Persistent Link:
http://hdl.handle.net/10150/191897
Title:
Prediction of sediment and runoff from Korisheleko Watershed
Author:
Abegaz, Gizachew Abebe,1956-
Issue Date:
1986
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:
An event based model for estimation of sediment yield and runoff volume showed a reasonable result when compared to the measured values. MUSLE and SCS runoff models were used to predict sediment yield and runoff volume from the Korisheleko Watershed. Parameters for the models were estimated using soil loss data from test plots, soil survey data, land use data, and topographic map of the watershed. The predicted sediment yield and runoff volume were compared with the measured values. Statistical analysis including a paired comparison test and simple regression were made to validate the MUSLE and SCS runoff models. A peak flow equation for the watershed was developed applying a Unit hydrograph principle. The developed equation was based upon common rainstorm events of 1983 with an effective rainfall duration of 30-minutes. Individual components of the models could be improved with further research and data.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; River sediments -- Ethiopia -- Korisheleko River Watershed.; Rivers -- Ethiopia.
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.titlePrediction of sediment and runoff from Korisheleko Watersheden_US
dc.creatorAbegaz, Gizachew Abebe,1956-en_US
dc.contributor.authorAbegaz, Gizachew Abebe,1956-en_US
dc.date.issued1986en_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.abstractAn event based model for estimation of sediment yield and runoff volume showed a reasonable result when compared to the measured values. MUSLE and SCS runoff models were used to predict sediment yield and runoff volume from the Korisheleko Watershed. Parameters for the models were estimated using soil loss data from test plots, soil survey data, land use data, and topographic map of the watershed. The predicted sediment yield and runoff volume were compared with the measured values. Statistical analysis including a paired comparison test and simple regression were made to validate the MUSLE and SCS runoff models. A peak flow equation for the watershed was developed applying a Unit hydrograph principle. The developed equation was based upon common rainstorm events of 1983 with an effective rainfall duration of 30-minutes. Individual components of the models could be improved with further research and data.en_US
dc.description.notehydrology collectionen_US
dc.description.noteDigitization note: p. 66 missing from paper original and microfilm version.-
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshRiver sediments -- Ethiopia -- Korisheleko River Watershed.en_US
dc.subject.lcshRivers -- Ethiopia.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.contributor.committeememberFogel, Martin M.en_US
dc.contributor.committeememberFfolliott, Peter F.en_US
dc.identifier.oclc213359192en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.