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Stochastic Models in Hydrology
Author(s) -
Scheidegger Adrian E.
Publication year - 1970
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/wr006i003p00750
Subject(s) - autocorrelation , statistical physics , fractional brownian motion , mathematics , stochastic modelling , brownian motion , stochastic process , series (stratigraphy) , hydrology (agriculture) , statistics , geology , physics , geotechnical engineering , paleontology
The stochastic models that can be used to represent growth and steady state phenomena in hydrology are reviewed. It is shown that there are essentially two types of growth models possible; the cyclic growth model and the random configuration model. For steady state phenomena (time series) we are generally restricted to a Gaussian type of model with or without autocorrelation. Self‐similarity models (fractional Brownian motion) lead to physically absurd conditions if they are extrapolated to high frequencies.