Articles | Volume 24, issue 10
https://doi.org/10.5194/hess-24-4869-2020
© Author(s) 2020. 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-24-4869-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Oct 2020
Research article |
| 13 Oct 2020
| 13 Oct 2020
Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe
Stefania Camici
CORRESPONDING AUTHOR
National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
Christian Massari
National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
Luca Ciabatta
National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
Ivan Marchesini
National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
Luca Brocca
National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, Italy
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Jacopo Dari, Paolo Filippucci, and Luca Brocca
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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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Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
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Hydrol. Earth Syst. Sci., 26, 4773–4800, https://doi.org/10.5194/hess-26-4773-2022, https://doi.org/10.5194/hess-26-4773-2022, 2022
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The
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Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
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Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
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This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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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.
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.
Christian Massari, Francesco Avanzi, Giulia Bruno, Simone Gabellani, Daniele Penna, and Stefania Camici
Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, https://doi.org/10.5194/hess-26-1527-2022, 2022
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Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
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Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, Giorgio Vacchiano, Christian Massari, and Luca Brocca
Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, https://doi.org/10.5194/hess-25-5589-2021, 2021
Short summary
Short summary
We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
Cited articles
Adeyewa, Z. D. and Nakamura, K.: Validation of TRMM radar rainfall data
over major climatic regions in Africa, J. Appl. Meteorol., 42, 331–347,
https://doi.org/10.1175/1520-0450(2003)042<0331:VOTRRD>2.0.CO;2, 2003.
Artan, G., Gadain, H., Smith, J. L., Asante, K., Bandaragoda, C. J., and
Verdin, J. P.: Adequacy of satellite derived rainfall data for stream flow
modelling, Nat. Hazards, 43, 167–185, https://doi.org/10.1007/s11069-007-9121-6, 2007.
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017.
Berghuijs, W. R., Harrigan, S., Molnar, P., Slater, L. J., and Kirchner, J.
W.: The relative importance of different flood-generating mechanisms across
Europe, Water. Resour. Res., 55, 6, 4582–4593, https://doi.org/10.1029/2019WR024841, 2019.
Bisselink, B., Zambrano-Bigiarini, M., Burek, P., and De Roo, A.: Assessing
the role of uncertain precipitation estimates on the robustness of
hydrological model parameters under highly variable climate conditions, J.
Hydrol. Reg. Stud., 8, 112–129, https://doi.org/10.1016/j.ejrh.2016.09.003, 2016.
Bitew, M. M. and Gebremichael, M.: Evaluation of satellite rainfall products
through hydrologic simulation in a fully distributed hydrologic model, Water
Resour. Res., 47, W06526, https://doi.org/10.1029/2010WR009917,
2011.
Brocca, L., Melone, F., and Moramarco, T.: Distributed rainfall–runoff
modelling for flood frequency estimation and flood forecasting, Hydrol.
Process., 25, 18, 2801–2813, https://doi.org/10.1002/hyp.8042,
2011 (data available at: http://hydrology.irpi.cnr.it/download-area/midsc-code/, last access: 2 Ocotber 2020).
Brocca, L., Liersch, S., Melone, F., Moramarco, T., and Volk, M.: Application of a model-based rainfall–runoff database as efficient tool for flood risk management, Hydrol. Earth Syst. Sci., 17, 3159–3169, https://doi.org/10.5194/hess-17-3159-2013, 2013a.
Brocca, L., Moramarco, T., Dorigo, W., and Wagner, W.: Assimilation of
satellite soil moisture data into rainfall–runoff modelling for several
catchments worldwide. 2013 IEEE International Geoscience and Remote Sensing
Symposium – IGARSS, 21–26 July 2013, Melbourne, Australia, 2281–2284,
https://doi.org/10.1109/IGARSS.2013.6723273, 2013b.
Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer,
S., Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural
rain gauge: estimating global rainfall from satellite soil moisture data, J.
Geophys. Res., 119, 9, 5128–5141,
https://doi.org/10.1002/2014JD021489, 2014.
Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Schüller, L., Bojkov, B., and Wagner, W.: SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations, Earth Syst. Sci. Data, 11, 1583–1601, https://doi.org/10.5194/essd-11-1583-2019, 2019a.
Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Schüller, L., Bojkov, B., and Wagner, W.: SM2RAIN-ASCAT (2007–June 2020): global daily satellite rainfall from ASCAT soil moisture (Version 1.3), Zenodo, https://doi.org/10.5281/zenodo.3972958, 2019b.
Brown, J. E.: An analysis of the performance of hybrid infrared and
microwave satellite precipitation algorithms over India and adjacent
regions, Remote. Sens. Environ., 101, 63–81,
https://doi.org/10.1016/j.rse.2005.12.005, 2006.
Camici, S., Brocca, L., Melone, F., and Moramarco, T.: Impact of climate
change on flood frequency using different climate models and downscaling
approaches, J. Hydrol. Eng., 19, 8, 04014002, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000959, 2014.
Camici, S., Ciabatta, L., Massari, C., and Brocca, L.: How reliable are
satellite precipitation estimates for driving hydrological models: a
verification study over the Mediterranean area, J. Hydrol., 563, 950–961,
https://doi.org/10.1016/j.jhydrol.2018.06.067, 2018.
Casse, C., Gosset, M., Peugeot, C., Pedinotti, V., Boone, A., Tanimoun, B.
A., and Decharme, B.: Potential of satellite rainfall products to predict
Niger River flood events in Niamey, Atmos. Res., 163, 162–176, https://doi.org/10.1016/j.atmosres.2015.01.010, 2015.
Chen, F., Crow, W., and Holmes, T. R.: Improving long-term, retrospective
precipitation datasets using satellite surface soil moisture retrievals and
the soil moisture analysis rainfall tool, J. Appl. Remote Sens., 6, 063604,
https://doi.org/10.1117/1.JRS.6.063604, 2012.
Chintalapudi, S., Sharif, H., and Xie, H.: Sensitivity of distributed
hydrologic simulations to ground and satellite based rainfall products,
Water, 6, 5, 1221–1245, https://doi.org/10.3390/w6051221, 2014.
Cislaghi, A., Masseroni, D., Massari, C., Camici, S., and Brocca, L.:
Combining rainfall–runoff model and regionalization approach for flood and
water resource assessment in the western Po-Valley (Italy). Hydrolog. Sci.
J., 65, 348–370, https://doi.org/10.1080/02626667.2019.1690656, 2019.
Condom, T., Rau, P., and Espinoza, J. C.: Correction of TRMM 3B43 monthly
precipitation data over the mountainous areas of Peru during the period
1998–2007, Hydrol. Process., 25, 12, 1924–1933, https://doi.org/10.1002/hyp.7949, 2011.
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J., and Jones, P. D.: An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets, J. Geophys. Res.-Atmos., 123, 17, 9391–9409, https://doi.org/10.1029/2017JD028200, 2018.
Crochemore, L., Isberg, K., Pimentel, R., Pineda, L., Hasan, A., and
Arheimer, B.: Lessons learnt from checking the quality of openly accessible
river flow data worldwide, Hydrolog. Sci. J., 65, 5, 699–711,
https://doi.org/10.1080/02626667.2019.1659509, 2020.
Demaria, E. M., Nijssen, B., Valdés, J. B., Rodriguez, D. A., and Su,
F.: Satellite precipitation in southeastern South America: how do sampling
errors impact high flow simulations?, Int. J. River Basin Manag., 12,
1–13, https://doi.org/10.1080/15715124.2013.865637, 2014.
Do, H. X., Gudmundsson, L., Leonard, M., and Westra, S.: The Global Streamflow Indices and Metadata Archive (GSIM) – Part 1: The production of a daily streamflow archive and metadata, Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, 2018.
Ebert, E. E., Janowiak, J. E., and Kidd, C.: Comparison of near-real-time
precipitation estimates from satellite observations and numerical models,
B. Am. Meteorol. Soc., 88, 47–64, https://doi.org/10.1175/BAMS-88-1-47, 2007.
Ehsan Bhuiyan, M. A., Nikolopoulos, E. I., Anagnostou, E. N., Polcher, J., Albergel, C., Dutra, E., Fink, G., Martínez-de la Torre, A., and Munier, S.: Assessment of precipitation error propagation in multi-model global water resource reanalysis, Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, 2019.
Elgamal, A., Reggiani, P., and Jonoski, A.: Impact analysis of satellite
rainfall products on flow simulations in the Magdalena River Basin,
Colombia, J. Hydrol. Reg. Stud., 9, 85–103, https://doi.org/10.1016/j.ejrh.2016.09.001, 2017.
Gebregiorgis, A. S., Tian, Y., Peters-Lidard, C. D., and Hossain, F.:
Tracing hydrologic model simulation error as a function of satellite
rainfall estimation bias components and land use and land cover conditions,
Water Resour. Res., 48, W11509, https://doi.org/10.1029/2011WR011643, 2012.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition
of the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 1–2, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P.
D., and New, M.: A European daily high-resolution gridded data set of
surface temperature and precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113, D20119, https://doi.org/10.1029/2008JD010201, 2008 (data available at: https://www.ecad.eu/download/ensembles/download.php#datafiles, last access: 2 October 2020).
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface
temperature, J. Geophys. Res.-Atmos., 114, D21101, https://doi.org/10.1029/2009JD011799, 2009.
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dynam., 35, 5, 841–858, https://doi.org/10.1007/s00382-009-0698-1, 2010.
Hong, Y., Hsu, K. L., Moradkhani, H., and Sorooshian, S.: Uncertainty
quantification of satellite precipitation estimation and Monte Carlo
assessment of the error propagation into hydrologic response, Water Resour.
Res., 42, W08421, https://doi.org/10.1029/2005WR004398, 2006.
Hossain, F. and Anagnostou, E. N.: A two-dimensional satellite rainfall
error model, IEEE T. Geosci. Remote., 44, 6, 1511–1522, https://doi.org/10.1109/TGRS.2005.863866, 2006.
Hossain, F. and Huffman, G. J.: Investigating error metrics for satellite
rainfall data at hydrologically relevant scales, J. Hydrometeorol., 9,
563–575, https://doi.org/10.1175/2007JHM925.1, 2008.
Huffman, G.: TRMM (TMPA-RT) Near Real-Time Precipitation L3 3 hour 0.25 degree x 0.25 degree V7, edited by: MacRitchie, K., Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/TRMM/TMPA/3H-E/7, 2016.
Huffman, G. J., Adler, R. F., Bolvin, D. T., and Nelkin, E. J.: The TRMM
multi-satellite precipitation analysis (TMPA), in: Satellite rainfall
applications for surface hydrology, edited by: Gebremichael, M. and Hossain, F., Springer, Dordrecht, 3–22, https://doi.org/10.1007/978-90-481-2915-7, 2010.
Huffman, G., Bolvin, D., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C.,
Nelkin, E., and Xie, P.: Algorithm Theoretical Basis Document (ATBD) Version
4.5. NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE
Retrievals for GPM (IMERG) NASA, available at: https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/IMERG_ATBD_V5.pdf (last access: 2 October 2020), 2018.
Jiang, D. and Wang, K.: The Role of Satellite Remote Sensing in Improving
Simulated Streamflow: A Review, Water, 11, 1615, https://doi.org/10.3390/w11081615, 2019.
Joyce, R. J., Janowiak, J. E., Arkin, P. A., and Xie, P.: CMORPH: A method
that produces global precipitation estimates from passive microwave and
infrared data at high spatial and temporal resolution, J. Hydrometeorol.,
5, 487–503, https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2, 2004 (data available at: ftp://ftp.cpc.ncep.noaa.gov/precip/global_CMORPH/3-hourly_025deg/, last access: 2 October).
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube
basin under an ensemble of climate change scenarios, J. Hydrol., 424,
264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012.
Klok, E. J. and Tank, A. K.: Updated and extended European dataset of daily
climate observations, Int. J. Climatol., 29, 8, 1182–1191, https://doi.org/10.1002/joc.1779, 2009.
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019.
Kyselý, J. and Plavcová, E.: A critical remark on the applicability
of E-OBS European gridded temperature data set for validating control
climate simulations, J. Geophys. Res.-Atmos., 115, D23118, https://doi.org/10.1029/2010JD014123, 2010.
Lu, D. and Yong, B.: Evaluation and Hydrological Utility of the Latest GPM
IMERG V5 and GSMaP V7 Precipitation Products over the Tibetan Plateau,
Remote Sens., 10, 2022, https://doi.org/10.3390/rs10122022,
2018.
Maggioni, V., Reichle, R. H., and Anagnostou, E. N.: The effect of satellite
rainfall error modeling on soil moisture prediction uncertainty, J.
Hydrometeorol., 12, 413–428, https://doi.org/10.1175/2011JHM1355.1, 2011.
Maggioni, V., Vergara, H. J., Anagnostou, E. N., Gourley, J. J., Hong, Y.,
and Stampoulis, D.: Investigating the applicability of error correction
ensembles of satellite rainfall products in river flow simulations, J.
Hydrometeorol., 14, 1194–1211, https://doi.org/10.1175/JHM-D-12-074.1, 2013.
Maggioni, V. and Massari, C.: On the performance of satellite precipitation
products in riverine flood modeling: A review, J. Hydrol., 558, 214–224,
https://doi.org/10.1016/j.jhydrol.2018.01.039, 2018.
Massari, C., Brocca, L., Ciabatta, L., Moramarco, T., Gabellani, S.,
Albergel, C., de Rosnay, P., Puca, S., and Wagner, W.: The use of H-SAF soil
moisture products for operational hydrology: flood modelling over Italy,
Hydrology, 2, 2–22, https://doi.org/10.3390/hydrology2010002, 2015.
Massari, C., Camici, S., Ciabatta, L., and Brocca, L.: Exploiting satellite
surface soil moisture for flood forecasting in the Mediterranean area: state
update versus rainfall correction, Remote Sens., 10, 292, https://doi.org/10.3390/rs10020292, 2018.
Masseroni, D., Cislaghi, A., Camici, S., Massari, C., and Brocca, L.: A
reliable rainfall–runoff model for flood forecasting: review and
application to a semi-urbanized watershed at high flood risk in Italy,
Hydrol. Res., 48, 726–740, https://doi.org/10.2166/nh.2016.037, 2016.
Mei, Y., Nikolopoulos, E., Anagnostou, E., Zoccatelli, D., and Borga, M.:
Error analysis of satellite precipitation-driven modeling of flood events in
complex alpine terrain, Remote Sens., 8, 293, https://doi.org/10.3390/rs8040293, 2016.
Mei, Y., Anagnostou, E. N., Shen, X., and Nikolopoulos, E. I.: Decomposing
the satellite precipitation error propagation through the rainfall-runoff
processes, Adv. Water Resour., 109, 253–266, https://doi.org/10.1016/j.advwatres.2017.09.012, 2017.
Montani, A., Cesari, D., Marsigli, C., and Paccagnella, T.: Seven years of
activity in the field of mesoscale ensemble forecasting by the COSMO-LEPS
system: main achievements and open challenges, Tellus A, 63, 605–624, https://doi.org/10.1111/j.1600-0870.2010.00499.x, 2011.
Mouratidis, A., and Ampatzidis, D.: European Digital Elevation Model
Validation against Extensive Global Navigation Satellite Systems Data and
Comparison with SRTM DEM and ASTER GDEM in Central Macedonia (Greece). ISPRS
Int. J. Geo.-Inf., 8, 108, https://doi.org/10.3390/ijgi8030108, 2019.
Mugnai, A., Casella, D., Cattani, E., Dietrich, S., Laviola, S., Levizzani, V., Panegrossi, G., Petracca, M., Sanò, P., Di Paola, F., Biron, D., De Leonibus, L., Melfi, D., Rosci, P., Vocino, A., Zauli, F., Pagliara, P., Puca, S., Rinollo, A., Milani, L., Porcù, F., and Gattari, F.: Precipitation products from the hydrology SAF, Nat. Hazards Earth Syst. Sci., 13, 1959–1981, https://doi.org/10.5194/nhess-13-1959-2013, 2013.
Nikolopoulos, E. I., Anagnostou, E. N., Hossain, F., Gebremichael, M., and
Borga, M.: Understanding the scale relationships of uncertainty propagation
of satellite rainfall through a distributed hydrologic model, J.
Hydrometeorol., 11, 520–532, https://doi.org/10.1175/2009JHM1169.1, 2010.
Nikolopoulos, E. I., Anagnostou, E. N., and Borga, M.: Using high-resolution
satellite rainfall products to simulate a major flash flood event in
northern Italy, J. Hydrometeorol., 14, 171–185, https://doi.org/10.1175/JHM-D-12-09.1, 2012.
Pakoksung, K. and Takagi, M.: Effect of satellite based rainfall products
on river basin responses of runoff simulation on flood event, Model. Earth
Sys. Environ., 2, 143, https://doi.org/10.1007/s40808-016-0200-0, 2016.
Pan, M., Li, H., and Wood, E.: Assessing the skill of satellite-based
precipitation estimates in hydrologic applications, Water Resour. Res.,
46, W09535, https://doi.org/10.1029/2009WR008290, 2010.
Qi, W., Zhang, C., Fu, G., Sweetapple, C., and Zhou, H.: Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations, Hydrol. Earth Syst. Sci., 20, 903–920, https://doi.org/10.5194/hess-20-903-2016, 2016.
Quintero, F., Krajewski, W. F., Mantilla, R., Small, S., and Seo, B. C.: A
spatial–dynamical framework for evaluation of satellite rainfall products
for flood prediction, J Hydrometeorol, 17, 2137–2154, https://doi.org/10.1175/JHM-D-15-0195.1, 2016.
Ren, P., Li, J., Feng, P., Guo, Y., and Ma, Q.: Evaluation of multiple
satellite precipitation products and their use in hydrological modelling
over the Luanhe River basin, China. Water, 10, 677, https://doi.org/10.3390/w10060677, 2018.
Ricciardelli, E., Di Paola, F., Gentile, S., Cersosimo, A., Cimini, D.,
Gallucci, D., Geraldi, E., Larosa, S., Nilo, S. T., Ripepi, E., Romano, F.,
Viggiano, M.: Analysis of Livorno Heavy Rainfall Event: Examples of
Satellite Observation Techniques in Support of Numerical Weather Prediction,
Remote Sens., 10, 1549, https://doi.org/10.3390/rs10101549,
2018.
Satgé, F., Bonnet, M. P., Gosset, M., Molina, J., Lima, W. H. Y.,
Zolá, R. P., Timouk, F., and Garnier, J.: Assessment of satellite
rainfall products over the Andean plateau, Atmos. Res., 167, 1–14,
https://doi.org/10.1016/j.atmosres.2015.07.012, 2016.
Satgé, F., Ruelland, D., Bonnet, M.-P., Molina, J., and Pillco, R.: Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow-hydrological modelling in the Lake Titicaca region, Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, 2019.
Schaefli, B. and Gupta, H. V.: Do Nash values have value?, Hydrol.
Process., 21, 2075–2080, https://doi.org/10.1002/hyp.6825, 2007.
Serpetzoglou, E., Anagnostou, E. N., Papadopoulos, A., Nikolopoulos, E. I.,
and Maggioni, V.: Error propagation of remote sensing rainfall estimates in
soil moisture prediction from a land surface model, J. Hydrometeorol., 11,
705–720, https://doi.org/10.1175/2009JHM1166.1, 2010.
Shah, H. L., and Mishra, V.: Uncertainty and bias in satellite-based
precipitation estimates over Indian subcontinental basins: Implications for
real-time streamflow simulation and flood prediction, J. Hydrometeorol., 17,
615–636, https://doi.org/10.1175/JHM-D-15-0115.1, 2016.
Shrestha, N. K., Qamer, F. M., Pedreros, D., Murthy, M. S. R., Wahid, S. M.,
and Shrestha, M.: Evaluating the accuracy of Climate Hazard Group (CHG)
satellite rainfall estimates for precipitation based drought monitoring in
Koshi basin, Nepal, J. Hydrol. Reg. Stud., 13, 138–151, https://doi.org/10.1016/j.ejrh.2017.08.004, 2017.
Tapiador, F. J., Navarro, A., Levizzani, V., García-Ortega, E., Huffman,
G. J., Kidd, C., Kucera, P. A., Kummerow, C. D., Masunaga, H., Petersen, W. A., Roca, R., Sánchez, J.-L., Tao, W.-K., and Turk, F. J.: Global precipitation measurements for validating climate models, Atmos. Res., 197, 1–20, https://doi.org/10.1016/j.atmosres.2017.06.021, 2017.
Thiemig, V., Rojas, R., Zambrano-Bigiarini, M., and De Roo, A.: Hydrological
evaluation of satellite rainfall estimates over the Volta and Baro-Akobo
Basin, J. Hydrol., 499, 324–338, https://doi.org/10.1016/j.jhydrol.2013.07.012, 2013.
Valdés-Pineda, R., Demaría, E. M. C., Valdés, J. B., Wi, S., and Serrat-Capdevilla, A.: Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-473, 2016.
Vergara, H., Hong, Y., Gourley, J. J., Anagnostou, E. N., Maggioni, V.,
Stampoulis, D., and Kirstetter, P. E.: Effects of resolution of satellite
rainfall estimates on hydrologic modeling skill at different scales, J.
Hydrometeorol., 15, 593–613, https://doi.org/10.1175/JHM-D-12-0113.1, 2014.
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S., Figa, J., de Rosnay, P., Jann, A., Schneider, S., Komma, J., Kubu, G., Brugger, K., Aubrecht, C., Zuger, J., Gangkofner, U., Kienberger, S., Brocca, L., Wang, Y., Bloeschl, G., Eitzinger, J., Steinnocher, K., Zeil, P., and Rubel, F.: The ASCAT soil moisture product: A review of its
specifications, validation results, and emerging applications,
Meteorol. Z. (contrib. Atm. Sci.), 22, 5–33, https://doi.org/10.1127/0941-2948/2013/0399, 2013.
Yang, Y. and Luo, Y.: Evaluating the performance of remote sensing
precipitation products CMORPH, PERSIANN, and TMPA, in the arid region of
northwest China, Theor. Appl. Climatol., 118, 429–445, https://doi.org/10.1007/s00704-013-1072-0, 2014.
Yilmaz, K. K., Hogue, T. S., Hsu, K. L., Sorooshian, S., Gupta, H. V., and
Wagener, T.: Intercomparison of rain gauge, radar, and satellite
precipitation estimates with emphasis on hydrologic forecasting, J.
Hydrometeorol., 6, 497–517, https://doi.org/10.1175/JHM431.1,
2005.
Yong, B., Ren, L. L., Hong, Y., Wang, J. H., Gourley, J. J., Jiang, S. H.,
Gourley, J. J. Jiang, S.-H., Chen, X., and Wang, W.: Hydrologic evaluation
of Multisatellite Precipitation Analysis standard precipitation products in
basins beyond its inclined latitude band: A case study in Laohahe basin,
China, Water Resour. Res., 46, W07542, https://doi.org/10.1029/2009WR008965, 2010.
Zappa, M., Rotach, M. W., Arpagaus, M., Dorninger, M., Hegg, C., Montani,
A., Ranzi, R., Ament, F., Germann, U., Grossi, G., Jaun, S., Rossa, A., Vogt, S., Walser, A., Wehrhan, J., and Wunram, C.: MAP D-PHASE: real-time demonstration of hydrological
ensemble prediction systems, Atmos. Sci. Lett., 9, 80–87, https://doi.org/10.1002/asl.183, 2008.
Zeng, Q., Chen, H., Xu, C. Y., Jie, M. X., Chen, J., Guo, S. L., and Liu,
J.: The effect of rain gauge density and distribution on runoff simulation
using a lumped hydrological modelling approach, J. Hydrol., 563, 106–122,
https://doi.org/10.1016/j.jhydrol.2018.05.058, 2018.
Zhu, Q., Xuan, W., Liu, L., and Xu, Y. P.: Evaluation and hydrological
application of precipitation estimates derived from PERSIANN-CDR, TRMM
3B42V7, and NCEP-CFSR over humid regions in China, Hydrol. Process., 30, 17,
3061–3083, https://doi.org/10.1002/hyp.10846, 2016.
Short summary
The paper performs the most comprehensive European-scale evaluation to date of satellite rainfall products for river flow prediction. In doing so, how errors transfer from satellite-based rainfall products into flood simulation is investigated in depth and, for the first time, quantitative guidelines on the use of these products for hydrological applications are provided. This result can represent a keystone in the use of satellite rainfall products, especially in data-scarce regions.
The paper performs the most comprehensive European-scale evaluation to date of satellite...
