A joint probability approach for the confluence flood frequency analysis
Date
Authors
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.
History
In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.
Dates of Existence
1905–present
Historical Names
- Department of Agricultural Engineering (1907–1990)
Related Units
- College of Agriculture and Life Sciences (parent college)
- College of Engineering (parent college)
- Department of Industrial Education and Technology, (merged, 2004)
Journal Issue
Is Version Of
Versions
Series
Department
Abstract
The flood frequency analysis at or nearby the confluence of two tributaries is of interest because it is necessary for the design of the highway drainage structures. However, The shortage of the hydrological data at the confluence point makes the flood estimation challenging. This thesis presents a practical procedure for the flood frequency analysis at the confluence of two streams by multivariate simulation of the annual peak flow of the tributaries based on joint probability and Monte Carlo simulation. Copulas are introduced to identify the joint probability. The results of two case studies are compared with the flood estimated by the univariate flood frequency analysis based on the observation data. The results are also compared with the ones by the National Flood Frequency program developed by United State Geological Survey. The results by the proposed model are very close to ones by the unvariate flood frequency analysis.