Ordinary kriging as a tool to estimate historical daily streamflow records

Abstract

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.

Prediction of streamflow regimes over large geographical areas: interpolated flow–duration curves for the Danube region

“…The scientific literature illustrates successful applications of top-kriging for predicting a wide spectrum of streamflow indices and variables: low flows (see e.g. Castiglioni et al 2011, Laaha et al 2014; high flows and floods (Merz et al 2008, Archfield et al 2013; stream temperature (Laaha et al 2013); habitat suitability indices (Ceola and Pugliese 2014); and daily streamflow series (Skøien and Blöschl 2007, de Lavenne et al 2016, Farmer 2016. Pugliese et al (2014Pugliese et al ( , 2016 proposed a method for using top-kriging to predict continuous FDCs at ungauged locations, as opposed to regional regression approaches, which model streamflow quantiles independently of each other.…”

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

“…We addressed the limited differences existing between drainage areas of E-HYPE and gauged basins by adopting the drainage-area ratio technique (DAR, see e.g. Farmer and Vogel, 2013), that is by rescaling daily streamflows according to drainage areas of the corresponding catchment. Such a method assumes the same unit daily streamflow for any pair of hydrologically similar catchments i and j , which reads as follows:…”

A Comparative Study of Statistical Methods for Daily Streamflow Estimation at Ungauged Basins in Turkey

“…Moreover, ANN methods coupled with the MA performed the best among all methods. On the other hand, statistical methods such as interpolation by inverse distance weighted (IDW) [21,22] and kriging [23,24], regression analysis [25,26], flow duration curves [27,28], and information transfer methods [29,30] are widely used in the estimation of streamflow. This study focuses on statistical methods for improving estimation accuracy and reliability for ungauged basins.…”