Stochastic Hydrology.

Author(s):  
Larry D. Haugh ◽  
Ian B. MacNeill ◽  
Gary J. Umphrey
Keyword(s):  
1984 ◽  
Vol 16 (1) ◽  
pp. 19-19
Author(s):  
V. Klemeš

Most of what is routinely labeled ‘stochastic hydrology’ does not contain any hydrology at all and could be more properly identified as the fitting of stochastic models to samples of data of hydrologic origin. T0 engage in this enterprise, no hydrologic knowledge is necessary, nor do the results contribute to hydrologic knowledge. Moreover, the bulk of the current stochastic hydrology does not appreciably enhance the quality of water management decisions-an aim which provided the original impetus for its development. It seems that the mainstream of stochastic hydrology follows in the steps of ‘dam theory’, the only difference being that while the latter has become a self-contained branch of pure probability theory, the former is on the way to becoming a branch of pure mathematical statistics.


1966 ◽  
Vol 92 (2) ◽  
pp. 446-450
Author(s):  
R. Robinson Rowe ◽  
Myron B. Fiering ◽  
Thomas Blench ◽  
Stanley S. Butler
Keyword(s):  

1966 ◽  
Vol 92 (5) ◽  
pp. 238-241
Author(s):  
Sundaresa Ramaseshan ◽  
Robert L. McFall
Keyword(s):  

2020 ◽  
Vol 163 ◽  
pp. 06001
Author(s):  
Mikhail Bolgov

Among many problems of stochastic hydrology, several major problems may be singled out. (1) The methodology problem – may fluctuation of hydro-meteorological values be considered within the framework of probabilities and random processes? Was this topic discussed after 1953? (2) One-dimensional probability distributions – is there progress? Are there new models? (3) Random Processes: Is Markovian property sufficient or more complex models with memory are needed? (4) Lack of stability resulting from climate changes: Is there progress in understanding the approaches to probabilistic forecasts?


1992 ◽  
Vol 6 (2) ◽  
pp. 101-115
Author(s):  
Gwo-Fong Lin ◽  
Fong-Chung Lee
Keyword(s):  

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