A generalized maintenance of variance extension procedure for extending correlated series

Grygier, Jan C.; Stedinger, Jery R.; Yin, Hongbing

doi:10.1029/wr025i003p00345

Cited by 25 publications

(17 citation statements)

References 15 publications

(13 reference statements)

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“…Various MOVE techniques were first suggested by Hirsch (1982), and later improved slightly by Vogel & Stedinger (1985) Grygier et al (1989) and others, to reduce the bias and variance in estimates of the mean and variance of the flows at the short record site and to obtain a reasonable and unique extended streamflow record.…”

Section: Extension Of Short Daily Streamflow Recordsmentioning

confidence: 99%

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Beránková

Vogel

Fiala

et al. 2010

Hydrological Sciences Journal

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Agricultural watersheds in the Czech Republic are one of the primary sources of non-point-source phosphorus (P) loads in receiving waters. Since such non-point sources are generally located in headwater catchments, streamflow and P concentration data are sparse. We show how very short daily streamflow and P concentration records can be combined with nearby longer existing daily streamflow records to result in reliable estimates of daily and annual P concentrations and loads. Maintenance of variance streamflow record extension methods (MOVE) can be employed to extend short streamflow records. Constituent load regressions are used to predict daily P constituent loads from streamflow and other time varying characteristics. Annual P loads are then estimated for individual watersheds. Resulting annual P load estimates ranged from 0.21 to 95.4 kg year -1 with a mean value of 11.77 kg year -1 . Similarly annual P yield estimates ranged from 0.01 to 0.3 kg ha -1 year -1 with an average yield of 0.07 kg ha -1 year -1. We document how short records of daily streamflow and P concentrations can be combined with a national network of daily streamflow records in the Czech Republic to arrive at meaningful and reliable estimates of annual P loads for small agricultural watersheds.

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Section: Extension Of Short Daily Streamflow Recordsmentioning

confidence: 99%

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Beránková

Vogel

Fiala

et al. 2010

Hydrological Sciences Journal

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“…MOVEs can also use multiple long flow series to extend the short flow series (Alley and Burns, 1983;Grygier et al, 1989). However, it is generally believed that better performance can be achieved by using a single nearby long flow series with a strong correlation with the short flow series.…”

Section: Maintenance Of Variance Extensionsmentioning

confidence: 98%

Bootstrapped artificial neural networks for synthetic flow generation with a small data sample

Jia

Culver

2006

Journal of Hydrology

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“…A suite of methods, including the maintenance of variance extension (MOVE) techniques, the Generalized MOVE (GMOVE), the modified Kendall-Theil Robust Line (KTRL2) and the Robust Line of Organic Correlation (RLOC), do not suffer from this problem (e.g. Grygier et al 1989;Hirsch 1979;Hirsch 1982;Vogel and Stedinger 1985;Khalil and Adamowski 2012;. Another difficulty is that variables may be nonlinearly correlated.…”

Section: Introductionmentioning

confidence: 98%

Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series

Pedretti

Beckie

2015

Stoch Environ Res Risk Assess

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Two-station pairing approaches are routinely used to infill missing information in incomplete rainfall databases. We evaluated the performance of three simple methodologies to reconstruct incomplete time series in presence of variable nonlinear correlation between data pairs. Nonlinearity stems from the statistics describing the marginal peak-over-threshold (POT) values of rainfall events. A Monte Carlo analysis was developed to quantitatively assess expected errors from the use of chronological pairing (CP) with linear and nonlinear regression and frequency pairing (FP). CP is based on a priori selection of regression functions, while FP is based on matching the probability of non-exceedance of an event from one time series with the probability of non-exceedance of a similar event from another time series. We adopted a generalized Pareto (GP) model to describe POT events, and a t-copula algorithm to generate reference nonlinearly correlated pairs of random temporal distributions distributed according with the GP model. The results suggest that the optimal methodology strongly depends on GP statistics. In general, CP seems to provide the lowest errors when GP statistics were similar and correlation became linear; we found that a power-2 function performs well for the selected statistics when the number of missing points is limited. FP outperforms the other methods when POT statistics are different and variables are markedly nonlinearly correlated. Ensemble-based results seem to be supported by the analysis of observed precipitation at two real-world gauge stations.

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A generalized maintenance of variance extension procedure for extending correlated series

Cited by 25 publications

References 15 publications

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Bootstrapped artificial neural networks for synthetic flow generation with a small data sample

Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series

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