Articles | Volume 26, issue 13
https://doi.org/10.5194/hess-26-3337-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3337-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Exploring the combined use of SMAP and Sentinel-1 data for downscaling soil moisture beyond the 1 km scale
Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
now at: Hydrogeology and Landscape Hydrology Group, Institute for
Biology and Environmental Sciences, Carl von Ossietzky University of Oldenburg, Ammerländer Heerstr. 114–118, 26129 Oldenburg, Germany
Wenmin Zhang
Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
Søren Julsgaard Kragh
Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, Denmark
Mie Andreasen
Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, Denmark
Karsten Høgh Jensen
Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
Rasmus Fensholt
Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
Simon Stisen
Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, Denmark
Majken C. Looms
Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, Denmark
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Earth Syst. Sci. Data, 17, 1551–1572, https://doi.org/10.5194/essd-17-1551-2025, https://doi.org/10.5194/essd-17-1551-2025, 2025
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Hydrol. Earth Syst. Sci., 28, 1001–1026, https://doi.org/10.5194/hess-28-1001-2024, https://doi.org/10.5194/hess-28-1001-2024, 2024
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Hydrol. Earth Syst. Sci., 27, 255–287, https://doi.org/10.5194/hess-27-255-2023, https://doi.org/10.5194/hess-27-255-2023, 2023
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Raphael Schneider, Julian Koch, Lars Troldborg, Hans Jørgen Henriksen, and Simon Stisen
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Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
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Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
M. C. A. Picoli, J. Radoux, X. Tong, A. Bey, P. Rufin, M. Brandt, R. Fensholt, and P. Meyfroidt
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 975–981, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-975-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-975-2022, 2022
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
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.
Djamil Al-Halbouni, Robert A. Watson, Eoghan P. Holohan, Rena Meyer, Ulrich Polom, Fernando M. Dos Santos, Xavier Comas, Hussam Alrshdan, Charlotte M. Krawczyk, and Torsten Dahm
Hydrol. Earth Syst. Sci., 25, 3351–3395, https://doi.org/10.5194/hess-25-3351-2021, https://doi.org/10.5194/hess-25-3351-2021, 2021
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The rapid decline of the Dead Sea level since the 1960s has provoked a dynamic reaction from the coastal groundwater system, with physical and chemical erosion creating subsurface voids and conduits. By combining remote sensing, geophysical methods, and numerical modelling at the Dead Sea’s eastern shore, we link groundwater flow patterns to the formation of surface stream channels, sinkholes and uvalas. Better understanding of this karst system will improve regional hazard assessment.
Wim Verbruggen, Guy Schurgers, Stéphanie Horion, Jonas Ardö, Paulo N. Bernardino, Bernard Cappelaere, Jérôme Demarty, Rasmus Fensholt, Laurent Kergoat, Thomas Sibret, Torbern Tagesson, and Hans Verbeeck
Biogeosciences, 18, 77–93, https://doi.org/10.5194/bg-18-77-2021, https://doi.org/10.5194/bg-18-77-2021, 2021
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A large part of Earth's land surface is covered by dryland ecosystems, which are subject to climate extremes that are projected to increase under future climate scenarios. By using a mathematical vegetation model, we studied the impact of single years of extreme rainfall on the vegetation in the Sahel. We found a contrasting response of grasses and trees to these extremes, strongly dependent on the way precipitation is spread over the rainy season, as well as a long-term impact on CO2 uptake.
Cited articles
Andreasen, M., Jensen, K. H., Zreda, M., Desilets, D., Bogena, H., and Looms,
M. C.: Modelling cosmic ray neutron field measurements, Water Resour. Res., 52, 5794–5812, https://doi.org/10.1002/2016WR018814, 2016.
Andreasen, M., Jensen, K. H., Desilets, D., Trenton, E., Zreda, M., Bogena, H. R., and Looms, M. C.: Status and Perspectives on the Cosmic-Ray Neutron
Method for Soil Moisture Estimation and Other Environmental Science
Applications, Vadose Zone J., 16, 1–11, https://doi.org/10.2136/vzj2017.04.0086, 2017.
Andreasen, M., Looms, M. C., and Jensen, K. H.: Cosmic-ray neutron intensity and soil moisture estimates in the period 2013–2019 at three field sites locations in the western part of Denmark, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.909271, 2019.
Andreasen, M., Jensen, K. H., Bogena, H., Desilets, D., Zreda, M., and Looms,
M. C.: Cosmic Ray Neutron Soil Moisture Estimation Using Physically Based
Site-Specific Conversion Functions, Water Resour. Res., 56, 1–20,
https://doi.org/10.1029/2019WR026588, 2020.
Bartsch, A., Balzter, H., and George, C.: The influence of regional surface
soil moisture anomalies on forest fires in Siberia observed from satellites,
Environ. Res. Lett., 4, 045021, https://doi.org/10.1088/1748-9326/4/4/045021, 2009.
Bircher, S., Skou, N., Jensen, K. H., Walker, J. P., and Rasmussen, L.: A soil moisture and temperature network for SMOS validation in Western Denmark, Hydrol. Earth Syst. Sci., 16, 1445–1463, https://doi.org/10.5194/hess-16-1445-2012, 2012a.
Bircher, S., Balling, J. E., Skou, N., and Kerr, Y. H.: Validation of SMOS
brightness temperatures during the HOBE airborne campaign, western Denmark,
IEEE T. Geosci. Remote, 50, 1468–1482, https://doi.org/10.1109/TGRS.2011.2170177, 2012b.
Bogena, H. R., Schrön, M., Jakobi, J., Ney, P., Zacharias, S., Andreasen, M., Baatz, R., Boorman, D., Duygu, M. B., Eguibar-Galán, M. A., Fersch, B., Franke, T., Geris, J., González Sanchis, M., Kerr, Y., Korf, T., Mengistu, Z., Mialon, A., Nasta, P., Nitychoruk, J., Pisinaras, V., Rasche, D., Rosolem, R., Said, H., Schattan, P., Zreda, M., Achleitner, S., Albentosa-Hernández, E., Akyürek, Z., Blume, T., del Campo, A., Canone, D., Dimitrova-Petrova, K., Evans, J. G., Ferraris, S., Frances, F.,
Gisolo, D., Güntner, A., Herrmann, F., Iwema, J., Jensen, K. H., Kunstmann, H., Lidón, A., Looms, M. C., Oswald, S., Panagopoulos, A.,
Patil, A., Power, D., Rebmann, C., Romano, N., Scheiffele, L., Seneviratne,
S., Weltin, G., and Vereecken, H.: COSMOS-Europe: a European network of
cosmic-ray neutron soil moisture sensors, Earth Syst. Sci. Data, 1125–1151,
https://doi.org/10.5194/essd-14-1125-2022, 2022.
Calvet, J. C., Wigneron, J. P., Walker, J., Karbou, F., Chanzy, A., and Albergel, C.: Sensitivity of passive microwave observations to soil moisture
and vegetation water content: L-band to W-band, IEEE T. Geosci. Remote, 49, 1190–1199, https://doi.org/10.1109/TGRS.2010.2050488, 2011.
Chaparro, D., Vall-Llossera, M., Piles, M., Camps, A., Rudiger, C., and
Riera-Tatche, R.: Predicting the Extent of Wildfires Using Remotely Sensed
Soil Moisture and Temperature Trends, IEEE J. Select. Top. Appl. Earth Obs.
Remote Sens., 9, 2818–2829, https://doi.org/10.1109/JSTARS.2016.2571838, 2016.
Colliander, A., Jackson, T. J., Bindlish, R., Chan, S., Das, N., Kim, S. B.,
Cosh, M. H., Dunbar, R. S., Dang, L., Pashaian, L., Asanuma, J., Aida, K.,
Berg, A., Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D.,
al Jassar, H., Lopez-Baeza, E., Martínez-Fernández, J., González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J., Pulliainen, J., Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z., Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J. P., Wu, X., Monerris, A., O'Neill, P. E., Entekhabi, D., Njoku, E. G., and Yueh, S.: Validation of SMAP surface soil moisture products with core validation sites, Remote Sens. Environ., 191, 215–231, https://doi.org/10.1016/j.rse.2017.01.021, 2017.
Das, N. N., Entekhabi, D., Member, S., and Njoku, E. G.: An Algorithm for
Merging SMAP Radiometer and Radar Data for High-Resolution Soil-Moisture
Retrieval, IEEE T. Geosci. Remote, 49, 1504–1512, https://doi.org/10.1109/TGRS.2010.2089526, 2011.
Das, N. N., Entekhabi, D., Member, S., Njoku, E. G., Shi, J. J. C., Member,
S., Johnson, J. T., Colliander, A., and Member, S.: Tests of the SMAP Combined Radar and Radiometer Algorithm Using Airborne Field Campaign Observations and Simulated Data, IEEE T. Geosci. Remote, 52, 2018–2028, https://doi.org/10.1109/TGRS.2013.2257605, 2014.
Das, N. N., Entekhabi, D., Dunbar, R. S., Colliander, A., Chen, F., Crow, W., Jackson, T. J., Berg, A., Bosch, D. D., Caldwell, T., Cosh, M. H., Collins, C. H., Lopez-baeza, E., Moghaddam, M., Rowlandson, T., Starks, P. J., Thibeault, M., Walker, P., Wu, X., Neill, P. E. O., Yueh, S., and Njoku, E. G.: The SMAP mission combined active-passive soil moisture product at 9 km and 3 km spatial resolutions, Remote Sens. Environ., 211, 204–217, https://doi.org/10.1016/j.rse.2018.04.011, 2018.
Das, N. N., Entekhabi, D., Dunbar, R. S., Chaubell, M. J., Colliander, A., Yueh, S., Jagdhuber, T., Chen, F., Crow, W., O'Neill, P. E., Walker, J. P., Berg, A., Bosch, D. D., Caldwell, T., Cosh, M. H., Collins, C. H., Lopez-Baeza, E., and Thibeault, M.: The SMAP and Copernicus Sentinel 1A/B
microwave active-passive high resolution surface soil moisture product, Remote Sens. Environ., 233, 111380, https://doi.org/10.1016/j.rse.2019.111380, 2019.
Decagon Devices Inc: 5TE – Water Content, EC and Temperature Sensor,
https://www.metergroup.com/en/meter-environment (last access: 27 April 2021), 2016.
Denager, T., Looms, M. C., Sonnenborg, T. O., and Jensen, K. H.: Comparison
of evapotranspiration estimates using the water balance and the eddy
covariance methods, Vadose Zone J., 19, 1–21, https://doi.org/10.1002/vzj2.20032, 2020.
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, 1–7, https://doi.org/10.1029/2009WR008726, 2010.
DMI.dk: Frie Data, Danish Meteoroligical Inst., https://www.dmi.dk/, last access: 27 April 2021.
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., Xaver, A.. Vreugdenhil, M.. Gruber, A., Hegyiová, A., Sanchis-Dufau, A. D., Zamojski, D., Cordes, C., Wagner, W., and Drusch, M. : Global Automated Quality Control of In situ Soil Moisture data from the International Soil Moisture Network, Vadose Zone J., 12, 3, https://doi.org/10.2136/vzj2012.0097, 2013.
Entekhabi, D., Yueh, S., O'Neill, P. E., Kellogg, K. H., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., Crow, W. T., Das, N. N., Lannoy, G., Dunbar, R., Edelstein, W. N., Entin, J. K., Escobar, V., Goodman, S. D., Jackson, T. J., Jai, B., Johnson, J., Kim, E., Kim, S., Kimball, J., Koster, R. D., Leon, A., McDonald, K. C., Moghaddam, M., Mohammed, P., Moran, S., Njoku, E. G., Piepmeier, J. R., Reichle, R., Rogez, F., Shi, J. C., Spencer, M. W., Thurman, S. W., Tsang, L., Van Zyl, J., Weiss, B., and West, R.: SMAP Handbook – Soil Moisture Active Passive: Mapping Soil Moisture and Freeze/Thaw from Space, JPL Publication, Pasadena, CA, 2014.
Fang, B., Lakshmi, V., Bindlish, R., Jackson, T. J., Cosh, M., and Basara, J.: Passive Microwave Soil Moisture Downscaling Using Vegetation Index and
Skin Surface Temperature, Vadose Zone J., 12, vzj2013.05.0089er,
https://doi.org/10.2136/vzj2013.05.0089er, 2013.
Fang, B., Lakshmi, V., Bindlish, R., and Jackson, T. J.: Downscaling of SMAP
Soil Moisture Using Land Surface Temperature and Vegetation Data, Vadose Zone J., 17, 170198, https://doi.org/10.2136/vzj2017.11.0198, 2018.
Filipponi, F.: Sentinel-1 GRD Preprocessing Workflow, MDPI Proc., 18, 11,
https://doi.org/10.3390/ecrs-3-06201, 2019.
GeoDanmark-data: Orthofoto spring 2018, https://eng.sdfe.dk/ (last access: 1 September 2021), 2018.
González-Zamora, Á., Sánchez, N., Martínez-Fernández,
J., Gumuzzio, Á., Piles, M., and Olmedo, E.: Long-term SMOS soil moisture
products: A comprehensive evaluation across scales and methods in the Duero
Basin (Spain), Phys. Chem. Earth, 83–84, 123–136, https://doi.org/10.1016/j.pce.2015.05.009, 2015.
Grillakis, M. G., Koutroulis, A. G., Komma, J., Tsanis, I. K., Wagner, W.,
and Blöschl, G.: Initial soil moisture effects on flash flood generation
– A comparison between basins of contrasting hydro-climatic conditions, J.
Hydrol., 541, 206–217, https://doi.org/10.1016/j.jhydrol.2016.03.007, 2016.
El Hajj, M., Baghdadi, N., Bazzi, H., and Zribi, M.: Penetration analysis of
SAR signals in the C and L bands for wheat, maize, and grasslands, Remote
Sens., 11, 22–24, https://doi.org/10.3390/rs11010031, 2019.
Harfenmeister, K., Spengler, D., and Weltzien, C.: Analyzing temporal and
spatial characteristics of crop parameters using Sentinel-1 backscatter data, Remote Sens., 11, 1–30, https://doi.org/10.3390/rs11131569, 2019.
He, L., Hong, Y., Wu, X., Ye, N., Walker, J. P., and Chen, X.: Investigation
of SMAP Active – Passive Downscaling Algorithms Using Combined Sentinel-1
SAR and SMAP Radiometer Data, IEEE T. Geosci. Remote, 56, 4906–4918, https://doi.org/10.1109/TGRS.2018.2842153, 2018.
Henriksen, H. J., Troldborg, L., Nyegaard, P., Sonnenborg, T. O., Refsgaard,
J. C., and Madsen, B.: Methodology for construction, calibration and validation of a national hydrological model for Denmark, J. Hydrol., 280, 52–71, https://doi.org/10.1016/S0022-1694(03)00186-0, 2003.
ISMN – International Soil Moisture Network: HOBE, ISMN [data set], https://ismn.earth/en/networks/?id=HOBE, last access: 24 June 2022.
Jensen, K. H. and Illangasekare, T. H.: HOBE: A Hydrological Observatory,
Vadose Zone J., 10, 1–7, https://doi.org/10.2136/vzj2011.0006, 2011.
Jensen, K. H. and Refsgaard, J. C.: HOBE: The Danish Hydrological Observatory, Vadose Zone J., 17, 1–24, https://doi.org/10.2136/vzj2018.03.0059, 2018.
Levin, G., Iosub, C.-I., and Jepsen, M. R.: Basemap02, Technical documentation of a model for elaboration of a land-use and land-cover map for Denmark, in: Technical Report from DCE – Danish Centre for Environment and Energy, Aarhus University, DCE – Danish Centre for Environment and Energy, https://dce2.au.dk/pub/TR95.pdf (last access: 24 June 2022), 2017.
Lloyd, S. P.: Least Squares Quantization in PCM, IEEE Trans. Inf. Theory,
28, 129–137, https://doi.org/10.1109/TIT.1982.1056489, 1982.
Mascaro, G., Vivoni, E. R., and Deidda, R.: Downscaling soil moisture in the
southern Great Plains through a calibrated multifractal model for land surface modeling applications, Water Resour. Res., 46, 1–18,
https://doi.org/10.1029/2009WR008855, 2010.
Mascaro, G., Vivoni, E. R., and Deidda, R.: Soil moisture downscaling across
climate regions and its emergent properties, J. Geophys. Res.-Atmos., 116, 1–19, https://doi.org/10.1029/2011JD016231, 2011.
Meyer, R., Engesgaard, P., Hinsby, K., Piotrowski, J. A., and Sonnenborg, T.
O.: Estimation of effective porosity in large-scale groundwater models by
combining particle tracking, auto-calibration and 14C dating, Hydrol. Earth Syst. Sci., 22, 4843–4865, https://doi.org/10.5194/hess-22-4843-2018,
2018a.
Meyer, R., Engesgaard, P., Høyer, A.-S., Jørgensen, F., Vignoli, G.,
and Sonnenborg, T. O.: Regional flow in a complex coastal aquifer system:
Combining voxel geological modelling with regularized calibration, J. Hydrol., 562, 544–563, https://doi.org/10.1016/j.jhydrol.2018.05.020, 2018b.
Meyer, R., Engesgaard, P., and Sonnenborg, T. O.: Origin and dynamics of
saltwater intrusions in regional aquifers; combining 3D saltwater modelling
with geophysical and geochemical data, Water Resour. Res., 55, 1792–1813, https://doi.org/10.1029/2018WR023624, 2019.
Mladenova, I. E., Jackson, T. J., Bindlish, R., Member, S., Hensley, S., and
Member, S.: Incidence Angle Normalization of Radar Backscatter Data, IEEE
T. Geosci. Remote., 51, 1791–1804, https://doi.org/10.1109/TGRS.2012.2205264, 2013.
Mohanty, B. P., Cosh, M. H., Lakshmi, V., and Montzka, C.: Soil Moisture
Remote Sensing: State-of-the-Science, Vadose Zone J., 16, 1–9, https://doi.org/10.2136/vzj2016.10.0105, 2017.
Montzka, C., Bogena, H. R., 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, 1–30,
https://doi.org/10.3390/rs9020103, 2017.
Ochsner, T. E., Cuenca, R. H., and Draper, C. S.: State of the Art in Large-Scale Soil Moisture Monitoring, Soil Sci. Soc. Am. J., 77, 1888–1919,
https://doi.org/10.2136/sssaj2013.03.0093, 2013.
O'Neill, P. E., Chan, S., Njoku, E. G., Jackson, T., and Bindlish, R.: SMAP
Enhanced L3 Radiometer Global Daily 9 km EASE-Grid Soil Moisture, Version 2, NASA Natl. Snow Ice Data Cent. Distrib. Act. Arch. Cent., Boulder, Colorado, USA, https://doi.org/10.5067/RFKIZ5QY5ABN (last access: 1 February 2019), 2018.
Peng, J., Loew, A., Zhang, S., Wang, J., and Niesel, J.: Spatial Downscaling
of Satellite Soil Moisture Data Using a Vegetation Temperature Condition
Index, IEEE T. Geosci. Remote, 54, 558–566, https://doi.org/10.1109/TGRS.2015.2462074, 2016.
Peng, J., Loew, A., Merlin, O., and Verhoest, N. E. C.: A review of spatial
downscaling satelllite remotely sensed soil moisture, Rev. Geophys., 55, 341–366, https://doi.org/10.1002/2016RG000543, 2017.
Ridler, M.-E., Madsen, H., Stisen, S., Bircher, S., and Fensholt, R.: Assimilation of SMOS-derived soil moisture in a fully integrated hydrological and soil-vegetation-atmosphere transfer model in Western Denmark, Water Resour. Res., 50, 8962–8981, https://doi.org/10.1002/2014WR015392, 2014.
Rosenqvist, A.: A Layman's Interpretation Guide to L-band and C-band
Synthetic Aperture Radar data, http://ceos.org (last access: 22 June 2021), 2018.
Sabaghy, S., Walker, P., Renzullo, L. J., and Jackson, T. J.: Remote Sensing
of Environment Spatially enhanced passive microwave derived soil moisture:
Capabilities and opportunities, Remote Sens. Environ., 209, 551–580,
https://doi.org/10.1016/j.rse.2018.02.065, 2018.
Shahrban, M., Walker, J. P., Wang, Q. J., and Robertson, D. E.: On the
importance of soil moisture in calibration of rainfall–runoff models: two
case studies, Hydrolog. Sci. J., 63, 1292–1312, https://doi.org/10.1080/02626667.2018.1487560, 2018.
Stelljes, N., Albrecht, S., Martinez, G., and McGlade, K.: Proposals for new
governance concepts and policy options, BONUS SOIL2SEA Deliv. 6.2, Ecologic I, http://www.soils2sea.eu/about_uk/main.html (last access: 23 May 2021), 2017.
Tagesson, T., Horion, S., Nieto, H., Zaldo Fornies, V., Mendiguren González, G., Bulgin, C. E., Ghent, D., and Fensholt, R.: Disaggregation of SMOS soil moisture over West Africa using the Temperature and Vegetation Dryness Index based on SEVIRI land surface parameters, Remote Sens. Environ., 206, 424–441, https://doi.org/10.1016/j.rse.2017.12.036, 2018.
Veloso, A., Mermoz, S., Bouvet, A., Le Toan, T., Planells, M., Dejoux, J. F.,
and Ceschia, E.: Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications, Remote
Sens. Environ., 199, 415–426, https://doi.org/10.1016/j.rse.2017.07.015, 2017.
Vereecken, H., Huisman, J. A., Bogena, H., Vanderborght, J., Vrugt, J. A., and Hopmans, J. W.: On the value of soil moisture measurements in vadose zone hydrology: A review, Water Resour. Res., 46, 1–21, https://doi.org/10.1029/2008WR006829, 2008.
Vereecken, H., Huisman, J. A., Pachepsky, Y., Montzka, C., van der Kruk, J.,
Bogena, H., Weihermüller, L., Herbst, M., Martinez, G., and Vanderborght,
J.: On the spatio-temporal dynamics of soil moisture at the field scale, J.
Hydrol., 516, 76–96, https://doi.org/10.1016/j.jhydrol.2013.11.061, 2014.
Vreugdenhil, M., Wagner, W., Bauer-Marschallinger, B., Pfeil, I., Teubner,
I., Rüdiger, C., and Strauss, P.: Sensitivity of Sentinel-1 backscatter
to vegetation dynamics: An Austrian case study, Remote Sens., 10), 1–19,
https://doi.org/10.3390/rs10091396, 2018.
Wagner, W., Blöschl, G., Pampaloni, P., Calvet, J. C., Bizzarri, B.,
Wigneron, J. P., and Kerr, Y.: Operational readiness of microwave remote
sensing of soil moisture for hydrologic applications, Nord. Hydrol., 38, 1–20, https://doi.org/10.2166/nh.2007.029, 2007.
Short summary
The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of...