Articles | Volume 23, issue 1
Hydrol. Earth Syst. Sci., 23, 277–301, 2019
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.
Hydrol. Earth Syst. Sci., 23, 277–301, 2019
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
Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation
Bibi S. Naz et al.
Related authors
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
Short summary
Short summary
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.
Yafei Huang, Jonas Weis, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-569, https://doi.org/10.5194/hess-2021-569, 2021
Preprint under review for HESS
Short summary
Short summary
Trends in agricultural droughts cannot be easily deduced from measurements. Here trends in agricultural droughts over 31 German and Dutch sites were calculated with model simulations and long-term observed meteorological data as input. We found that agricultural droughts are increasing although precipitation hardly decreases. The increase is driven by increase in evapotranspiration. The year 2018 was for half of the sites the year with the most extreme agricultural drought in the last 55 years.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
Short summary
Short summary
The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
Short summary
Short summary
In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Lukas Strebel, Heye Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-38, https://doi.org/10.5194/gmd-2021-38, 2021
Revised manuscript under review for GMD
Short summary
Short summary
We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-180, https://doi.org/10.5194/gmd-2021-180, 2021
Preprint under review for GMD
Short summary
Short summary
Air is transporting moisture and heat, shaping the weather we experience. When and where was this air moistened and warmed by the surface? To address this question, atmospheric models trace the history of air parcels in space and time. However, their uncertainties remain unexplored, which hinders their utility and application. Here, we present a framework that sheds light on these uncertainties. Our approach sets a new standard in the assessment of atmospheric moisture and heat trajectories.
Yueling Ma, Carsten Montzka, Bagher Bayat, and Stefan Kollet
Hydrol. Earth Syst. Sci., 25, 3555–3575, https://doi.org/10.5194/hess-25-3555-2021, https://doi.org/10.5194/hess-25-3555-2021, 2021
Short summary
Short summary
This study utilized spatiotemporally continuous precipitation anomaly (pra) and water table depth anomaly (wtda) data from integrated hydrologic simulation results over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the time-varying and time-lagged relationship between pra and wtda in order to obtain reliable models to estimate wtda at the individual pixel level.
Susannah Rennie, Klaus Goergen, Christoph Wohner, Sander Apweiler, Johannes Peterseil, and John Watkins
Earth Syst. Sci. Data, 13, 631–644, https://doi.org/10.5194/essd-13-631-2021, https://doi.org/10.5194/essd-13-631-2021, 2021
Short summary
Short summary
This paper describes a pan-European climate service data product intended for ecological researchers. Access to regional climate scenario data will save ecologists time, and, for many, it will allow them to work with data resources that they will not previously have used due to a lack of knowledge and skills to access them. Providing easy access to climate scenario data in this way enhances long-term ecological research, for example in general regional climate change or impact assessments.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
Short summary
Short summary
In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Jie Tian, Zhibo Han, Heye Reemt Bogena, Johan Alexander Huisman, Carsten Montzka, Baoqing Zhang, and Chansheng He
Hydrol. Earth Syst. Sci., 24, 4659–4674, https://doi.org/10.5194/hess-24-4659-2020, https://doi.org/10.5194/hess-24-4659-2020, 2020
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Large-scale sensitivities of groundwater and surface water to groundwater withdrawal
A hydrography upscaling method for scale-invariant parametrization of distributed hydrological models
A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods
Bright and blind spots of water research in Latin America and the Caribbean
Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters
Nonstationary weather and water extremes: a review of methods for their detection, attribution, and management
Robust historical evapotranspiration trends across climate regimes
A note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modeling
Global scenarios of irrigation water abstractions for bioenergy production: a systematic review
Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling
Uncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble study
Ubiquitous increases in flood magnitude in the Columbia River basin under climate change
Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors
The role of household adaptation measures in reducing vulnerability to flooding: a coupled agent-based and flood modelling approach
Assessing global water mass transfers from continents to oceans over the period 1948–2016
Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface model
The influence of assimilating leaf area index in a land surface model on global water fluxes and storages
Comparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time steps
The pantropical response of soil moisture to El Niño
HESS Opinions: Beyond the long-term water balance: evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds
Global assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration rates
Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling
Quantification of drainable water storage volumes on landmasses and in river networks based on GRACE and river runoff using a cascaded storage approach – first application on the Amazon
Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation
Projected increases in magnitude and socioeconomic exposure of global droughts in 1.5 and 2 °C warmer climates
Spatiotemporal assimilation–interpolation of discharge records through inverse streamflow routing
Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets
Climate change, reforestation/afforestation, and urbanization impacts on evapotranspiration and streamflow in Europe
Multi-decadal hydrologic change and variability in the Amazon River basin: understanding terrestrial water storage variations and drought characteristics
Multimodel assessments of human and climate impacts on mean annual streamflow in China
Toward continental hydrologic–hydrodynamic modeling in South America
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed
The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models
Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation
Remote land use impacts on river flows through atmospheric teleconnections
Understanding terrestrial water storage variations in northern latitudes across scales
Assimilation of river discharge in a land surface model to improve estimates of the continental water cycles
Harnessing big data to rethink land heterogeneity in Earth system models
Predicting groundwater recharge for varying land cover and climate conditions – a global meta-study
Near-real-time adjusted reanalysis forcing data for hydrology
Deduction of reservoir operating rules for application in global hydrological models
A global hydrological simulation to specify the sources of water used by humans
A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010
Comparing soil moisture anomalies from multiple independent sources over different regions across the globe
Hydrological impacts of global land cover change and human water use
Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods
The effect of GCM biases on global runoff simulations of a land surface model
Toward seamless hydrologic predictions across spatial scales
Human–water interface in hydrological modelling: current status and future directions
Skill of a global forecasting system in seasonal ensemble streamflow prediction
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Salma Tafasca, Agnès Ducharne, and Christian Valentin
Hydrol. Earth Syst. Sci., 24, 3753–3774, https://doi.org/10.5194/hess-24-3753-2020, https://doi.org/10.5194/hess-24-3753-2020, 2020
Short summary
Short summary
In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we use different input global soil texture maps from the literature to investigate the impact of soil texture on the simulated water budget in an LSM. The medium loamy textures give the highest evapotranspiration and lowest total runoff rates. However, the different soil texture maps result in similar water budgets because of their inherent similarities, especially when upscaled at the 0.5° resolution.
Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko
Hydrol. Earth Syst. Sci., 24, 3775–3788, https://doi.org/10.5194/hess-24-3775-2020, https://doi.org/10.5194/hess-24-3775-2020, 2020
Short summary
Short summary
This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mark D. Wahl, and Michael L. Follum
Hydrol. Earth Syst. Sci., 24, 2711–2729, https://doi.org/10.5194/hess-24-2711-2020, https://doi.org/10.5194/hess-24-2711-2020, 2020
Short summary
Short summary
Global-scale hydrologic forecasts should account for attenuation through lakes and reservoirs. There is no consensus on the best approach to estimating this attenuation in large-spatial-scale hydrologic forecasts. This article investigates two existing parsimonious approaches to estimating reservoir outflows. We test each method at 60 reservoirs in the United States. We find that a method first developed in 2003 can provide a reasonable approximation of diurnal reservoir outflows.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
Short summary
Short summary
We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
A. Sankarasubramanian, Dingbao Wang, Stacey Archfield, Meredith Reitz, Richard M. Vogel, Amirhossein Mazrooei, and Sudarshana Mukhopadhyay
Hydrol. Earth Syst. Sci., 24, 1975–1984, https://doi.org/10.5194/hess-24-1975-2020, https://doi.org/10.5194/hess-24-1975-2020, 2020
Short summary
Short summary
The Budyko framework which relies on the supply and demand concept could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response. This framework is extended with a few illustrative examples for quantifying the variability in land-surface fluxes for natural and human-altered watersheds. Potential for using observed and remotely sensed datasets in capturing this variability is also discussed.
Elham Rouholahnejad Freund, Ying Fan, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 1927–1938, https://doi.org/10.5194/hess-24-1927-2020, https://doi.org/10.5194/hess-24-1927-2020, 2020
Short summary
Short summary
Evapotranspiration (ET) rates and properties that regulate them are spatially heterogeneous. Averaging over spatial heterogeneity in precipitation (P) and potential evapotranspiration (PET) as the main drivers of ET may lead to biased estimates of energy and water fluxes from the land to the atmosphere. We show that this bias is largest in mountainous terrains, in regions with temperate climates and dry summers, and in landscapes where spatial variations in P and PET are inversely correlated.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
Short summary
Short summary
Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Johannes Riegger
Hydrol. Earth Syst. Sci., 24, 1447–1465, https://doi.org/10.5194/hess-24-1447-2020, https://doi.org/10.5194/hess-24-1447-2020, 2020
Short summary
Short summary
The combined use of GRACE mass anomalies and observed river discharge for the first time allows us to quantify the water storage volumes drainable by gravity on global scales. Modelling of catchment and river network storages in a cascade with different dynamics reveals the time lag between total mass and runoff is caused by a non-zero river network storage. This allows catchment and river network storage volumes to be distinguished and is thus of great importance for water resources management.
Berit Arheimer, Rafael Pimentel, Kristina Isberg, Louise Crochemore, Jafet C. M. Andersson, Abdulghani Hasan, and Luis Pineda
Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, https://doi.org/10.5194/hess-24-535-2020, 2020
Short summary
Short summary
How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide, covering the entire globe with a relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.
Lei Gu, Jie Chen, Jiabo Yin, Sylvia C. Sullivan, Hui-Min Wang, Shenglian Guo, Liping Zhang, and Jong-Suk Kim
Hydrol. Earth Syst. Sci., 24, 451–472, https://doi.org/10.5194/hess-24-451-2020, https://doi.org/10.5194/hess-24-451-2020, 2020
Short summary
Short summary
Focusing on the multifaceted nature of droughts, this study quantifies the change in global drought risks for 1.5 and 2.0 °C warming trajectories by a multi-model ensemble under three representative concentration pathways (RCP2.6, 4.5 and 8.5). Socioeconomic exposures are investigated by incorporating the dynamic shared socioeconomic pathways (SSPs) into the drought impact assessment. The results show that even the ambitious 1.5 °C warming level can cause substantial increases on the global scale.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305, https://doi.org/10.5194/hess-24-293-2020, https://doi.org/10.5194/hess-24-293-2020, 2020
Short summary
Short summary
Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Frederik Kratzert, Daniel Klotz, Guy Shalev, Günter Klambauer, Sepp Hochreiter, and Grey Nearing
Hydrol. Earth Syst. Sci., 23, 5089–5110, https://doi.org/10.5194/hess-23-5089-2019, https://doi.org/10.5194/hess-23-5089-2019, 2019
Short summary
Short summary
A new approach for regional rainfall–runoff modeling using long short-term memory (LSTM)-based models is presented and benchmarked against a range of well-known hydrological models. The approach significantly outperforms regionally calibrated hydrological models but also basin-wise calibrated models. Furthermore, we propose an adaption of the LSTM that allows us to extract the learned catchment understanding of the model and show that it matches our hydrology expert knowledge.
Adriaan J. Teuling, Emile A. G. de Badts, Femke A. Jansen, Richard Fuchs, Joost Buitink, Anne J. Hoek van Dijke, and Shannon M. Sterling
Hydrol. Earth Syst. Sci., 23, 3631–3652, https://doi.org/10.5194/hess-23-3631-2019, https://doi.org/10.5194/hess-23-3631-2019, 2019
Short summary
Short summary
Over the past decades, changes in land use and climate over Europe have impacted the average flow of water flowing through rivers and reservoirs (the so-called
water yield). We quantify these changes using a simple but widely tested modelling approach constrained by observations of lysimeters across Europe. Results show that the contribution of land use to changes in water yield are of the same order as changes in climate, showing that impacts of land use changes cannot be neglected.
Suyog Chaudhari, Yadu Pokhrel, Emilio Moran, and Gonzalo Miguez-Macho
Hydrol. Earth Syst. Sci., 23, 2841–2862, https://doi.org/10.5194/hess-23-2841-2019, https://doi.org/10.5194/hess-23-2841-2019, 2019
Short summary
Short summary
Comprehensive characterization of extreme drought events in the Amazon is provided with respect to their cause, type, spatial extent, and impact on different water stores. Basin-averaged trends in water storage indicate that the Amazon is getting wetter; however its southern and southeastern portions are getting drier. Water deficit is found to be 3-fold higher than the total water supplied during some drought years. Water deficit due to low precipitation events is absorbed by the groundwater.
Xingcai Liu, Wenfeng Liu, Hong Yang, Qiuhong Tang, Martina Flörke, Yoshimitsu Masaki, Hannes Müller Schmied, Sebastian Ostberg, Yadu Pokhrel, Yusuke Satoh, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 23, 1245–1261, https://doi.org/10.5194/hess-23-1245-2019, https://doi.org/10.5194/hess-23-1245-2019, 2019
Short summary
Short summary
Human activities associated with water resource management have significantly increased in China during the past decades. This assessment helps us understand how streamflow has been affected by climate and human activities in China. Our analyses indicate that the climate impact has dominated streamflow changes in most areas, and human activities (in terms of water withdrawals) have increasingly decreased streamflow in the northern basins of China which are vulnerable to future climate change.
Vinícius A. Siqueira, Rodrigo C. D. Paiva, Ayan S. Fleischmann, Fernando M. Fan, Anderson L. Ruhoff, Paulo R. M. Pontes, Adrien Paris, Stéphane Calmant, and Walter Collischonn
Hydrol. Earth Syst. Sci., 22, 4815–4842, https://doi.org/10.5194/hess-22-4815-2018, https://doi.org/10.5194/hess-22-4815-2018, 2018
Short summary
Short summary
Providing reliable estimates of water fluxes at the continental scale is challenging. We extended a regional hydrological model to the entirety of South America and assessed its performance using multiple observations. After a comparison with global models, we show the extent to which estimates of daily river discharge can be improved, even by using global forcing data. Issues of global-/continental-scale modeling and future directions for simulating discharge in this continent are discussed.
David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine
Hydrol. Earth Syst. Sci., 22, 4685–4697, https://doi.org/10.5194/hess-22-4685-2018, https://doi.org/10.5194/hess-22-4685-2018, 2018
Short summary
Short summary
In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.
Anouk I. Gevaert, Ted I. E. Veldkamp, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 4649–4665, https://doi.org/10.5194/hess-22-4649-2018, https://doi.org/10.5194/hess-22-4649-2018, 2018
Short summary
Short summary
Drought is a natural hazard that has severe environmental and socioeconomic impacts around the globe. Here, we quantified the time taken for drought to propagate from precipitation droughts to soil moisture and streamflow droughts. Results show that propagation timescales are strongly related to climate type, with fast responses in tropical regions and slow responses in arid regions. Insight into the timescales of drought propagation globally may help improve seasonal drought forecasting.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619, https://doi.org/10.5194/hess-22-4605-2018, https://doi.org/10.5194/hess-22-4605-2018, 2018
Short summary
Short summary
We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
Lan Wang-Erlandsson, Ingo Fetzer, Patrick W. Keys, Ruud J. van der Ent, Hubert H. G. Savenije, and Line J. Gordon
Hydrol. Earth Syst. Sci., 22, 4311–4328, https://doi.org/10.5194/hess-22-4311-2018, https://doi.org/10.5194/hess-22-4311-2018, 2018
Short summary
Short summary
Winds carry air moisture from one place to another. Thus, land-use change that alters air moisture content can also modify downwind rainfall and distant river flows. This aspect has rarely been taken into account in studies of river flow changes. We show here that remote land-use change effect on rainfall can exceed that of local, and that foreign nation influence on river flows is much more prevalent than previously thought. This has important implications for both land and water governance.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung
Hydrol. Earth Syst. Sci., 22, 4061–4082, https://doi.org/10.5194/hess-22-4061-2018, https://doi.org/10.5194/hess-22-4061-2018, 2018
Short summary
Short summary
In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage. We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis. While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Fuxing Wang, Jan Polcher, Philippe Peylin, and Vladislav Bastrikov
Hydrol. Earth Syst. Sci., 22, 3863–3882, https://doi.org/10.5194/hess-22-3863-2018, https://doi.org/10.5194/hess-22-3863-2018, 2018
Short summary
Short summary
This work improves river discharge estimation by taking advantages of observation and model simulations. The new estimation takes into account both gauged and un-gauged rivers, and it compensates model systematic errors and missing processes (e.g., human water usage). This improved estimation is important not only for water resources management and ecosystem health over continent but also for ocean dynamics and salinity.
Nathaniel W. Chaney, Marjolein H. J. Van Huijgevoort, Elena Shevliakova, Sergey Malyshev, Paul C. D. Milly, Paul P. G. Gauthier, and Benjamin N. Sulman
Hydrol. Earth Syst. Sci., 22, 3311–3330, https://doi.org/10.5194/hess-22-3311-2018, https://doi.org/10.5194/hess-22-3311-2018, 2018
Short summary
Short summary
The petabytes of existing global environmental data provide an invaluable asset to improve the characterization of land heterogeneity in Earth system models. This study introduces a clustering algorithm that summarizes a domain's heterogeneity through spatially interconnected clusters. A series of land model simulations in central California using this approach illustrate the critical role that multi-scale heterogeneity can have on the macroscale water, energy, and carbon cycles.
Chinchu Mohan, Andrew W. Western, Yongping Wei, and Margarita Saft
Hydrol. Earth Syst. Sci., 22, 2689–2703, https://doi.org/10.5194/hess-22-2689-2018, https://doi.org/10.5194/hess-22-2689-2018, 2018
Short summary
Short summary
To ensure a sustainable supply of groundwater, scientific information about what is going into the system as recharge and what is taken out of the system via pumping is essential. This study identified the most influential factors in groundwater recharge and developed an empirical global recharge model. The meteorological and vegetation factors were the most important factors, and the long-term global average recharge was 134 mm per year. This model will aid in groundwater policy-making.
Peter Berg, Chantal Donnelly, and David Gustafsson
Hydrol. Earth Syst. Sci., 22, 989–1000, https://doi.org/10.5194/hess-22-989-2018, https://doi.org/10.5194/hess-22-989-2018, 2018
Short summary
Short summary
A new product (Global Forcing Data, GFD) that provides bias-adjusted meteorological forcing data for impact models, such as hydrological models, is presented. The main novelty with the product is the near-real time updating of the data which allows more up-to-date impact modeling. This is performed by combining climatological data sets with climate monitoring data sets. The potential in using the data to initialize hydrological forecasts is further investigated.
Hubertus M. Coerver, Martine M. Rutten, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 22, 831–851, https://doi.org/10.5194/hess-22-831-2018, https://doi.org/10.5194/hess-22-831-2018, 2018
Short summary
Short summary
Global hydrological models aim to model hydrological processes, like flows in a river, on a global scale, as opposed to traditional models which are regional. A big challenge in creating these models is the inclusion of impacts on the hydrological cycle caused by humans, for example by the operation of large (hydropower) dams. The presented study investigates a new way to include these impacts by dams into global hydrological models.
Naota Hanasaki, Sayaka Yoshikawa, Yadu Pokhrel, and Shinjiro Kanae
Hydrol. Earth Syst. Sci., 22, 789–817, https://doi.org/10.5194/hess-22-789-2018, https://doi.org/10.5194/hess-22-789-2018, 2018
Short summary
Short summary
Six schemes were added to the H08 global hydrological model (GHM) to represent human water abstraction more accurately and ensure that all water fluxes and storage are traceable in each grid cell at a daily interval. The schemes of local reservoirs, aqueduct water transfer, and seawater desalination were incorporated into GHMs for the first time, to the best of our knowledge. H08 has become one of the most detailed GHMs for attributing water sources available to humanity.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
Short summary
Short summary
A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Carmelo Cammalleri, Jürgen V. Vogt, Bernard Bisselink, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 6329–6343, https://doi.org/10.5194/hess-21-6329-2017, https://doi.org/10.5194/hess-21-6329-2017, 2017
Short summary
Short summary
Drought can affect large regions of the world, implying the need for a global monitoring tool. For the JRC Global Drought Observatory (GDO,
http://edo.jrc.ec.europa.eu/gdo/), 3 soil moisture anomaly datasets have been compared, in order to evaluate their consistency. The analysis performed on five macro-regions (North America, Europe, India, southern Africa and Australia) suggests the need to combine these different data sources in order to obtain robust assessments over a variety of conditions.
Joyce H. C. Bosmans, Ludovicus P. H. van Beek, Edwin H. Sutanudjaja, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 21, 5603–5626, https://doi.org/10.5194/hess-21-5603-2017, https://doi.org/10.5194/hess-21-5603-2017, 2017
Short summary
Short summary
We investigate how changes in land cover, such as deforestation, affect river runoff and evaporation from the land surface. We use computer simulations to show that the impact of land cover changes is significant and, when globally averaged, it is as important as more direct human impacts through water use (such as irrigation). There is large spatial variability in the impact of land cover change, with the largest changes when tall vegetation (such as forests) is replaced by crop fields.
Cherry May R. Mateo, Dai Yamazaki, Hyungjun Kim, Adisorn Champathong, Jai Vaze, and Taikan Oki
Hydrol. Earth Syst. Sci., 21, 5143–5163, https://doi.org/10.5194/hess-21-5143-2017, https://doi.org/10.5194/hess-21-5143-2017, 2017
Short summary
Short summary
Providing large-scale (regional or global) simulation of floods at fine spatial resolution is difficult due to computational constraints but is necessary to provide consistent estimates of hazards, especially in data-scarce regions. We assessed the capability of an advanced global-scale river model to simulate an extreme flood at fine resolution. We found that when multiple flow connections in rivers are represented, the model can provide reliable fine-resolution predictions of flood inundation.
Lamprini V. Papadimitriou, Aristeidis G. Koutroulis, Manolis G. Grillakis, and Ioannis K. Tsanis
Hydrol. Earth Syst. Sci., 21, 4379–4401, https://doi.org/10.5194/hess-21-4379-2017, https://doi.org/10.5194/hess-21-4379-2017, 2017
Short summary
Short summary
Bias correction of climate model outputs has become a standard procedure accompanying climate change impact studies. However, it introduces a new level of uncertainty in the modelling chain which remains relatively unexplored. In this work we present a new framework for the quantification and categorization of the effect of bias correction on global hydrological simulations and we derive information on the sensitivity and magnitude of the effect of GCM biases on runoff, at the global scale.
Luis Samaniego, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Matthias Zink, Niko Wanders, Stephanie Eisner, Hannes Müller Schmied, Edwin H. Sutanudjaja, Kirsten Warrach-Sagi, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, https://doi.org/10.5194/hess-21-4323-2017, 2017
Short summary
Short summary
We inspect the state-of-the-art of several land surface (LSMs) and hydrologic models (HMs) and show that most do not have consistent and realistic parameter fields for land surface geophysical properties. We propose to use the multiscale parameter regionalization (MPR) technique to solve, at least partly, the scaling problem in LSMs/HMs. A general model protocol is presented to describe how MPR can be applied to a specific model.
Yoshihide Wada, Marc F. P. Bierkens, Ad de Roo, Paul A. Dirmeyer, James S. Famiglietti, Naota Hanasaki, Megan Konar, Junguo Liu, Hannes Müller Schmied, Taikan Oki, Yadu Pokhrel, Murugesu Sivapalan, Tara J. Troy, Albert I. J. M. van Dijk, Tim van Emmerik, Marjolein H. J. Van Huijgevoort, Henny A. J. Van Lanen, Charles J. Vörösmarty, Niko Wanders, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, https://doi.org/10.5194/hess-21-4169-2017, 2017
Short summary
Short summary
Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.
Naze Candogan Yossef, Rens van Beek, Albrecht Weerts, Hessel Winsemius, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 21, 4103–4114, https://doi.org/10.5194/hess-21-4103-2017, https://doi.org/10.5194/hess-21-4103-2017, 2017
Short summary
Short summary
This paper presents a skill assessment of the global seasonal streamflow forecasting system FEWS-World. For 20 large basins of the world, forecasts using the ESP procedure are compared to forecasts using actual S3 seasonal meteorological forecast ensembles by ECMWF. The results are discussed in the context of prevailing hydroclimatic conditions per basin. The study concludes that in general, the skill of ECMWF S3 forecasts is close to that of the ESP forecasts.
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.
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.
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.
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.
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.
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.
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...
