Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3879-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-3879-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
28 Jul 2017
Review article |
| 28 Jul 2017
The future of Earth observation in hydrology
Matthew F. McCabe
CORRESPONDING AUTHOR
Water Desalination and Reuse Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Matthew Rodell
Hydrological Science Laboratory, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA), Greenbelt, Maryland, USA
Douglas E. Alsdorf
Byrd Polar and Climate Research Center, The Ohio State University, Columbus, Ohio, USA
Diego G. Miralles
Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
Remko Uijlenhoet
Hydrology and Quantitative Water Management Group, Wageningen University, Wageningen, the Netherlands
Wolfgang Wagner
Department of Geodesy and Geoinformation, Technische Universität Wien, Vienna, Austria
Center for Water Resource Systems, Technische Universität Wien, Vienna, Austria
Arko Lucieer
School of Land and Food, University of Tasmania, Hobart, TAS 7001, Australia
Rasmus Houborg
Water Desalination and Reuse Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Niko E. C. Verhoest
Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
Trenton E. Franz
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska 68583, USA
Jiancheng Shi
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, Beijing, China
Huilin Gao
Zachry Department of Civil Engineering, Texas A & M University, College Station, Texas 77843, USA
Eric F. Wood
Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
Related authors
P. Rouault, D. Courault, G. Pouget, F. Flamain, R. Lopez-Lozano, C. Doussan, M. Debolini, and M. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1531–1536, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1531-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1531-2023, 2023
M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Oliver Miguel López Valencia, Kasper Johansen, Bruno José Luis Aragón Solorio, Ting Li, Rasmus Houborg, Yoann Malbeteau, Samer AlMashharawi, Muhammad Umer Altaf, Essam Mohammed Fallatah, Hari Prasad Dasari, Ibrahim Hoteit, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 24, 5251–5277, https://doi.org/10.5194/hess-24-5251-2020, https://doi.org/10.5194/hess-24-5251-2020, 2020
Short summary
Short summary
The agricultural sector in Saudi Arabia has expanded rapidly over the last few decades, supported by non-renewable groundwater abstraction. This study describes a novel data–model fusion approach to compile national-scale groundwater abstractions and demonstrates its use over 5000 individual center-pivot fields. This method will allow both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.
K. Johansen, M. J. L. Morton, Y. Malbeteau, B. Aragon, S. Al-Mashharawi, M. Ziliani, Y. Angel, G. Fiene, S. Negrao, M. A. A. Mousa, M. A. Tester, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 407–411, https://doi.org/10.5194/isprs-archives-XLII-2-W13-407-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-407-2019, 2019
Khan Zaib Jadoon, Muhammad Umer Altaf, Matthew Francis McCabe, Ibrahim Hoteit, Nisar Muhammad, Davood Moghadas, and Lutz Weihermüller
Hydrol. Earth Syst. Sci., 21, 5375–5383, https://doi.org/10.5194/hess-21-5375-2017, https://doi.org/10.5194/hess-21-5375-2017, 2017
Short summary
Short summary
In this study electromagnetic induction (EMI) measurements were used to estimate soil salinity in an agriculture field irrigated with a drip irrigation system. Electromagnetic model parameters and uncertainty were estimated using adaptive Bayesian Markov chain Monte Carlo (MCMC). Application of the MCMC-based inversion to the synthetic and field measurements demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil.
D. Turner, A. Lucieer, M. McCabe, S. Parkes, and I. Clarke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 379–384, https://doi.org/10.5194/isprs-archives-XLII-2-W6-379-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-379-2017, 2017
Stephen D. Parkes, Matthew F. McCabe, Alan D. Griffiths, Lixin Wang, Scott Chambers, Ali Ershadi, Alastair G. Williams, Josiah Strauss, and Adrian Element
Hydrol. Earth Syst. Sci., 21, 533–548, https://doi.org/10.5194/hess-21-533-2017, https://doi.org/10.5194/hess-21-533-2017, 2017
Short summary
Short summary
Determining atmospheric moisture sources is required for understanding the water cycle. The role of land surface fluxes is a particular source of uncertainty for moisture budgets. Water vapour isotopes have the potential to improve constraints on moisture sources. In this work relationships between water vapour isotopes and land–atmosphere exchange are studied. Results show that land surface evaporative fluxes play a minor role in the daytime water and isotope budgets in semi-arid environments.
Jason P. Evans, Xianhong Meng, and Matthew F. McCabe
Hydrol. Earth Syst. Sci., 21, 409–422, https://doi.org/10.5194/hess-21-409-2017, https://doi.org/10.5194/hess-21-409-2017, 2017
Short summary
Short summary
This work demonstrates that changes in surface albedo and vegetation, caused by the millennium drought in south-east Australia, affected the atmosphere in a way that decreased precipitation further. This land–surface feedback increased the severity of the drought by 10 %. This suggests that climate models need to simulate changes in surface characteristics (other than soil moisture) in response to a developing drought if they are to capture this kind of multi-year drought.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, https://doi.org/10.5194/hess-21-323-2017, 2017
Short summary
Short summary
The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Raghavendra B. Jana, Ali Ershadi, and Matthew F. McCabe
Hydrol. Earth Syst. Sci., 20, 3987–4004, https://doi.org/10.5194/hess-20-3987-2016, https://doi.org/10.5194/hess-20-3987-2016, 2016
Short summary
Short summary
Interactions between soil moisture and terrestrial evaporation affect responses between land surface and the atmosphere across scales. We present an analysis of the link between soil moisture and evaporation estimates from three distinct models. The relationships were examined over nearly 2 years of observation data. Results show that while direct correlations of raw data were mostly not useful, the root-zone soil moisture and the modelled evaporation estimates reflect similar distributions.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
Short summary
Short summary
The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
Short summary
Short summary
In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
Short summary
Short summary
In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
Short summary
Short summary
A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
A. D. Griffiths, S. D. Parkes, S. D. Chambers, M. F. McCabe, and A. G. Williams
Atmos. Meas. Tech., 6, 207–218, https://doi.org/10.5194/amt-6-207-2013, https://doi.org/10.5194/amt-6-207-2013, 2013
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
Short summary
Short summary
Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 15, 265–291, https://doi.org/10.5194/esd-15-265-2024, https://doi.org/10.5194/esd-15-265-2024, 2024
Short summary
Short summary
Changes in land use are crucial to achieve lower global warming. However, despite their importance, the effects of these changes on moisture fluxes are poorly understood. We analyse land cover and management scenarios in three climate models involving cropland expansion, afforestation, and irrigation. Results show largely consistent influences on moisture fluxes, with cropland expansion causing a drying and reduced local moisture recycling, while afforestation and irrigation show the opposite.
Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
Earth Syst. Dynam., 15, 131–154, https://doi.org/10.5194/esd-15-131-2024, https://doi.org/10.5194/esd-15-131-2024, 2024
Short summary
Short summary
The 2022 summer was accompanied by widespread soil moisture deficits, including an unprecedented drought in Europe. Combining several observation-based estimates and models, we find that such an event has become at least 5 and 20 times more likely due to human-induced climate change in western Europe and the northern extratropics, respectively. Strong regional warming fuels soil desiccation; hence, projections indicate even more potent future droughts as we progress towards a 2 °C warmer world.
Louise J. Schreyers, Tim H. M. van Emmerik, Thanh-Khiet L. Bui, Khoa L. van Thi, Bart Vermeulen, Hong-Q. Nguyen, Nicholas Wallerstein, Remko Uijlenhoet, and Martine van der Ploeg
Hydrol. Earth Syst. Sci., 28, 589–610, https://doi.org/10.5194/hess-28-589-2024, https://doi.org/10.5194/hess-28-589-2024, 2024
Short summary
Short summary
River plastic emissions into the ocean are of global concern, but the transfer dynamics between fresh water and the marine environment remain poorly understood. We developed a simple Eulerian approach to estimate the net and total plastic transport in tidal rivers. Applied to the Saigon River, Vietnam, we found that net plastic transport amounted to less than one-third of total transport, highlighting the need to better integrate tidal dynamics in plastic transport and emission models.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
Short summary
Short summary
Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
Bich Ngoc Tran, Johannes van der Kwast, Solomon Seyoum, Remko Uijlenhoet, Graham Jewitt, and Marloes Mul
Hydrol. Earth Syst. Sci., 27, 4505–4528, https://doi.org/10.5194/hess-27-4505-2023, https://doi.org/10.5194/hess-27-4505-2023, 2023
Short summary
Short summary
Satellite data are increasingly used to estimate evapotranspiration (ET) or the amount of water moving from plants, soils, and water bodies into the atmosphere over large areas. Uncertainties from various sources affect the accuracy of these calculations. This study reviews the methods to assess the uncertainties of such ET estimations. It provides specific recommendations for a comprehensive assessment that assists in the potential uses of these data for research, monitoring, and management.
P. Rouault, D. Courault, G. Pouget, F. Flamain, R. Lopez-Lozano, C. Doussan, M. Debolini, and M. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1531–1536, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1531-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1531-2023, 2023
J. Zhao, F. Roth, B. Bauer-Marschallinger, W. Wagner, M. Chini, and X. X. Zhu
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 911–918, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-911-2023, 2023
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
Short summary
Short summary
Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Athanasios Tsiokanos, Martine Rutten, Ruud J. van der Ent, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-263, https://doi.org/10.5194/hess-2023-263, 2023
Revised manuscript under review for HESS
Short summary
Short summary
We focus on past high-flow events to identify flood drivers in the Geul catchment. We also explore flood drivers’ trends across various times and develop a new method to detect the main direction of a trend. Our results show that extreme 24-hour precipitation cannot solely lead to floods. The combination of long heavy rainfall and wet initial conditions determines the chances of flooding. Precipitation that leads to floods increases during winter, while no consistent trends are found in summer.
Florian Roth, Bernhard Bauer-Marschallinger, Mark Edwin Tupas, Christoph Reimer, Peter Salamon, and Wolfgang Wagner
Nat. Hazards Earth Syst. Sci., 23, 3305–3317, https://doi.org/10.5194/nhess-23-3305-2023, https://doi.org/10.5194/nhess-23-3305-2023, 2023
Short summary
Short summary
In August and September 2022, millions of people were impacted by a severe flood event in Pakistan. Since many roads and other infrastructure were destroyed, satellite data were the only way of providing large-scale information on the flood's impact. Based on the flood mapping algorithm developed at Technische Universität Wien (TU Wien), we mapped an area of 30 492 km2 that was flooded at least once during the study's time period. This affected area matches about the total area of Belgium.
Liqing Peng, Justin Sheffield, Zhongwang Wei, Michael Ek, and Eric F. Wood
EGUsphere, https://doi.org/10.5194/egusphere-2023-2100, https://doi.org/10.5194/egusphere-2023-2100, 2023
Short summary
Short summary
A convenient way of predicting drought is to calculate drought indicators with near-surface meteorology. We propose a simple way to utilize the satellite-derived vegetation information into a drought indicator. This simple approach only requires the minimum amount of ancillary data and is easy to implement and interpret. Adding vegetation dynamics effectively improves the spatial and temporal representations of soil-moisture drought, especially in the case of forests.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2023-1971, https://doi.org/10.5194/egusphere-2023-1971, 2023
Short summary
Short summary
Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-195, https://doi.org/10.5194/hess-2023-195, 2023
Revised manuscript under review for HESS
Short summary
Short summary
This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWS). The methodology and useability for every QG algorithm are described. All QC algorithms were applied in a case study using a PWS data from the Amsterdam region in the Netherlands. The results highlight the necessity for adequate data filtering and show the advantages and disadvantages of each QC algorithm.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
EGUsphere, https://doi.org/10.5194/egusphere-2023-147, https://doi.org/10.5194/egusphere-2023-147, 2023
Short summary
Short summary
This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves across four seasons. From that, we could know the drought (or heatwave) starts on which day and ends on which day. We found an increase in the frequency of heatwaves and the co-occurring droughts and heatwaves in Belgium caused by climate change. We also found that different months have different chances of co-occurring droughts and heatwaves.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
EGUsphere, https://doi.org/10.5194/egusphere-2023-953, https://doi.org/10.5194/egusphere-2023-953, 2023
Preprint archived
Short summary
Short summary
Land cover and management changes can affect the climate and water availability. In this study we use climate model simulations of extreme global land cover changes (afforestation, deforestation) and land management changes (irrigation) to understand the effects on the global water cycle and local to continental water availability. We show that cropland expansion generally leads to higher evaporation and lower amounts of precipitation and afforestation and irrigation expansion to the opposite.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, https://doi.org/10.5194/hess-26-5647-2022, 2022
Short summary
Short summary
A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1° spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
M. Tupas, C. Navacchi, F. Roth, B. Bauer-Marschallinger, F. Reuß, and W. Wagner
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 495–502, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022, 2022
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
Short summary
Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
Short summary
Short summary
This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Femke A. Jansen, Remko Uijlenhoet, Cor M. J. Jacobs, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 26, 2875–2898, https://doi.org/10.5194/hess-26-2875-2022, https://doi.org/10.5194/hess-26-2875-2022, 2022
Short summary
Short summary
We studied the controls on open water evaporation with a focus on Lake IJssel, the Netherlands, by analysing eddy covariance observations over two summer periods at two locations at the borders of the lake. Wind speed and the vertical vapour pressure gradient can explain most of the variation in observed evaporation, which is in agreement with Dalton's model. We argue that the distinct characteristics of inland waterbodies need to be taken into account when parameterizing their evaporation.
Peilin Song, Yongqiang Zhang, Jianping Guo, Jiancheng Shi, Tianjie Zhao, and Bing Tong
Earth Syst. Sci. Data, 14, 2613–2637, https://doi.org/10.5194/essd-14-2613-2022, https://doi.org/10.5194/essd-14-2613-2022, 2022
Short summary
Short summary
Soil moisture information is crucial for understanding the earth surface, but currently available satellite-based soil moisture datasets are imperfect either in their spatiotemporal resolutions or in ensuring image completeness from cloudy weather. In this study, therefore, we developed one soil moisture data product over China that has tackled most of the above problems. This data product has the potential to promote the investigation of earth hydrology and be extended to the global scale.
M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Paolo Filippucci, Luca Brocca, Raphael Quast, Luca Ciabatta, Carla Saltalippi, Wolfgang Wagner, and Angelica Tarpanelli
Hydrol. Earth Syst. Sci., 26, 2481–2497, https://doi.org/10.5194/hess-26-2481-2022, https://doi.org/10.5194/hess-26-2481-2022, 2022
Short summary
Short summary
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using observed data (gauge and radar) over the Po River Valley, Italy, as a benchmark. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 has great benefits. Possible applications include water management, agriculture and index-based insurances.
Jorn Van de Velde, Matthias Demuzere, Bernard De Baets, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 26, 2319–2344, https://doi.org/10.5194/hess-26-2319-2022, https://doi.org/10.5194/hess-26-2319-2022, 2022
Short summary
Short summary
An important step in projecting future climate is the bias adjustment of the climatological and hydrological variables. In this paper, we illustrate how bias adjustment can be impaired by bias nonstationarity. Two univariate and four multivariate methods are compared, and for both types bias nonstationarity can be linked with less robust adjustment.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
Short summary
Short summary
To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles
Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, https://doi.org/10.5194/gmd-15-1875-2022, 2022
Short summary
Short summary
Air transports 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.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
Short summary
Short summary
The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Ruben Imhoff, Claudia Brauer, Klaas-Jan van Heeringen, Hidde Leijnse, Aart Overeem, Albrecht Weerts, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 25, 4061–4080, https://doi.org/10.5194/hess-25-4061-2021, https://doi.org/10.5194/hess-25-4061-2021, 2021
Short summary
Short summary
Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.
Xiangjin Meng, Kebiao Mao, Fei Meng, Jiancheng Shi, Jiangyuan Zeng, Xinyi Shen, Yaokui Cui, Lingmei Jiang, and Zhonghua Guo
Earth Syst. Sci. Data, 13, 3239–3261, https://doi.org/10.5194/essd-13-3239-2021, https://doi.org/10.5194/essd-13-3239-2021, 2021
Short summary
Short summary
In order to improve the accuracy of China's regional agricultural drought monitoring and climate change research, we produced a long-term series of soil moisture products by constructing a time and depth correction model for three soil moisture products with the help of ground observation data. The spatial resolution is improved by building a spatial weight decomposition model, and validation indicates that the new product can meet application needs.
A. Iglseder, M. Bruggisser, A. Dostálová, N. Pfeifer, S. Schlaffer, W. Wagner, and M. Hollaus
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 567–574, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-567-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-567-2021, 2021
Mengmeng Cao, Kebiao Mao, Yibo Yan, Jiancheng Shi, Han Wang, Tongren Xu, Shu Fang, and Zijin Yuan
Earth Syst. Sci. Data, 13, 2111–2134, https://doi.org/10.5194/essd-13-2111-2021, https://doi.org/10.5194/essd-13-2111-2021, 2021
Short summary
Short summary
We constructed a temperature depth and observation time correction model to eliminate the sampling depth and temporal differences among different data. Then, we proposed a reconstructed spatial model that filters and removes missing pixels and low-quality pixels contaminated by clouds from raw SST images and retrieves real sea surface temperatures under cloud coverage based on multisource data to generate a high-quality unified global SST product with long-term spatiotemporal continuity.
Simone Gelsinari, Valentijn R. N. Pauwels, Edoardo Daly, Jos van Dam, Remko Uijlenhoet, Nicholas Fewster-Young, and Rebecca Doble
Hydrol. Earth Syst. Sci., 25, 2261–2277, https://doi.org/10.5194/hess-25-2261-2021, https://doi.org/10.5194/hess-25-2261-2021, 2021
Short summary
Short summary
Estimates of recharge to groundwater are often driven by biophysical processes occurring in the soil column and, particularly in remote areas, are also always affected by uncertainty. Using data assimilation techniques to merge remotely sensed observations with outputs of numerical models is one way to reduce this uncertainty. Here, we show the benefits of using such a technique with satellite evapotranspiration rates and coupled hydrogeological models applied to a semi-arid site in Australia.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
Short summary
Short summary
Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
Short summary
Short summary
Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Rui Tong, Juraj Parajka, Andreas Salentinig, Isabella Pfeil, Jürgen Komma, Borbála Széles, Martin Kubáň, Peter Valent, Mariette Vreugdenhil, Wolfgang Wagner, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1389–1410, https://doi.org/10.5194/hess-25-1389-2021, https://doi.org/10.5194/hess-25-1389-2021, 2021
Short summary
Short summary
We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
Jolijn van Engelenburg, Erik van Slobbe, Adriaan J. Teuling, Remko Uijlenhoet, and Petra Hellegers
Drink. Water Eng. Sci., 14, 1–43, https://doi.org/10.5194/dwes-14-1-2021, https://doi.org/10.5194/dwes-14-1-2021, 2021
Short summary
Short summary
This study analysed the impact of extreme weather events, water quality deterioration, and a growing drinking water demand on the sustainability of drinking water supply in the Netherlands. The results of the case studies were compared to sustainability issues for drinking water supply that are experienced worldwide. This resulted in a set of sustainability characteristics describing drinking water supply on a local scale in terms of hydrological, technical, and socio-economic characteristics.
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.
Oliver Miguel López Valencia, Kasper Johansen, Bruno José Luis Aragón Solorio, Ting Li, Rasmus Houborg, Yoann Malbeteau, Samer AlMashharawi, Muhammad Umer Altaf, Essam Mohammed Fallatah, Hari Prasad Dasari, Ibrahim Hoteit, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 24, 5251–5277, https://doi.org/10.5194/hess-24-5251-2020, https://doi.org/10.5194/hess-24-5251-2020, 2020
Short summary
Short summary
The agricultural sector in Saudi Arabia has expanded rapidly over the last few decades, supported by non-renewable groundwater abstraction. This study describes a novel data–model fusion approach to compile national-scale groundwater abstractions and demonstrates its use over 5000 individual center-pivot fields. This method will allow both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.
Bing Zhao, Kebiao Mao, Yulin Cai, Jiancheng Shi, Zhaoliang Li, Zhihao Qin, Xiangjin Meng, Xinyi Shen, and Zhonghua Guo
Earth Syst. Sci. Data, 12, 2555–2577, https://doi.org/10.5194/essd-12-2555-2020, https://doi.org/10.5194/essd-12-2555-2020, 2020
Short summary
Short summary
Land surface temperature is a key variable for climate and ecological environment research. We reconstructed a land surface temperature dataset (2003–2017) to take advantage of the ground observation site through building a reconstruction model which overcomes the effects of cloud. The reconstructed dataset exhibited significant improvements and can be used for the spatiotemporal evaluation of land surface temperature and for high-temperature and drought-monitoring studies.
Renaud Hostache, Dominik Rains, Kaniska Mallick, Marco Chini, Ramona Pelich, Hans Lievens, Fabrizio Fenicia, Giovanni Corato, Niko E. C. Verhoest, and Patrick Matgen
Hydrol. Earth Syst. Sci., 24, 4793–4812, https://doi.org/10.5194/hess-24-4793-2020, https://doi.org/10.5194/hess-24-4793-2020, 2020
Short summary
Short summary
Our objective is to investigate how satellite microwave sensors, particularly Soil Moisture and Ocean Salinity (SMOS), may help to reduce errors and uncertainties in soil moisture simulations with a large-scale conceptual hydro-meteorological model. We assimilated a long time series of SMOS observations into a hydro-meteorological model and showed that this helps to improve model predictions. This work therefore contributes to the development of faster and more accurate drought prediction tools.
Brecht Martens, Dominik L. Schumacher, Hendrik Wouters, Joaquín Muñoz-Sabater, Niko E. C. Verhoest, and Diego G. Miralles
Geosci. Model Dev., 13, 4159–4181, https://doi.org/10.5194/gmd-13-4159-2020, https://doi.org/10.5194/gmd-13-4159-2020, 2020
Short summary
Short summary
Climate reanalyses are widely used in different fields and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets. In this study, we show the improvements of ECMWF's latest climate reanalysis (ERA5) upon its predecessor (ERA-Interim) in partitioning the available energy at the land surface.
J. Zhao, M. Chini, R. Pelich, P. Matgen, R. Hostache, S. Cao, and W. Wagner
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 395–400, https://doi.org/10.5194/isprs-annals-V-1-2020-395-2020, https://doi.org/10.5194/isprs-annals-V-1-2020-395-2020, 2020
W. Wagner, V. Freeman, S. Cao, P. Matgen, M. Chini, P. Salamon, N. McCormick, S. Martinis, B. Bauer-Marschallinger, C. Navacchi, M. Schramm, C. Reimer, and C. Briese
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 641–648, https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-641-2020, 2020
Thomas C. van Leth, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 13, 1797–1815, https://doi.org/10.5194/amt-13-1797-2020, https://doi.org/10.5194/amt-13-1797-2020, 2020
Short summary
Short summary
We present a method of using collocated microwave link instruments to estimate the average size distribution of raindrops along a path of several kilometers. Our method is validated using simulated fields as well as five laser disdrometers installed along a path. We also present preliminary results from an experimental setup measuring at 26 and 38 GHz along a 2.2 km path. We show that a retrieval on the basis of microwave links can be highly accurate, provided the base power level is stable.
Jorn Van de Velde, Bernard De Baets, Matthias Demuzere, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-83, https://doi.org/10.5194/hess-2020-83, 2020
Revised manuscript not accepted
Short summary
Short summary
Though climate models have different types of biases in comparison to the observations, most research is focused on adjusting the intensity. Yet, variables like precipitation are also biased in the occurrence: there are too many days with rainfall. We compared four methods for adjusting the occurrence, with the goal of improving flood representation. From this comparison, we concluded that more advanced methods do not necessarily add value, especially in multivariate settings.
Jian Peng, Simon Dadson, Feyera Hirpa, Ellen Dyer, Thomas Lees, Diego G. Miralles, Sergio M. Vicente-Serrano, and Chris Funk
Earth Syst. Sci. Data, 12, 753–769, https://doi.org/10.5194/essd-12-753-2020, https://doi.org/10.5194/essd-12-753-2020, 2020
Short summary
Short summary
Africa has been severely influenced by intense drought events, which has led to crop failure, food shortages, famine, epidemics and even mass migration. The current study developed a high spatial resolution drought dataset entirely from satellite-based products. The dataset has been comprehensively inter-compared with other drought indicators and may contribute to an improved characterization of drought risk and vulnerability and minimize drought's impact on water and food security in Africa.
Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
Short summary
Short summary
Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
Short summary
Short summary
The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
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.
Jeroen Claessen, Annalisa Molini, Brecht Martens, Matteo Detto, Matthias Demuzere, and Diego G. Miralles
Biogeosciences, 16, 4851–4874, https://doi.org/10.5194/bg-16-4851-2019, https://doi.org/10.5194/bg-16-4851-2019, 2019
Short summary
Short summary
Bidirectional interactions between vegetation and climate are unraveled over short (monthly) and long (inter-annual) temporal scales. Analyses use a novel causal inference method based on wavelet theory. The performance of climate models at representing these interactions is benchmarked against satellite data. Climate models can reproduce the overall climate controls on vegetation at all temporal scales, while their performance at representing biophysical feedbacks on climate is less adequate.
Adrien Guyot, Jayaram Pudashine, Alain Protat, Remko Uijlenhoet, Valentijn R. N. Pauwels, Alan Seed, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 4737–4761, https://doi.org/10.5194/hess-23-4737-2019, https://doi.org/10.5194/hess-23-4737-2019, 2019
Short summary
Short summary
We characterised for the first time the rainfall microphysics for Southern Hemisphere temperate latitudes. Co-located instruments were deployed to provide information on the sampling effect and spatio-temporal variabilities at micro scales. Substantial differences were found across the instruments, increasing with increasing values of the rain rate. Specific relations for reflectivity–rainfall are presented together with related uncertainties for drizzle and stratiform and convective rainfall.
Luca Brocca, Paolo Filippucci, Sebastian Hahn, Luca Ciabatta, Christian Massari, Stefania Camici, Lothar Schüller, Bojan Bojkov, and Wolfgang Wagner
Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, https://doi.org/10.5194/essd-11-1583-2019, 2019
Short summary
Short summary
SM2RAIN–ASCAT is a new 12-year (2007–2018) global-scale rainfall dataset obtained by applying the SM2RAIN algorithm to ASCAT soil moisture data. The dataset has a spatiotemporal sampling resolution of 12.5 km and 1 d. Results show that the new dataset performs particularly well in Africa and South America, i.e. in the continents in which ground observations are scarce and the need for satellite rainfall data is high. SM2RAIN–ASCAT is available at http://doi.org/10.5281/zenodo.340556.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
Short summary
Short summary
Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
G. T. Alckmin, L. Kooistra, A. Lucieer, and R. Rawnsley
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1827–1831, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1827-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1827-2019, 2019
C. Iseli and A. Lucieer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 379–384, https://doi.org/10.5194/isprs-archives-XLII-2-W13-379-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-379-2019, 2019
K. Johansen, M. J. L. Morton, Y. Malbeteau, B. Aragon, S. Al-Mashharawi, M. Ziliani, Y. Angel, G. Fiene, S. Negrao, M. A. A. Mousa, M. A. Tester, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 407–411, https://doi.org/10.5194/isprs-archives-XLII-2-W13-407-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-407-2019, 2019
Hendrik Wouters, Irina Y. Petrova, Chiel C. van Heerwaarden, Jordi Vilà-Guerau de Arellano, Adriaan J. Teuling, Vicky Meulenberg, Joseph A. Santanello, and Diego G. Miralles
Geosci. Model Dev., 12, 2139–2153, https://doi.org/10.5194/gmd-12-2139-2019, https://doi.org/10.5194/gmd-12-2139-2019, 2019
Short summary
Short summary
The free software CLASS4GL (http://class4gl.eu) is designed to investigate the dynamic atmospheric boundary layer (ABL) with weather balloons. It mines observational data from global radio soundings, satellite and reanalysis data from the last 40 years to constrain and initialize an ABL model and automizes multiple experiments in parallel. CLASS4GL aims at fostering a better understanding of land–atmosphere feedbacks and the drivers of extreme weather.
Alexander Gruber, Tracy Scanlon, Robin van der Schalie, Wolfgang Wagner, and Wouter Dorigo
Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, https://doi.org/10.5194/essd-11-717-2019, 2019
Short summary
Short summary
Soil moisture is a key variable in our Earth system. Knowledge of soil moisture and its dynamics across scales is vital for many applications such as the prediction of agricultural yields or irrigation demands, flood and drought monitoring, weather forecasting and climate modelling. To date, the ESA CCI SM products are the only consistent long-term multi-satellite soil moisture data sets available. This paper reviews the evolution of these products and their underlying merging methodology.
Joost Buitink, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 23, 1593–1609, https://doi.org/10.5194/hess-23-1593-2019, https://doi.org/10.5194/hess-23-1593-2019, 2019
Short summary
Short summary
This study describes how the spatial resolution of hydrological models affects the model results. The high-resolution model allowed for more spatial variability than the low-resolution model. As a result, the low-resolution model failed to capture most variability that was simulated with the high-resolution model. This has implications for the interpretation of results carried out at coarse resolutions, as they may fail to represent the local small-scale variability.
Bart van Osnabrugge, Remko Uijlenhoet, and Albrecht Weerts
Hydrol. Earth Syst. Sci., 23, 1453–1467, https://doi.org/10.5194/hess-23-1453-2019, https://doi.org/10.5194/hess-23-1453-2019, 2019
Short summary
Short summary
A correct estimate of the amount of future precipitation is the most important factor in making a good streamflow forecast, but evaporation is also an important component that determines the discharge of a river. However, in this study for the Rhine River we found that evaporation forecasts only give an almost negligible improvement compared to methods that use statistical information on climatology for a 10-day streamflow forecast. This is important to guide research on low flow forecasts.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 23, 925–948, https://doi.org/10.5194/hess-23-925-2019, https://doi.org/10.5194/hess-23-925-2019, 2019
Short summary
Short summary
Potential evaporation (Ep) is the amount of water an ecosystem would consume if it were not limited by water availability or other stress factors. In this study, we compared several methods to estimate Ep using a global dataset of 107 FLUXNET sites. A simple radiation-driven method calibrated per biome consistently outperformed more complex approaches and makes a suitable tool to investigate the impact of water use and demand, drought severity and biome productivity.
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277–301, https://doi.org/10.5194/hess-23-277-2019, https://doi.org/10.5194/hess-23-277-2019, 2019
Short summary
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.
Hylke E. Beck, Ming Pan, Tirthankar Roy, Graham P. Weedon, Florian Pappenberger, Albert I. J. M. van Dijk, George J. Huffman, Robert F. Adler, and Eric F. Wood
Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, https://doi.org/10.5194/hess-23-207-2019, 2019
Short summary
Short summary
We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
Sara Sadri, Eric F. Wood, and Ming Pan
Hydrol. Earth Syst. Sci., 22, 6611–6626, https://doi.org/10.5194/hess-22-6611-2018, https://doi.org/10.5194/hess-22-6611-2018, 2018
Short summary
Short summary
Of particular interest to NASA's SMAP-based agricultural applications is a monitoring product that assesses near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for the meaningful assessment of its indices. This study presents initial insights about using SMAP Level 3 and Level 4 for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS).
Tjitske J. Geertsema, Adriaan J. Teuling, Remko Uijlenhoet, Paul J. J. F. Torfs, and Antonius J. F. Hoitink
Hydrol. Earth Syst. Sci., 22, 5599–5613, https://doi.org/10.5194/hess-22-5599-2018, https://doi.org/10.5194/hess-22-5599-2018, 2018
Short summary
Short summary
This study investigate the processes and effects of simultaneous flood peaks at a lowland confluence. The flood peaks are analyzed with the relatively new dynamic time warping method, which offers a robust means of tracing flood waves in discharge time series at confluences. The time lag between discharge peaks in the main river and its lowland tributaries is small compared to the wave duration; therefore the exact timing of discharge peaks may be little relevant to flood risk.
Christina Papagiannopoulou, Diego G. Miralles, Matthias Demuzere, Niko E. C. Verhoest, and Willem Waegeman
Geosci. Model Dev., 11, 4139–4153, https://doi.org/10.5194/gmd-11-4139-2018, https://doi.org/10.5194/gmd-11-4139-2018, 2018
Short summary
Short summary
Common global land cover and climate classifications are based on vegetation–climatic characteristics derived from observational data, ignoring the interaction between the local climate and biome. Here, we model the interplay between vegetation and local climate by discovering spatial relationships among different locations. The resulting global
hydro-climatic biomescorrespond to regions of coherent climate–vegetation interactions that agree well with traditional global land cover maps.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
Short summary
Short summary
Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Thomas C. van Leth, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4645–4669, https://doi.org/10.5194/amt-11-4645-2018, https://doi.org/10.5194/amt-11-4645-2018, 2018
Short summary
Short summary
We present a campaign to address several error sources associated with rainfall estimates from microwave links in cellular communication networks. The set-up consists of three co-located links, complemented with reference instruments. We investigate events covering different attenuating phenomena: Rainfall, solid precipitation, temperature, fog, antenna wetting due to rain or dew, and clutter.
Manuel F. Rios Gaona, Aart Overeem, Timothy H. Raupach, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4465–4476, https://doi.org/10.5194/amt-11-4465-2018, https://doi.org/10.5194/amt-11-4465-2018, 2018
Short summary
Short summary
Rainfall estimates from commercial microwave links were obtained for the city of Sao Paulo (Brazil). The results show the potential of such networks as complementary rainfall measurements for more robust networks (e.g. radars, gauges, satellites).
S. Talebi, J. Shi, and T. Zhao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1623–1627, https://doi.org/10.5194/isprs-archives-XLII-3-1623-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1623-2018, 2018
Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, https://doi.org/10.5194/hess-22-1775-2018, 2018
Short summary
Short summary
Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.
Minh Tu Pham, Hilde Vernieuwe, Bernard De Baets, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 22, 1263–1283, https://doi.org/10.5194/hess-22-1263-2018, https://doi.org/10.5194/hess-22-1263-2018, 2018
Short summary
Short summary
In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Still, the developed model has great potential for hydrological impact analysis.
Wouter H. Maes, Pierre Gentine, Niko E. C. Verhoest, and Diego G. Miralles
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-682, https://doi.org/10.5194/hess-2017-682, 2018
Revised manuscript not accepted
Short summary
Short summary
Potential evaporation is a key parameter in numerous models used for assessing water use and drought severity. Yet, multiple incompatible methods have been proposed, thus estimates of potential evaporation remain uncertain. Based on the largest available dataset of FLUXNET data, we identify the best method to calculate potential evaporation globally. A simple radiation-driven method calibrated per biome consistently performed best; more complex models did not perform as good.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
Short summary
Short summary
Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
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.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
Short summary
Short summary
This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
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.
Joost Buitink, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-629, https://doi.org/10.5194/hess-2017-629, 2017
Revised manuscript not accepted
Short summary
Short summary
We compared the hydrological response simulated at two different spatial resolutions. The low resolution model was not able to simulate the complex response as was simulated with the high resolution model. The low resolution model underestimated the anomalies when compared with the high resolution model. This has implications on the interpretation of global scale impact studies (low resolution) on local or regional scales (high resolution).
Khan Zaib Jadoon, Muhammad Umer Altaf, Matthew Francis McCabe, Ibrahim Hoteit, Nisar Muhammad, Davood Moghadas, and Lutz Weihermüller
Hydrol. Earth Syst. Sci., 21, 5375–5383, https://doi.org/10.5194/hess-21-5375-2017, https://doi.org/10.5194/hess-21-5375-2017, 2017
Short summary
Short summary
In this study electromagnetic induction (EMI) measurements were used to estimate soil salinity in an agriculture field irrigated with a drip irrigation system. Electromagnetic model parameters and uncertainty were estimated using adaptive Bayesian Markov chain Monte Carlo (MCMC). Application of the MCMC-based inversion to the synthetic and field measurements demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil.
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
Short summary
Short summary
Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
S. Talebi, J. Shi, T. Zhao, Y. Li, X. Chuan, and L. Chai
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W4, 259–263, https://doi.org/10.5194/isprs-archives-XLII-4-W4-259-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W4-259-2017, 2017
Seyed Hamed Alemohammad, Bin Fang, Alexandra G. Konings, Filipe Aires, Julia K. Green, Jana Kolassa, Diego Miralles, Catherine Prigent, and Pierre Gentine
Biogeosciences, 14, 4101–4124, https://doi.org/10.5194/bg-14-4101-2017, https://doi.org/10.5194/bg-14-4101-2017, 2017
Short summary
Short summary
Water, Energy, and Carbon with Artificial Neural Networks (WECANN) is a statistically based estimate of global surface latent and sensible heat fluxes and gross primary productivity. The retrieval uses six remotely sensed observations as input, including the solar-induced fluorescence. WECANN provides estimates on a 1° × 1° geographic grid and on a monthly time scale and outperforms other global products in capturing the seasonality of the fluxes when compared to eddy covariance tower data.
D. Turner, A. Lucieer, M. McCabe, S. Parkes, and I. Clarke
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 379–384, https://doi.org/10.5194/isprs-archives-XLII-2-W6-379-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W6-379-2017, 2017
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
Short summary
Short summary
Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Christa D. Peters-Lidard, Martyn Clark, Luis Samaniego, Niko E. C. Verhoest, Tim van Emmerik, Remko Uijlenhoet, Kevin Achieng, Trenton E. Franz, and Ross Woods
Hydrol. Earth Syst. Sci., 21, 3701–3713, https://doi.org/10.5194/hess-21-3701-2017, https://doi.org/10.5194/hess-21-3701-2017, 2017
Short summary
Short summary
In this synthesis of hydrologic scaling and similarity, we assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modeling, have laid the foundation for a data-driven framework for scrutinizing hydrological hypotheses. We call upon the community to develop a focused effort towards a fourth paradigm for hydrology.
Martyn P. Clark, Marc F. P. Bierkens, Luis Samaniego, Ross A. Woods, Remko Uijlenhoet, Katrina E. Bennett, Valentijn R. N. Pauwels, Xitian Cai, Andrew W. Wood, and Christa D. Peters-Lidard
Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, https://doi.org/10.5194/hess-21-3427-2017, 2017
Short summary
Short summary
The diversity in hydrologic models has led to controversy surrounding the “correct” approach to hydrologic modeling. In this paper we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, summarize modeling advances that address these challenges, and define outstanding research needs.
Patricia M. Lawston, Joseph A. Santanello Jr., Trenton E. Franz, and Matthew Rodell
Hydrol. Earth Syst. Sci., 21, 2953–2966, https://doi.org/10.5194/hess-21-2953-2017, https://doi.org/10.5194/hess-21-2953-2017, 2017
Short summary
Short summary
Irrigation can affect the weather by making the air cooler and more humid, potentially causing changes to clouds and rainfall. This study uses new datasets to test how well irrigation is simulated in a model. We find the model applies more water than farmers' data show, but the water is applied at the right time in the growing season and improves the modeled wetness of the soil. These results will help improve irrigation modeling and thus understanding of human impacts on the water cycle.
Hidayat Hidayat, Adriaan J. Teuling, Bart Vermeulen, Muh Taufik, Karl Kastner, Tjitske J. Geertsema, Dinja C. C. Bol, Dirk H. Hoekman, Gadis Sri Haryani, Henny A. J. Van Lanen, Robert M. Delinom, Roel Dijksma, Gusti Z. Anshari, Nining S. Ningsih, Remko Uijlenhoet, and Antonius J. F. Hoitink
Hydrol. Earth Syst. Sci., 21, 2579–2594, https://doi.org/10.5194/hess-21-2579-2017, https://doi.org/10.5194/hess-21-2579-2017, 2017
Short summary
Short summary
Hydrological prediction is crucial but in tropical lowland it is difficult, considering data scarcity and river system complexity. This study offers a view of the hydrology of two tropical lowlands in Indonesia. Both lowlands exhibit the important role of upstream wetlands in regulating the flow downstream. We expect that this work facilitates a better prediction of fire-prone conditions in these regions.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
Short summary
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Christina Papagiannopoulou, Diego G. Miralles, Stijn Decubber, Matthias Demuzere, Niko E. C. Verhoest, Wouter A. Dorigo, and Willem Waegeman
Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, https://doi.org/10.5194/gmd-10-1945-2017, 2017
Short summary
Short summary
Global satellite observations provide a means to unravel the influence of climate on vegetation. Common statistical methods used to study the relationships between climate and vegetation are often too simplistic to capture the complexity of these relationships. Here, we present a novel causality framework that includes data fusion from various databases, time series decomposition, and machine learning techniques. Results highlight the highly non-linear nature of climate–vegetation interactions.
Di Tian, Eric F. Wood, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 1477–1490, https://doi.org/10.5194/hess-21-1477-2017, https://doi.org/10.5194/hess-21-1477-2017, 2017
Short summary
Short summary
This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation and temperature indices over the contiguous United States. The presence of active Madden-Julian Oscillation (MJO) events improved weekly mean precipitation forecast skill over most regions. Sub-seasonal forecast indices calculated from the daily forecast showed higher skill than temporally downscaled forecasts, suggesting the usefulness of the daily forecast for sub-seasonal hydrological forecasting.
Foad Foolad, Trenton E. Franz, Tiejun Wang, Justin Gibson, Ayse Kilic, Richard G. Allen, and Andrew Suyker
Hydrol. Earth Syst. Sci., 21, 1263–1277, https://doi.org/10.5194/hess-21-1263-2017, https://doi.org/10.5194/hess-21-1263-2017, 2017
Short summary
Short summary
Estimates of evapotranspiration are vital for validation of models. However, those datasets are often limited to research applications. Here, we explore using vadose zone modeling with widespread and readily available soil water content monitoring networks. While this work focused on one agricultural site, the framework can be used everywhere there is basic data. The resulting evapotranspiration and soil water content measurements are valuable benchmarks for evaluation of land surface models.
Justin Gibson, Trenton E. Franz, Tiejun Wang, John Gates, Patricio Grassini, Haishun Yang, and Dean Eisenhauer
Hydrol. Earth Syst. Sci., 21, 1051–1062, https://doi.org/10.5194/hess-21-1051-2017, https://doi.org/10.5194/hess-21-1051-2017, 2017
Short summary
Short summary
The human use of water for irrigation is often ignored in models and operational forecasts. We describe four plausible and relatively simple irrigation routines that can be coupled to the next generation of models. The routines are tested against a unique irrigation dataset from western Nebraska. The most aggressive water-saving irrigation routine indicates a potential irrigation savings of 120 mm yr−1 and yield losses of less than 3 % against the crop model benchmark and historical averages.
Lotte de Vos, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 21, 765–777, https://doi.org/10.5194/hess-21-765-2017, https://doi.org/10.5194/hess-21-765-2017, 2017
Short summary
Short summary
Recent developments have made it possible to easily crowdsource meteorological measurements from automatic personal weather stations worldwide. This has offered free access to rainfall ground measurements at spatial and temporal resolutions far exceeding those of national operational sensor networks, especially in cities. This paper is the first step to make optimal use of this promising source of rainfall measurements and identify challenges for future implementation for urban applications.
Stephen D. Parkes, Matthew F. McCabe, Alan D. Griffiths, Lixin Wang, Scott Chambers, Ali Ershadi, Alastair G. Williams, Josiah Strauss, and Adrian Element
Hydrol. Earth Syst. Sci., 21, 533–548, https://doi.org/10.5194/hess-21-533-2017, https://doi.org/10.5194/hess-21-533-2017, 2017
Short summary
Short summary
Determining atmospheric moisture sources is required for understanding the water cycle. The role of land surface fluxes is a particular source of uncertainty for moisture budgets. Water vapour isotopes have the potential to improve constraints on moisture sources. In this work relationships between water vapour isotopes and land–atmosphere exchange are studied. Results show that land surface evaporative fluxes play a minor role in the daytime water and isotope budgets in semi-arid environments.
Jason P. Evans, Xianhong Meng, and Matthew F. McCabe
Hydrol. Earth Syst. Sci., 21, 409–422, https://doi.org/10.5194/hess-21-409-2017, https://doi.org/10.5194/hess-21-409-2017, 2017
Short summary
Short summary
This work demonstrates that changes in surface albedo and vegetation, caused by the millennium drought in south-east Australia, affected the atmosphere in a way that decreased precipitation further. This land–surface feedback increased the severity of the drought by 10 %. This suggests that climate models need to simulate changes in surface characteristics (other than soil moisture) in response to a developing drought if they are to capture this kind of multi-year drought.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, https://doi.org/10.5194/hess-21-323-2017, 2017
Short summary
Short summary
The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Markus Enenkel, Christoph Reimer, Wouter Dorigo, Wolfgang Wagner, Isabella Pfeil, Robert Parinussa, and Richard De Jeu
Hydrol. Earth Syst. Sci., 20, 4191–4208, https://doi.org/10.5194/hess-20-4191-2016, https://doi.org/10.5194/hess-20-4191-2016, 2016
Short summary
Short summary
Soil moisture is a crucial variable for a variety of applications, ranging from weather forecasting and agricultural production to the monitoring of floods and droughts. Satellite observations are particularly important in regions where no in situ measurements are available. Our study presents a method to integrate global near-real-time satellite observations from different sensors into one harmonized, daily data set. A first validation shows good results on a global scale.
Raghavendra B. Jana, Ali Ershadi, and Matthew F. McCabe
Hydrol. Earth Syst. Sci., 20, 3987–4004, https://doi.org/10.5194/hess-20-3987-2016, https://doi.org/10.5194/hess-20-3987-2016, 2016
Short summary
Short summary
Interactions between soil moisture and terrestrial evaporation affect responses between land surface and the atmosphere across scales. We present an analysis of the link between soil moisture and evaporation estimates from three distinct models. The relationships were examined over nearly 2 years of observation data. Results show that while direct correlations of raw data were mostly not useful, the root-zone soil moisture and the modelled evaporation estimates reflect similar distributions.
William Alexander Avery, Catherine Finkenbiner, Trenton E. Franz, Tiejun Wang, Anthony L. Nguy-Robertson, Andrew Suyker, Timothy Arkebauer, and Francisco Muñoz-Arriola
Hydrol. Earth Syst. Sci., 20, 3859–3872, https://doi.org/10.5194/hess-20-3859-2016, https://doi.org/10.5194/hess-20-3859-2016, 2016
Short summary
Short summary
Here we present a strategy to use globally available datasets in the calibration function used to convert observed moderated neutron counts into volumetric soil water content. While local sampling protocols are well documented for fixed probes, the use of roving probes presents new calibration challenges. With over 200 fixed probes and 10 roving probes in use globally, we anticipate this paper will serve as a keystone for the growing cosmic-ray neutron probe and hydrologic community.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
Short summary
Short summary
In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
C. Z. van de Beek, H. Leijnse, P. Hazenberg, and R. Uijlenhoet
Atmos. Meas. Tech., 9, 3837–3850, https://doi.org/10.5194/amt-9-3837-2016, https://doi.org/10.5194/amt-9-3837-2016, 2016
Short summary
Short summary
Quantitative precipitation estimation using weather radar is affected by many sources of error. This study is an attempt to separate and quantify sources of error very close to the radar. A 3-day event is analyzed using radar, rain gauge and disdrometer data. Without correction, the radar severely underestimates the total rain amount by more than 50 %. After correction for the errors, a good match with rain gauge measurements is found, with 5 to 8 % difference.
Lieke Melsen, Adriaan Teuling, Paul Torfs, Massimiliano Zappa, Naoki Mizukami, Martyn Clark, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, https://doi.org/10.5194/hess-20-2207-2016, 2016
Short summary
Short summary
In this study we investigated the sensitivity of a large-domain hydrological model for spatial and temporal resolution. We evaluated the results on a mesoscale catchment in Switzerland. Our results show that the model was hardly sensitive for the spatial resolution, which implies that spatial variability is likely underestimated. Our results provide a motivation to improve the representation of spatial variability in hydrological models in order to increase their credibility on a smaller scale.
Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 9, 2425–2444, https://doi.org/10.5194/amt-9-2425-2016, https://doi.org/10.5194/amt-9-2425-2016, 2016
Short summary
Short summary
Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and the corresponding code, which is freely provided at GitHub.
Benedikt Gräler, Andrea Petroselli, Salvatore Grimaldi, Bernard De Baets, and Niko Verhoest
Proc. IAHS, 373, 175–178, https://doi.org/10.5194/piahs-373-175-2016, https://doi.org/10.5194/piahs-373-175-2016, 2016
Short summary
Short summary
Many hydrological studies are devoted to the identification of events that are expected to occur on average within a certain time span. While this topic is well established in the univariate case, recent advances focus on a multivariate characterization of events based on copulas. Following a previous study, we show how the definition of the survival Kendall return period fits into the set of multivariate return periods.
Lieke A. Melsen, Adriaan J. Teuling, Paul J. J. F. Torfs, Remko Uijlenhoet, Naoki Mizukami, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 20, 1069–1079, https://doi.org/10.5194/hess-20-1069-2016, https://doi.org/10.5194/hess-20-1069-2016, 2016
Short summary
Short summary
A meta-analysis on 192 peer-reviewed articles reporting applications of a land surface model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
Short summary
Short summary
The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
Short summary
Short summary
In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
M. K. van der Molen, R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, T. C. Maximov, A. V. Kononov, T. Ohta, A. Kotani, M. C. Krol, and W. Peters
Hydrol. Earth Syst. Sci., 20, 605–624, https://doi.org/10.5194/hess-20-605-2016, https://doi.org/10.5194/hess-20-605-2016, 2016
Short summary
Short summary
Boreal Eurasia contains extensive forests, which play an important role in the terrestrial carbon cycle. Droughts can modify this cycle considerably, although very few ground-based observations are available in the region. We test whether satellite-observed soil moisture may be used to improve carbon cycle models in this region. This paper explains when and where this works best. The interpretation of satellite soil moisture is best in summer conditions, and is hampered by snow, ice and ponding.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
Short summary
Short summary
In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
A. P. Schreiner-McGraw, E. R. Vivoni, G. Mascaro, and T. E. Franz
Hydrol. Earth Syst. Sci., 20, 329–345, https://doi.org/10.5194/hess-20-329-2016, https://doi.org/10.5194/hess-20-329-2016, 2016
Short summary
Short summary
Soil moisture estimates from a novel method were evaluated in two semiarid watersheds. We found good agreements between the technique and estimates derived from watershed instruments designed to close the water balance. We then investigated local hydrologic processes and link between evapotranspiration and soil moisture obtained from the novel measurements.
G. Blöschl, A. P. Blaschke, M. Broer, C. Bucher, G. Carr, X. Chen, A. Eder, M. Exner-Kittridge, A. Farnleitner, A. Flores-Orozco, P. Haas, P. Hogan, A. Kazemi Amiri, M. Oismüller, J. Parajka, R. Silasari, P. Stadler, P. Strauss, M. Vreugdenhil, W. Wagner, and M. Zessner
Hydrol. Earth Syst. Sci., 20, 227–255, https://doi.org/10.5194/hess-20-227-2016, https://doi.org/10.5194/hess-20-227-2016, 2016
Short summary
Short summary
This paper illustrates the experimental and monitoring set-up of the 66 ha Hydrological Open Air Laboratory (HOAL) in Petzenkirchen, Lower Austria, which allows meaningful hypothesis testing. The HOAL catchment features a range of different runoff generation processes (surface runoff, springs, tile drains, wetlands), and is convenient from a logistic point of view as all instruments can be connected to the power grid and a high-speed glassfibre local area network.
W. Zhan, M. Pan, N. Wanders, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 4275–4291, https://doi.org/10.5194/hess-19-4275-2015, https://doi.org/10.5194/hess-19-4275-2015, 2015
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
Short summary
Short summary
We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
M. F. Rios Gaona, A. Overeem, H. Leijnse, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 3571–3584, https://doi.org/10.5194/hess-19-3571-2015, https://doi.org/10.5194/hess-19-3571-2015, 2015
Short summary
Short summary
Commercial cellular networks are built for telecommunication purposes. These kinds of networks have lately been used to obtain rainfall maps at country-wide scales. From previous studies, we now quantify the uncertainties associated with such maps. To do so, we divided the sources or error into two categories: from microwave link measurements and from mapping. It was found that the former is the source that contributes the most to the overall error in rainfall maps from microwave link network.
A. I. Stegehuis, R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild
Geosci. Model Dev., 8, 2285–2298, https://doi.org/10.5194/gmd-8-2285-2015, https://doi.org/10.5194/gmd-8-2285-2015, 2015
Short summary
Short summary
Many climate models have difficulties in properly reproducing climate extremes such as heat wave conditions. We use a regional climate model with different atmospheric physics schemes to simulate the heat wave events of 2003 in western Europe and 2010 in Russia. The five best-performing and diverse physics scheme combinations may be used in the future to perform heat wave analysis and to investigate the impact of climate change in summer in Europe.
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
Short summary
Short summary
Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
O. Rakovec, A. H. Weerts, J. Sumihar, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 2911–2924, https://doi.org/10.5194/hess-19-2911-2015, https://doi.org/10.5194/hess-19-2911-2015, 2015
Short summary
Short summary
This is the first analysis of the asynchronous ensemble Kalman filter in hydrological forecasting. The results of discharge assimilation into a hydrological model for the catchment show that including past predictions and observations in the filter improves model forecasts. Additionally, we show that elimination of the strongly non-linear relation between soil moisture and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting.
H. Vernieuwe, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, https://doi.org/10.5194/hess-19-2685-2015, 2015
M. A. Schull, M. C. Anderson, R. Houborg, A. Gitelson, and W. P. Kustas
Biogeosciences, 12, 1511–1523, https://doi.org/10.5194/bg-12-1511-2015, https://doi.org/10.5194/bg-12-1511-2015, 2015
M. G. De Kauwe, J. Kala, Y.-S. Lin, A. J. Pitman, B. E. Medlyn, R. A. Duursma, G. Abramowitz, Y.-P. Wang, and D. G. Miralles
Geosci. Model Dev., 8, 431–452, https://doi.org/10.5194/gmd-8-431-2015, https://doi.org/10.5194/gmd-8-431-2015, 2015
Short summary
Short summary
Stomatal conductance affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the CABLE land surface model (LSM). The new implementation resulted in a large reduction in the annual fluxes of transpiration across evergreen needleleaf, tundra and C4 grass regions. We conclude that optimisation theory can yield a tractable approach to predicting stomatal conductance in LSMs.
M. J. van den Berg, L. Delobbe, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 18, 5331–5344, https://doi.org/10.5194/hess-18-5331-2014, https://doi.org/10.5194/hess-18-5331-2014, 2014
M. Dessie, N. E. C. Verhoest, V. R. N. Pauwels, T. Admasu, J. Poesen, E. Adgo, J. Deckers, and J. Nyssen
Hydrol. Earth Syst. Sci., 18, 5149–5167, https://doi.org/10.5194/hess-18-5149-2014, https://doi.org/10.5194/hess-18-5149-2014, 2014
Short summary
Short summary
In this study, topography is considered as a proxy for the variability of most of the catchment characteristics. The model study suggests that classifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall–runoff process in the Upper Blue Nile basin well and yields a useful result for operational management of water resources in this data-scarce region.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
Short summary
Short summary
A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
K. Guan, S. P. Good, K. K. Caylor, H. Sato, E. F. Wood, and H. Li
Biogeosciences, 11, 6939–6954, https://doi.org/10.5194/bg-11-6939-2014, https://doi.org/10.5194/bg-11-6939-2014, 2014
Short summary
Short summary
Climate change is expected to modify the way that rainfall arrives, namely the frequency and intensity of rainfall events and rainy season length. Yet, the quantification of the impact of these possible rainfall changes across large biomes is lacking. Our study fills this gap by developing a new modeling framework, applying it to continental Africa. We show that African ecosystems are highly sensitive to these rainfall variabilities, with esp. large sensitivity to changes in rainy season length.
C. C. Brauer, A. J. Teuling, P. J. J. F. Torfs, and R. Uijlenhoet
Geosci. Model Dev., 7, 2313–2332, https://doi.org/10.5194/gmd-7-2313-2014, https://doi.org/10.5194/gmd-7-2313-2014, 2014
C. C. Brauer, P. J. J. F. Torfs, A. J. Teuling, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 18, 4007–4028, https://doi.org/10.5194/hess-18-4007-2014, https://doi.org/10.5194/hess-18-4007-2014, 2014
A. I. Gevaert, A. J. Teuling, R. Uijlenhoet, S. B. DeLong, T. E. Huxman, L. A. Pangle, D. D. Breshears, J. Chorover, J. D. Pelletier, S. R. Saleska, X. Zeng, and P. A. Troch
Hydrol. Earth Syst. Sci., 18, 3681–3692, https://doi.org/10.5194/hess-18-3681-2014, https://doi.org/10.5194/hess-18-3681-2014, 2014
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
M. T. Pham, W. J. Vanhaute, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 5167–5183, https://doi.org/10.5194/hess-17-5167-2013, https://doi.org/10.5194/hess-17-5167-2013, 2013
M. Pan and E. F. Wood
Hydrol. Earth Syst. Sci., 17, 4577–4588, https://doi.org/10.5194/hess-17-4577-2013, https://doi.org/10.5194/hess-17-4577-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
S. Shukla, J. Sheffield, E. F. Wood, and D. P. Lettenmaier
Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, https://doi.org/10.5194/hess-17-2781-2013, 2013
J. Minet, N. E. C. Verhoest, S. Lambot, and M. Vanclooster
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-4063-2013, https://doi.org/10.5194/hessd-10-4063-2013, 2013
Revised manuscript has not been submitted
B. Gräler, M. J. van den Berg, S. Vandenberghe, A. Petroselli, S. Grimaldi, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 1281–1296, https://doi.org/10.5194/hess-17-1281-2013, https://doi.org/10.5194/hess-17-1281-2013, 2013
B. Li and M. Rodell
Hydrol. Earth Syst. Sci., 17, 1177–1188, https://doi.org/10.5194/hess-17-1177-2013, https://doi.org/10.5194/hess-17-1177-2013, 2013
L. Loosvelt, H. Vernieuwe, V. R. N. Pauwels, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 461–478, https://doi.org/10.5194/hess-17-461-2013, https://doi.org/10.5194/hess-17-461-2013, 2013
A. D. Griffiths, S. D. Parkes, S. D. Chambers, M. F. McCabe, and A. G. Williams
Atmos. Meas. Tech., 6, 207–218, https://doi.org/10.5194/amt-6-207-2013, https://doi.org/10.5194/amt-6-207-2013, 2013
Related subject area
Subject: Global hydrology | Techniques and Approaches: Remote Sensing and GIS
Increasing seasonal variation in the extent of rivers and lakes from 1984 to 2022
Investigating sources of variability in closing the terrestrial water balance with remote sensing
Dynamic rainfall erosivity estimates derived from IMERG data
Technical note: Surface fields for global environmental modelling
Benchmarking multimodel terrestrial water storage seasonal cycle against GRACE observations over major global river basins
A global analysis of water storage variations from remotely sensed soil moisture and daily satellite gravimetry
Soil moisture estimates at 1 km resolution making a synergistic use of Sentinel data
Global evaluation of the “dry gets drier, and wet gets wetter” paradigm from a terrestrial water storage change perspective
Global assessment of subnational drought impact based on the Geocoded Disasters dataset and land reanalysis
Scaling methods of leakage correction in GRACE mass change estimates revisited for the complex hydro-climatic setting of the Indus Basin
Remotely sensed reservoir water storage dynamics (1984–2015) and the influence of climate variability and management at a global scale
Characterizing natural variability in complex hydrological systems using passive microwave-based climate data records: a case study for the Okavango Delta
High-resolution (1 km) satellite rainfall estimation from SM2RAIN applied to Sentinel-1: Po River basin as a case study
The accuracy of temporal upscaling of instantaneous evapotranspiration to daily values with seven upscaling methods
Global component analysis of errors in three satellite-only global precipitation estimates
Estimation of hydrological drought recovery based on precipitation and Gravity Recovery and Climate Experiment (GRACE) water storage deficit
Intercomparison of freshwater fluxes over ocean and investigations into water budget closure
Widespread decline in terrestrial water storage and its link to teleconnections across Asia and eastern Europe
Assimilation of vegetation optical depth retrievals from passive microwave radiometry
Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins
Global partitioning of runoff generation mechanisms using remote sensing data
Land–atmosphere interactions in the tropics – a review
Global-scale human pressure evolution imprints on sustainability of river systems
Using GRACE in a streamflow recession to determine drainable water storage in the Mississippi River basin
A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region
Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response
Using modelled discharge to develop satellite-based river gauging: a case study for the Amazon Basin
Global downscaling of remotely sensed soil moisture using neural networks
Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation
Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements
Estimating time-dependent vegetation biases in the SMAP soil moisture product
Daily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra Delta
Controls on surface soil drying rates observed by SMAP and simulated by the Noah land surface model
Quantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission data
Microwave implementation of two-source energy balance approach for estimating evapotranspiration
A global approach to estimate irrigated areas – a comparison between different data and statistics
Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data
Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data
Evaluating the strength of the land–atmosphere moisture feedback in Earth system models using satellite observations
Cloud tolerance of remote-sensing technologies to measure land surface temperature
Dynamic changes in terrestrial net primary production and their effects on evapotranspiration
Assessing changes in urban flood vulnerability through mapping land use from historical information
SACRA – a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI
A global data set of the extent of irrigated land from 1900 to 2005
Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors
Spatial patterns in timing of the diurnal temperature cycle
Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies
Global multi-scale segmentation of continental and coastal waters from the watersheds to the continental margins
Automated global water mapping based on wide-swath orbital synthetic-aperture radar
Björn Nyberg, Roger Sayre, and Elco Luijendijk
Hydrol. Earth Syst. Sci., 28, 1653–1663, https://doi.org/10.5194/hess-28-1653-2024, https://doi.org/10.5194/hess-28-1653-2024, 2024
Short summary
Short summary
Understanding the spatial and temporal distribution of surface water is crucial for effective water resource management, maintaining ecosystem health and assessing flood risks. This study examined permanent and seasonal rivers and lakes globally over 38 years, uncovering a statistically significant expansion in seasonal extent captured in the new SARL database. The findings offer valuable resources for assessing the impact of changing river and lake extents on ecosystems and human livelihoods.
Claire I. Michailovsky, Bert Coerver, Marloes Mul, and Graham Jewitt
Hydrol. Earth Syst. Sci., 27, 4335–4354, https://doi.org/10.5194/hess-27-4335-2023, https://doi.org/10.5194/hess-27-4335-2023, 2023
Short summary
Short summary
Many remote sensing products for precipitation, evapotranspiration, and water storage variations exist. However, when these are used with in situ runoff data in water balance closure studies, no single combination of products consistently outperforms others. We analyzed the water balance closure using different products in catchments worldwide and related the results to catchment characteristics. Our results can help identify the dataset combinations best suited for use in different catchments.
Robert A. Emberson
Hydrol. Earth Syst. Sci., 27, 3547–3563, https://doi.org/10.5194/hess-27-3547-2023, https://doi.org/10.5194/hess-27-3547-2023, 2023
Short summary
Short summary
Soil can be eroded by rainfall, and this is a major threat to agricultural sustainability. Estimating the erosivity of rainfall is essential as a first step to determine how much soil might be lost. Until recently, satellite data have not been used to estimate rainfall erosivity, but the data quality is now sufficient to do so. In this study, I test several methods to calculate rainfall erosivity using satellite rainfall data and contrast this with ground-based estimates.
Margarita Choulga, Francesca Moschini, Cinzia Mazzetti, Stefania Grimaldi, Juliana Disperati, Hylke Beck, Peter Salamon, and Christel Prudhomme
EGUsphere, https://doi.org/10.5194/egusphere-2023-1306, https://doi.org/10.5194/egusphere-2023-1306, 2023
Short summary
Short summary
CEMS_SurfaceFields_2022 dataset is a new set of high-resolution maps for land type (e.g. lake, forest), soil properties and population water needs at approximately 2 and 6 km at the Equator covering Europe and Globe (excluding Antarctica) respectively. Paper describes what new high-resolution information and how exactly to use to create the dataset. Paper suggests that dataset can be used as input for river/ weather/ other models, and also for statistical description of the region of interest.
Sadia Bibi, Tingju Zhu, Ashraf Rateb, Bridget R. Scanlon, Muhammad Aqeel Kamran, Abdelrazek Elnashar, Ali Bennour, and Ci Li
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-163, https://doi.org/10.5194/hess-2023-163, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
This study assessed 13 global models using GRACE satellite data over 29 river basins. Simulated seasonal water storage cycles showed discrepancies compared to GRACE. The models overestimated seasonal amplitude in boreal basins, while underestimated in tropical, arid, and temperate zones, and they had 2–3 month phase differences with GRACE in cold basins and 1 month in temperate, arid, and semi-arid basins. Seasonal amplitude and phase differences provide insights for model improvement.
Daniel Blank, Annette Eicker, Laura Jensen, and Andreas Güntner
Hydrol. Earth Syst. Sci., 27, 2413–2435, https://doi.org/10.5194/hess-27-2413-2023, https://doi.org/10.5194/hess-27-2413-2023, 2023
Short summary
Short summary
Soil moisture (SM), a key variable of the global water cycle, is analyzed using two types of satellite observations; microwave sensors measure the top few centimeters and satellite gravimetry (GRACE) the full vertical water column. As SM can change very fast, non-standard daily GRACE data are applied for the first time for this analysis. Jointly analyzing these data gives insight into the SM dynamics at different soil depths, and time shifts indicate the infiltration time into deeper layers.
Remi Madelon, Nemesio J. Rodríguez-Fernández, Hassan Bazzi, Nicolas Baghdadi, Clement Albergel, Wouter Dorigo, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
Short summary
Short summary
We present an approach to estimate soil moisture (SM) at 1 km resolution using Sentinel-1 and Sentinel-3 satellites. The estimates were compared to other high-resolution (HR) datasets over Europe, northern Africa, Australia, and North America, showing good agreement. However, the discrepancies between the different HR datasets and their lower performances compared with in situ measurements and coarse-resolution datasets show the remaining challenges for large-scale HR SM mapping.
Jinghua Xiong, Shenglian Guo, Abhishek, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
Short summary
Short summary
Although the "dry gets drier, and wet gets wetter (DDWW)" paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.
Yuya Kageyama and Yohei Sawada
Hydrol. Earth Syst. Sci., 26, 4707–4720, https://doi.org/10.5194/hess-26-4707-2022, https://doi.org/10.5194/hess-26-4707-2022, 2022
Short summary
Short summary
This study explores the link between hydrometeorological droughts and their socioeconomic impact at a subnational scale based on the newly developed disaster dataset with subnational location information. Hydrometeorological drought-prone areas were generally consistent with socioeconomic drought-prone areas in the disaster dataset. Our analysis clarifies the importance of the use of subnational disaster information.
Vasaw Tripathi, Andreas Groh, Martin Horwath, and Raaj Ramsankaran
Hydrol. Earth Syst. Sci., 26, 4515–4535, https://doi.org/10.5194/hess-26-4515-2022, https://doi.org/10.5194/hess-26-4515-2022, 2022
Short summary
Short summary
GRACE/GRACE-FO provided global observations of water storage change since 2002. Scaling is a common approach to compensate for the spatial filtering inherent to the results. However, for complex hydrological basins, the compatibility of scaling with the characteristics of regional hydrology has been rarely assessed. We assess traditional scaling approaches and a new scaling approach for the Indus Basin. Our results will help users with regional focus understand implications of scaling choices.
Jiawei Hou, Albert I. J. M. van Dijk, Hylke E. Beck, Luigi J. Renzullo, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 26, 3785–3803, https://doi.org/10.5194/hess-26-3785-2022, https://doi.org/10.5194/hess-26-3785-2022, 2022
Short summary
Short summary
We used satellite imagery to measure monthly reservoir water volumes for 6695 reservoirs worldwide for 1984–2015. We investigated how changing precipitation, streamflow, evaporation, and human activity affected reservoir water storage. Almost half of the reservoirs showed significant increasing or decreasing trends over the past three decades. These changes are caused, first and foremost, by changes in precipitation rather than by changes in net evaporation or dam release patterns.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
Short summary
Short summary
Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Paolo Filippucci, Luca Brocca, Raphael Quast, Luca Ciabatta, Carla Saltalippi, Wolfgang Wagner, and Angelica Tarpanelli
Hydrol. Earth Syst. Sci., 26, 2481–2497, https://doi.org/10.5194/hess-26-2481-2022, https://doi.org/10.5194/hess-26-2481-2022, 2022
Short summary
Short summary
A high-resolution (1 km) rainfall product with 10–30 d temporal resolution was obtained starting from SM data from Sentinel-1. Good performances are achieved using observed data (gauge and radar) over the Po River Valley, Italy, as a benchmark. The comparison with a product characterized by lower spatial resolution (25 km) highlights areas where the high spatial resolution of Sentinel-1 has great benefits. Possible applications include water management, agriculture and index-based insurances.
Zhaofei Liu
Hydrol. Earth Syst. Sci., 25, 4417–4433, https://doi.org/10.5194/hess-25-4417-2021, https://doi.org/10.5194/hess-25-4417-2021, 2021
Short summary
Short summary
Instantaneous evapotranspiration (ET), which is detected by the remote sensing technique, needs to be upscaled to daily values in order to practical applications. The accuracy of seven upscaling methods is evaluated by using global observations. The sine function and the evaporative fraction method using extraterrestrial solar irradiance are recommended. Although every upscaling scheme has high accuracy at most sites, it is less accurate at tropical rainforest and tropical monsoon sites.
Hanqing Chen, Bin Yong, Pierre-Emmanuel Kirstetter, Leyang Wang, and Yang Hong
Hydrol. Earth Syst. Sci., 25, 3087–3104, https://doi.org/10.5194/hess-25-3087-2021, https://doi.org/10.5194/hess-25-3087-2021, 2021
Alka Singh, John Thomas Reager, and Ali Behrangi
Hydrol. Earth Syst. Sci., 25, 511–526, https://doi.org/10.5194/hess-25-511-2021, https://doi.org/10.5194/hess-25-511-2021, 2021
Short summary
Short summary
The study demonstrates the utility of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies (TWSAs) for obtaining statistics of hydrological droughts, i.e., recovery periods and required precipitation in different precipitation scenarios. The findings of this study are that the GRACE-based drought index is valid for estimating the required precipitation for drought recovery, and the period of drought recovery depends on the intensity of the precipitation.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
Short summary
Short summary
The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Xianfeng Liu, Xiaoming Feng, Philippe Ciais, and Bojie Fu
Hydrol. Earth Syst. Sci., 24, 3663–3676, https://doi.org/10.5194/hess-24-3663-2020, https://doi.org/10.5194/hess-24-3663-2020, 2020
Short summary
Short summary
Freshwater availability is crucial for sustainable development across the Asian and eastern European regions. Our results indicate widespread decline in terrestrial water storage (TWS) over the region during 2002–2017, primarily due to the intensive over-extraction of groundwater and warmth-induced surface water loss. The findings provide insights into changes in TWS and its components over the Asian and eastern European regions, where there is growing demand for food grains and water supplies.
Sujay V. Kumar, Thomas R. Holmes, Rajat Bindlish, Richard de Jeu, and Christa Peters-Lidard
Hydrol. Earth Syst. Sci., 24, 3431–3450, https://doi.org/10.5194/hess-24-3431-2020, https://doi.org/10.5194/hess-24-3431-2020, 2020
Short summary
Short summary
Vegetation optical depth (VOD) is a byproduct of the soil moisture retrieval from passive microwave instruments. This study demonstrates that VOD information can be utilized for improving land surface water budget and carbon conditions through data assimilation.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
Short summary
Short summary
The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Joseph T. D. Lucey, John T. Reager, and Sonya R. Lopez
Hydrol. Earth Syst. Sci., 24, 1415–1427, https://doi.org/10.5194/hess-24-1415-2020, https://doi.org/10.5194/hess-24-1415-2020, 2020
Short summary
Short summary
This work relates total water storage (TWS) and rainfall to surface water inundation (SWI) using NASA satellite data. We determine whether TWS and/or rainfall control global SWI developments. Regression methods and cross-correlations were used to relate the measurements and correct for time differences among peaks. Results show TWS and rainfall control most global SWI developments. To our knowledge, this is the first global study on SWI controls and validates previous findings.
Pierre Gentine, Adam Massmann, Benjamin R. Lintner, Sayed Hamed Alemohammad, Rong Fu, Julia K. Green, Daniel Kennedy, and Jordi Vilà-Guerau de Arellano
Hydrol. Earth Syst. Sci., 23, 4171–4197, https://doi.org/10.5194/hess-23-4171-2019, https://doi.org/10.5194/hess-23-4171-2019, 2019
Short summary
Short summary
Land–atmosphere interactions are key for the exchange of water, energy, and carbon dioxide, especially in the tropics. We here review some of the recent findings on land–atmosphere interactions in the tropics and where we see potential challenges and paths forward.
Serena Ceola, Francesco Laio, and Alberto Montanari
Hydrol. Earth Syst. Sci., 23, 3933–3944, https://doi.org/10.5194/hess-23-3933-2019, https://doi.org/10.5194/hess-23-3933-2019, 2019
Short summary
Short summary
A simple and effective index for the quantitative estimation of the evolution of human pressure on rivers at global scale is proposed. This index, based on nightlights and river discharge data, shows a significant increase from 1992 to 2013 worldwide. The most notable changes are found in river basins across Africa and Asia, where human pressure on rivers is growing markedly. This index identifies priority areas that can be targeted for the implementation of mitigation strategies and plans.
Heloisa Ehalt Macedo, Ralph Edward Beighley, Cédric H. David, and John T. Reager
Hydrol. Earth Syst. Sci., 23, 3269–3277, https://doi.org/10.5194/hess-23-3269-2019, https://doi.org/10.5194/hess-23-3269-2019, 2019
Short summary
Short summary
The water stored under the surface is very important for defining the amount of water available for human and environmental applications; however, it is still a challenge to obtain such measurements. NASA's GRACE satellites provide information on total terrestrial water storage based on observations of gravity changes. Here, we relate GRACE data to streamflow measurements, providing estimations of the fraction of baseflow and total drainable storage for the Mississippi River basin.
Linlin Li, Andrew Skidmore, Anton Vrieling, and Tiejun Wang
Hydrol. Earth Syst. Sci., 23, 3037–3056, https://doi.org/10.5194/hess-23-3037-2019, https://doi.org/10.5194/hess-23-3037-2019, 2019
Short summary
Short summary
We derived an 8 d, 500 m resolution surface water fraction product over the Mediterranean region for 2000–2017 based on MODIS data. This dataset complements existing surface water/wetland datasets by adding more temporal detail. It allows for the seasonal, inter-annual, and long-term dynamics of the surface water extent to be monitored, inclusive of small-sized and highly dynamic water bodies; it can also contribute to biodiversity and climate change assessment.
Siyuan Tian, Luigi J. Renzullo, Albert I. J. M. van Dijk, Paul Tregoning, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 1067–1081, https://doi.org/10.5194/hess-23-1067-2019, https://doi.org/10.5194/hess-23-1067-2019, 2019
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, and Robert A. Vertessy
Hydrol. Earth Syst. Sci., 22, 6435–6448, https://doi.org/10.5194/hess-22-6435-2018, https://doi.org/10.5194/hess-22-6435-2018, 2018
Short summary
Short summary
Satellite-based river gauging can be constructed based on remote-sensing-derived surface water extent and modelled discharge, and used to estimate river discharges with satellite observations only. This provides opportunities for monitoring river discharge in the absence of a real-time hydrological model or gauging stations.
Seyed Hamed Alemohammad, Jana Kolassa, Catherine Prigent, Filipe Aires, and Pierre Gentine
Hydrol. Earth Syst. Sci., 22, 5341–5356, https://doi.org/10.5194/hess-22-5341-2018, https://doi.org/10.5194/hess-22-5341-2018, 2018
Short summary
Short summary
A new machine learning algorithm is developed to downscale satellite-based soil moisture estimates from their native spatial scale of 9 km to 2.25 km.
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
Short summary
Short summary
Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
Short summary
Short summary
Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Simon Zwieback, Andreas Colliander, Michael H. Cosh, José Martínez-Fernández, Heather McNairn, Patrick J. Starks, Marc Thibeault, and Aaron Berg
Hydrol. Earth Syst. Sci., 22, 4473–4489, https://doi.org/10.5194/hess-22-4473-2018, https://doi.org/10.5194/hess-22-4473-2018, 2018
Short summary
Short summary
Satellite soil moisture products can provide critical information on incipient droughts and the interplay between vegetation and water availability. However, time-variant systematic errors in the soil moisture products may impede their usefulness. Using a novel statistical approach, we detect such errors (associated with changing vegetation) in the SMAP soil moisture product. The vegetation-associated biases impede drought detection and the quantification of vegetation–water interactions.
Ben T. Gouweleeuw, Andreas Kvas, Christian Gruber, Animesh K. Gain, Thorsten Mayer-Gürr, Frank Flechtner, and Andreas Güntner
Hydrol. Earth Syst. Sci., 22, 2867–2880, https://doi.org/10.5194/hess-22-2867-2018, https://doi.org/10.5194/hess-22-2867-2018, 2018
Short summary
Short summary
Daily GRACE gravity field solutions have been evaluated against daily river runoff data for major flood events in the Ganges–Brahmaputra Delta in 2004 and 2007. Compared to the monthly gravity field solutions, the trends over periods of a few days in the daily gravity field solutions are able to reflect temporal variations in river runoff during major flood events. This implies that daily gravity field solutions released in near-real time may support flood monitoring for large events.
Peter J. Shellito, Eric E. Small, and Ben Livneh
Hydrol. Earth Syst. Sci., 22, 1649–1663, https://doi.org/10.5194/hess-22-1649-2018, https://doi.org/10.5194/hess-22-1649-2018, 2018
Short summary
Short summary
After soil gets wet, much of the surface moisture evaporates directly back into the air. Recent satellite data show that this process is enhanced when there is more water in the soil, less humidity in the air, and less vegetation covering the ground. A widely used model shows similar effects of soil water and humidity, but it largely misses the role of vegetation and assigns outsized importance to soil type. These results are encouraging evidence that the satellite can be used to improve models.
Cassandra Normandin, Frédéric Frappart, Bertrand Lubac, Simon Bélanger, Vincent Marieu, Fabien Blarel, Arthur Robinet, and Léa Guiastrennec-Faugas
Hydrol. Earth Syst. Sci., 22, 1543–1561, https://doi.org/10.5194/hess-22-1543-2018, https://doi.org/10.5194/hess-22-1543-2018, 2018
Thomas R. H. Holmes, Christopher R. Hain, Wade T. Crow, Martha C. Anderson, and William P. Kustas
Hydrol. Earth Syst. Sci., 22, 1351–1369, https://doi.org/10.5194/hess-22-1351-2018, https://doi.org/10.5194/hess-22-1351-2018, 2018
Short summary
Short summary
In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.
Jonas Meier, Florian Zabel, and Wolfram Mauser
Hydrol. Earth Syst. Sci., 22, 1119–1133, https://doi.org/10.5194/hess-22-1119-2018, https://doi.org/10.5194/hess-22-1119-2018, 2018
Short summary
Short summary
The following study extends existing irrigation maps based on official reports. The main idea was to extend the reported irrigated areas using agricultural suitability data and compare them with remote sensing information about plant conditions. The analysis indicates an increase in irrigated land by 18 % compared to the reported statistics. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated.
Liangjing Zhang, Henryk Dobslaw, Tobias Stacke, Andreas Güntner, Robert Dill, and Maik Thomas
Hydrol. Earth Syst. Sci., 21, 821–837, https://doi.org/10.5194/hess-21-821-2017, https://doi.org/10.5194/hess-21-821-2017, 2017
Short summary
Short summary
Global numerical models perform differently, as has been found in some model intercomparison studies, which mainly focused on components like evapotranspiration, soil moisture or runoff. We have applied terrestrial water storage that is estimated from a GRACE-based state-of-art post-processing method to validate four global numerical models and try to identify the advantages and deficiencies of a certain model. GRACE-based TWS demonstrates its additional benefits to improve the models in future.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
Short summary
Short summary
MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
Oliver López, Rasmus Houborg, and Matthew Francis McCabe
Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, https://doi.org/10.5194/hess-21-323-2017, 2017
Short summary
Short summary
The study evaluated the spatial and temporal consistency of satellite-based hydrological products based on the water budget equation, including three global evaporation products. The products were spatially matched using spherical harmonics analysis. The results highlighted the difficulty in obtaining agreement between independent satellite products, even over regions with simple water budgets. However, imposing a time lag on water storage data improved results considerably.
Paul A. Levine, James T. Randerson, Sean C. Swenson, and David M. Lawrence
Hydrol. Earth Syst. Sci., 20, 4837–4856, https://doi.org/10.5194/hess-20-4837-2016, https://doi.org/10.5194/hess-20-4837-2016, 2016
Short summary
Short summary
We demonstrate a new approach to assess the strength of feedbacks resulting from land–atmosphere coupling on decadal timescales. Our approach was tailored to enable evaluation of Earth system models (ESMs) using data from Earth observation satellites that measure terrestrial water storage anomalies and relevant atmospheric variables. Our results are consistent with previous work demonstrating that ESMs may be overestimating the strength of land surface feedbacks compared with observations.
Thomas R. H. Holmes, Christopher R. Hain, Martha C. Anderson, and Wade T. Crow
Hydrol. Earth Syst. Sci., 20, 3263–3275, https://doi.org/10.5194/hess-20-3263-2016, https://doi.org/10.5194/hess-20-3263-2016, 2016
Short summary
Short summary
We test the cloud tolerance of two technologies to estimate land surface temperature (LST) from space: microwave (MW) and thermal infrared (TIR). Although TIR has slightly lower errors than MW with ground data under clear-sky conditions, it suffers increasing negative bias as cloud cover increases. In contrast, we find no direct impact of clouds on the accuracy and bias of MW-LST. MW-LST can therefore be used to improve TIR cloud screening and increase sampling in clouded regions.
Zhi Li, Yaning Chen, Yang Wang, and Gonghuan Fang
Hydrol. Earth Syst. Sci., 20, 2169–2178, https://doi.org/10.5194/hess-20-2169-2016, https://doi.org/10.5194/hess-20-2169-2016, 2016
Short summary
Short summary
Global net primary production (NPP) slightly increased in 2000–2014. More than 64 % of vegetated land in the Northern Hemisphere (NH) showed increased NPP, while 60.3 % in Southern Hemisphere (SH) showed a decreasing trend. Vegetation greening and climate change promote rises of global evapotranspiration (ET). The increased rate of ET in the NH is faster than that in the SH. Meanwhile, global warming and vegetation greening accelerate evaporation in soil moisture. Continuation of these trends will likely exacerbate the risk of ecological drought.
M. Boudou, B. Danière, and M. Lang
Hydrol. Earth Syst. Sci., 20, 161–173, https://doi.org/10.5194/hess-20-161-2016, https://doi.org/10.5194/hess-20-161-2016, 2016
Short summary
Short summary
This paper presents an appraisal of flood vulnerability of two French cities, Besançon and Moissac, which have been largely impacted by two ancient major floods (resp. in January 1910 and March 1930). An analysis of historical sources allows the mapping of land use and occupation within the flood extent of the two historical floods, both in past and present contexts. It gives an insight into the complexity of flood risk evolution, at a local scale.
S. Kotsuki and K. Tanaka
Hydrol. Earth Syst. Sci., 19, 4441–4461, https://doi.org/10.5194/hess-19-4441-2015, https://doi.org/10.5194/hess-19-4441-2015, 2015
Short summary
Short summary
This study aims to develop a new global data set of a satellite-derived crop calendar (SACRA) and to reveal its advantages and disadvantages compared to other global products. The cultivation period of SACRA is identified from the time series of NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most areas.
S. Siebert, M. Kummu, M. Porkka, P. Döll, N. Ramankutty, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 19, 1521–1545, https://doi.org/10.5194/hess-19-1521-2015, https://doi.org/10.5194/hess-19-1521-2015, 2015
Short summary
Short summary
We developed the historical irrigation data set (HID) depicting the spatio-temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5arcmin resolution.
The HID reflects very well the spatial patterns of irrigated land as shown on two historical maps for 1910 and 1960.
Global AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. Mean aridity on irrigated land increased and mean natural river discharge decreased from 1900 to 1950.
B. Revilla-Romero, J. Thielen, P. Salamon, T. De Groeve, and G. R. Brakenridge
Hydrol. Earth Syst. Sci., 18, 4467–4484, https://doi.org/10.5194/hess-18-4467-2014, https://doi.org/10.5194/hess-18-4467-2014, 2014
Short summary
Short summary
One of the main challenges in global hydrological modelling is the limited availability of observational data for calibration and model verification. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System (GFDS) for converting the flood detection signal into river discharge values. This work also provides a first analysis of the local factors influencing the accuracy of discharge measurement as provided by this system.
T. R. H. Holmes, W. T. Crow, and C. Hain
Hydrol. Earth Syst. Sci., 17, 3695–3706, https://doi.org/10.5194/hess-17-3695-2013, https://doi.org/10.5194/hess-17-3695-2013, 2013
A. Loew, T. Stacke, W. Dorigo, R. de Jeu, and S. Hagemann
Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, https://doi.org/10.5194/hess-17-3523-2013, 2013
G. G. Laruelle, H. H. Dürr, R. Lauerwald, J. Hartmann, C. P. Slomp, N. Goossens, and P. A. G. Regnier
Hydrol. Earth Syst. Sci., 17, 2029–2051, https://doi.org/10.5194/hess-17-2029-2013, https://doi.org/10.5194/hess-17-2029-2013, 2013
R. S. Westerhoff, M. P. H. Kleuskens, H. C. Winsemius, H. J. Huizinga, G. R. Brakenridge, and C. Bishop
Hydrol. Earth Syst. Sci., 17, 651–663, https://doi.org/10.5194/hess-17-651-2013, https://doi.org/10.5194/hess-17-651-2013, 2013
Cited articles
Aires, F., Prigent, C., Rossow, W. B., and Rothstein, M.: A new neural network approach including first guess for retrieval of atmospheric water vapor, cloud liquid water path, surface temperature, and emissivities over land from satellite microwave observations, J. Geophys. Res.-Atmos., 106, 14887–14907, 2001.
Aker, J. C. and Mbiti, I. M.: Mobile phones and economic development in Africa, J. Econ. Perspect., 24, 207–232, https://doi.org/10.1257/jep.24.3.207, 2010.
Alemohammad, S. H., Fang, B., Konings, A. G., Green, J. K., Kolassa, J., Prigent, C., Aires, F., Miralles, D., and Gentine, P.: Water, Energy, and Carbon with Artificial Neural Networks (WECANN): A statistically-based estimate of global surface turbulent fluxes using solar-induced fluorescence, Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-495, in review, 2016.
Allamano, P., Croci, A., and Laio, F.: Toward the camera rain gauge, Water Resour. Res., 51, 1744–1757, https://doi.org/10.1002/2014WR016298, 2015.
Alsdorf, D. E., Rodríguez, E., and Lettenmaier, D. P.: Measuring surface water from space, Rev. Geophys., 45, RG2002, https://doi.org/10.1029/2006RG000197, 2007.
Anderson, C.: The end of theory: The data deluge makes the scientific method obsolete, in: Wired Magazine, https://www.wired.com/2008/06/pb-theory/ (last access: 26 July 2017), 2008.
Anderson, K. and Gaston, K. J.: Lightweight unmanned aerial vehicles will revolutionize spatial ecology, Front. Ecol. Environ., 11, 138–146, https://doi.org/10.1890/120150, 2013.
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Torn, R. D., Kustas, W. P., and Basara, J. B.: A Multiscale Remote Sensing Model for Disaggregating Regional Fluxes to Micrometeorological Scales, J. Hydrometeorol., 5, 343–363, 2004.
Anderson, M. C., Hain, C., Otkin, J., Zhan, X., Mo, K., Svoboda, M., Wardlow, B., and Pimstein, A.: An Intercomparison of Drought Indicators Based on Thermal Remote Sensing and NLDAS-2 Simulations with U.S. Drought Monitor Classifications, J. Hydrometeorol., 14, 1035–1056, https://doi.org/10.1175/jhm-d-12-0140.1, 2013.
Andreasen, M., Jensen, K. H., Desilets, D., Zreda, M., Bogena, H., and Looms, M. C.: Can canopy interception and biomass be inferred from cosmic-ray neutron intensity? Results from neutron transport modeling, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-226, in review, 2016.
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., and Zaharia, M.: A view of cloud computing, Commun. ACM, 53, 50–58, https://doi.org/10.1145/1721654.1721672, 2010.
Astsatryan, H., Narsisian, W., and Asmaryan, S.: SWAT hydrological model as a DaaS cloud service, Earth Sci. Inform., 9, 401–407, https://doi.org/10.1007/s12145-016-0254-6, 2016.
Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the aqua mission: Design, science objectives, data products, and processing systems, IEEE T. Geosci. Remote, 41, 253–263, https://doi.org/10.1109/TGRS.2002.808356, 2003.
Barnhart, D. J., Vladimirova, T., Baker, A. M., and Sweeting, M. N.: A low-cost femtosatellite to enable distributed space missions, Acta Astronaut., 64, 1123–1143, https://doi.org/10.1016/j.actaastro.2009.01.025, 2009.
Barthès, L. and Mallet, C.: Rainfall measurement from the opportunistic use of an Earth–space link in the Ku band, Atmos. Meas. Tech., 6, 2181–2193, https://doi.org/10.5194/amt-6-2181-2013, 2013.
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., and Holtslag, A.: A remote sensing surface energy balance algorithm for land (SEBAL). I. Formulation, J. Hydrol., 212–213, 198–212, 1998.
Baur, O., Kuhn, M., and Featherstone, W. E.: GRACE-derived ice-mass variations over Greenland by accounting for leakage effects, J. Geophys. Res.-Solid Ea., 114, B06407, https://doi.org/10.1029/2008JB006239, 2009.
Bayard, D., Stähli, M., Parriaux, A., and Flühler, H.: The influence of seasonally frozen soil on the snowmelt runoff at two Alpine sites in southern Switzerland, J. Hydrol., 309, 66–84, https://doi.org/10.1016/j.jhydrol.2004.11.012, 2005.
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017.
Beckett, K.: UrtheCast second-generation earth observation sensors, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives, 1069–1073, 2015.
Bellvert, J., Zarco-Tejada, P. J., Marsal, J., Girona, J., González-Dugo, V., and Fereres, E.: Vineyard irrigation scheduling based on airborne thermal imagery and water potential thresholds, Aust. J. Grape Wine Res., 22, 307–315, https://doi.org/10.1111/ajgw.12173, 2016.
Berne, A., Delrieu, G., Creutin, J.-D., and Obled, C.: Temporal and spatial resolution of rainfall measurements required for urban hydrology, J. Hydrol., 299, 166–179, https://doi.org/10.1016/j.jhydrol.2004.08.002, 2004.
Biancamaria, S., Durand, M., Andreadis, K. M., Bates, P. D., Boone, A., Mognard, N. M., Rodríguez, E., Alsdorf, D. E., Lettenmaier, D. P., and Clark, E. A.: Assimilation of virtual wide swath altimetry to improve Arctic river modeling, Remote Sens. Environ., 115, 373–381, https://doi.org/10.1016/j.rse.2010.09.008, 2011.
Bierkens, M. F. P., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David, C. H., de Roo, A., Döll, P., Drost, N., Famiglietti, J. S., Flörke, M., Gochis, D. J., Houser, P., Hut, R., Keune, J., Kollet, S., Maxwell, R. M., Reager, J. T., Samaniego, L., Sudicky, E., Sutanudjaja, E. H., van de Giesen, N., Winsemius, H., and Wood, E. F.: Hyper-resolution global hydrological modelling: what is next?, Hydrol. Process., 29, 310–320, https://doi.org/10.1002/hyp.10391, 2015.
Bormann, K. J., Westra, S., Evans, J. P., and McCabe, M. F.: Spatial and temporal variability in seasonal snow density, J. Hydrol., 484, 63–73, 2013.
Bouwmeester, J. and Guo, J.: Survey of worldwide pico- and nanosatellite missions, distributions and subsystem technology, Acta Astronaut., 67, 854–862, https://doi.org/10.1016/j.actaastro.2010.06.004, 2010.
Brando, V. E. and Dekker, A. G.: Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality, IEEE T. Geosci. Remote, 41, 1378–1387, https://doi.org/10.1109/TGRS.2003.812907, 2003.
Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data, J. Geophys. Res.-Atmos., 119, 5128–5141, https://doi.org/10.1002/2014JD021489, 2014.
Brooks, B. A., Glennie, C., Hudnut, K. W., Ericksen, T., and Hauser, D.: Mobile laser scanning applied to the earth sciences, Eos, 94, 313–315, 2013.
Buytaert, W., Zulkafli, Z., Grainger, S., Acosta, L., Alemie, T. C., Bastiaensen, J., De Bièvre, B., Bhusal, J., Clark, J., Dewulf, A., Foggin, M., Hannah, D. M., Hergarten, C., Isaeva, A., Karpouzoglou, T., Pandeya, B., Paudel, D., Sharma, K., Steenhuis, T., Tilahun, S., Van Hecken, G., and Zhumanova, M.: Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development, Front. Earth Sci., 2, 26, https://doi.org/10.3389/feart.2014.00026, 2014.
Calmant, S. and Seyler, F.: Continental surface waters from satellite altimetry, Comptes Rendus Geoscience, 338, 1113–1122, https://doi.org/10.1016/j.crte.2006.05.012, 2006.
Cammalleri, C., Anderson, M. C., Gao, F., Hain, C. R., and Kustas, W. P.: Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion, Agr. Forest Meteorol., 186, 1–11, https://doi.org/10.1016/j.agrformet.2013.11.001, 2014.
Carroll, M. L., Townshend, J. R., DiMiceli, C. M., Noojipady, P., and Sohlberg, R. A.: A new global raster water mask at 250 m resolution, Int. J. Digit. Earth, 2, 291–308, https://doi.org/10.1080/17538940902951401, 2009.
Chaney, N. W., Wood, E. F., McBratney, A. B., Hempel, J. W., Nauman, T. W., Brungard, C. W., and Odgers, N. P.: POLARIS: A 30-meter probabilistic soil series map of the contiguous United States, Geoderma, 274, 54–67, https://doi.org/10.1016/j.geoderma.2016.03.025, 2016.
Chen, L., Yeh, K. C., Wei, H. P., and Liu, G. R.: An improved genetic programming to SSM/I estimation typhoon precipitation over ocean, Hydrol. Process., 25, 2573–2583, https://doi.org/10.1002/hyp.8132, 2011.
Chen, X. and Vierling, L.: Spectral mixture analyses of hyperspectral data acquired using a tethered balloon, Remote Sens. Environ., 103, 338–350, https://doi.org/10.1016/j.rse.2005.05.023, 2006.
Chrisman, B. and Zreda, M.: Quantifying mesoscale soil moisture with the cosmic-ray rover, Hydrol. Earth Syst. Sci., 17, 5097–5108, https://doi.org/10.5194/hess-17-5097-2013, 2013.
Coccia, G., Siemann, A. L., Pan, M., and Wood, E. F.: Creating consistent datasets by combining remotely-sensed data and land surface model estimates through Bayesian uncertainty post-processing: The case of Land Surface Temperature from HIRS, Remote Sens. Environ., 170, 290–305, https://doi.org/10.1016/j.rse.2015.09.010, 2015.
Coopersmith, J.: The cost of reaching orbit: Ground-based launch systems, Space Policy, 27, 77–80, https://doi.org/10.1016/j.spacepol.2011.03.001, 2011.
d'Angelo, P., Máttyus, G., and Reinartz, P.: Skybox image and video product evaluation, Int. J. Image Data Fusion, 7, 3–18, https://doi.org/10.1080/19479832.2015.1109565, 2016.
Das, N. N. and Mohanty, B. P.: Root zone soil moisture assessment using remote sensing and vadose zone modeling, Vadose Zone J., 5, 296–307, https://doi.org/10.2136/vzj2005.0033, 2006.
Dash, J. and Ogutu, B. O.: Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems, Prog. Phys. Geogr., 40, 322–351, https://doi.org/10.1177/0309133316639403, 2016.
Denis, G., de Boissezon, H., Hosford, S., Pasco, X., Montfort, B., and Ranera, F.: The evolution of Earth Observation satellites in Europe and its impact on the performance of emergency response services, Acta Astronaut., 127, 619–633, https://doi.org/10.1016/j.actaastro.2016.06.012, 2016.
Deo, R. C. and Şahin, M.: An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland, Environ. Monit. Assess., 188, 1–24, https://doi.org/10.1007/s10661-016-5094-9, 2016.
Desilets, D., Zreda, M., and Ferré, T. P. A.: Nature's neutron probe: Land surface hydrology at an elusive scale with cosmic rays, Water Resour. Res., 46, W11505, https://doi.org/10.1029/2009WR008726, 2010.
de Vos, L., Leijnse, H., Overeem, A., and Uijlenhoet, R.: The potential of urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam, Hydrol. Earth Syst. Sci., 21, 765–777, https://doi.org/10.5194/hess-21-765-2017, 2017.
De Wulf, R. R., Goossens, R. E., De Roover, B. P., and Borry, F. C.: Extraction of forest stand parameters from panchromatic and multispectral SPOT-1 data, Int. J. Remote Sens., 11, 1571–1588, https://doi.org/10.1080/01431169008955115, 1990.
Donchyts, G., Baart, F., Winsemius, H., Gorelick, N., Kwadijk, J., and Van De Giesen, N.: Earth's surface water change over the past 30 years, Nat. Clim. Change, 6, 810–813, https://doi.org/10.1038/nclimate3111, 2016.
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T.: The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011.
Dorigo, W. A., Gruber, A., De Jeu, R. A. M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R. M., and Kidd, R.: Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sens. Environ., 162, 380–395, https://doi.org/10.1016/j.rse.2014.07.023, 2015.
Doumounia, A., Gosset, M., Cazenave, F., Kacou, M., and Zougmore, F.: Rainfall monitoring based on microwave links from cellular telecommunication networks: First results from a West African test bed, Geophys. Res. Lett., 41, 6016–6022, https://doi.org/10.1002/2014GL060724, 2014.
Drüe, C., Frey, W., Hoff, A., and Hauf, T.: Aircraft type-specific errors in AMDAR weather reports from commercial aircraft, Q. J. Roy. Meteorol. Soc., 134, 229–239, https://doi.org/10.1002/qj.205, 2008.
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., Meygret, A., Spoto, F., Sy, O., Marchese, F., and Bargellini, P.: Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services, Remote Sens. Environ., 120, 25–36, https://doi.org/10.1016/j.rse.2011.11.026, 2012.
Edberg, S. J., Evans, D. L., Graf, J. E., Hyon, J. J., Rosen, P. A., and Waliser, D. E.: Studying Earth in the New Millennium: NASA Jet Propulsion Laboratory's Contributions to Earth Science and Applications Space Agencies, IEEE Geosci. Remote Sens. Mag., 4, 26–39, https://doi.org/10.1109/MGRS.2016.2525678, 2016.
Elefante, S., Wagner, W., Briese, C., Cao, S., and Naeimi, V.: High-performance computing for soil moisture estimation, in: Proceedings of the 2016 conference on Big Data from Space (BiDS'16), Santa Cruz de Tenerife, Spain, 2016.
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, https://doi.org/10.1109/JPROC.2010.2043918, 2010.
Ershadi, A., McCabe, M. F., Evans, J. P., and Walker, J. P.: Effects of spatial aggregation on the multi-scale estimation of evapotranspiration, Remote Sens. Environ., 131, 51–62, https://doi.org/10.1016/j.rse.2012.12.007, 2013.
Ershadi, A., McCabe, M. F., Evans, J. P., Chaney, N. W., and Wood, E. F.: Multi-site evaluation of terrestrial evaporation models using FLUXNET data, Agr. Forest Meteorol., 187, 46–61, https://doi.org/10.1016/j.agrformet.2013.11.008, 2014.
Everitt, J. H., Escobar, D. E., and Noriega, J.: A high resolution multispectral video system, Geocarto Int., 6, 45–51, https://doi.org/10.1080/10106049109354339, 1991.
Faghmous, J. H. and Kumar, V.: A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science, Big Data, 2, 155–163, https://doi.org/10.1089/big.2014.0026, 2014.
Fekete, B. M., Looser, U., Pietroniro, A., and Robarts, R. D.: Rationale for Monitoring Discharge on the Ground, J. Hydrometeorol., 13, 1977–1986, https://doi.org/10.1175/jhm-d-11-0126.1, 2012.
Feng, Q., Liu, J., and Gong, J.: Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier – A Case of Yuyao, China, Water, 7, 1437–1455, 2015.
Fisher, J. B., Tu, K. P., and Baldocchi, D. D.: Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901–919, https://doi.org/10.1016/j.rse.2007.06.025, 2008.
Fleming, R. J.: The Use of Commercial Aircraft as Platforms for Environmental Measurements, B. Am. Meteorol. Soc., 77, 2229–2242, https://doi.org/10.1175/1520-0477(1996)077<2229:tuocaa>2.0.co;2, 1996.
Flying Aquila: Early lessons from the first full-scale test flight and the path ahead: https://code.facebook.com/posts/268598690180189, last access: 10 November 2016.
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
Franz, T. E., Wang, T., Avery, W., Finkenbiner, C., and Brocca, L.: Combined analysis of soil moisture measurements from roving and fixed cosmic ray neutron probes for multiscale real-time monitoring, Geophys. Res. Lett., 42, 3389–3396, https://doi.org/10.1002/2015GL063963, 2015.
Giardino, C., Brando, V. E., Dekker, A. G., Strömbeck, N., and Candiani, G.: Assessment of water quality in Lake Garda (Italy) using Hyperion, Remote Sens. Environ., 109, 183–195, https://doi.org/10.1016/j.rse.2006.12.017, 2007.
Gorelick, N.: Google Earth Engine, European Geophysical Union, 7–12 April 2013, Vienna, Austria, 2013.
Gosset, M., Kunstmann, H., Zougmore, F., Cazenave, F., Leijnse, H., Uijlenhoet, R., Chwala, C., Keis, F., Doumounia, A., Boubacar, B., Kacou, M., Alpert, P., Messer, H., Rieckermann, J., and Hoedjes, J.: Improving Rainfall Measurement in Gauge Poor Regions Thanks to Mobile Telecommunication Networks, B. Am. Meteorol. Soc., 97, ES49–ES51, https://doi.org/10.1175/bams-d-15-00164.1, 2016.
Green, R. O., Eastwood, M. L., Sarture, C. M., Chrien, T. G., Aronsson, M., Chippendale, B. J., Faust, J. A., Pavri, B. E., Chovit, C. J., Solis, M., Olah, M. R., and Williams, O.: Imaging spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Remote Sens. Environ., 65, 227–248, https://doi.org/10.1016/S0034-4257(98)00064-9, 1998.
Haddad, Z. S., Peral, E., Tanelli, S., Sy, O., and Stephens, G.: RaInCube: A proposed constellation of atmospheric profiling radars in cubesat, Proc. SPIE, 9876, 987606, https://doi.org/doi:10.1117/12.2228188, 2016.
Hall, D. K., Riggs, G. A., and Salomonson, V. V.: Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data, Remote Sens. Environ., 54, 127–140, https://doi.org/10.1016/0034-4257(95)00137-P, 1995.
Han, F., Zhang, Z., Wang, Z., Zhang, S., Liang, Y., and Chen, Y.: Real-time earth observation system based on Micro-Nano networks, Proceedings of the International Astronautical Congress, IAC, 12–16 October 2015, Jerusalem, Israel, 3271–3278, 2015.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., and Ullah Khan, S.: The rise of “big data” on cloud computing: Review and open research issues, Inform. Syst., 47, 98–115, https://doi.org/10.1016/j.is.2014.07.006, 2015.
Hauser, D., Glennie, C., and Brooks, B.: Calibration and accuracy analysis of a low-cost mapping-grade mobile laser scanning system, J. Surv. Eng., 142, 04016011, https://doi.org/10.1061/(ASCE)SU.1943-5428.0000178, 2016.
Heimann, M. and Reichstein, M.: Terrestrial ecosystem carbon dynamics and climate feedbacks, Nature, 451, 289–292, 2008.
Heistermann, M., Jacobi, S., and Pfaff, T.: Technical Note: An open source library for processing weather radar data (wradlib), Hydrol. Earth Syst. Sci., 17, 863–871, https://doi.org/10.5194/hess-17-863-2013, 2013.
Herrick, J. E., Karl, J. W., McCord, S. E., Buenemann, M., Riginos, C., Courtright, E., Van Zee, J., Ganguli, A. C., Angerer, J., Brown, J. R., Kimiti, D. W., Saltzman, R., Beh, A., and Bestelmeyer, B.: Two New Mobile Apps for Rangeland Inventory and Monitoring by Landowners and Land Managers, Rangelands, 39, 46–55, https://doi.org/10.1016/j.rala.2016.12.003, 2017.
Hevner, R., Puig-Suari, J., and Twiggs, R.: An advanced standard for CubeSats, in: Paper SSC11-II-13, 25th Annual AIAA/USU Conference on Small Satellites, Logan, UT, 2011.
Hidalgo, H. G., Das, T., Dettinger, M. D., Cayan, D. R., Pierce, D. W., Barnett, T. P., Bala, G., Mirin, A., Wood, A. W., Bonfils, C., Santer, B. D., and Nozawa, T.: Detection and attribution of streamflow timing changes to climate change in the Western United States, J. Climate, 22, 3838–3855, https://doi.org/10.1175/2009JCLI2470.1, 2009.
Hoffmann, H., Nieto, H., Jensen, R., Guzinski, R., Zarco-Tejada, P., and Friborg, T.: Estimating evaporation with thermal UAV data and two-source energy balance models, Hydrol. Earth Syst. Sci., 20, 697–713, https://doi.org/10.5194/hess-20-697-2016, 2016.
Houborg, R. and McCabe, M. F.: High-Resolution NDVI from Planet's Constellation of Earth Observing Nano-Satellites: A New Data Source for Precision Agriculture, Remote Sens., 8, 768, https://doi.org/10.3390/rs8090768, 2016.
Houborg, R., Fisher, J. B., and Skidmore, A. K.: Advances in remote sensing of vegetation function and traits, Int. J. Appl. Earth Obs. Geoinf., 43, 1–6, https://doi.org/10.1016/j.jag.2015.06.001, 2015.
Irons, J. R., Dwyer, J. L., and Barsi, J. A.: The next Landsat satellite: The Landsat Data Continuity Mission, Remote Sens. Environ., 122, 11–21, https://doi.org/10.1016/j.rse.2011.08.026, 2012.
Jana, R. B., Ershadi, A., and McCabe, M. F.: Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland, Hydrol. Earth Syst. Sci., 20, 3987–4004, https://doi.org/10.5194/hess-20-3987-2016, 2016.
Jasinski, M. F., Stoll, J. D., Cook, W. B., Ondrusek, M., Stengel, E., and Brunt, K.: Inland and Near-Shore Water Profiles Derived from the High-Altitude Multiple Altimeter Beam Experimental Lidar (MABEL), J. Coast. Res., 76, 44–55, https://doi.org/10.2112/si76-005, 2016.
Jha, S. K., Mariethoz, G., Evans, J. P., and McCabe, M. F.: Demonstration of a geostatistical approach to physically consistent downscaling of climate modeling simulations, Water Resour. Res., 49, 245–259, https://doi.org/10.1029/2012WR012602, 2013.
Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model, Biogeosciences, 6, 2001–2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
Kalma, J., McVicar, T., and McCabe, M.: Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data, Surv. Geophys., 29, 421–469, 2008.
Kidd, C.: Satellite rainfall climatology: a review, Int. J. Climatol., 21, 1041–1066, https://doi.org/10.1002/joc.635, 2001.
Kidd, C. and Huffman, G. J.: Global precipitation measurement, Meteorol. Appl., 18, 334–353, https://doi.org/10.1002/met.284, 2011.
Kimball, J. S., McDonald, K. C., Keyser, A. R., Frolking, S., and Running, S. W.: Application of the NASA Scatterometer (NSCAT) for Determining the Daily Frozen and Nonfrozen Landscape of Alaska, Remote Sens. Environ., 75, 113–126, https://doi.org/10.1016/S0034-4257(00)00160-7, 2001.
King, D. J.: Airborne multispectral digital camera and video sensors: A critical review of system designs and applications, Can. J. Remote Sens., 21, 245–273, https://doi.org/10.1080/07038992.1995.10874621, 1995.
Klemeš, V.: Dilettantism in hydrology: Transition or destiny?, Water Resour. Res., 22, 177S–188S, https://doi.org/10.1029/WR022i09Sp0177S, 1986.
Koch, J., Jensen, K. H., and Stisen, S.: Toward a true spatial model evaluation in distributed hydrological modeling: Kappa statistics, Fuzzy theory, and EOF-analysis benchmarked by the human perception and evaluated against a modeling case study, Water Resour. Res., 51, 1225–1246, https://doi.org/10.1002/2014WR016607, 2015.
Kursinski, E. R., Hajj, G. A., Schofield, J. T., Linfield, R. P., and Hardy, K. R.: Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System, J. Geophys. Res.-Atmos., 102, 23429–23465, https://doi.org/10.1029/97JD01569, 1997.
Lanfear, K. J. and Hirsch, R. M.: USGS study reveals a decline in long-record streamgages, Eos, 80, 605–607, https://doi.org/10.1029/99EO00406, 1999.
Larson, K. M., Small, E. E., Gutmann, E. D., Bilich, A. L., Braun, J. J., and Zavorotny, V. U.: Use of GPS receivers as a soil moisture network for water cycle studies, Geophys. Res. Lett., 35, L24405, https://doi.org/10.1029/2008GL036013, 2008.
Larson, K. M., Gutmann, E. D., Zavorotny, V. U., Braun, J. J., Williams, M. W., and Nievinski, F. G.: Can we measure snow depth with GPS receivers?, Geophys. Res. Lett., 36, L17502, https://doi.org/10.1029/2009GL039430, 2009.
Lary, D. J., Alavi, A. H., Gandomi, A. H., and Walker, A. L.: Machine learning in geosciences and remote sensing, Geosci. Front., 7, 3–10, https://doi.org/10.1016/j.gsf.2015.07.003, 2016.
Le Coz, J., Patalano, A., Collins, D., Guillén, N. F., García, C. M., Smart, G. M., Bind, J., Chiaverini, A., Le Boursicaud, R., Dramais, G., and Braud, I.: Crowdsourced data for flood hydrology: Feedback from recent citizen science projects in Argentina, France and New Zealand, J. Hydrol., 541, 766–777, https://doi.org/10.1016/j.jhydrol.2016.07.036, 2016.
Lee, Y. R., Shin, D. B., Kim, J. H., and Park, H. S.: Precipitation estimation over radar gap areas based on satellite and adjacent radar observations, Atmos. Meas. Tech., 8, 719–728, https://doi.org/10.5194/amt-8-719-2015, 2015.
Leijnse, H., Uijlenhoet, R., and Stricker, J. N. M.: Rainfall measurement using radio links from cellular communication networks, Water Resour. Res., 43, W03201, https://doi.org/10.1029/2006WR005631, 2007.
Lethbridge, M.: Precipitation probability and satellite radiation data, Mon. Weather Rev., 95, 487–490, https://doi.org/10.1175/1520-0493(1967)095<0487:ppasrd>2.3.co;2, 1967.
Lettenmaier, D. P., Alsdorf, D., Dozier, J., Huffman, G. J., Pan, M., and Wood, E. F.: Inroads of remote sensing into hydrologic science during the WRR era, Water Resour. Res., 51, 7309–7342, https://doi.org/10.1002/2015WR017616, 2015.
Li, F., Crow, W. T., and Kustas, W. P.: Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals, Adv. Water Resour., 33, 201–214, https://doi.org/10.1016/j.advwatres.2009.11.007, 2010.
Liu, L., Zhang, T., and Wahr, J.: InSAR measurements of surface deformation over permafrost on the North Slope of Alaska, J. Geophys. Res.-Earth Surf., 115, F03023, https://doi.org/10.1029/2009JF001547, 2010.
Liu, Y. Y., de Jeu, R. A. M., McCabe, M. F., Evans, J. P., and van Dijk, A. I. J. M.: Global long-term passive microwave satellite-based retrievals of vegetation optical depth, Geophys. Res. Lett., 38, L18402, https://doi.org/10.1029/2011GL048684, 2011a.
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, 2011b.
Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., De Jeu, R. A. M., Wagner, W., McCabe, M. F., Evans, J. P., and Van Dijk, A. I. J. M.: Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sens. Environ., 123, 280–297, 2012.
Liu, Y. Y., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P., and de Jeu, R. A. M.: Global vegetation biomass change (1988–2008) and attribution to environmental and human drivers, Global Ecol. Biogeogr., 22, 692–705, 2013.
Liu, Y. Y., Van Dijk, A. I. J. M., De Jeu, R. A. M., Canadell, J. G., McCabe, M. F., Evans, J. P., and Wang, G.: Recent reversal in loss of global terrestrial biomass, Nat. Clim. Change, 5, 470–474, https://doi.org/10.1038/nclimate2581, 2015.
López, O., Houborg, R., and McCabe, M. F.: Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data, Hydrol. Earth Syst. Sci., 21, 323–343, https://doi.org/10.5194/hess-21-323-2017, 2017.
Lorenz, C. and Kunstmann, H.: The hydrological cycle in three state-of-the-art reanalyses: Intercomparison and performance analysis, J. Hydrometeorol., 13, 1397–1420, https://doi.org/10.1175/JHM-D-11-088.1, 2012.
Mace, G. G., Zhang, Q., Vaughan, M., Marchand, R., Stephens, G., Trepte, C., and Winker, D.: A description of hydrometeor layer occurrence statistics derived from the first year of merged Cloudsat and CALIPSO data, J. Geophys. Res.-Atmos., 114, D00A26, https://doi.org/10.1029/2007JD009755, 2009.
McCabe, M. F., Franks, S. W., and Kalma, J. D.: Calibration of a land surface model using multiple data sets, J. Hydrol., 302, 209–222, https://doi.org/10.1016/j.jhydrol.2004.07.002, 2005.
McCabe, M. F., Wood, E. F., Wójcik, R., Pan, M., Sheffield, J., Gao, H., and Su, H.: Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies, Remote Sens. Environ., 112, 430–444, https://doi.org/10.1016/j.rse.2007.03.027, 2008.
McCabe, M. F., Ershadi, A., Jimenez, C., Miralles, D. G., Michel, D., and Wood, E. F.: The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data, Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, 2016.
McGuire, M. P., Roberge, M. C., and Lian, J.: HydroCloud: A cloud-based system for hydrologic data integration and analysis, in: Proceedings – 5th International Conference on Computing for Geospatial Research and Application, COM.Geo 2014, 4–6 August 2014, Washington, D.C., USA, 9–16, 2014.
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., Al Bitar, A., Walker, J. P., and Kerr, Y.: An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data, Remote Sens. Environ., 114, 2305–2316, https://doi.org/10.1016/j.rse.2010.05.007, 2010.
Meroni, M., Rossini, M., Guanter, L., Alonso, L., Rascher, U., Colombo, R., and Moreno, J.: Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications, Remote Sens. Environ., 113, 2037–2051, https://doi.org/10.1016/j.rse.2009.05.003, 2009.
Messer, H., Zinevich, A., and Alpert, P.: Environmental Monitoring by Wireless Communication Networks, Science, 312, 713, 2006.
Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman, A. J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrol. Earth Syst. Sci., 15, 967–981, https://doi.org/10.5194/hess-15-967-2011, 2011.
Miralles, D. G., van den Berg, M. J., Gash, J. H., Parinussa, R. M., de Jeu, R. A. M., Beck, H. E., Holmes, T. R. H., Jiménez, C., Verhoest, N. E. C., Dorigo, W. A., Teuling, A. J., and Johannes Dolman, A.: El Niño–La Niña cycle and recent trends in continental evaporation, Nat. Clim. Change, 4, 122–126, https://doi.org/10.1038/nclimate2068, 2014.
Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., McCabe, M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets, Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, 2016.
Mladenova, I. E., Jackson, T. J., Njoku, E., Bindlish, R., Chan, S., Cosh, M. H., Holmes, T. R. H., de Jeu, R. A. M., Jones, L., Kimball, J., Paloscia, S., and Santi, E.: Remote monitoring of soil moisture using passive microwave-based techniques — Theoretical basis and overview of selected algorithms for AMSR-E, Remote Sens. Environ., 144, 197–213, https://doi.org/10.1016/j.rse.2014.01.013, 2014.
Moghaddam, M., Rahmat-Samii, Y., Rodriguez, E., Entekhabi, D., Hoffman, J., Moller, D., Pierce, L. E., Saatchi, S., and Thomson, M.: Microwave Observatory of Subcanopy and Subsurface (MOSS): A Mission Concept for Global Deep Soil Moisture Observations, IEEE T. Geosci. Remote, 45, 2630–2643, https://doi.org/10.1109/TGRS.2007.898236, 2007.
Montzka, C., Bogena, H., Zreda, M., Monerris, A., Morrison, R., Muddu, S., and Vereecken, H.: Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes, Remote Sens., 9, 103, 2017.
Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I.: Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis, Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, 2013.
Muller, C. L., Chapman, L., Johnston, S., Kidd, C., Illingworth, S., Foody, G., Overeem, A., and Leigh, R. R.: Crowdsourcing for climate and atmospheric sciences: current status and future potential, Int. J. Climatol., 35, 3185–3203, https://doi.org/10.1002/joc.4210, 2015.
Müller, M. F., Yoon, J., Gorelick, S. M., Avisse, N., and Tilmant, A.: Impact of the Syrian refugee crisis on land use and transboundary freshwater resources, P. Natl. Acad. Sci. USA, 113, 14932–14937, 2016.
Murthy, K., Shearn, M., Smiley, B. D., Chau, A. H., Levine, J., and Robinson, M. D.: Skysat-1: Very high-resolution imagery from a small satellite, Proc. SPIE, 9241, 92411E, https://doi.org/10.1117/12.2074163, 2014.
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations, IEEE T. Geosci. Remote, 47, 1999–2013, https://doi.org/10.1109/TGRS.2008.2011617, 2009.
Nagy, G. and Nagy, G.: Digital image-processing activities in remote sensing for earth resources, Proc. IEEE, 60, 1177–1200, https://doi.org/10.1109/PROC.1972.8879, 1972.
NASA: CubeSat Launch Initiative, https://www.nasa.gov/directorates/heo/home/CubeSats_initiative/ (last access: 10 November 2016), 2016a.
NASA: Small Spacecraft Technology Program: https://www.nasa.gov/directorates/spacetech/small_spacecraft/index.html (last access: 10 November 2016), 2016b.
National Research Council: Earth Science and Applications From Space: National Imperatives for the Next Decade and Beyond, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, National Academies Press, Washington, D.C., 400 pp., 2007.
Niu, G.-Y., Seo, K.-W., Yang, Z.-L., Wilson, C., Su, H., Chen, J., and Rodell, M.: Retrieving snow mass from GRACE terrestrial water storage change with a land surface model, Geophys. Res. Lett., 34, L15704, https://doi.org/10.1029/2007GL030413, 2007.
Njoku, E. G. and Entekhabi, D.: Passive microwave remote sensing of soil moisture, J. Hydrol., 184, 101–129, 1996.
Njoku, E. G. and Li, L.: Retrieval of land surface parameters using passive microwave measurements at 6–18 GHz, IEEE T. Geosci. Remote, 37, 79–93, https://doi.org/10.1109/36.739125, 1999.
Nordberg, W.: Geophysical observations from Nimbus I, Science, 150, 559–572, 1965.
Ochoa-Rodriguez, S., Wang, L. P., Gires, A., Pina, R. D., Reinoso-Rondinel, R., Bruni, G., Ichiba, A., Gaitan, S., Cristiano, E., Van Assel, J., Kroll, S., Murlà-Tuyls, D., Tisserand, B., Schertzer, D., Tchiguirinskaia, I., Onof, C., Willems, P., and Ten Veldhuis, M. C.: Impact of spatial and temporal resolution of rainfall inputs on urban hydrodynamic modelling outputs: A multi-catchment investigation, J. Hydrol., 531, 389–407, https://doi.org/10.1016/j.jhydrol.2015.05.035, 2015.
Odermatt, D., Gitelson, A., Brando, V. E., and Schaepman, M.: Review of constituent retrieval in optically deep and complex waters from satellite imagery, Remote Sens. Environ., 118, 116–126, https://doi.org/10.1016/j.rse.2011.11.013, 2012.
Overeem, A., Leijnse, H., and Uijlenhoet, R.: Country-wide rainfall maps from cellular communication networks, P. Natl. Acad. Sci. USA, 110, 2741–2745, https://doi.org/10.1073/pnas.1217961110, 2013a.
Overeem, A., Robinson, J. C. R., Leijnse, H., Steeneveld, G. J., Horn, B. K. P., and Uijlenhoet, R.: Crowdsourcing urban air temperatures from smartphone battery temperatures, Geophys. Res. Lett., 40, 4081–4085, https://doi.org/10.1002/grl.50786, 2013b.
Overeem, A., Leijnse, H., and Uijlenhoet, R.: Two and a half years of country-wide rainfall maps using radio links from commercial cellular telecommunication networks, Water Resour. Res., 52, 8039-8065, https://doi.org/10.1002/2016WR019412, 2016.
Paloscia, S., Pettinato, S., Santi, E., Notarnicola, C., Pasolli, L., and Reppucci, A.: Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation, Remote Sens. Environ., 134, 234–248, https://doi.org/10.1016/j.rse.2013.02.027, 2013.
Pan, M., Cai, X., Chaney, N. W., Entekhabi, D., and Wood, E. F.: An initial assessment of SMAP soil moisture retrievals using high-resolution model simulations and in situ observations, Geophys. Res. Lett., 43, 9662–9668, https://doi.org/10.1002/2016GL069964, 2016.
Papagiannopoulou, C., Miralles, D. G., Decubber, S., Demuzere, M., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger-causality framework to investigate climate–vegetation dynamics, Geosci. Model Dev., 10, 1945–1960, https://doi.org/10.5194/gmd-10-1945-2017, 2017.
Petersen, R. A.: On the Impact and Benefits of AMDAR Observations in Operational Forecasting – Part I: A Review of the Impact of Automated Aircraft Wind and Temperature Reports, B. Am. Meteorol. Soc., 97, 585–602, https://doi.org/10.1175/bams-d-14-00055.1, 2016.
Peters-Lidard, C. D., Clark, M., Samaniego, L., Verhoest, N. E. C., van Emmerik, T., Uijlenhoet, R., Achieng, K., Franz, T. E., and Woods, R.: Scaling, similarity, and the fourth paradigm for hydrology, Hydrol. Earth Syst. Sci., 21, 3701–3713, https://doi.org/10.5194/hess-21-3701-2017, 2017.
Planet Team: Planet Application Program Interface: In Space for Life on Earth, San Francisco, CA, 2017.
Prata, A. J., Dezitter, F., Davies, I., Weber, K., Birnfeld, M., Moriano, D., Bernardo, C., Vogel, A., Prata, G. S., Mather, T. A., Thomas, H. E., Cammas, J., and Weber, M.: Artificial cloud test confirms volcanic ash detection using infrared spectral imaging, Scient. Rep., 6, 25620, https://doi.org/10.1038/srep25620, 2016.
Puig-Suari, J., Turner, C., and Ahlgren, W.: Development of the standard CubeSat deployer and a CubeSat class picosatellite, in: IEEE Aerospace Conference Proceedings, 10–17 March 2001, Big Sky, MO, USA, 1347–1353, 2001.
Rabiei, E., Haberlandt, U., Sester, M., Fitzner, D., and Wallner, M.: Areal rainfall estimation using moving cars – computer experiments including hydrological modeling, Hydrol. Earth Syst. Sci., 20, 3907–3922, https://doi.org/10.5194/hess-20-3907-2016, 2016.
Rasouli, K., Hsieh, W. W., and Cannon, A. J.: Daily streamflow forecasting by machine learning methods with weather and climate inputs, J. Hydrol., 414–415, 284–293, https://doi.org/10.1016/j.jhydrol.2011.10.039, 2012.
Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A., Ikonen, J., Derksen, C., Davydov, S., Davydova, A., Boike, J., Langer, M., Drusch, M., and Pulliainen, J.: SMOS prototype algorithm for detecting autumn soil freezing, Remote Sens. Environ., 180, 346–360, https://doi.org/10.1016/j.rse.2016.01.012, 2016.
Reges, H. W., Doesken, N., Turner, J., Newman, N., Bergantino, A., and Schwalbe, Z.: CoCoRaHS: The Evolution and Accomplishments of a Volunteer Rain Gauge Network, B. Am. Meteorol. Soc., 97, 1831–1846, https://doi.org/10.1175/BAMS-D-14-00213.1, 2016.
Reichle, R. H., Koster, R. D., Liu, P., Mahanama, S. P. P., Njoku, E. G., and Owe, M.: Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR), J. Geophys. Res.-Atmos., 112, D09108, https://doi.org/10.1029/2006JD008033, 2007.
Rios Gaona, M. F., Overeem, A., Leijnse, H., and Uijlenhoet, R.: First-year evaluation of GPM rainfall over the Netherlands: IMERG day 1 final run (V03D), J. Hydrometeorol., 17, 2799–2814, https://doi.org/10.1175/JHM-D-16-0087.1, 2016.
Roberts, D. A., Quattrochi, D. A., Hulley, G. C., Hook, S. J., and Green, R. O.: Synergies between VSWIR and TIR data for the urban environment: An evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) Decadal Survey mission, Remote Sens. Environ., 117, 83–101, https://doi.org/10.1016/j.rse.2011.07.021, 2012.
Rodell, M. and Famiglietti, J. S.: Detectability of variations in continental water storage from satellite observations of the time dependent gravity field, Water Resour. Res., 35, 2705–2723, https://doi.org/10.1029/1999WR900141, 1999.
Rodell, M., Chen, J., Kato, H., Famiglietti, J. S., Nigro, J., and Wilson, C. R.: Estimating groundwater storage changes in the Mississippi River basin (USA) using GRACE, Hydrogeol. J., 15, 159-166, 10.1007/s10040-006-0103-7, 2007.
Rodríguez-Fernández, N., Kerr, Y., van der Schalie, R., Al-Yaari, A., Wigneron, J.-P., de Jeu, R., Richaume, P., Dutra, E., Mialon, A., and Drusch, M.: Long Term Global Surface Soil Moisture Fields Using an SMOS-Trained Neural Network Applied to AMSR-E Data, Remote Sens., 8, 959, 2016.
Roy, D. P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M., and Lindquist, E.: Multi-temporal MODIS–Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data, Remote Sens. Environ., 112, 3112–3130, https://doi.org/10.1016/j.rse.2008.03.009, 2008.
Sabel, D., Bartsch, A., Schlaffer, S., Klein, J. P., and Wagner, W.: Soil moisture mapping in permafrost regions – An outlook to Sentinel-1, in: 2012 IEEE International Geoscience and Remote Sensing Symposium, 22–27 July 2012, Munich, Germany, 1216–1219, 2012.
Sanchez, P. A., Ahamed, S., Carré, F., Hartemink, A. E., Hempel, J., Huising, J., Lagacherie, P., McBratney, A. B., McKenzie, N. J., Mendonça-Santos, M. D. L., Minasny, B., Montanarella, L., Okoth, P., Palm, C. A., Sachs, J. D., Shepherd, K. D., Vågen, T.-G., Vanlauwe, B., Walsh, M. G., Winowiecki, L. A., and Zhang, G.-L.: Digital Soil Map of the World, Science, 325, 680–681, https://doi.org/10.1126/science.1175084, 2009.
Schmugge, T. J., Kustas, W. P., Ritchie, J. C., Jackson, T. J., and Rango, A.: Remote sensing in hydrology, Adv. Water Resour., 25, 1367–1385, https://doi.org/10.1016/S0309-1708(02)00065-9, 2002.
Selva, D. and Krejci, D.: A survey and assessment of the capabilities of Cubesats for Earth observation, Acta Astronaut., 74, 50–68, https://doi.org/10.1016/j.actaastro.2011.12.014, 2012.
Sharman, R. D., Cornman, L. B., Meymaris, G., Pearson, J., and Farrar, T.: Description and Derived Climatologies of Automated In Situ Eddy-Dissipation-Rate Reports of Atmospheric Turbulence, J. Appl. Meteorol. Clim., 53, 1416–1432, https://doi.org/10.1175/jamc-d-13-0329.1, 2014.
Shaw, J. A., Nugent, P. W., Kaufman, N. A., Pust, N. J., Mikes, D., Knierim, C., Faulconer, N., Larimer, R. M., Desjardins, A. C., and Knighton, W. B.: Multispectral imaging systems on tethered balloons for optical remote sensing education and research, J. Appl. Remote Sens., 6, 063613, https://doi.org/10.1117/1.JRS.6.063613, 2012.
Sheffield, J., Ferguson, C. R., Troy, T. J., Wood, E. F., and McCabe, M. F.: Closing the terrestrial water budget from satellite remote sensing, Geophys. Res. Lett., 36, L07403, https://doi.org/10.1029/2009GL037338, 2009.
Shiklomanov, A. I., Lammers, R. B., and Vörösmarty, C. J.: Widespread decline in hydrological monitoring threatens Pan-Arctic research, Eos, 83, 13–17, 2002.
Small, E. E., Larson, K. M., and Braun, J. J.: Sensing vegetation growth with reflected GPS signals, Geophys. Res. Lett., 37, L12401, https://doi.org/10.1029/2010GL042951, 2010.
Solar Explorer 2: Solar Impulse 2 completes chemistry world tour: TCE The Chemical Engineer, Institution of Chemical Engineers, 13 pp., 2016.
Stahl, K., Hisdal, H., Hannaford, J., Tallaksen, L. M., van Lanen, H. A. J., Sauquet, E., Demuth, S., Fendekova, M., and Jódar, J.: Streamflow trends in Europe: evidence from a dataset of near-natural catchments, Hydrol. Earth Syst. Sci., 14, 2367–2382, https://doi.org/10.5194/hess-14-2367-2010, 2010.
Steiner, M., Smith, J. A., Burges, S. J., Alonso, C. V., and Darden, R. W.: Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation, Water Resour. Res., 35, 2487–2503, https://doi.org/10.1029/1999WR900142, 1999.
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z., Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., and Mitrescu, C.: The cloudsat mission and the A-Train: A new dimension of space-based observations of clouds and precipitation, B. Am. Meteorol. Soc., 83, 1771–1790, 2002.
Stisen, S., McCabe, M. F., Refsgaard, J. C., Lerer, S., and Butts, M. B.: Model parameter analysis using remotely sensed pattern information in a multi-constraint framework, J. Hydrol., 409, 337–349, 2011.
Su, C.-H., Ryu, D., Dorigo, W., Zwieback, S., Gruber, A., Albergel, C., Reichle, R. H., and Wagner, W.: Homogeneity of a global multisatellite soil moisture climate data record, Geophys. Res. Lett., 43, 11245–11252, https://doi.org/10.1002/2016GL070458, 2016.
Swenson, S., Wahr, J., and Milly, P. C. D.: Estimated accuracies of regional water storage variations inferred from the Gravity Recovery and Climate Experiment (GRACE), Water Resour. Res., 39, 1223, https://doi.org/10.1029/2002WR001808, 2003.
Tang, Q., Gao, H., Lu, H., and Lettenmaier, D. P.: Remote sensing: Hydrology, Prog. Phys. Geogr., 33, 490–509, https://doi.org/10.1177/0309133309346650, 2009.
Tapley, B. D., Bettadpur, S., Ries, J. C., Thompson, P. F., and Watkins, M. M.: GRACE measurements of mass variability in the Earth system, Science, 305, 503–505, 2004.
Tollefson, J.: Race to provide commercial weather data heats up, Nature, 542, 18, https://doi.org/10.1038/542018a, 2017.
Townshend, J. R. G.: The spatial resolving power of earth resources satellites, Prog. Phys. Geogr., 5, 32–55, https://doi.org/10.1177/030913338100500102, 1981.
Turner, D., Lucieer, A., and Watson, C.: An automated technique for generating georectified mosaics from ultra-high resolution Unmanned Aerial Vehicle (UAV) imagery, based on Structure from Motion (SFM) point clouds, Remote Sens., 4, 1392–1410, https://doi.org/10.3390/rs4051392, 2012.
van de Giesen, N., Hut, R., and Selker, J.: The Trans-African Hydro-Meteorological Observatory (TAHMO), Wiley Interdisc. Rev. Water, 1, 341–348, https://doi.org/10.1002/wat2.1034, 2014.
Vander Jagt, B., Lucieer, A., Wallace, L., Turner, D., and Durand, M.: Snow Depth Retrieval with UAS Using Photogrammetric Techniques, Geosciences, 5, 264–285, 2015.
van Vliet, M. T. H., Franssen, W. H. P., Yearsley, J. R., Ludwig, F., Haddeland, I., Lettenmaier, D. P., and Kabat, P.: Global river discharge and water temperature under climate change, Global Environ. Change, 23, 450–464, https://doi.org/10.1016/j.gloenvcha.2012.11.002, 2013.
Vaughan, W. W. and Johnson, D. L.: Meteorological Satellites – The Very Early Years Prior to Launch of TIROS-1, B. Am. Meteorol. Soc., 75, 2295–2302, https://doi.org/10.1175/1520-0477(1994)075<2295:MSVEYP>2.0.CO;2, 1994.
Vierling, L. A., Fersdahl, M., Chen, X., Li, Z., and Zimmerman, P.: The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon, Remote Sens. Environ., 103, 255–264, https://doi.org/10.1016/j.rse.2005.01.021, 2006.
Villien, A., Pedersen, G., Charvet, P., and Maliet, E.: Geostationary observation space surveillance system (GO3S) – Real time video from space, in: Proceedings of the International Astronautical Congress, IAC, 29 September–3 October 2014, Toronto, Canada, 2460–2464, 2014.
Vivoni, E. R., Rango, A., Anderson, C. A., Pierini, N. A., Schreiner-Mcgraw, A. P., Saripalli, S., and Laliberte, A. S.: Ecohydrology with unmanned aerial vehicles, Ecosphere, 5, 130, https://doi.org/10.1890/ES14-00217.1, 2014.
Wagner, W., Naeimi, V., Scipal, K., de Jeu, R., and Martínez-Fernández, J.: Soil moisture from operational meteorological satellites, Hydrogeol. J., 15, 121–131, https://doi.org/10.1007/s10040-006-0104-6, 2007.
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S., Figa-Saldaña, J., De Rosnay, P., Jann, A., Schneider, S., Komma, J., Kubu, G., Brugger, K., Aubrecht, C., Züger, J., Gangkofner, U., Kienberger, S., Brocca, L., Wang, Y., Blöschl, G., Eitzinger, J., Steinnocher, K., Zeil, P., and Rubel, F.: The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications, Meteorol. Z., 22, 5–33, https://doi.org/10.1127/0941-2948/2013/0399, 2013.
Wagner, W., Fröhlich, J., Wotawa, G., Stowasser, R., Staudinger, M., Hoffmann, C., Walli, A., Federspiel, C., Aspetsberger, M., Atzberger, C., Briese, C., Notarnicola, C., Zebisch, M., Boresch, A., Enenkel, M., Kidd, R., von Beringe, A., Hasenauer, S., Naeimi, V., and Mücke, W.: Addressing Grand Challenges in Earth Observation Science: The Earth Observation Data Centre for Water Resources Monitoring, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-7, 81–88, https://doi.org/10.5194/isprsannals-II-7-81-2014, 2014.
Wang, K. and Dickinson, R. E.: A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability, Rev. Geophys., 50, RG2005, https://doi.org/10.1029/2011rg000373, 2012.
Warren, M. S., Brumby, S. P., Skillman, S. W., Kelton, T., Wohlberg, B., Mathis, M., Chartrand, R., Keisler, R., and Johnson, M.: Seeing the Earth in the Cloud: Processing one petabyte of satellite imagery in one day, in: 2015 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 14–16 October 2014, Washington, D.C., USA, 1–12, 2015.
Whitehead, P. G., Wilby, R. L., Battarbee, R. W., Kernan, M., and Wade, A. J.: A review of the potential impacts of climate change on surface water quality, Hydrolog. Sci. J., 54, 101–123, https://doi.org/10.1623/hysj.54.1.101, 2009.
Woellert, K., Ehrenfreund, P., Ricco, A. J., and Hertzfeld, H.: Cubesats: Cost-effective science and technology platforms for emerging and developing nations, Adv. Space Res., 47, 663–684, https://doi.org/10.1016/j.asr.2010.10.009, 2011.
Woo, M. K., Kane, D. L., Carey, S. K., and Yang, D.: Progress in permafrost hydrology in the new millennium, Permafrost Periglac. Process., 19, 237–254, https://doi.org/10.1002/ppp.613, 2008.
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, Water Resour. Res., 47, W05301, https://doi.org/10.1029/2010WR010090, 2011.
Wulder, M. A., White, J. C., Goward, S. N., Masek, J. G., Irons, J. R., Herold, M., Cohen, W. B., Loveland, T. R., and Woodcock, C. E.: Landsat continuity: Issues and opportunities for land cover monitoring, Remote Sens. Environ., 112, 955–969, https://doi.org/10.1016/j.rse.2007.07.004, 2008.
Wyche, S. and Steinfield, C.: Why Don't Farmers Use Cell Phones to Access Market Prices? Technology Affordances and Barriers to Market Information Services Adoption in Rural Kenya, Inform. Technol. Dev., 22, 320–333, https://doi.org/10.1080/02681102.2015.1048184, 2016.
Zacharias, S., Bogena, H., Samaniego, L., Mauder, M., Fuß, R., Pütz, T., Frenzel, M., Schwank, M., Baessler, C., Butterbach-Bahl, K., Bens, O., Borg, E., Brauer, A., Dietrich, P., Hajnsek, I., Helle, G., Kiese, R., Kunstmann, H., Klotz, S., Munch, J. C., Papen, H., Priesack, E., Schmid, H. P., Steinbrecher, R., Rosenbaum, U., Teutsch, G., and Vereecken, H.: A network of terrestrial environmental observatories in Germany, Vadose Zone J., 10, 955–973, https://doi.org/10.2136/vzj2010.0139, 2011.
Zaitchik, B. F., Rodell, M., and Reichle, R. H.: Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin, J. Hydrometeorol., 9, 535–548, https://doi.org/10.1175/2007jhm951.1, 2008.
Zarco-Tejada, P. J., González-Dugo, V., and Berni, J. A. J.: Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera, Remote Sens. Environ., 117, 322–337, https://doi.org/10.1016/j.rse.2011.10.007, 2012.
Zarco-Tejada, P. J., Guillén-Climent, M. L., Hernández-Clemente, R., Catalina, A., González, M. R., and Martín, P.: Estimating leaf carotenoid content in vineyards using high resolution hyperspectral imagery acquired from an unmanned aerial vehicle (UAV), Agr. Forest Meteorol., 171–172, 281–294, https://doi.org/10.1016/j.agrformet.2012.12.013, 2013.
Zhang, C. and Kovacs, J. M.: The application of small unmanned aerial systems for precision agriculture: a review, Precision Agric., 13, 693–712, https://doi.org/10.1007/s11119-012-9274-5, 2012.
Zhang, K., Kimball, J. S., and Running, S. W.: A review of remote sensing based actual evapotranspiration estimation, Wiley Interdisciplin. Rev. Water, 3, 834–853, https://doi.org/10.1002/wat2.1168, 2016.
Zhang, Y., Pan, M., and Wood, E. F.: On Creating Global Gridded Terrestrial Water Budget Estimates from Satellite Remote Sensing, Surv. Geophys., 37, 249–268, https://doi.org/10.1007/s10712-015-9354-y, 2016a.
Zhang, Y., Peña-Arancibia, J. L., McVicar, T. R., Chiew, F. H. S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y. Y., Miralles, D. G., and Pan, M.: Multi-decadal trends in global terrestrial evapotranspiration and its components, Scient. Rep., 6, 19124, https://doi.org/10.1038/srep19124, 2016b.
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012.
Zuckerberg: Technology behind Aquila, https://www.facebook.com/notes/mark-zuckerberg/the-technology-behind-aquila/10153916136506634/, last access: 10 November 2016.
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.
We examine the opportunities and challenges that technological advances in Earth observation...
