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Approximate confidence intervals for design floods for a single site using a neural network
Author(s) -
Whitley Robert,
Hromadka T. V.
Publication year - 1999
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/1998wr900016
Subject(s) - confidence interval , statistics , skew , robust confidence intervals , artificial neural network , flood myth , cdf based nonparametric confidence interval , standard deviation , confidence distribution , computation , mathematics , hydrology (agriculture) , computer science , algorithm , geology , geography , artificial intelligence , geotechnical engineering , telecommunications , archaeology
A basic problem in hydrology is the computation of confidence levels for the value of the T ‐year flood when it is obtained from a log Pearson III distribution using the estimated mean, estimated standard deviation, and estimated skew. Here we give a practical method for finding approximate one‐sided or two‐sided confidence intervals for the 100‐year flood based on data from a single site. These confidence intervals are generally accurate to within a percent or two, as tested by simulations, and are obtained by use of a neural network.
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