Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
HESS | Articles | Volume 22, issue 9
Hydrol. Earth Syst. Sci., 22, 4633–4648, 2018
https://doi.org/10.5194/hess-22-4633-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 4633–4648, 2018
https://doi.org/10.5194/hess-22-4633-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 06 Sep 2018

Research article | 06 Sep 2018

A geostatistical data-assimilation technique for enhancing macro-scale rainfall–runoff simulations

Alessio Pugliese et al.

Related authors

Geostatistical prediction of flow–duration curves in an index-flow framework
A. Pugliese, A. Castellarin, and A. Brath
Hydrol. Earth Syst. Sci., 18, 3801–3816, https://doi.org/10.5194/hess-18-3801-2014,https://doi.org/10.5194/hess-18-3801-2014, 2014

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe
Stefania Camici, Christian Massari, Luca Ciabatta, Ivan Marchesini, and Luca Brocca
Hydrol. Earth Syst. Sci., 24, 4869–4885, https://doi.org/10.5194/hess-24-4869-2020,https://doi.org/10.5194/hess-24-4869-2020, 2020
Short summary
Assimilation of Soil Moisture and Ocean Salinity (SMOS) brightness temperature into a large-scale distributed conceptual hydrological model to improve soil moisture predictions: the Murray–Darling basin in Australia as a test case
Renaud Hostache, Dominik Rains, Kaniska Mallick, Marco Chini, Ramona Pelich, Hans Lievens, Fabrizio Fenicia, Giovanni Corato, Niko E. C. Verhoest, and Patrick Matgen
Hydrol. Earth Syst. Sci., 24, 4793–4812, https://doi.org/10.5194/hess-24-4793-2020,https://doi.org/10.5194/hess-24-4793-2020, 2020
Short summary
Frequency and magnitude variability of Yalu River flooding: numerical analyses for the last 1000 years
Hui Sheng, Xiaomei Xu, Jian Hua Gao, Albert J. Kettner, Yong Shi, Chengfeng Xue, Ya Ping Wang, and Shu Gao
Hydrol. Earth Syst. Sci., 24, 4743–4761, https://doi.org/10.5194/hess-24-4743-2020,https://doi.org/10.5194/hess-24-4743-2020, 2020
Short summary
Assessing the degree of detail of temperature-based snow routines for runoff modelling in mountainous areas in central Europe
Marc Girons Lopez, Marc J. P. Vis, Michal Jenicek, Nena Griessinger, and Jan Seibert
Hydrol. Earth Syst. Sci., 24, 4441–4461, https://doi.org/10.5194/hess-24-4441-2020,https://doi.org/10.5194/hess-24-4441-2020, 2020
Short summary
Adaptive clustering: reducing the computational costs of distributed (hydrological) modelling by exploiting time-variable similarity among model elements
Uwe Ehret, Rik van Pruijssen, Marina Bortoli, Ralf Loritz, Elnaz Azmi, and Erwin Zehe
Hydrol. Earth Syst. Sci., 24, 4389–4411, https://doi.org/10.5194/hess-24-4389-2020,https://doi.org/10.5194/hess-24-4389-2020, 2020
Short summary

Cited articles

Alcamo, J., Döll, P., Henrichs, T., Kaspar, F., Lehner, B., Rösch, T., and Siebert, S.: Development and testing of the WaterGAP 2 global model of water use and availability, Hydrolog. Sci. J., 48, 317–337, https://doi.org/10.1623/hysj.48.3.317.45290, 2003. a
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. a
Archfield, S. A., Pugliese, A., Castellarin, A., Skøien, J. O., and Kiang, J. E.: Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?, Hydrol. Earth Syst. Sci., 17, 1575-1588, https://doi.org/10.5194/hess-17-1575-2013, 2013. a
Archfield, S. A., Clark, M., Arheimer, B., Hay, L. E., McMillan, H., Kiang, J. E., Seibert, J., Hakala, K., Bock, A., Wagener, T., Farmer, W. H., Andréassian, V., Attinger, S., Viglione, A., Knight, R., Markstrom, S., and Over, T.: Accelerating advances in continental domain hydrologic modeling, Water Resour. Res., 51, 10078–10091, https://doi.org/10.1002/2015WR017498, 2015. a
Arheimer, B., Wallman, P., Donnelly, C., Nyström, K., and Pers, C.: E-HypeWeb: Service for Water and Climate Information – and Future Hydrological Collaboration across Europe?, in: Environmental Software Systems. Frameworks of eEnvironment, IFIP Advances in Information and Communication Technology, Springer, Berlin, Heidelberg, 657–666, https://doi.org/10.1007/978-3-642-22285-6_71, 2011. a
Publications Copernicus
Download
Short summary
This research work focuses on the development of an innovative method for enhancing the predictive capability of macro-scale rainfall–runoff models by means of a geostatistical apporach. In our method, one can get enhanced streamflow simulations without any further model calibration. Indeed, this method is neither computational nor data-intensive and is implemented only using observed streamflow data and a GIS vector layer with catchment boundaries. Assessments are performed in the Tyrol region.
This research work focuses on the development of an innovative method for enhancing the...
Citation