Ordinary kriging as a tool to estimate historical daily streamflow records

Hydrology and Earth System Sciences
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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.

Publication type Article
Publication Subtype Journal Article
Title Ordinary kriging as a tool to estimate historical daily streamflow records
Series title Hydrology and Earth System Sciences
DOI 10.5194/hess-20-2721-2016
Volume 20
Issue 7
Year Published 2016
Language English
Publisher Copernicus Publications
Contributing office(s) National Research Program - Central Branch
Description 15 p.
First page 2721
Last page 2735
Online Only (Y/N) N
Additional Online Files (Y/N) N
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