Persistent Link:
http://hdl.handle.net/10150/191632
Title:
A sedimentation model for small watersheds
Author:
Wells, Wade G.(Wade Glen),1939-
Issue Date:
1976
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The digital computer model presented here is designed to predict sediment yields from individual storms occurring on small watersheds. It is also designed to use minimal amounts of actual storm data. In the model, rainfall, runoff and the erosion process are represented by three component models which can also function as separate entities. Rainfall and runoff are treated similarly in that both are simulated by probability density functions of the Erlang distribution which are fitted to their total amounts and maximum rates. The erosion process is partitioned into several of its component processes, and each of these components is then represented by a single mathematical function. When tested, the model showed some deficiencies, particularly in its representation of the actual regimen of rainfall and runoff. Despite these deficiencies, however, it accurately predicted the observed sediment yields from 17 of the 29 storms on which it was tested. It appears that correction of these deficiencies will result in an improved success rate,
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Sedimentation and deposition -- Data processing.; Soil erosion -- Data processing.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Renewable Natural Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Thames, John L.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleA sedimentation model for small watershedsen_US
dc.creatorWells, Wade G.(Wade Glen),1939-en_US
dc.contributor.authorWells, Wade G.(Wade Glen),1939-en_US
dc.date.issued1976en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe digital computer model presented here is designed to predict sediment yields from individual storms occurring on small watersheds. It is also designed to use minimal amounts of actual storm data. In the model, rainfall, runoff and the erosion process are represented by three component models which can also function as separate entities. Rainfall and runoff are treated similarly in that both are simulated by probability density functions of the Erlang distribution which are fitted to their total amounts and maximum rates. The erosion process is partitioned into several of its component processes, and each of these components is then represented by a single mathematical function. When tested, the model showed some deficiencies, particularly in its representation of the actual regimen of rainfall and runoff. Despite these deficiencies, however, it accurately predicted the observed sediment yields from 17 of the 29 storms on which it was tested. It appears that correction of these deficiencies will result in an improved success rate,en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshSedimentation and deposition -- Data processing.en_US
dc.subject.lcshSoil erosion -- Data processing.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineRenewable Natural Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairThames, John L.en_US
dc.identifier.oclc212761467en_US
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