Articles | Volume 20, issue 7
https://doi.org/10.5194/hess-20-2721-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-2721-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Ordinary kriging as a tool to estimate historical daily streamflow records
U.S. Geological Survey, Box 25046, Denver Federal Center, MS 410,
Denver, CO 80225, USA
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41 citations as recorded by crossref.
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- Calibration of a hydrologic model in data-scarce Alaska using satellite and other gridded products K. Schneider & T. Hogue 10.1016/j.ejrh.2021.100979
- Spatial variations of runoff generation at watershed scale M. Vafakhah et al. 10.1007/s13762-018-1784-x
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- Calibration of the US Geological Survey National Hydrologic Model in Ungauged Basins Using Statistical At-Site Streamflow Simulations W. Farmer et al. 10.1061/(ASCE)HE.1943-5584.0001854
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- A geostatistical data-assimilation technique for enhancing macro-scale rainfall–runoff simulations A. Pugliese et al. 10.5194/hess-22-4633-2018
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- Proposal of methodology for spatial analysis applied to human development index in water basins J. Sales et al. 10.1007/s10708-018-9894-z
- Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework T. Roksvåg et al. 10.5194/hess-24-4109-2020
- Bias correction of simulated historical daily streamflow at ungauged locations by using independently estimated flow duration curves W. Farmer et al. 10.5194/hess-22-5741-2018
- Geospatial tools effectively estimate nonexceedance probabilities of daily streamflow at ungauged and intermittently gauged locations in Ohio W. Farmer & G. Koltun 10.1016/j.ejrh.2017.08.006
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Latest update: 23 Nov 2024
Short summary
The potential of geostatistical tools, leveraging the spatial structure and dependency of correlated time series, for the prediction of daily streamflow time series at unmonitored locations is explored. Simple geostatistical tools improve on traditional estimates of daily streamflow. The temporal evolution of spatial structure, including seasonal fluctuations, is also explored. The proposed method is contrasted with more advanced geostatistical methods and shown to be comparable.
The potential of geostatistical tools, leveraging the spatial structure and dependency of...