Mapping long-term regional runoff in the eastern United States using automated approaches

Bishop, Gary D.; Church, M. Robbins

doi:10.1016/0022-1694(94)02641-n

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…The FHWA used streamflow estimates that were generalized from a national annual-runoff map to estimate the effects of highway runoff on streams and lakes (Driscoll and others, 1990a, b). The USEPA also has developed runoff-contour maps for use in planning-level analyses of water-quality data (Bishop and Church, 1995).…”

Section: Mass Balance Approachmentioning

confidence: 99%

Stochastic empirical loading and dilution model (SELDM) version 1.0.0

Granato¹

2013

Techniques and Methods

305

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Section: Mass Balance Approachmentioning

confidence: 99%

Stochastic empirical loading and dilution model (SELDM) version 1.0.0

Granato¹

2013

Techniques and Methods

305

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“…Streamflows are organized hierarchically along a stream network and typically conserve mass (Sauquet et al, 2000;Sauquet, 2006;Skøien and Blöschl, 2007). For this reason, topological kriging (top-kriging) was developed to incorporate the river network and its geographic extent into kriging estimates (Bishop et al, 1998;Sauquet et al, 2000;Sauquet, 2006;Skøien et al, 2006). In studies exploring the prediction of mean annual runoff (Skøien et al, 2006), percentiles, and other indices of the streamflow distribution (Castiglioni et al, 2011;Archfield et al, 2013) and streamflow signatures (Viglione et al, 2013), top-kriging has been shown to outperform many other techniques, including ordinary kriging.…”

Section: Introductionmentioning

confidence: 99%

Ordinary kriging as a tool to estimate historical daily streamflow records

Farmer

2016

Hydrol. Earth Syst. Sci.

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Abstract. Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash-Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.

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Section: Introductionmentioning

confidence: 99%

Ordinary kriging as a tool to estimate historical daily streamflow records

Farmer¹

2016

Preprint

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Abstract. Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial covariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial covariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more-common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash-Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.

show abstract

Mapping long-term regional runoff in the eastern United States using automated approaches

Cited by 9 publications

References 9 publications

Stochastic empirical loading and dilution model (SELDM) version 1.0.0

Stochastic empirical loading and dilution model (SELDM) version 1.0.0

Ordinary kriging as a tool to estimate historical daily streamflow records

Ordinary kriging as a tool to estimate historical daily streamflow records

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