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DETERMINATION OF SEDIMENT YIELD BY TRANSFERRING RAINFALL DATA 1
Author(s) -
Smith Jeffrey H.,
Davis Donald R.,
Fogel Martin
Publication year - 1977
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.1752-1688.1977.tb05565.x
Subject(s) - sediment , context (archaeology) , watershed , environmental science , hydrology (agriculture) , sampling (signal processing) , streams , yield (engineering) , soil science , computer science , geology , geotechnical engineering , computer vision , paleontology , computer network , materials science , filter (signal processing) , machine learning , metallurgy
A methodology for obtaining the optimal design value to allow for sediment storage in a reservoir is presented for the situation where no data on sediment loads in the incoming streams are available. Information concerning the amount of sediment delivered to the reservoir over its life‐time is obtained by a sediment yield model which uses data on rainfall amount and duration obtained from a nearby experimental watershed. Bayesian Decision Theory is used to obtain the optimal storage requirements in order to consider the natural variation of rainfall and the sampling error due to the short rainfall record available. The normally difficult calculations involved were made tractable by the use of simplifications and approximations valid in the context of the problem. Results show that sediment storage requirements can be calculated in this manner and that consideration of the uncertainties involved leads to a storage requirement substantially larger than that calculated without such consideration.