Articles | Volume 20, issue 10
https://doi.org/10.5194/hess-20-4191-2016
© Author(s) 2016. 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-20-4191-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
17 Oct 2016
Research article |
| 17 Oct 2016
Combining satellite observations to develop a global soil moisture product for near-real-time applications
Markus Enenkel
CORRESPONDING AUTHOR
Vienna University of Technology, Department of Geodesy and Geoinformation, Vienna, Austria
Columbia University, International Research Institute for Climate and Society, New York, NY, USA
Christoph Reimer
Vienna University of Technology, Department of Geodesy and Geoinformation, Vienna, Austria
Wouter Dorigo
Vienna University of Technology, Department of Geodesy and Geoinformation, Vienna, Austria
Wolfgang Wagner
Vienna University of Technology, Department of Geodesy and Geoinformation, Vienna, Austria
Isabella Pfeil
Vienna University of Technology, Department of Geodesy and Geoinformation, Vienna, Austria
Robert Parinussa
UNSW Water Research Centre, School of Civil and Environmental Engineering, The University of New South Wales, Sydney, Australia
VanderSat B.V., Noordwijk, the Netherlands
Richard De Jeu
VanderSat B.V., Noordwijk, the Netherlands
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EGUsphere, https://doi.org/10.5194/egusphere-2025-1489, https://doi.org/10.5194/egusphere-2025-1489, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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An improved understanding of land-atmosphere coupling processes during flash (rapid-onset) droughts is needed to aid the development of forecasts for these events. We use satellite observations to investigate the surface energy budget during flash droughts globally. The most intense events show a perturbed surface energy budget months before onset. In some regions, vegetation observations 1–2 months before onset provide information on the likelihood of heat extremes during an event.
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Hydrol. Earth Syst. Sci., 29, 397–425, https://doi.org/10.5194/hess-29-397-2025, https://doi.org/10.5194/hess-29-397-2025, 2025
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We investigate the potential of long-term satellite and reanalysis products for characterising soil drying by analysing their 2000–2022 soil moisture trends and their representation of agroecological drought events of this period. Soil moisture trends are globally diverse and partly contradictory between products. This also affects the products' drought-detection capacity. Based on the best-estimate products, consistent soil drying is observed over more than 40 % of the land area covered.
Wolfgang Preimesberger, Pietro Stradiotti, and Wouter Dorigo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-610, https://doi.org/10.5194/essd-2024-610, 2025
Revised manuscript under review for ESSD
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Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
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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
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
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We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
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
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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.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
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
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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.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
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Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
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The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
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The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
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
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
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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.
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
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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.
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
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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.
Rui Tong, Juraj Parajka, Borbála Széles, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Jürgen Komma, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, https://doi.org/10.5194/hess-26-1779-2022, 2022
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The role and impact of using additional data (other than runoff) for the prediction of daily hydrographs in ungauged basins are not well understood. In this study, we assessed the model performance in terms of runoff, soil moisture, and snow cover predictions with the existing regionalization approaches. Results show that the best transfer methods are the similarity and the kriging approaches. The performance of the transfer methods differs between lowland and alpine catchments.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
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Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
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
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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.
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
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
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Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
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
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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.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
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
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
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We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Angelika Xaver, Luca Zappa, Gerhard Rab, Isabella Pfeil, Mariette Vreugdenhil, Drew Hemment, and Wouter Arnoud Dorigo
Geosci. Instrum. Method. Data Syst., 9, 117–139, https://doi.org/10.5194/gi-9-117-2020, https://doi.org/10.5194/gi-9-117-2020, 2020
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Soil moisture plays a key role in the hydrological cycle and the climate system. Although soil moisture can be observed by the means of satellites, ground observations are still crucial for evaluating and improving these satellite products. In this study, we investigate the performance of a consumer low-cost soil moisture sensor in the lab and in the field. We demonstrate that this sensor can be used for scientific applications, for example to create a dataset valuable for satellite validation.
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
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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.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
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Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
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
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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.
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
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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.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
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About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
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Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner
Earth Syst. Sci. Data, 10, 267–280, https://doi.org/10.5194/essd-10-267-2018, https://doi.org/10.5194/essd-10-267-2018, 2018
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In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
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Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
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LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
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
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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.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
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This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon 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
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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
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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.
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
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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. J. E. van Marle, G. R. van der Werf, R. A. M. de Jeu, and Y. Y. Liu
Biogeosciences, 13, 609–624, https://doi.org/10.5194/bg-13-609-2016, https://doi.org/10.5194/bg-13-609-2016, 2016
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We have quantified large-scale forest loss over a 21-year period (1990–2010) in the tropical biomes of South America using a new satellite-based data set. We found that South American forest exhibited interannual variability without a clear trend during the 1990s, but increased from 2000 to 2004. After 2004, forest loss decreased again, mainly as a result of a decrease in the Brazilian Amazon, whereas at the same time regions south of the arc of deforestation showed an increase in forest loss.
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
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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.
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
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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.
C. Szczypta, J.-C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais
Geosci. Model Dev., 7, 931–946, https://doi.org/10.5194/gmd-7-931-2014, https://doi.org/10.5194/gmd-7-931-2014, 2014
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
Related subject area
Subject: Water Resources Management | Techniques and Approaches: Remote Sensing and GIS
Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin
The development of an operational system for estimating irrigation water use reveals socio-political dynamics in Ukraine
An inter-comparison of approaches and frameworks to quantify irrigation from satellite data
The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators
Technical note: NASAaccess – a tool for access, reformatting, and visualization of remotely sensed earth observation and climate data
Monitoring the combined effects of drought and salinity stress on crops using remote sensing in the Netherlands
A framework for irrigation performance assessment using WaPOR data: the case of a sugarcane estate in Mozambique
Satellite observations reveal 13 years of reservoir filling strategies, operating rules, and hydrological alterations in the Upper Mekong River basin
Satellite soil moisture data assimilation for improved operational continental water balance prediction
Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach
Multi-constellation GNSS interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring
Can we trust remote sensing evapotranspiration products over Africa?
Influence of multi-decadal land use, irrigation practices and climate on riparian corridors across the Upper Missouri River headwaters basin, Montana
Developing GIS-based water poverty and rainwater harvesting suitability maps for domestic use in the Dead Sea region (West Bank, Palestine)
Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels
Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data
A conceptual model of organochlorine fate from a combined analysis of spatial and mid- to long-term trends of surface and ground water contamination in tropical areas (FWI)
Spatio-temporal assessment of annual water balance models for upper Ganga Basin
Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin
Wetlands inform how climate extremes influence surface water expansion and contraction
Participatory flood vulnerability assessment: a multi-criteria approach
Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas
Performance of the METRIC model in estimating evapotranspiration fluxes over an irrigated field in Saudi Arabia using Landsat-8 images
The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets
A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval
Effect of the revisit interval and temporal upscaling methods on the accuracy of remotely sensed evapotranspiration estimates
Downstream ecosystem responses to middle reach regulation of river discharge in the Heihe River Basin, China
Supplemental irrigation potential and impact on downstream flow of Karkheh River basin in Iran
Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes
Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data
Spatial evapotranspiration, rainfall and land use data in water accounting – Part 2: Reliability of water acounting results for policy decisions in the Awash Basin
Combining high-resolution satellite images and altimetry to estimate the volume of small lakes
Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications
A new stream and nested catchment framework for Australia
GRACE water storage estimates for the Middle East and other regions with significant reservoir and lake storage
An original interpretation of the wet edge of the surface temperature–albedo space to estimate crop evapotranspiration (SEB-1S), and its validation over an irrigated area in northwestern Mexico
Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations
Regional effects of vegetation restoration on water yield across the Loess Plateau, China
Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks
Accounting for seasonality in a soil moisture change detection algorithm for ASAR Wide Swath time series
Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia
Extension of the Hapke bidirectional reflectance model to retrieve soil water content
Estimating river discharge from earth observation measurements of river surface hydraulic variables
Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops
Mapping surface soil moisture over the Gourma mesoscale site (Mali) by using ENVISAT ASAR data
Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation
Particular uncertainties encountered in using a pre-packaged SEBS model to derive evapotranspiration in a heterogeneous study area in South Africa
Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR
Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region
Identification and mapping of soil erosion areas in the Blue Nile, Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model
Devi Purnamasari, Adriaan J. Teuling, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 29, 1483–1503, https://doi.org/10.5194/hess-29-1483-2025, https://doi.org/10.5194/hess-29-1483-2025, 2025
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This paper introduces a method to identify irrigated areas by combining hydrology models with satellite temperature data. Our method was tested in the Rhine basin and aligns well with official statistics. It performs best in regions with large farms and less well in areas with small farms. Observed differences to existing data are influenced by data resolution and methods.
Jacopo Dari, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 28, 2651–2659, https://doi.org/10.5194/hess-28-2651-2024, https://doi.org/10.5194/hess-28-2651-2024, 2024
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We have developed the first operational system (10 d latency) for estimating irrigation water use from accessible satellite and reanalysis data. As a proof of concept, the method has been implemented over an irrigated area fed by the Kakhovka Reservoir, in Ukraine, which collapsed on June 6, 2023. Estimates for the period 2015–2023 reveal that, as expected, the irrigation season of 2023 was characterized by the lowest amounts of irrigation.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
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This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
Meghan Halabisky, Dan Miller, Anthony J. Stewart, Amy Yahnke, Daniel Lorigan, Tate Brasel, and Ludmila Monika Moskal
Hydrol. Earth Syst. Sci., 27, 3687–3699, https://doi.org/10.5194/hess-27-3687-2023, https://doi.org/10.5194/hess-27-3687-2023, 2023
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Accurate wetland inventories are critical to monitor and protect wetlands. However, in many areas a large proportion of wetlands are unmapped because they are hard to detect in imagery. We developed a machine learning approach using spatially mapped variables of wetland indicators (i.e., vegetation, hydrology, soils), including novel multi-scale topographic indicators, to predict wetland probability. Our approach can be adapted to diverse landscapes to improve wetland detection.
Ibrahim Nourein Mohammed, Elkin Giovanni Romero Bustamante, John Dennis Bolten, and Everett James Nelson
Hydrol. Earth Syst. Sci., 27, 3621–3642, https://doi.org/10.5194/hess-27-3621-2023, https://doi.org/10.5194/hess-27-3621-2023, 2023
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We present an open-source platform in response to the NASA Open-Source Science Initiative for accessing and presenting quantitative remote-sensing earth observation,and climate data. With our platform scientists, stakeholders and concerned citizens can engage in the exploration, modeling, and understanding of data. We envisioned this platform as lowering the technical barriers and simplifying the process of accessing and leveraging additional modeling frameworks for data.
Wen Wen, Joris Timmermans, Qi Chen, and Peter M. van Bodegom
Hydrol. Earth Syst. Sci., 26, 4537–4552, https://doi.org/10.5194/hess-26-4537-2022, https://doi.org/10.5194/hess-26-4537-2022, 2022
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A novel approach for evaluating individual and combined impacts of drought and salinity in real-life settings is proposed using Sentinel-2. We found that crop responses to drought and salinity differ between growth stages. Compared to salinity, crop growth is most strongly affected by drought stress and is, in general, further exacerbated when co-occurring with salinity stress. Our approach facilitates a way to monitor crop health under multiple stresses with potential large-scale applications.
Abebe D. Chukalla, Marloes L. Mul, Pieter van der Zaag, Gerardo van Halsema, Evaristo Mubaya, Esperança Muchanga, Nadja den Besten, and Poolad Karimi
Hydrol. Earth Syst. Sci., 26, 2759–2778, https://doi.org/10.5194/hess-26-2759-2022, https://doi.org/10.5194/hess-26-2759-2022, 2022
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New techniques to monitor the performance of irrigation schemes are vital to improve land and water productivity. We developed a framework and applied the remotely sensed FAO WaPOR dataset to assess uniformity, equity, adequacy, and land and water productivity at the Xinavane sugarcane estate, segmented by three irrigation methods. The developed performance assessment framework and the Python script in Jupyter Notebooks can aid in such irrigation performance analysis in other regions.
Dung Trung Vu, Thanh Duc Dang, Stefano Galelli, and Faisal Hossain
Hydrol. Earth Syst. Sci., 26, 2345–2364, https://doi.org/10.5194/hess-26-2345-2022, https://doi.org/10.5194/hess-26-2345-2022, 2022
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The lack of data on how big dams are operated in the Upper Mekong, or Lancang, largely contributes to the ongoing controversy between China and the other Mekong countries. Here, we rely on satellite observations to reconstruct monthly storage time series for the 10 largest reservoirs in the Lancang. Our analysis shows how quickly reservoirs were filled in, what decisions were made during recent droughts, and how these decisions impacted downstream discharge.
Siyuan Tian, Luigi J. Renzullo, Robert C. Pipunic, Julien Lerat, Wendy Sharples, and Chantal Donnelly
Hydrol. Earth Syst. Sci., 25, 4567–4584, https://doi.org/10.5194/hess-25-4567-2021, https://doi.org/10.5194/hess-25-4567-2021, 2021
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Accurate daily continental water balance predictions are valuable in monitoring and forecasting water availability and land surface conditions. A simple and robust method was developed for an operational water balance model to constrain model predictions temporally and spatially with satellite soil moisture observations. The improved soil water storage prediction can provide constraints in model forecasts that persist for several weeks.
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
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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.
Angel Martín, Sara Ibáñez, Carlos Baixauli, Sara Blanc, and Ana Belén Anquela
Hydrol. Earth Syst. Sci., 24, 3573–3582, https://doi.org/10.5194/hess-24-3573-2020, https://doi.org/10.5194/hess-24-3573-2020, 2020
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In the case study presented in this paper, the GNSS-IR technique was used to monitor soil moisture during 66 d, from 3 December 2018 to 6 February 2019, in the installations of the Cajamar Centre of Experiences, Paiporta, Valencia, Spain. Two main objectives were pursued. The first was the extension of the technique to a multi-constellation solution using GPS, GLONASS, and GALILEO satellites, and the second was to test whether mass-market sensors could be used for this technique.
Imeshi Weerasinghe, Wim Bastiaanssen, Marloes Mul, Li Jia, and Ann van Griensven
Hydrol. Earth Syst. Sci., 24, 1565–1586, https://doi.org/10.5194/hess-24-1565-2020, https://doi.org/10.5194/hess-24-1565-2020, 2020
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Water resource allocation to various sectors requires an understanding of the hydrological cycle, where evapotranspiration (ET) is a key component. Satellite-derived products estimate ET but are hard to evaluate at large scales. This work presents an alternate evaluation methodology to point-scale observations in Africa. The paper enables users to select an ET product based on their performance regarding selected criteria using a ranking system. The highest ranked products are WaPOR and CMRSET.
Melanie K. Vanderhoof, Jay R. Christensen, and Laurie C. Alexander
Hydrol. Earth Syst. Sci., 23, 4269–4292, https://doi.org/10.5194/hess-23-4269-2019, https://doi.org/10.5194/hess-23-4269-2019, 2019
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We evaluated trends (1984–2016) in riparian wetness across the Upper Missouri River headwaters basin during peak irrigation months (June, July and August). We found that 8 of the 19 riparian reaches across the basin showed a significant drying trend from 1984 to 2016. The temporal drying trends persisted after removing variability attributable to climate. Instead, the drying trends co-occurred with a shift towards center-pivot irrigation across the basin.
Sameer M. Shadeed, Tariq G. Judeh, and Mohammad N. Almasri
Hydrol. Earth Syst. Sci., 23, 1581–1592, https://doi.org/10.5194/hess-23-1581-2019, https://doi.org/10.5194/hess-23-1581-2019, 2019
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The paper aimed to develop DWP and DRWHS maps in the West Bank (Palestine) using an integrated GIS-based MCDA approach. The obtained maps will assist the decision makers to formulate proper strategies including the development of efficient and comprehensive water resource management strategies in trying to bridge the increasing water supply–demand gap for domestic purposes in the West Bank as a recognized area in the Dead Sea region which is facing a series water resource shortage challenges.
Fugen Li, Xiaozhou Xin, Zhiqing Peng, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 23, 949–969, https://doi.org/10.5194/hess-23-949-2019, https://doi.org/10.5194/hess-23-949-2019, 2019
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This study proposes a simple but efficient model for estimating daily evapotranspiration considering heterogeneity of mixed pixels. In order to do so, an equation to calculate evapotranspiration fraction (EF) of mixed pixels was derived based on two key hypotheses. The model is easy to apply and is independent and easy to be embedded in the traditional remote sensing algorithms of heat fluxes to get daily ET.
Felix Zaussinger, Wouter Dorigo, Alexander Gruber, Angelica Tarpanelli, Paolo Filippucci, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 897–923, https://doi.org/10.5194/hess-23-897-2019, https://doi.org/10.5194/hess-23-897-2019, 2019
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About 70 % of global freshwater is consumed by irrigation. Yet, policy-relevant estimates of irrigation water use (IWU) are virtually lacking at regional to global scales. To bridge this gap, we develop a method for quantifying IWU from a combination of state-of-the-art remotely sensed and modeled soil moisture products and apply it over the United States for the period 2013–2016. Overall, our estimates agree well with reference data on irrigated area and irrigation water withdrawals.
Philippe Cattan, Jean-Baptiste Charlier, Florence Clostre, Philippe Letourmy, Luc Arnaud, Julie Gresser, and Magalie Jannoyer
Hydrol. Earth Syst. Sci., 23, 691–709, https://doi.org/10.5194/hess-23-691-2019, https://doi.org/10.5194/hess-23-691-2019, 2019
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We investigated the management of long-term environmental pollution by organochlorine pesticides. We selected the case of chlordecone on the island of Martinique. We propose a conceptual model of organochlorine fate accounting for physical conditions relative to soils and geology. This model explains pollution variability in water but also the dynamics of pollution trends. It helps to identify risky areas where pollution will last for a long time and where more attention is needed.
Anoop Kumar Shukla, Shray Pathak, Lalit Pal, Chandra Shekhar Prasad Ojha, Ana Mijic, and Rahul Dev Garg
Hydrol. Earth Syst. Sci., 22, 5357–5371, https://doi.org/10.5194/hess-22-5357-2018, https://doi.org/10.5194/hess-22-5357-2018, 2018
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In this study, we carried out a comparative evaluation of water yield using two approaches, the Lumped Zhang model and the pixel-based approach. Even in pixel-level computations, experiments are made with existing models of some of the involved parameters. The study indicates not only the suitability of pixel-based computations but also clarifies the suitable model of some of the parameters to be used with pixel-based computations to obtain better results.
Anoop Kumar Shukla, Chandra Shekhar Prasad Ojha, Ana Mijic, Wouter Buytaert, Shray Pathak, Rahul Dev Garg, and Satyavati Shukla
Hydrol. Earth Syst. Sci., 22, 4745–4770, https://doi.org/10.5194/hess-22-4745-2018, https://doi.org/10.5194/hess-22-4745-2018, 2018
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Geospatial technologies and OIP are promising tools to study the effect of demographic changes and LULC transformations on the spatiotemporal variations in the water quality (WQ) across a large river basin. Therefore, this study could help to assess and solve local and regional WQ-related problems over a river basin. It may help the policy makers and planners to understand the status of water pollution so that suitable strategies could be planned for sustainable development in a river basin.
Melanie K. Vanderhoof, Charles R. Lane, Michael G. McManus, Laurie C. Alexander, and Jay R. Christensen
Hydrol. Earth Syst. Sci., 22, 1851–1873, https://doi.org/10.5194/hess-22-1851-2018, https://doi.org/10.5194/hess-22-1851-2018, 2018
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Effective monitoring and prediction of flood and drought events requires an improved understanding of surface water dynamics. We examined how the relationship between surface water extent, as mapped using Landsat imagery, and climate, is a function of landscape characteristics, using the Prairie Pothole Region and adjacent Northern Prairie in the United States as our study area. We found that at a landscape scale wetlands play a key role in informing how climate extremes influence surface water.
Mariana Madruga de Brito, Mariele Evers, and Adrian Delos Santos Almoradie
Hydrol. Earth Syst. Sci., 22, 373–390, https://doi.org/10.5194/hess-22-373-2018, https://doi.org/10.5194/hess-22-373-2018, 2018
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This paper sheds light on the integration of interdisciplinary knowledge in the assessment of flood vulnerability in Taquari-Antas river basin, Brazil. It shows how stakeholder participation is crucial for increasing not only the acceptance of model results but also its quality.
Nicolas Avisse, Amaury Tilmant, Marc François Müller, and Hua Zhang
Hydrol. Earth Syst. Sci., 21, 6445–6459, https://doi.org/10.5194/hess-21-6445-2017, https://doi.org/10.5194/hess-21-6445-2017, 2017
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Information on small reservoir storage is crucial for water management in a river basin. However, it is most of the time not freely available in remote, ungauged, or conflict-torn areas. We propose a novel approach using satellite imagery information only to quantitatively estimate storage variations in such inaccessible areas. We apply the method to southern Syria, where ground monitoring is impeded by the ongoing civil war, and validate it against in situ measurements in neighbouring Jordan.
Rangaswamy Madugundu, Khalid A. Al-Gaadi, ElKamil Tola, Abdalhaleem A. Hassaballa, and Virupakshagouda C. Patil
Hydrol. Earth Syst. Sci., 21, 6135–6151, https://doi.org/10.5194/hess-21-6135-2017, https://doi.org/10.5194/hess-21-6135-2017, 2017
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In view of the pressing need to assess the productivity of agricultural fields in Saudi Arabia, this study was undertaken in an attempt to apply the METRIC model with Landsat-8 imagery for the determination of spatial and temporal variability in ET aiming at optimizing the quantification of crop water requirement and the formulation of efficient irrigation schedules. This paper will be of great interest to readers in the areas of agriculture (in general), water management and remote sensing.
Clara Linés, Micha Werner, and Wim Bastiaanssen
Hydrol. Earth Syst. Sci., 21, 4747–4765, https://doi.org/10.5194/hess-21-4747-2017, https://doi.org/10.5194/hess-21-4747-2017, 2017
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This paper aims at identifying Earth observation data sets that can help river basin managers detect drought conditions that may lead to impacts early enough to take mitigation actions. Six remote sensing products were assessed using two types of impact data as a benchmark: media records from a regional newspaper and crop yields. Precipitation, vegetation condition and evapotranspiration products showed the best results, offering early signs of impacts up to 6 months before the reported damages.
Zeinab Takbiri, Ardeshir M. Ebtehaj, and Efi Foufoula-Georgiou
Hydrol. Earth Syst. Sci., 21, 2685–2700, https://doi.org/10.5194/hess-21-2685-2017, https://doi.org/10.5194/hess-21-2685-2017, 2017
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We present a multi-sensor retrieval algorithm for flood extent mapping at high spatial and temporal resolution. While visible bands provide flood mapping at fine spatial resolution, their capability is very limited in a cloudy sky. Passive microwaves can penetrate through clouds but cannot detect small-scale flooded surfaces due to their coarse resolution. The proposed method takes advantage of these two observations to retrieve sub-pixel flooded surfaces in all-sky conditions.
Joseph G. Alfieri, Martha C. Anderson, William P. Kustas, and Carmelo Cammalleri
Hydrol. Earth Syst. Sci., 21, 83–98, https://doi.org/10.5194/hess-21-83-2017, https://doi.org/10.5194/hess-21-83-2017, 2017
Yan Zhao, Yongping Wei, Shoubo Li, and Bingfang Wu
Hydrol. Earth Syst. Sci., 20, 4469–4481, https://doi.org/10.5194/hess-20-4469-2016, https://doi.org/10.5194/hess-20-4469-2016, 2016
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The paper finds that combined inflow from both current and previous years' discharge determines water availability in downstream regions. Temperature determines broad vegetation distribution while hydrological variables show significant effects only in near-river-channel regions. Agricultural development curtailed further vegetation recovery in the studied area. Enhancing current water allocation schemes and regulating regional agricultural activities are required for future restoration.
Behzad Hessari, Adriana Bruggeman, Ali Mohammad Akhoond-Ali, Theib Oweis, and Fariborz Abbasi
Hydrol. Earth Syst. Sci., 20, 1903–1910, https://doi.org/10.5194/hess-20-1903-2016, https://doi.org/10.5194/hess-20-1903-2016, 2016
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Yields of rainfed winter crops such as wheat can be substantially improved with limited supplemental irrigation. The upper Karkheh River basin in Iran has 15 840 km2 of rainfed crops. A GIS method was designed to identify suitable areas for irrigation and a routine was developed to allocate water uses and route the flows downstream. A maximum of 13 % of the rainfed cropland could be irrigated under normal flow, 9 % if environmental flow requirements are considered and 6 % under drought conditions.
Ting Xia, William P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Feng Gao, Lynn McKee, John H. Prueger, Hatim M. E. Geli, Christopher M. U. Neale, Luis Sanchez, Maria Mar Alsina, and Zhongjing Wang
Hydrol. Earth Syst. Sci., 20, 1523–1545, https://doi.org/10.5194/hess-20-1523-2016, https://doi.org/10.5194/hess-20-1523-2016, 2016
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This paper describes a model inter-comparison and validation study conducted using sub-meter resolution thermal data from an aircraft. The model inter-comparison is between a physically based model and a very simple empirical model. The strengths and weaknesses of both modeling approaches for high-resolution mapping of water use in vineyards is described. The findings provide significant insight into the utility of complex versus simple models for precise water resources management.
P. Karimi and W. G. M. Bastiaanssen
Hydrol. Earth Syst. Sci., 19, 507–532, https://doi.org/10.5194/hess-19-507-2015, https://doi.org/10.5194/hess-19-507-2015, 2015
P. Karimi, W. G. M. Bastiaanssen, A. Sood, J. Hoogeveen, L. Peiser, E. Bastidas-Obando, and R. J. Dost
Hydrol. Earth Syst. Sci., 19, 533–550, https://doi.org/10.5194/hess-19-533-2015, https://doi.org/10.5194/hess-19-533-2015, 2015
F. Baup, F. Frappart, and J. Maubant
Hydrol. Earth Syst. Sci., 18, 2007–2020, https://doi.org/10.5194/hess-18-2007-2014, https://doi.org/10.5194/hess-18-2007-2014, 2014
C. Cammalleri, M. C. Anderson, and W. P. Kustas
Hydrol. Earth Syst. Sci., 18, 1885–1894, https://doi.org/10.5194/hess-18-1885-2014, https://doi.org/10.5194/hess-18-1885-2014, 2014
J. L. Stein, M. F. Hutchinson, and J. A. Stein
Hydrol. Earth Syst. Sci., 18, 1917–1933, https://doi.org/10.5194/hess-18-1917-2014, https://doi.org/10.5194/hess-18-1917-2014, 2014
L. Longuevergne, C. R. Wilson, B. R. Scanlon, and J. F. Crétaux
Hydrol. Earth Syst. Sci., 17, 4817–4830, https://doi.org/10.5194/hess-17-4817-2013, https://doi.org/10.5194/hess-17-4817-2013, 2013
O. Merlin
Hydrol. Earth Syst. Sci., 17, 3623–3637, https://doi.org/10.5194/hess-17-3623-2013, https://doi.org/10.5194/hess-17-3623-2013, 2013
R. Guzinski, M. C. Anderson, W. P. Kustas, H. Nieto, and I. Sandholt
Hydrol. Earth Syst. Sci., 17, 2809–2825, https://doi.org/10.5194/hess-17-2809-2013, https://doi.org/10.5194/hess-17-2809-2013, 2013
X. M. Feng, G. Sun, B. J. Fu, C. H. Su, Y. Liu, and H. Lamparski
Hydrol. Earth Syst. Sci., 16, 2617–2628, https://doi.org/10.5194/hess-16-2617-2012, https://doi.org/10.5194/hess-16-2617-2012, 2012
N. Baghdadi, R. Cresson, M. El Hajj, R. Ludwig, and I. La Jeunesse
Hydrol. Earth Syst. Sci., 16, 1607–1621, https://doi.org/10.5194/hess-16-1607-2012, https://doi.org/10.5194/hess-16-1607-2012, 2012
J. Van doninck, J. Peters, H. Lievens, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 16, 773–786, https://doi.org/10.5194/hess-16-773-2012, https://doi.org/10.5194/hess-16-773-2012, 2012
R. R. E. Vernimmen, A. Hooijer, Mamenun, E. Aldrian, and A. I. J. M. van Dijk
Hydrol. Earth Syst. Sci., 16, 133–146, https://doi.org/10.5194/hess-16-133-2012, https://doi.org/10.5194/hess-16-133-2012, 2012
G.-J. Yang, C.-J. Zhao, W.-J. Huang, and J.-H. Wang
Hydrol. Earth Syst. Sci., 15, 2317–2326, https://doi.org/10.5194/hess-15-2317-2011, https://doi.org/10.5194/hess-15-2317-2011, 2011
J. Negrel, P. Kosuth, and N. Bercher
Hydrol. Earth Syst. Sci., 15, 2049–2058, https://doi.org/10.5194/hess-15-2049-2011, https://doi.org/10.5194/hess-15-2049-2011, 2011
R. Fieuzal, B. Duchemin, L. Jarlan, M. Zribi, F. Baup, O. Merlin, O. Hagolle, and J. Garatuza-Payan
Hydrol. Earth Syst. Sci., 15, 1117–1129, https://doi.org/10.5194/hess-15-1117-2011, https://doi.org/10.5194/hess-15-1117-2011, 2011
F. Baup, E. Mougin, P. de Rosnay, P. Hiernaux, F. Frappart, P. L. Frison, M. Zribi, and J. Viarre
Hydrol. Earth Syst. Sci., 15, 603–616, https://doi.org/10.5194/hess-15-603-2011, https://doi.org/10.5194/hess-15-603-2011, 2011
M. Zribi, A. Chahbi, M. Shabou, Z. Lili-Chabaane, B. Duchemin, N. Baghdadi, R. Amri, and A. Chehbouni
Hydrol. Earth Syst. Sci., 15, 345–358, https://doi.org/10.5194/hess-15-345-2011, https://doi.org/10.5194/hess-15-345-2011, 2011
L. A. Gibson, Z. Münch, and J. Engelbrecht
Hydrol. Earth Syst. Sci., 15, 295–310, https://doi.org/10.5194/hess-15-295-2011, https://doi.org/10.5194/hess-15-295-2011, 2011
H. Lievens, N. E. C. Verhoest, E. De Keyser, H. Vernieuwe, P. Matgen, J. Álvarez-Mozos, and B. De Baets
Hydrol. Earth Syst. Sci., 15, 151–162, https://doi.org/10.5194/hess-15-151-2011, https://doi.org/10.5194/hess-15-151-2011, 2011
D. Courault, R. Hadria, F. Ruget, A. Olioso, B. Duchemin, O. Hagolle, and G. Dedieu
Hydrol. Earth Syst. Sci., 14, 1731–1744, https://doi.org/10.5194/hess-14-1731-2010, https://doi.org/10.5194/hess-14-1731-2010, 2010
M. El Haj Tahir, A. Kääb, and C.-Y. Xu
Hydrol. Earth Syst. Sci., 14, 1167–1178, https://doi.org/10.5194/hess-14-1167-2010, https://doi.org/10.5194/hess-14-1167-2010, 2010
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Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martínez-Fernández, J., Llorens, P., Latron, J., Martin, C., and Bittelli, M.: Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe, Remote Sens. Environ., 115, 3390–3408, https://doi.org/10.1016/j.rse.2011.08.003, 2011.
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Lei, F., Crow, W. T., Shen, H., Parinussa, R. M., and Holmes, T. R. H.: The Impact of Local Acquisition Time on the Accuracy of Microwave Surface Soil Moisture Retrievals over the Contiguous United States, Remote Sens., 7, 13448–13465, https://doi.org/10.3390/rs71013448, 2015.
Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., and Holmes, T. R. H.: An analysis of spatiotemporal variations of soil and vegetation moisture from a 29-year satellite-derived data set over mainland Australia, Water Resour. Res., 45, W07405, https://doi.org/10.1029/2008WR007187, 2009.
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, 2011a.
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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.
Soil moisture is a crucial variable for a variety of applications, ranging from weather...
