Annualmeeting:2017 CSDMS meeting-089: Difference between revisions

From CSDMS
(Created page with "{{CSDMS meeting personal information template-2014 |CSDMS meeting first name=Kendra |CSDMS meeting last name=Kaiser |CSDMS meeting institute=Boise State University |CSDMS meet...")
 
No edit summary
Line 1: Line 1:
{{CSDMS meeting personal information template-2014
{{CSDMS meeting personal information template-2014
|CSDMS meeting first name=Kendra
|CSDMS meeting first name=Md Tazmul
|CSDMS meeting last name=Kaiser
|CSDMS meeting last name=Islam
|CSDMS meeting institute=Boise State University
|CSDMS meeting institute=The University of Alabama,
|CSDMS meeting city=Boise
|CSDMS meeting city=Tuscaloosa
|CSDMS meeting country=United States
|CSDMS meeting country=United States
|CSDMS meeting state=Idaho
|CSDMS meeting state=Alabama
|CSDMS meeting email address=kend
|CSDMS meeting email address=mislam6@ua.edu
|CSDMS meeting phone=9197249731
|CSDMS meeting phone=2058617536
}}
}}
{{CSDMS meeting scholar and pre-meeting
{{CSDMS meeting scholar and pre-meeting
|CSDMS meeting pre-conference=Bootcamp
|CSDMS meeting pre-conference=None
|CSDMS meeting post-conference=No
|CSDMS meeting post-conference=No
}}
}}
{{CSDMS meeting select clinics1
{{CSDMS meeting select clinics1
|CSDMS_meeting_select_clinics1=4) Spatial agent-based models
|CSDMS_meeting_select_clinics1=2) ANUGA - river flood morphodynamics
}}
}}
{{CSDMS meeting select clinics2
{{CSDMS meeting select clinics2
|CSDMS_meeting_select_clinics2=2) Landlab I
|CSDMS_meeting_select_clinics2=4) The Sediment Experimentalist Network (SEN)
}}
}}
{{CSDMS meeting select clinics3
{{CSDMS meeting select clinics3
|CSDMS_meeting_select_clinics3=1) Parflow groundwater modeling
|CSDMS_meeting_select_clinics3=5) Will not attend a clinic
}}
}}
{{CSDMS scholarships yes no
{{CSDMS scholarships yes no
Line 26: Line 26:
}}
}}
{{CSDMS meeting abstract yes no
{{CSDMS meeting abstract yes no
|CSDMS meeting abstract submit=No
|CSDMS meeting abstract submit=Yes
}}
{{CSDMS meeting abstract title temp
|CSDMS meeting abstract title=Testing a New Global Bedload Flux Model
}}
{{CSDMS meeting authors template
|CSDMS meeting coauthor first name abstract=Sagy
|CSDMS meeting coauthor last name abstract=Cohen
|CSDMS meeting coauthor institute / Organization=The University of Alabama,
|CSDMS meeting coauthor town-city=Tuscaloosa
|CSDMS meeting coauthor country=United States
|State=Alabama
|CSDMS meeting coauthor email address=sagy.cohen@ua.edu
}}
{{CSDMS meeting authors template
|CSDMS meeting coauthor first name abstract=James
|CSDMS meeting coauthor last name abstract=Syvitski
|CSDMS meeting coauthor institute / Organization=University of Colorado,
|CSDMS meeting coauthor town-city=Boulder
|CSDMS meeting coauthor country=United States
|State=Colorado
|CSDMS meeting coauthor email address=james.syvitski@colorado.edu
}}
{{CSDMS meeting abstract template
|CSDMS meeting abstract=Proper quantification of sediment flux has always been an area of interest both for scientist and engineers involved in hydraulic engineering and management of rivers, estuaries and coastal waters. In spite of the importance of bedload flux globally, either for monitoring water quality, maintaining coastal and marine ecology or during dam construction or even for food security, bedload data, especially for large rivers,  extremely scarce. This is due to the fact that bedload flux measurements are relatively expensive and time consuming and introduce large spatial and temporal uncertainties. Lack of adequate and continuous field observation is a hindrance to developing a globally accepted numerical model. We developed a new global riverine bedload flux model as an extension of the WBMsed framework. Here we present an evaluation of the model predictions using over eighty field observations for large rivers (over 1000 km2), collected from different sources.  This model will be used to study various aspects of fluvial geomorphology globally, which is most common interest area for the researcher to see the impacts of different issues at global scale. Also, considering the contribution of bedload as sediment in the global level, it will elucidate the relationship between suspended sediment and bedload. The observational dataset we compiled is in itself a unique product that can be instrumental for future studies.
}}
}}
{{CSDMS meeting abstract title temp}}
{{CSDMS meeting abstract template}}
{{blank line template}}
{{blank line template}}

Revision as of 16:46, 21 March 2017






Browse  abstracts



Testing a New Global Bedload Flux Model

Md Tazmul Islam, The University of Alabama, Tuscaloosa Alabama, United States. mislam6@ua.edu
Sagy Cohen, The University of Alabama, Tuscaloosa Alabama, United States. sagy.cohen@ua.edu
James Syvitski, University of Colorado, Boulder Colorado, United States. james.syvitski@colorado.edu


[[Image:|300px|right|link=File:]]Proper quantification of sediment flux has always been an area of interest both for scientist and engineers involved in hydraulic engineering and management of rivers, estuaries and coastal waters. In spite of the importance of bedload flux globally, either for monitoring water quality, maintaining coastal and marine ecology or during dam construction or even for food security, bedload data, especially for large rivers, extremely scarce. This is due to the fact that bedload flux measurements are relatively expensive and time consuming and introduce large spatial and temporal uncertainties. Lack of adequate and continuous field observation is a hindrance to developing a globally accepted numerical model. We developed a new global riverine bedload flux model as an extension of the WBMsed framework. Here we present an evaluation of the model predictions using over eighty field observations for large rivers (over 1000 km2), collected from different sources. This model will be used to study various aspects of fluvial geomorphology globally, which is most common interest area for the researcher to see the impacts of different issues at global scale. Also, considering the contribution of bedload as sediment in the global level, it will elucidate the relationship between suspended sediment and bedload. The observational dataset we compiled is in itself a unique product that can be instrumental for future studies.