Journal ArticleDOI
a Comparison of Methods for Estimating Low Flow Characteristics of Streams
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TLDR
In this paper, the authors compared four methods for estimating the 7-day, 10-year and 7day, 20-year low flows for streams using the bootstrap method.Abstract:
Four methods for estimating the 7-day, 10-year and 7-day, 20-year low flows for streams are compared by the bootstrap method. The bootstrap method is a Monte Carlo technique in which random samples are drawn from an unspecified sampling distribution defined from observed data. The nonparametric nature of the bootstrap makes it suitable for comparing methods based on a flow series for which the true distribution is unknown. Results show that the two methods based on hypothetical distributions (Log-Pearson III and Weibull) had lower mean square errors than did the Box-Cox transformation method or the Log-Boughton method which is based on a fit of plotting positions.read more
Citations
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Journal ArticleDOI
Low flow hydrology: a review
TL;DR: Low-flow hydrology is a discipline which deals with minimum flow in a river during the dry periods of the year as mentioned in this paper, and it has been extensively studied in the literature.
Journal ArticleDOI
A Nearest Neighbor Bootstrap For Resampling Hydrologic Time Series
Upmanu Lall,Ashish Sharma +1 more
TL;DR: The motivation for this work comes from a desire to preserve the dependence structure of the time series while bootstrapping (resampling it with replacement), and the method is data driven and is preferred where the investigator is uncomfortable with prior assumptions.
Journal ArticleDOI
A k‐nearest‐neighbor simulator for daily precipitation and other weather variables
Balaji Rajagopalan,Upmanu Lall +1 more
TL;DR: In this paper, a multivariate, nonparametric time series simulation method is provided to generate random sequences of daily weather variables that "honor" the statistical properties of the historical data of the same weather variables at the site.
Journal ArticleDOI
Drought Analysis in the Awash River Basin, Ethiopia
TL;DR: In this paper, the authors analyzed the Awash River Basin of Ethiopia based on meteorological and hydrological variables and found that extreme events occur most frequently in the Upper and Middle Awash Basin.
Journal ArticleDOI
Streamflow simulation: A nonparametric approach
TL;DR: In this article, a nonparametric method for the synthesis of streamflow that is data-driven and avoids prior assumptions as to the form of dependence (e.g., linear or nonlinear) and the shape of the probability density functions (i.e., Gaussian) is presented.
References
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Journal ArticleDOI
Bootstrap Methods: Another Look at the Jackknife
TL;DR: In this article, the authors discuss the problem of estimating the sampling distribution of a pre-specified random variable R(X, F) on the basis of the observed data x.
Journal ArticleDOI
An Analysis of Transformations
George E. P. Box,David Cox +1 more
TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.
Book
Statistical methods in hydrology
TL;DR: In this paper, the authors present many statistical tools helpful to engineers and hydrologists, then demonstrate their uses in solving hydrologic problems, and provide examples and problems with which they can be used.
Journal ArticleDOI
The Probability Plot Correlation Coefficient Test for Normality
TL;DR: In this paper, the normal probability plot correlation coefficient (NPC) was used as a test statistic for the composite hypothesis of normality, and the proposed test statistic is conceptnally simple, is compntationally convenient, and is readily extendible to testing non-normal distributional hypotheses.
Journal ArticleDOI
Unbiased plotting positions — A review
TL;DR: In this article, it is shown that a worthwhile criterion can be based on desired statistical properties of the plot, rather than on comparison of plotting positions with estimates of probability for individual sample values.