette, J.-J. Park, B.-K., Peubey, C., de Rosnay, P.,
Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis:
Configuration and performance of the data assimilation system, Q. J. Roy.
Meteorol. Soc., 137, 553–597, 2011.
De Lannoy, G. J. and Reichle, R. H.: Global assimilation of multiangle and
multipolarization SMOS brightness temperature observations into the GEOS-5
catchment land surface model for soil moisture estimation, J. Hydrometeorol.,
17, 669–691, 2016.
De Lannoy, G. J., Reichle, R. H., Arsenault, K. R., Houser, P. R., Kumar, S.,
Verhoest, N. E., and Pauwels, V. R.: Multiscale assimilation of Advanced
Microwave Scanning Radiometer – EOS snow water equivalent and Moderate
Resolution Imaging Spectroradiometer snow cover fraction observations in
northern Colorado, Water Resour. Res., 48, W01522, https://doi.org/10.1029/2011wr010588, 2012.
De Rosnay, P., Drusch, M., Boone, A., Balsamo, G., Decharme, B., Harris, P.,
Kerr, Y., Pellarin, T., Polcher, J., and Wigneron, J.-P.: AMMA land surface
model intercomparison experiment coupled to the community microwave emission
model: ALMIP-MEM, J. Geophys. Res.-Atmos., 114, D05108, https://doi.org/10.1029/2008jd010724, 2009.
De Rosnay, P., Drusch, M., Vasiljevic, D., Balsamo, G., Albergel, C., and
Isaksen, L.: A simplified Extended Kalman Filter for the global operational
soil moisture analysis at ECMWF, Q. J. Roy. Meteorol. Soc., 139, 1199–1213, 2013.
Dickinson, R. E., Oleson, K. W., Bonan, G., Hoffman, F., Thornton, P.,
Vertenstein, M., Yang, Z.-L., and Zeng, X.: The Community Land Model and its
climate statistics as a component of the Community Climate System Model, J.
Climate, 19, 2302–2324, 2006.
Dobriyal, P., Qureshi, A., Badola, R., and Hussain, S. A.: A review of the
methods available for estimating soil moisture and its implications for water
resource management, J. Hydrol., 458, 110–117, 2012.
Dorigo, W., de Jeu, R., Chung, D., Parinussa, R., Liu, Y., Wagner, W., and
Fernández-Prieto, D.: Evaluating global trends (1988–2010) in harmonized
multi-satellite surface soil moisture, Geophys. Res. Lett., 39, L18405,
https://doi.org/10.1029/2012gl052988, 2012.
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L.,
Chung, D., Ertl, M., Forkel, M., and Gruber, A.: ESA CCI Soil Moisture for
improved Earth system understanding: State-of-the art and future directions,
Remote Sens. Environ., 203, 185–215, 2017.
Draper, C., Mahfouf, J.-F., and Walker, J.: An EKF assimilation of AMSR-E soil
moisture into the ISBA land surface scheme, J. Geophys. Res.-Atmos., 114,
D20104, https://doi.org/10.1029/2008JD011650, 2009.
Draper, C., Mahfouf, J.-F., Calvet, J.-C., Martin, E., and Wagner, W.:
Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model
over France, Hydrol. Earth Syst. Sci., 15, 3829–3841, https://doi.org/10.5194/hess-15-3829-2011, 2011.
Drusch, M.: Initializing numerical weather prediction models with
satellite-derived surface soil moisture: Data assimilation experiments with
ECMWF's Integrated Forecast System and the TMI soil moisture data set, J.
Geophys. Res.-Atmos., 112, D03102, https://doi.org/10.1029/2006jd007478, 2007.
Drusch, M., Wood, E., and Gao, H.: Observation operators for the direct
assimilation of TRMM microwave imager retrieved soil moisture, Geophys. Res.
Lett., 32, L15403, https://doi.org/10.1029/2005gl023623, 2005.
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T.,
Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J.,
Kimball, J., Piepmeier, J. R., Koster, R. D., Martin, N., McDonald, K. C.,
Moghaddam, M., Moran, S., Reichle, R., Shi, J. C., Spencer, M. W., Thurman, S.
W., Tsang, L., and Van Zyl, J.: The soil moisture active passive (SMAP) mission,
Proc. IEEE, 98, 704–716, 2010.
Evensen, G.: The ensemble Kalman filter: Theoretical formulation and practical
implementation, Ocean Dynam., 53, 343–367, 2003.
Friedl, M. A., McIver, D. K., Hodges, J. C., Zhang, X. Y., Muchoney, D.,
Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., and Cooper, A.:
Global land cover mapping from MODIS: algorithms and early results, Remote
Sens. Environ., 83, 287–302, 2002.
Gasper, F., Goergen, K., Shrestha, P., Sulis, M., Rihani, J., Geimer, M., and
Kollet, S.: Implementation and scaling of the fully coupled Terrestrial Systems
Modeling Platform (TerrSysMP v1.0) in a massively parallel supercomputing
environment – a case study on JUQUEEN (IBM Blue Gene/Q), Geosci. Model Dev.,
7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, 2014.
Gharamti, M. E., Ait-El-Fquih, B., and Hoteit, I.: An iterative ensemble Kalman
filter with one-step-ahead smoothing for state-parameters estimation of
contaminant transport models, J. Hydrol., 527, 442–457, 2015.
Global Runoff Data Center: Long-term mean monthly discharges and annual
characteristics of GRDC stations, Technical Report, The Federal Institute of
Hydrology, Koblenz, Germany, 2011.
Gudmundsson, L. and Seneviratne, S. I.: Observation-based gridded runoff
estimates for Europe (E-RUN version 1.1), Earth Syst. Sci. Data, 8, 279–295,
https://doi.org/10.5194/essd-8-279-2016, 2016.
Gutowski Jr., W. J., Giorgi, F., Timbal, B., Frigon, A., Jacob, D., Kang, H.-S.,
Raghavan, K., Lee, B., Lennard, C., Nikulin, G., O'Rourke, E., Rixen, M., Solman,
S., Stephenson, T., and Tangang, F.: WCRP COordinated Regional Downscaling
EXperiment (CORDEX): a diagnostic MIP for CMIP6, Geosci. Model Dev., 9,
4087–4095, https://doi.org/10.5194/gmd-9-4087-2016, 2016.
Han, X., Franssen, H.-J. H., Montzka, C., and Vereecken, H.: Soil moisture and
soil properties estimation in the Community Land Model with synthetic brightness
temperature observations, Water Resour. Res., 50, 6081–6105, 2014.
Haylock, M. R., Hofstra, N., Tank, A. K., Klok, E. J., Jones, P. D., and New,
M.: A European daily high-resolution gridded data set of surface temperature
and precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113, D20119,
https://doi.org/10.1029/2008jd010201, 2008.
Hijmans, R., Cameron, S., Parra, J., Jones, P., Jarvis, A., and Richardson, K.:
WorldClim, version 1.3, University of California, Berkeley, 2005.
Hunt, B. R., Kostelich, E. J., and Szunyogh, I.: Efficient data assimilation
for spatiotemporal chaos: A local ensemble transform Kalman filter, Physica D,
230, 112–126, 2007.
Jones, P. W.: First-and second-order conservative remapping schemes for grids
in spherical coordinates, Mon. Weather Rev., 127, 2204–2210, 1999.
Kerr, Y. H., Waldteufel, P., Wigneron, J.-P., Martinuzzi, J., Font, J., and
Berger, M.: Soil moisture retrieval from space: The Soil Moisture and Ocean
Salinity (SMOS) mission, IEEE T. Geosci. Remote, 39, 1729–1735, 2001.
Keune, J., Gasper, F., Goergen, K., Hense, A., Shrestha, P., Sulis, M., and
Kollet, S.: Studying the influence of groundwater representations on land
surface–atmosphere feedbacks during the European heat wave in 2003, J. Geophys.
Res.-Atmos., 121, 13301–13325, https://doi.org/10.1002/2016jd025426, 2016.
Kiehl, J. T. and Trenberth, K. E.: Earth's annual global mean energy budget, B.
Am. Meteorol. Soc., 78, 197–208, 1997.
Kumar, S. V., Reichle, R. H., Peters-Lidard, C. D., Koster, R. D., Zhan, X.,
Crow, W. T., Eylander, J. B., and Houser, P. R.: A land surface data assimilation
framework using the land information system: Description and applications, Adv.
Water Resour., 31, 1419–1432, 2008.
Kurtz, W., He, G., Kollet, S. J., Maxwell, R. M., Vereecken, H., and
Hendricks Franssen, H.-J.: TerrSysMP-PDAF (version 1.0): a modular high-performance
data assimilation framework for an integrated land surface–subsurface model,
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, 2016.
Lahoz, W. A. and De Lannoy, G. J.: Closing the gaps in our knowledge of the
hydrological cycle over land: Conceptual problems, Surv. Geophys., 35, 623–660, 2014.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C.,
Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S., Sakaguchi, K., Bonan, G. B.,
and Slater, A. G.: Parameterization improvements and functional and structural
advances in version 4 of the Community Land Model, J. Adv. Model. Earth Syst.,
3, 1, https://doi.org/10.1029/2011ms00045, 2011.
Li, H., Huang, M., Wigmosta, M. S., Ke, Y., Coleman, A. M., Leung, L. R., Wang,
A., and Ricciuto, D. M.: Evaluating runoff simulations from the Community Land
Model 4.0 using observations from flux towers and a mountainous watershed, J.
Geophys. Res.-Atmos., 116, D24120, https://doi.org/10.1029/2011jd016276, 2011.
Li, M. and Ma, Z.: Soil moisture drought detection and multi-temporal variability
across China, Sci. China Earth Sci., 58, 1798–1813, 2015.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple
hydrologically based model of land surface water and energy fluxes for general
circulation models, J. Geophys. Res.-Atmos., 99, 14415–14428, 1994.
Liang, X., Wood, E. F., and Lettenmaier, D. P.: Surface soil moisture
parameterization of the VIC-2L model: Evaluation and modification, Global
Planet. Change, 13, 195–206, 1996.
Lievens, H., Tomer, S. K., Al Bitar, A., De Lannoy, G. J., Drusch, M., Dumedah,
G., Franssen, H.-J. H., Kerr, Y. H., Martens, B., and Pan, M.: SMOS soil
moisture assimilation for improved hydrologic simulation in the Murray Darling
Basin, Australia, Remote Sens. Environ., 168, 146–162, 2015.
Lievens, H., De Lannoy, G. J. M., Al Bitar, A., Drusch, M., Dumedah, G.,
Hendricks Franssen, H.-J., Kerr, Y. H., Tomer, S. K., Martens, B., Merlin, O.,
Pan, M., Roundy, J. K., Vereecken, H., Walker, J. P., Wood, E. F., Verhoest, N.
E. C., and Pauwels, V. R. N.: Assimilation of SMOS soil moisture and brightness
temperature products into a land surface model, Remote Sens. Environ., 180, 292–304, 2016.
Liu, D. and Mishra, A. K.: Performance of AMSR_E soil moisture data assimilation
in CLM4.5 model for monitoring hydrologic fluxes at global scale, J. Hydrol.,
547, 67–79, 2017.
Liu, D., Mishra, A. K., and Yu, Z.: Evaluating uncertainties in multi-layer
soil moisture estimation with support vector machines and ensemble Kalman
filtering, J. Hydrol., 538, 243–255, 2016.
Liu, Y. and Gupta, H. V.: Uncertainty in hydrologic modeling: Toward an
integrated data assimilation framework, Water Resour. Res., 43, W07401,
https://doi.org/10.1029/2006wr005756, 2007.
Liu, Y., Wang, W., and Liu, Y.: ESA CCI Soil Moisture Assimilation in SWAT for
Improved Hydrological Simulation in Upper Huai River Basin, Adv. Meteorol.,
2018, 1–13, https://doi.org/10.1155/2018/7301314, 2018.
Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W.,
van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P.: Developing an improved
soil moisture dataset by blending passive and active microwave satellite-based
retrievals, Hydrol. Earth Syst. Sci., 15, 425–436, https://doi.org/10.5194/hess-15-425-2011, 2011.
Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., de Jeu, R. A., Wagner, W., McCabe,
M. F., Evans, J. P., and Van Dijk, A.: Trend-preserving blending of passive and
active microwave soil moisture retrievals, Remote Sens. Environ., 123, 280–297, 2012.
López López, P., Wanders, N., Schellekens, J., Renzullo, L. J.,
Sutanudjaja, E. H., and Bierkens, M. F. P.: Improved large-scale hydrological
modelling through the assimilation of streamflow and downscaled satellite soil
moisture observations, Hydrol. Earth Syst. Sci., 20, 3059–3076, https://doi.org/10.5194/hess-20-3059-2016, 2016.
Matgen, P., Fenicia, F., Heitz, S., Plaza, D., de Keyser, R., Pauwels, V. R.,
Wagner, W., and Savenije, H.: Can ASCAT-derived soil wetness indices reduce
predictive uncertainty in well-gauged areas? A comparison with in situ observed
soil moisture in an assimilation application, Adv. Water Resour., 44, 49–65, 2012.
McNally, A., Shukla, S., Arsenault, K. R., Wang, S., Peters-Lidard, C. D., and
Verdin, J. P.: Evaluating ESA CCI soil moisture in East Africa, Int. J. Appl.
Earth Obs. Geoinform., 48, 96–109, 2016.
Mecklenburg, S., Drusch, M., Kaleschke, L., Rodriguez-Fernandez, N., Reul, N.,
Kerr, Y., Font, J., Martin-Neira, M., Oliva, R., Daganzo-Eusebio, E., Grant, J.
P., Sabia, R., Macelloni, G., Rautiainen, K., Fauste, J., de Rosnay, P.,
Munoz-Sabater, J., Verhoest, N., Lievens, H., Delwart, S., Crapolicchio, R.,
de la Fuente, A., and Kornberg, M.: ESA's Soil Moisture and Ocean Salinity
mission: From science to operational applications, Remote Sens. Environ., 180,
3–18, https://doi.org/10.1016/j.rse.2015.12.025, 2016.
Merlin, O., Escorihuela, M. J., Mayoral, M. A., Hagolle, O., Al Bitar, A., and
Kerr, Y.: Self-calibrated evaporation-based disaggregation of SMOS soil moisture:
An evaluation study at 3 km and 100 m resolution in Catalunya, Spain, Remote
Sens. Environ., 130, 25–38, 2013.
Mohanty, B. P., Cosh, M., Lakshmi, V., and Montzka, C.: Remote sensing for
vadose zone hydrology – a synthesis from the vantage point, Vadose Zone J.,
12, 3, https://doi.org/10.2136/vzj2013.07.012, 2013.
Montzka, C., Pauwels, V., Franssen, H.-J. H., Han, X., and Vereecken, H.:
Multivariate and multiscale data assimilation in terrestrial systems: A review,
Sensors, 12, 16291–16333, 2012.
Moradkhani, H., Sorooshian, S., Gupta, H. V., and Houser, P. R.: Dual
state–parameter estimation of hydrological models using ensemble Kalman filter,
Adv. Water Resour., 28, 135–147, 2005.
Nerger, L. and Hiller, W.: Software for ensemble-based data assimilation
systems – Implementation strategies and scalability, Comput. Geosci., 55, 110–118, 2013.
Nie, S., Zhu, J., and Luo, Y.: Simultaneous estimation of land surface scheme
states and parameters using the ensemble Kalman filter: identical twin
experiments, Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, 2011.
Ni-Meister, W., Houser, P. R., and Walker, J. P.: Soil moisture initialization
for climate prediction: Assimilation of scanning multifrequency microwave
radiometer soil moisture data into a land surface model, J. Geophys. Res.-Atmos.,
111, D20102, https://doi.org/10.1029/2006jd007190, 2006.
Niu, G.-Y., Yang, Z.-L., Dickinson, R. E., and Gulden, L. E.: A simple
TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate
models, J. Geophys. Res.-Atmos., 110, D21106, https://doi.org/10.1029/2005jd006111, 2005.
Niu, G.-Y., Yang, Z.-L., Dickinson, R. E., Gulden, L. E., and Su, H.: Development
of a simple groundwater model for use in climate models and evaluation with
Gravity Recovery and Climate Experiment data, J. Geophys. Res.-Atmos., 112,
D07103, https://doi.org/10.1029/2006jd007522, 2007.
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M.,
Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The
community Noah land surface model with multiparameterization options (Noah-MP):
1. Model description and evaluation with local-scale measurements, J. Geophys.
Res.-Atmos., 116, D12109, https://doi.org/10.1029/2010jd015139, 2011.
Oleson, K. W., Dai, Y., Bonan, G., Bosilovich, M., Dickinson, R., Dirmeyer, P.,
Hoffman, F., Houser, P., Levis, S., and Niu, G. Y.: Technical description of
the community land model (CLM), NCAR Technical Note NCAR/TN−461+STR,
National Center for Atmospheric Research, Boulder, CO, 2004.
Oleson, K. W., Niu, G.-Y., Yang, Z.-L., Lawrence, D. M., Thornton, P. E.,
Lawrence, P. J., Stöckli, R., Dickinson, R. E., Bonan, G. B., and Levis, S.:
Improvements to the Community Land Model and their impact on the hydrological
cycle, J. Geophys. Res.-Biogeo., 113, G01021, https://doi.org/10.1029/2007jg000563, 2008.
Owe, M., de Jeu, R., and Holmes, T.: Multisensor historical climatology of
satellite-derived global land surface moisture, J. Geophys. Res.-Earth, 113,
F01002, https://doi.org/10.1029/2007jf000769, 2008.
Pan, M. and Wood, E. F.: Impact of accuracy, spatial availability, and revisit
time of satellite-derived surface soil moisture in a multiscale ensemble data
assimilation system, IEEE Select. Top. Appl. Earth Obs. Remote Sens., 3, 49–56, 2010.
Pan, M., Wood, E. F., Wójcik, R., and McCabe, M. F.: Estimation of regional
terrestrial water cycle using multi-sensor remote sensing observations and data
assimilation, Remote Sens. Environ., 112, 1282–1294, 2008.
Pathiraja, S., Marshall, L., Sharma, A., and Moradkhani, H.: Detecting
non-stationary hydrologic model parameters in a paired catchment system using
data assimilation, Adv. Water Resour., 94, 103–119, 2016.
Pauwels, V. R., Hoeben, R., Verhoest, N. E., and De Troch, F. P.: The importance
of the spatial patterns of remotely sensed soil moisture in the improvement of
discharge predictions for small-scale basins through data assimilation, J.
Hydrol., 251, 88–102, 2001.
Pauwels, V. R., Hoeben, R., Verhoest, N. E., De Troch, F. P., and Troch, P. A.:
Improvement of TOPLATS-based discharge predictions through assimilation of
ERS-based remotely sensed soil moisture values, Hydrol. Process., 16, 995–1013, 2002.
Rafieeinasab, A., Seo, D.-J., Lee, H., and Kim, S.: Comparative evaluation of
maximum likelihood ensemble filter and ensemble Kalman filter for real-time
assimilation of streamflow data into operational hydrologic models, J. Hydrol.,
519, 2663–2675, 2014.
Rains, D., Han, X., Lievens, H., Montzka, C., and Verhoest, N. E. C.: SMOS
brightness temperature assimilation into the Community Land Model, Hydrol. Earth
Syst. Sci., 21, 5929–5951, https://doi.org/10.5194/hess-21-5929-2017, 2017.
Reichle, R. H. and Koster, R. D.: Bias reduction in short records of satellite
soil moisture, Geophys. Res. Lett., 31, L19501, https://doi.org/10.1029/2004gl020938, 2004.
Reichle, R. H. and Koster, R. D.: Global assimilation of satellite surface soil
moisture retrievals into the NASA Catchment land surface model, Geophys. Res.
Lett., 32, L02404, https://doi.org/10.1029/2004gl021700, 2005.
Renzullo, L. J., Van Dijk, A., Perraud, J.-M., Collins, D., Henderson, B., Jin,
H., Smith, A. B., and McJannet, D. L.: Continental satellite soil moisture data
assimilation improves root-zone moisture analysis for water resources assessment,
J. Hydrol., 519, 2747–2762, 2014.
Rodell, M., Houser, P. R., Jambor, U. E. A., Gottschalck, J., Mitchell, K.,
Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., and Bosilovich, M.:
The global land data assimilation system, B. Am. Meteorol. Soc., 85, 381–394, 2004.
Running, S. W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., and
Hashimoto, H.: A continuous satellite-derived measure of global terrestrial
primary production, AIBS Bull., 54, 547–560, 2004.
Sahoo, A. K., De Lannoy, G. J., Reichle, R. H., and Houser, P. R.: Assimilation
and downscaling of satellite observed soil moisture over the Little River
Experimental Watershed in Georgia, USA, Adv. Water Resour., 52, 19–33, 2013.
Samuel, J., Coulibaly, P., Dumedah, G., and Moradkhani, H.: Assessing model
state and forecasts variation in hydrologic data assimilation, J. Hydrol.,
513, 127–141, 2014.
Schaap, M. G. and Leij, F. J.: Database-related accuracy and uncertainty of
pedotransfer functions, Soil Science, 163, 765–779, 1998.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner,
I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate
interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, 2010.
Sheng, M., Lei, H., Jiao, Y., and Yang, D.: Evaluation of the runoff and river
routing schemes in the Community Land Model of the Yellow River basin, J. Adv.
Model. Earth Syst., 9, 2993–3018, 2017.
Shock, C. C., Barnum, J. M., and Seddigh, M.: Calibration of Watermark Soil
Moisture Sensors for Irrigation Management, Plant Soil, 143, 213–217,
https://doi.org/10.1007/bf00007875, 1998.
Shrestha, P., Sulis, M., Masbou, M., Kollet, S., and Simmer, C.: A
scale-consistent terrestrial systems modeling platform based on COSMO, CLM,
and ParFlow, Mon. Weather Rev., 142, 3466–3483, 2014.
Simmer, C., Adrian, G., Jones, S., Wirth, V., Göber, M., Hohenegger, C.,
Janjic, T., Keller, J., Ohlwein, C., and Seifert, A.: Herz: The german hans-ertel
centre for weather research, B. Am. Meteorol. Soc., 97, 1057–1068, 2016.
Springer, A., Eicker, A., Bettge, A., Kusche, J., and Hense, A.: Evaluation
of the Water Cycle in the European COSMO-REA6 Reanalysis Using GRACE, Water,
9, 289, https://doi.org/10.3390/w9040289, 2017.
Sridhar, V., Hubbard, K. G., You, J., and Hunt, E. D.: Development of the soil
moisture index to quantify agricultural drought and its “user friendliness”
in severity-area-duration assessment, J. Hydrometeorol., 9, 660–676, 2008.
Stöckli, R., Lawrence, D. M., Niu, G.-Y., Oleson, K. W., Thornton, P. E.,
Yang, Z.-L., Bonan, G. B., Denning, A. S., and Running, S. W.: Use of FLUXNET
in the Community Land Model development, J. Geophys. Res.-Biogeo., 113, 001025,
https://doi.org/10.1029/2007jg000562, 2008.
Trenberth, K. E., Smith, L., Qian, T., Dai, A., and Fasullo, J.: Estimates of
the global water budget and its annual cycle using observational and model data,
J. Hydrometeorol., 8, 758–769, 2007.
Vereecken, H., Schnepf, A., Hopmans, J. W., Javaux, M., Or, D., Roose, T.,
Vanderborght, J., Young, M. H., Amelung, W., Aitkenhead, M., Allison, S. D.,
Assouline, S., Baveye, P., Berli, M., Brüggemann, N., Finke, P., Flury, M.,
Gaiser, T., Govers, G., Ghezzehei, T., Hallett, P., Franssen, H. J. H., Heppell,
J., Horn, R., Huisman, J. A., Jacques, D., Jonard, F., Kollet, S., Lafolie, F.,
Lamorski, K., Leitner, D., McBratney, A., Minasny, B., Montzka, C., Nowak, W.,
Pachepsky, Y., Padarian, J., Romano, N., Roth, K., Rothfuss, Y., Rowe, E. C.,
Schwen, A., Šimunek, J., Tiktak, A., Dam, J. V., van der Zee, S. E. A.
T. M., Vogel, H. J., Vrugt, J. A., Wöhling, T., and Young, I. M.: Modeling
soil processes: Review, key challenges, and new perspectives, Vadose Zone J.,
15, https://doi.org/10.2136/vzj2015.09.0131, 2016.
Verhoest, N. E. C., van den Berg, M. J., Martens, B., Lievens, H., Wood, E. F.,
Pan, M., Kerr, Y. H., Al Bitar, A., Tomer, S. K., Drusch, M., Vernieuwe, H.,
De Baets, B., Walker, J. P., Dumedah, G., and Pauwels, V. R. N.: Copula-based
downscaling of coarse-scale soil moisture observations with implicit bias
correction, IEEE T. Geosci. Remote, 53, 3507–3521, 2015.
Vinukollu, R. K., Wood, E. F., Ferguson, C. R., and Fisher, J. B.: Global
estimates of evapotranspiration for climate studies using multi-sensor remote
sensing data: Evaluation of three process-based approaches, Remote Sens. Environ.,
115, 801–823, 2011.
Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E.,
and Ertl, M.: Fusion of active and passive microwave observations to create
an essential climate variable data record on soil moisture, ISPRS Annals,
7, 315–321, 2012.
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S.,
Figa-Saldaña, J., de Rosnay, P., Jann, A., and Schneider, S.: The ASCAT
soil moisture product: A review of its specifications, validation results, and
emerging applications, Meteorol. Z., 22, 5–33, 2013.
Wang, J.: Microwave Emission from Smooth Bare Fields and Soil Moisture Sampling
Depth, IEEE T. Geosci. Remote, GE-25, 616–622, https://doi.org/10.1109/TGRS.1987.289840, 1987.
Wahl, S., Bollmeyer, C., Crewell, S., Figura, C., Friederichs, P., Hense, A.,
Keller, J. D., and Ohlwein, C.: A novel convective-scale regional reanalysis
COSMO-REA2: Improving the representation of precipitation, Meteorol. Z., 26,
345–361, https://doi.org/10.1127/metz/2017/0824, 2017.
Western, A. W., Zhou, S.-L., Grayson, R. B., McMahon, T. A., Blöschl, G.,
and Wilson, D. J.: Spatial correlation of soil moisture in small catchments
and its relationship to dominant spatial hydrological processes, J. Hydrol.,
286, 113–134, 2004.
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F. P.,
Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de
Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B., Lettenmaier,
D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade, A., and Whitehead,
P.: Hyperresolution global land surface modeling: Meeting a grand challenge for
monitoring Earth's terrestrial water: OPINION, Water Resour. Res., 47, W05301,
https://doi.org/10.1029/2010WR010090, 2011.
Xiao, Z., Liang, S., Wang, J., Chen, P., Yin, X., Zhang, L., and Song, J.: Use
of General Regression Neural Networks for Generating the GLASS Leaf Area Index
Product From Time-Series MODIS Surface Reflectance, IEEE T. Geosci. Remote.,
52, 209–223, https://doi.org/10.1109/TGRS.2013.2237780 2014.
Xie, X. and Zhang, D.: Data assimilation for distributed hydrological catchment
modeling via ensemble Kalman filter, Adv. Water Resour., 33, 678–690, 2010.
Yang, Z.-L. and Niu, G.-Y.: The versatile integrator of surface and atmosphere
processes: Part 1. Model description, Global Planet. Change, 38, 175–189, 2003.
Yin, J., Zhan, X., Zheng, Y., Hain, C. R., Liu, J., and Fang, L.: Optimal
ensemble size of ensemble Kalman filter in sequential soil moisture data
assimilation, Geophys. Res. Lett., 42, 6710–6715, https://doi.org/10.1002/2015GL063366, 2015.
Zeng, X. and Decker, M.: Improving the numerical solution of soil moisture-based
Richards equation for land models with a deep or shallow water table, J.
Hydrometeorol., 10, 308–319, 2009.
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...
