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NONPARAMETRIC STATISTICAL METHODS IN URBAN HYDROLOGIC RESEARCH 1
Author(s) -
McCuen Richard H.,
James L. Douglas
Publication year - 1972
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1972.tb05984.x
Subject(s) - watershed , nonparametric statistics , urbanization , surface runoff , flood myth , environmental science , hydrology (agriculture) , precipitation , hydrological modelling , time of concentration , statistics , computer science , geography , mathematics , meteorology , geology , climatology , geotechnical engineering , ecology , archaeology , machine learning , economics , biology , economic growth
. In urban hydrologic studies, it is often necessary to determine the effect of changes in urban land use patterns on such runoff characteristics as flood peaks and flow volumes. Nonparametric statistical methods have certain properties that make them a valuable tool for detecting hydrologic change caused by a treatment, such as urbanization, that changes watershed over a period of time. As many hydrologists do not have a working familiarity with nonparametric methods, a number of them are used for illustrative purposes to analyze the effect of urbanization on 24 years of annual flood peaks for a Louisville, Kentucky, watershed. In the example, urbanization was found to increase the central tendency, but not the dispersion of the peaks. Peak flows modeled by holding watershed parameters constant were also found to be increasing because of an upward trend in precipitation. By following the numerical examples in the paper and looking up test statistics in referenced sources, the reader can easily apply these methods to other situations.