Articles | Volume 10, issue 4
https://doi.org/10.5194/hess-10-469-2006
© Author(s) 2006. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
https://doi.org/10.5194/hess-10-469-2006
© Author(s) 2006. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
03 Jul 2006
Mapping mean and variance of runoff in a river basin
L. Gottschalk
Department of Geosciences, University of Oslo, P.O.~Box~1022 Blindern, 0315 Oslo, Norway
I. Krasovskaia
Department of Geosciences, University of Oslo, P.O.~Box~1022 Blindern, 0315 Oslo, Norway
E. Leblois
Cemagref, 3 bis quai Chauveau, CP 220, 69336 Lyon Cedex 09, France
E. Sauquet
Cemagref, 3 bis quai Chauveau, CP 220, 69336 Lyon Cedex 09, France
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Cited
26 citations as recorded by crossref.
- atakrig: An R package for multivariate area-to-area and area-to-point kriging predictions M. Hu & Y. Huang https://doi.org/10.1016/j.cageo.2020.104471
- Current awareness https://doi.org/10.1002/hyp.6661
- Enhancing SWOT discharge assimilation through spatiotemporal correlations Y. Yang et al. https://doi.org/10.1016/j.rse.2019.111450
- Does Catchment Nestedness Enhance Hydrological Similarity? A. Betterle & G. Botter https://doi.org/10.1029/2021GL094148
- Geostatistics for automatic estimation of environmental variables—some simple solutions J. Sk⊘ien et al. https://doi.org/10.1080/17499510802086769
- Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria A. Viglione et al. https://doi.org/10.5194/hess-17-2263-2013
- Hydro-stochastic interpolation coupling with the Budyko approach for prediction of mean annual runoff N. Qiu et al. https://doi.org/10.5194/hess-22-2891-2018
- Multifractal analysis of streamflow records of the East River basin (Pearl River), China Q. Zhang et al. https://doi.org/10.1016/j.physa.2008.11.025
- A top-down model to generate ensembles of runoff from a large number of hillslopes P. Furey et al. https://doi.org/10.5194/npg-20-683-2013
- A Comparison of Low Flow Estimates in Ungauged Catchments Using Regional Regression and the HBV-Model K. Engeland & H. Hisdal https://doi.org/10.1007/s11269-008-9397-7
- Distance measures for hydrological data having a support L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2011.03.020
- Spatial prediction on river networks: comparison of top-kriging with regional regression G. Laaha et al. https://doi.org/10.1002/hyp.9578
- Spatial Prediction of Stream Temperatures Using Top-Kriging with an External Drift G. Laaha et al. https://doi.org/10.1007/s10666-013-9373-3
- Conditioned empirical orthogonal functions for interpolation of runoff time series along rivers: Application to reconstruction of missing monthly records L. Li et al. https://doi.org/10.1016/j.jhydrol.2017.11.014
- Correlation and covariance of runoff revisited L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2010.12.011
- Simulated hydrological effects of grooming and snowmaking in a ski resort on the local water balance S. Morin et al. https://doi.org/10.5194/hess-27-4257-2023
- TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks M. Müller & S. Thompson https://doi.org/10.5194/hess-19-2925-2015
- A consistent set of trans-basin floods in Germany between 1952–2002 S. Uhlemann et al. https://doi.org/10.5194/hess-14-1277-2010
- rtop: An R package for interpolation of data with a variable spatial support, with an example from river networks J. Skøien et al. https://doi.org/10.1016/j.cageo.2014.02.009
- Space-time variability of climate variables and intermittent renewable electricity production – A review K. Engeland et al. https://doi.org/10.1016/j.rser.2017.05.046
- Spatiotemporal topological kriging of runoff time series J. Skøien & G. Blöschl https://doi.org/10.1029/2006WR005760
- Interpolation of monthly runoff along rivers applying empirical orthogonal functions: Application to the Upper Magdalena River, Colombia L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2015.06.029
- Ordinary kriging as a tool to estimate historical daily streamflow records W. Farmer https://doi.org/10.5194/hess-20-2721-2016
- Spatiotemporal interpolation of discharge across a river network by using synthetic SWOT satellite data R. Paiva et al. https://doi.org/10.1002/2014WR015618
- Joint mapping of statistical streamflow descriptors L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2012.11.040
- An approach to propagate streamflow statistics along the river network D. Ganora et al. https://doi.org/10.1080/02626667.2012.745643
26 citations as recorded by crossref.
- atakrig: An R package for multivariate area-to-area and area-to-point kriging predictions M. Hu & Y. Huang https://doi.org/10.1016/j.cageo.2020.104471
- Current awareness https://doi.org/10.1002/hyp.6661
- Enhancing SWOT discharge assimilation through spatiotemporal correlations Y. Yang et al. https://doi.org/10.1016/j.rse.2019.111450
- Does Catchment Nestedness Enhance Hydrological Similarity? A. Betterle & G. Botter https://doi.org/10.1029/2021GL094148
- Geostatistics for automatic estimation of environmental variables—some simple solutions J. Sk⊘ien et al. https://doi.org/10.1080/17499510802086769
- Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria A. Viglione et al. https://doi.org/10.5194/hess-17-2263-2013
- Hydro-stochastic interpolation coupling with the Budyko approach for prediction of mean annual runoff N. Qiu et al. https://doi.org/10.5194/hess-22-2891-2018
- Multifractal analysis of streamflow records of the East River basin (Pearl River), China Q. Zhang et al. https://doi.org/10.1016/j.physa.2008.11.025
- A top-down model to generate ensembles of runoff from a large number of hillslopes P. Furey et al. https://doi.org/10.5194/npg-20-683-2013
- A Comparison of Low Flow Estimates in Ungauged Catchments Using Regional Regression and the HBV-Model K. Engeland & H. Hisdal https://doi.org/10.1007/s11269-008-9397-7
- Distance measures for hydrological data having a support L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2011.03.020
- Spatial prediction on river networks: comparison of top-kriging with regional regression G. Laaha et al. https://doi.org/10.1002/hyp.9578
- Spatial Prediction of Stream Temperatures Using Top-Kriging with an External Drift G. Laaha et al. https://doi.org/10.1007/s10666-013-9373-3
- Conditioned empirical orthogonal functions for interpolation of runoff time series along rivers: Application to reconstruction of missing monthly records L. Li et al. https://doi.org/10.1016/j.jhydrol.2017.11.014
- Correlation and covariance of runoff revisited L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2010.12.011
- Simulated hydrological effects of grooming and snowmaking in a ski resort on the local water balance S. Morin et al. https://doi.org/10.5194/hess-27-4257-2023
- TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks M. Müller & S. Thompson https://doi.org/10.5194/hess-19-2925-2015
- A consistent set of trans-basin floods in Germany between 1952–2002 S. Uhlemann et al. https://doi.org/10.5194/hess-14-1277-2010
- rtop: An R package for interpolation of data with a variable spatial support, with an example from river networks J. Skøien et al. https://doi.org/10.1016/j.cageo.2014.02.009
- Space-time variability of climate variables and intermittent renewable electricity production – A review K. Engeland et al. https://doi.org/10.1016/j.rser.2017.05.046
- Spatiotemporal topological kriging of runoff time series J. Skøien & G. Blöschl https://doi.org/10.1029/2006WR005760
- Interpolation of monthly runoff along rivers applying empirical orthogonal functions: Application to the Upper Magdalena River, Colombia L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2015.06.029
- Ordinary kriging as a tool to estimate historical daily streamflow records W. Farmer https://doi.org/10.5194/hess-20-2721-2016
- Spatiotemporal interpolation of discharge across a river network by using synthetic SWOT satellite data R. Paiva et al. https://doi.org/10.1002/2014WR015618
- Joint mapping of statistical streamflow descriptors L. Gottschalk et al. https://doi.org/10.1016/j.jhydrol.2012.11.040
- An approach to propagate streamflow statistics along the river network D. Ganora et al. https://doi.org/10.1080/02626667.2012.745643
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