Articles | Volume 25, issue 3
https://doi.org/10.5194/hess-25-1389-2021
© Author(s) 2021. 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-25-1389-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model
Centre for Water Resource Systems, TU Wien, Vienna 1040, Austria
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna 1040, Austria
Juraj Parajka
Centre for Water Resource Systems, TU Wien, Vienna 1040, Austria
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna 1040, Austria
Andreas Salentinig
Department of Geodesy and Geoinformation, TU Wien, Vienna 1040,
Austria
Isabella Pfeil
Centre for Water Resource Systems, TU Wien, Vienna 1040, Austria
Department of Geodesy and Geoinformation, TU Wien, Vienna 1040,
Austria
Jürgen Komma
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna 1040, Austria
Borbála Széles
Centre for Water Resource Systems, TU Wien, Vienna 1040, Austria
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna 1040, Austria
Martin Kubáň
Department of Land and Water Resources Management, Slovak University of Technology in Bratislava, Bratislava 810 05, Slovakia
Peter Valent
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna 1040, Austria
Department of Land and Water Resources Management, Slovak University of Technology in Bratislava, Bratislava 810 05, Slovakia
Mariette Vreugdenhil
Department of Geodesy and Geoinformation, TU Wien, Vienna 1040,
Austria
Wolfgang Wagner
Centre for Water Resource Systems, TU Wien, Vienna 1040, Austria
Department of Geodesy and Geoinformation, TU Wien, Vienna 1040,
Austria
Günter Blöschl
Centre for Water Resource Systems, TU Wien, Vienna 1040, Austria
Institute of Hydraulic Engineering and Water Resources Management, TU Wien, Vienna 1040, Austria
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Alberto Montanari, Bruno Merz, and Günter Blöschl
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J. Zhao, F. Roth, B. Bauer-Marschallinger, W. Wagner, M. Chini, and X. X. Zhu
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Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anaïs Barella-Ortiz, Pere Quintana-Seguí, David Bretreger, and Espen Volden
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Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci., 27, 1201–1219, https://doi.org/10.5194/hess-27-1201-2023, https://doi.org/10.5194/hess-27-1201-2023, 2023
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Enrico Bonanno, Günter Blöschl, and Julian Klaus
Hydrol. Earth Syst. Sci., 26, 6003–6028, https://doi.org/10.5194/hess-26-6003-2022, https://doi.org/10.5194/hess-26-6003-2022, 2022
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Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 5015–5033, https://doi.org/10.5194/hess-26-5015-2022, https://doi.org/10.5194/hess-26-5015-2022, 2022
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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
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Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Shengping Wang, Borbala Szeles, Carmen Krammer, Elmar Schmaltz, Kepeng Song, Yifan Li, Zhiqiang Zhang, Günter Blöschl, and Peter Strauss
Hydrol. Earth Syst. Sci., 26, 3021–3036, https://doi.org/10.5194/hess-26-3021-2022, https://doi.org/10.5194/hess-26-3021-2022, 2022
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This study explored the quantitative contribution of agricultural intensification and climate change to the sediment load of a small agricultural watershed. Rather than a change in climatic conditions, changes in the land structure notably altered sediment concentrations under high-flow conditions, thereby contributing most to the increase in annual sediment loads. More consideration of land structure improvement is required when combating the transfer of soil from land to water.
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.
Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 2469–2480, https://doi.org/10.5194/hess-26-2469-2022, https://doi.org/10.5194/hess-26-2469-2022, 2022
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Sound understanding of how floods come about allows for the development of more reliable flood management tools that assist in mitigating their negative impacts. This article reviews river flood generation processes and flow paths across space scales, starting from water movement in the soil pores and moving up to hillslopes, catchments, regions and entire continents. To assist model development, there is a need to learn from observed patterns of flood generation processes at all spatial scales.
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.
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.
David Lun, Alberto Viglione, Miriam Bertola, Jürgen Komma, Juraj Parajka, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 5535–5560, https://doi.org/10.5194/hess-25-5535-2021, https://doi.org/10.5194/hess-25-5535-2021, 2021
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We investigate statistical properties of observed flood series on a European scale. There are pronounced regional patterns, for instance: regions with strong Atlantic influence show less year-to-year variability in the magnitude of observed floods when compared with more arid regions of Europe. The hydrological controls on the patterns are quantified and discussed. On the European scale, climate seems to be the dominant driver for the observed patterns.
Concetta Di Mauro, Renaud Hostache, Patrick Matgen, Ramona Pelich, Marco Chini, Peter Jan van Leeuwen, Nancy K. Nichols, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 4081–4097, https://doi.org/10.5194/hess-25-4081-2021, https://doi.org/10.5194/hess-25-4081-2021, 2021
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This study evaluates how the sequential assimilation of flood extent derived from synthetic aperture radar data can help improve flood forecasting. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. Our empirical results demonstrate the efficiency of the proposed data assimilation framework, as forecasting errors are substantially reduced as a result of the assimilation.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
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The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
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
Lovrenc Pavlin, Borbála Széles, Peter Strauss, Alfred Paul Blaschke, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 2327–2352, https://doi.org/10.5194/hess-25-2327-2021, https://doi.org/10.5194/hess-25-2327-2021, 2021
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We compared the dynamics of streamflow, groundwater and soil moisture to investigate how different parts of an agricultural catchment in Lower Austria are connected. Groundwater is best connected around the stream and worse uphill, where groundwater is deeper. Soil moisture connectivity increases with increasing catchment wetness but is not influenced by spatial position in the catchment. Groundwater is more connected to the stream on the seasonal scale compared to the event scale.
Miriam Bertola, Alberto Viglione, Sergiy Vorogushyn, David Lun, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1347–1364, https://doi.org/10.5194/hess-25-1347-2021, https://doi.org/10.5194/hess-25-1347-2021, 2021
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We estimate the contribution of extreme precipitation, antecedent soil moisture and snowmelt to changes in small and large floods across Europe.
In northwestern and eastern Europe, changes in small and large floods are driven mainly by one single driver (i.e. extreme precipitation and snowmelt, respectively). In southern Europe both antecedent soil moisture and extreme precipitation significantly contribute to flood changes, and their relative importance depends on flood magnitude.
Mattia Neri, Juraj Parajka, and Elena Toth
Hydrol. Earth Syst. Sci., 24, 5149–5171, https://doi.org/10.5194/hess-24-5149-2020, https://doi.org/10.5194/hess-24-5149-2020, 2020
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One of the most informative ways to gain information on ungauged river sections is through the implementation of a rainfall-runoff model, exploiting the information collected in gauged catchments in the study area. This study analyses how the performances of different model regionalisation approaches are influenced by the informative content of the available regional data set, in order to identify the methods that are more suitable for the data availability in the region.
Cited articles
Abowarda, A. S., Bai, L., Zhang, C., Long, D., Li, X., Huang, Q., and Sun,
Z.: Generating surface soil moisture at 30 m spatial resolution using both
data fusion and machine learning toward better water resources management at
the field scale, Remote Sens. Environ., 255, 112301,
https://doi.org/10.1016/j.rse.2021.112301, 2021.
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008.
Babaeian, E., Sadeghi, M., Jones, S. B., Montzka, C., Vereecken, H., and
Tuller, M.: Ground, Proximal, and Satellite Remote Sensing of Soil Moisture,
Rev. Geophys., 57, 530–616, https://doi.org/10.1029/2018rg000618,
2019.
Bai, P., Liu, X., and Liu, C.: Improving hydrological simulations by
incorporating GRACE data for model calibration, J. Hydrol., 557,
291–304, https://doi.org/10.1016/j.jhydrol.2017.12.025, 2018.
Bauer-Marschallinger, B., Freeman, V., Cao, S., Paulik, C., Schaufler, S.,
Stachl, T., Modanesi, S., Massari, C., Ciabatta, L., Brocca, L., and Wagner,
W.: Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing
Assets and Overcoming Obstacles, IEEE T. Geosci. Remote, 57, 520–539, https://doi.org/10.1109/TGRS.2018.2858004, 2019.
Bergström, S.: The HBV model – its structure and applications,
SMHI Reports RH 4, Swedish Meteorological and Hydrological
Institute (SMHI), Norrköping, Sweden, 1992.
BMLRT: ehyd – Hydrographic data and analyses, available at:
https://ehyd.gv.at/, last access: 20 August 2020.
Brocca, L., Tarpanelli, A., Moramarco, T., Melone, F., Ratto, S. M.,
Cauduro, M., Ferraris, S., Berni, N., Ponziani, F., Wagner, W., and Melzer,
T.: Soil Moisture Estimation in Alpine Catchments through Modeling and
Satellite Observations, Vadose Zone J., 12, 1–10,
https://doi.org/10.2136/vzj2012.0102, 2013.
Brocca, L., Crow, W. T., Ciabatta, L., Massari, C., Rosnay, P. d., Enenkel,
M., Hahn, S., Amarnath, G., Camici, S., Tarpanelli, A., and Wagner, W.: A
Review of the Applications of ASCAT Soil Moisture Products, IEEE J. Sel. Top. Appl., 10, 2285–2306, https://doi.org/10.1109/JSTARS.2017.2651140, 2017.
Chen, F., Crow, W. T., Bindlish, R., Colliander, A., Burgin, M. S., Asanuma,
J., and Aida, K.: Global-scale evaluation of SMAP, SMOS and ASCAT soil
moisture products using triple collocation, Remote Sens. Environ.,
214, 1–13, https://doi.org/10.1016/j.rse.2018.05.008, 2018.
Chu, W., Gao, X., and Sorooshian, S.: A new evolutionary search strategy for
global optimization of high-dimensional problems, Inform. Sciences, 181,
4909–4927, https://doi.org/10.1016/j.ins.2011.06.024, 2011.
Demirel, M. C., Özen, A., Orta, S., Toker, E., Demir, H. K.,
Ekmekcioğlu, Ö., Tayşi, H., Eruçar, S., Sağ, A. B., and
Sarı, Ö.: Additional value of using satellite-based soil moisture and
two sources of groundwater data for hydrological model calibration, Water-Sui., 11, 2083, https://doi.org/10.3390/w11102083, 2019.
Didan, K.: MOD13A3 MODIS/Terra vegetation Indices Monthly L3
Global 1 km SIN Grid V006 [September 2002 to August 2014], [Dataset], NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD13A3.006, 2015.
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L.,
Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D.,
Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y.,
Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C.,
Reimer, C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and
Lecomte, P.: ESA CCI Soil Moisture for improved Earth system understanding:
State-of-the art and future directions, Remote Sens. Environ., 203,
185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017.
Duethmann, D., Peters, J., Blume, T., Vorogushyn, S., and Güntner, A.:
The value of satellite – snow cover images for calibrating a
hydrological model in snow – catchments in Central Asia, Water
Resour. Res., 50, 2002–2021, https://doi.org/10.1002/2013WR014382,
2014.
Duethmann, D., Blöschl, G., and Parajka, J.: Why does a conceptual hydrological model fail to correctly predict discharge changes in response to climate change?, Hydrol. Earth Syst. Sci., 24, 3493–3511, https://doi.org/10.5194/hess-24-3493-2020, 2020.
Efstratiadis, A. and Koutsoyiannis, D.: One decade of multi-objective
calibration approaches in hydrological modelling: a review, Hydrol.
Sci. J., 55, 58–78, https://doi.org/10.1080/02626660903526292,
2010.
El Hajj, M., Baghdadi, N., Zribi, M., Rodríguez-Fernández, N.,
Wigneron, J. P., Al-Yaari, A., Al Bitar, A., Albergel, C., and Calvet,
J.-C.: Evaluation of SMOS, SMAP, ASCAT and Sentinel-1 soil moisture products
at sites in Southwestern France, Remote Sens., 10, 569,
https://doi.org/10.3390/rs10040569, 2018.
Finger, D., Vis, M., Huss, M., and Seibert, J.: The value of multiple data
set calibration versus model complexity for improving the performance of
hydrological models in mountain catchments, Water Resour. Res., 51,
1939–1958, https://doi.org/10.1002/2014wr015712, 2015.
Franz, K. J. and Karsten, L. R.: Calibration of a distributed snow model
using MODIS snow covered area data, J. Hydrol., 494, 160–175,
https://doi.org/10.1016/j.jhydrol.2013.04.026, 2013.
Hall, D. K. and Riggs, G. A.: MODIS/Terra Snow Cover Daily L3
Global 500 m Grid, Version 6, [September 2002 to August 2014], [Dataset], Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/MODIS/MOD10A1.006, 2016a.
Hall, D. K. and Riggs, G. A.: MODIS/Aqua Snow Cover Daily L3
Global 500m Grid, Version 6, [September 2002 to August 2014], [Dataset], Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/MODIS/MYD10A1.006, 2016b.
Hahn, S., Wagner, W., Steele-Dunne, S. C., Vreugdenhil, M., and Melzer, T.:
Improving ASCAT Soil Moisture Retrievals With an Enhanced Spatially Variable
Vegetation Parameterization, IEEE T. Geosci. Remote, 1–16, https://doi.org/10.1109/TGRS.2020.3041340, 2020.
Han, P., Long, D., Han, Z., Du, M., Dai, L., and Hao, X.: Improved
understanding of snowmelt runoff from the headwaters of China's Yangtze
River using remotely sensed snow products and hydrological modeling, Remote
Sens. Environ., 224, 44–59, https://doi.org/10.1016/j.rse.2019.01.041, 2019.
Hiebl, J. and Frei, C.: Daily temperature grids for Austria since
1961–concept, creation and applicability, Theor. Appl. Climatol., 124, 161–178, https://doi.org/10.1007/s00704-015-1411-4, 2016.
Hiebl, J. and Frei, C.: Daily precipitation grids for Austria since
1961–Development and evaluation of a spatial dataset for hydroclimatic
monitoring and modelling, Theor. Appl. Climatol., 132, 327–345,
https://doi.org/10.1007/s00704-017-2093-x, 2018.
Immerzeel, W. and Droogers, P.: Calibration of a distributed hydrological
model based on satellite evapotranspiration, J. Hydrol., 349,
411–424, https://doi.org/10.1016/j.jhydrol.2007.11.017, 2008.
Kim, H., Wigneron, J.-P., Kumar, S., Dong, J., Wagner, W., Cosh, M. H.,
Bosch, D. D., Collins, C. H., Starks, P. J., Seyfried, M., and Lakshmi, V.:
Global scale error assessments of soil moisture estimates from
microwave-based active and passive satellites and land surface models over
forest and mixed irrigated/dryland agriculture regions, Remote Sens.
Environ., 251, 112052, https://doi.org/10.1016/j.rse.2020.112052, 2020.
Kavetski, D., Kuczera, G., and Franks, S. W.: Bayesian analysis of input
uncertainty in hydrological modeling: 1. Theory, Water Resour. Res.,
42, W03408, https://doi.org/10.1029/2005WR004368, 2006.
Kosugi, K.: Three-parameter lognormal distribution model for soil water
retention, Water Resour. Res., 30, 891–901,
https://doi.org/10.1029/93wr02931, 1994.
Kosugi, K.: Lognormal Distribution Model for Unsaturated Soil Hydraulic
Properties, Water Resour. Res., 32, 2697–2703,
https://doi.org/10.1029/96wr01776, 1996.
Kundu, D., Vervoort, R. W., and van Ogtrop, F. F.: The value of remotely
sensed surface soil moisture for model calibration using SWAT, Hydrol.
Process., 31, 2764–2780, https://doi.org/10.1002/hyp.11219, 2017.
Kunnath-Poovakka, A., Ryu, D., Renzullo, L., and George, B.: The efficacy of
calibrating hydrologic model using remotely sensed evapotranspiration and
soil moisture for streamflow prediction, J. Hydrol., 535, 509–524,
https://doi.org/10.1016/j.jhydrol.2016.02.018, 2016.
Li, Y., Grimaldi, S., Pauwels, V. R., and Walker, J. P.: Hydrologic model
calibration using remotely sensed soil moisture and discharge measurements:
The impact on predictions at gauged and ungauged locations, J.
Hydrol., 557, 897–909, https://doi.org/10.1016/j.jhydrol.2018.01.013,
2018.
Lo, M. H., Famiglietti, J. S., Yeh, P. F., and Syed, T.: Improving parameter
estimation and water table depth simulation in a land surface model using
GRACE water storage and estimated base flow data, Water Resour. Res.,
46, W05517, https://doi.org/10.1029/2009WR007855, 2010.
Long, D., Bai, L., Yan, L., Zhang, C., Yang, W., Lei, H., Quan, J., Meng,
X., and Shi, C.: Generation of spatially complete and daily continuous
surface soil moisture of high spatial resolution, Remote Sens.
Environ., 233, 111364, https://doi.org/10.1016/j.rse.2019.111364, 2019.
López López, P., Sutanudjaja, E. H., Schellekens, J., Sterk, G., and Bierkens, M. F. P.: Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products, Hydrol. Earth Syst. Sci., 21, 3125–3144, https://doi.org/10.5194/hess-21-3125-2017, 2017.
Merz, R. and Blöschl, G.: A regional analysis of event runoff
coefficients with respect to climate and catchment characteristics in
Austria, Water Resour. Res., 45, W01405, https://doi.org/10.1029/2008wr007163,
2009.
Merz, R., Parajka, J., and Blöschl, G.: Time stability of catchment
model parameters: Implications for climate impact analyses, Water Resour.
Res., 47, W02531, https://doi.org/10.1029/2010wr009505, 2011.
Milzow, C., Krogh, P. E., and Bauer-Gottwein, P.: Combining satellite radar altimetry, SAR surface soil moisture and GRACE total storage changes for hydrological model calibration in a large poorly gauged catchment, Hydrol. Earth Syst. Sci., 15, 1729–1743, https://doi.org/10.5194/hess-15-1729-2011, 2011.
Mousa, B. G. and Shu, H.: Spatial Evaluation and Assimilation of SMAP,
SMOS, and ASCAT Satellite Soil Moisture Products Over Africa Using
Statistical Techniques, Earth Space Sci., 7, e2019EA000841,
https://doi.org/10.1029/2019ea000841, 2020.
Muñoz Sabater, J.: ERA5-Land hourly data from 1981 to present, [Dataset], Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.e2161bac, 2019.
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An
Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer
Observations, IEEE T. Geosci. Remote, 47,
1999–2013, https://doi.org/10.1109/TGRS.2008.2011617, 2009.
Naeini, M. R., Yang, T., Sadegh, M., AghaKouchak, A., Hsu, K.-l.,
Sorooshian, S., Duan, Q., and Lei, X.: Shuffled complex-self adaptive hybrid
evolution (SC-SAHEL) optimization framework, Environ. Modell.
Softw., 104, 215–235, https://doi.org/10.1016/j.envsoft.2018.03.019, 2018.
NASA National Snow and Ice Data Center: available at: https://nsidc.org/, last access: 22 March 2021.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I–A discussion of principles, J. Hydrol., 10,
282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Nijzink, R. C., Almeida, S., Pechlivanidis, I. G., Capell, R., Gustafssons,
D., Arheimer, B., Parajka, J., Freer, J., Han, D., Wagener, T., van Nooijen,
R. R. P., Savenije, H. H. G., and Hrachowitz, M.: Constraining Conceptual
Hydrological Models With Multiple Information Sources, Water Resour.
Res., 54, 8332–8362, https://doi.org/10.1029/2017wr021895, 2018.
Parajka, J. and Blöschl, G.: Validation of MODIS snow cover images over Austria, Hydrol. Earth Syst. Sci., 10, 679–689, https://doi.org/10.5194/hess-10-679-2006, 2006.
Parajka, J. and Blöschl, G.: The value of MODIS snow cover data in
validating and calibrating conceptual hydrologic models, J.
Hydrol., 358, 240–258, https://doi.org/10.1016/j.jhydrol.2008.06.006,
2008.
Parajka, J., Merz, R., and Blöschl, G.: Estimation of daily potential
evapotranspiration for regional water balance modeling in Austria, in: 11th
International Poster Day and Institute of Hydrology Open Day “Transport of
Water, Chemicals and Energy in the Soil – Crop Canopy – Atmosphere System”,
Slovak Academy of Sciences, 20 November 2003, Bratislava, 299–306, 2003.
Parajka, J., Naeimi, V., Blöschl, G., Wagner, W., Merz, R., and Scipal, K.: Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale, Hydrol. Earth Syst. Sci., 10, 353–368, https://doi.org/10.5194/hess-10-353-2006, 2006.
Parajka, J., Merz, R., and Blöschl, G.: Uncertainty and multiple
objective calibration in regional water balance modelling: case study in 320
Austrian catchments, Hydrol. Proc., 21, 435–446,
https://doi.org/10.1002/hyp.6253, 2007.
Parajka, J., Naeimi, V., Blöschl, G., and Komma, J.: Matching ERS scatterometer based soil moisture patterns with simulations of a conceptual dual layer hydrologic model over Austria, Hydrol. Earth Syst. Sci., 13, 259–271, https://doi.org/10.5194/hess-13-259-2009, 2009.
Pfeil, I., Vreugdenhil, M., Hahn, S., Wagner, W., Strauss, P., and
Blöschl, G.: Improving the seasonal representation of ASCAT soil
moisture and vegetation dynamics in a temperate climate, Remote Sens., 10,
1788, https://doi.org/10.3390/rs10111788, 2018.
Rajib, M. A., Merwade, V., and Yu, Z.: Multi-objective calibration of a
hydrologic model using spatially distributed remotely sensed/in-situ soil
moisture, J. Hydrol., 536, 192–207,
https://doi.org/10.1016/j.jhydrol.2016.02.037, 2016.
Rakovec, O., Kumar, R., Attinger, S., and Samaniego, L.: Improving the
realism of hydrologic model functioning through multivariate parameter
estimation, Water Resour. Res., 52, 7779–7792,
https://doi.org/10.1002/2016WR019430, 2016.
Seibert, J.: Multi-criteria calibration of a conceptual runoff model using a genetic algorithm, Hydrol. Earth Syst. Sci., 4, 215–224, https://doi.org/10.5194/hess-4-215-2000, 2000.
Sleziak, P., Szolgay, J., Hlavčová, K., Duethmann, D., Parajka, J.,
and Danko, M.: Factors controlling alterations in the performance of a
runoff model in changing climate conditions, J. Hydrol. Hydromech., 66, 381, https://doi.org/10.2478/johh-2018-0031, 2018.
Sleziak, P., Szolgay, J., Hlavčová, K., Danko, M., and Parajka, J.:
The effect of the snow weighting on the temporal stability of hydrologic
model efficiency and parameters, J. Hydrol., 583, 124639,
https://doi.org/10.1016/j.jhydrol.2020.124639, 2020.
Sutanudjaja, E. H., van Beek, L. P. H., de Jong, S. M., van Geer, F. C., and
Bierkens, M. F. P.: Calibrating a large-extent high-resolution coupled
groundwater-land surface model using soil moisture and discharge data, Water
Resour. Res., 50, 687–705, https://doi.org/10.1002/2013wr013807, 2014.
Széles, B., Parajka, J., Hogan, P., Silasari, R., Pavlin, L., Strauss,
P., and Blöschl, G.: The Added Value of Different Data Types for
Calibrating and Testing a Hydrologic Model in a Small Catchment, Water
Resour. Res., 56, e2019WR026153, https://doi.org/10.1029/2019WR026153,
2020.
Széles, B., Parajka, J., Hogan, P., Silasari, R., Pavlin, L., Strauss,
P., and Blöschl, G.: Stepwise prediction of runoff using proxy data in a
small agricultural catchment, J. Hydrol. Hydromech., 69,
691–711, https://doi.org/10.2478/johh-2020-0029, 2021.
Tong, R., Parajka, J., Komma, J., and Blöschl, G.: Mapping snow cover
from daily Collection 6 MODIS products over Austria, J. Hydrol.,
590, 125548, https://doi.org/10.1016/j.jhydrol.2020.125548, 2020.
Trautmann, T., Koirala, S., Carvalhais, N., Eicker, A., Fink, M., Niemann, C., and Jung, M.: Understanding terrestrial water storage variations in northern latitudes across scales, Hydrol. Earth Syst. Sci., 22, 4061–4082, https://doi.org/10.5194/hess-22-4061-2018, 2018.
TU Wien: Soil Water Index (SWI) V3, available at: https://land.copernicus.eu/global/products/swi/, Copernicus Global Land Service, last access: 17 March 2021.
Udnæs, H.-C., Alfnes, E., and Andreassen, L. M.: Improving runoff
modelling using satellite-derived snow covered area?, Hydrol. Res.,
38, 21–32, https://doi.org/10.2166/nh.2007.032, 2007.
Vergopolan, N., Chaney, N. W., Beck, H. E., Pan, M., Sheffield, J., Chan,
S., and Wood, E. F.: Combining hyper-resolution land surface modeling with
SMAP brightness temperatures to obtain 30-m soil moisture estimates, Remote
Sens. Environ., 242, 111740,
https://doi.org/10.1016/j.rse.2020.111740, 2020.
Viglione, A., Parajka, J., Rogger, M., Salinas, J. L., Laaha, G., Sivapalan, M., and Blöschl, G.: Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria, Hydrol. Earth Syst. Sci., 17, 2263–2279, https://doi.org/10.5194/hess-17-2263-2013, 2013.
Viglione, A. and Parajka, J.: TUWmodel: Lumped/Semi-Distributed Hydrological Model for Education Purposes, R package version 1.1-1, available at: https://CRAN.R-project.org/package=TUWmodel (last access: 17 March 2021), 2020.
Wagener, T. and Montanari, A.: Convergence of approaches toward reducing
uncertainty in predictions in ungauged basins, Water Resour. Res., 47,
https://doi.org/10.1029/2010WR009469, 2011.
Wagner, W., Lemoine, G., Borgeaud, M., and Rott, H.: A study of vegetation
cover effects on ERS scatterometer data, IEEE T. Geosci. Remote, 37, 938–948, https://doi.org/10.1109/36.752212, 1999.
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S.,
Figa-Saldaña, J., De Rosnay, P., Jann, A., and Schneider, S.: The ASCAT
soil moisture product: A review of its specifications, validation results,
and emerging applications, Meteorol. Z., 22, 5–33,
https://doi.org/10.1127/0941-2948/2013/0399, 2013.
Wagner, W., Brocca, L., Naeimi, V., Reichle, R., Draper, C., Jeu, R. d.,
Ryu, D., Su, C., Western, A., Calvet, J., Kerr, Y. H., Leroux, D. J.,
Drusch, M., Jackson, T. J., Hahn, S., Dorigo, W., and Paulik, C.:
Clarifications on the “Comparison Between SMOS, VUA, ASCAT, and ECMWF Soil
Moisture Products Over Four Watersheds in U.S.”, IEEE T.
Geosci. Remote, 52, 1901–1906,
https://doi.org/10.1109/TGRS.2013.2282172, 2014.
Wanders, N., Bierkens, M. F. P., de Jong, S. M., de Roo, A., and
Karssenberg, D.: The benefits of using remotely sensed soil moisture in
parameter identification of large-scale hydrological models, Water Resour.
Res., 50, 6874–6891, https://doi.org/10.1002/2013wr014639, 2014.
Werth, S. and Güntner, A.: Calibration analysis for water storage variability of the global hydrological model WGHM, Hydrol. Earth Syst. Sci., 14, 59–78, https://doi.org/10.5194/hess-14-59-2010, 2010.
Zhang, Y., Chiew, F. H., Zhang, L., and Li, H.: Use of remotely sensed
actual evapotranspiration to improve rainfall–runoff modeling in Southeast
Australia, J. Hydrometeorol., 10, 969–980,
https://doi.org/10.1175/2009JHM1061.1, 2009.
Zhang, Y., Schaap, M. G., and Zha, Y.: A High-Resolution Global Map of Soil
Hydraulic Properties Produced by a Hierarchical Parameterization of a
Physically Based Water Retention Model, Water Resour. Res., 54,
9774–9790, https://doi.org/10.1029/2018wr023539, 2018.
Zhang, Y. and Schaap, M. G.: A High-Resolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically-Based Water Retention Model, Harvard Dataverse, https://doi.org/10.7910/DVN/UI5LCE, 2018.
Short summary
We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index...