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Regression models for predicting on‐site runoff from short‐duration connective storms
Author(s) -
Schreiber H. A.,
Kincaid D. R.
Publication year - 1967
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/wr003i002p00389
Subject(s) - surface runoff , antecedent moisture , thunderstorm , storm , hydrology (agriculture) , environmental science , runoff curve number , precipitation , watershed , regression analysis , water content , vegetation (pathology) , convective storm detection , atmospheric sciences , meteorology , mathematics , geography , geology , statistics , geotechnical engineering , ecology , medicine , pathology , machine learning , computer science , biology
On‐site runoff resulting from summer convective thunderstorms was studied in the Walnut Gulch Experimental Watershed, using 6− × 12−foot plots at 2 locations, based on 5 location‐years of data from 34 storms. Average runoff increased as precipitation quantity increased, decreased as crown spread of vegetation increased, and decreased as antecedent soil moisture increased. In a stepwise multiple linear regression equation, these independent variables accounted for, respectively, 72, 3, and 0.5% of the prediction variance. Considering regression equations for any one location‐year, storm amount or intensity always was significant, crown spread usually was significant, and antecedent soil moisture rarely was significant. In simple correlations, antecedent soil moisture was never related significantly to runoff. The equations developed appear valid for a set of thunderstorms with at least one‐sixth of maximum 5‐minute intensities exceeding 3.7 inches per hour. (Key words: Hydrology; runoff; thunderstorms)