Judges’ Queries and Presenter’s Replies

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Presentation Discussion

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    Mauri PElto

    Guest
    May 22, 2012 | 09:05 a.m.

    This project has an interesting potential, for differential diagnosis of the sources of sediments. I was not clear on what type of stream sampling was completed for model verification, how often it was done and in how many locations? The video is poor, use videos as a chance to provide a compelling big picture idea of why the research is important and work in the field, not a recitation of the poster.

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    Benjamin Abban

    Presenter
    May 22, 2012 | 01:01 p.m.

    Thanks Mauri. The stream sampled data used in the study presented in the poster was obtained using several in-situ sampling traps considered to have minimal impact on the flow field. The stream sampling is only done at the watershed outlet and the samples are collected over a period of time depending on the size of the watershed – they are time-integrated.

    Thanks for the comment on the video… The purpose was to introduce the problems associated with excessive amounts of sediment and to provide a general overview of the Bayesian model being presented. The poster, on the other hand, provides more specific details on the model and the research being performed and gives a sample application.

  • May 22, 2012 | 12:28 p.m.

    Benjamin – An interesting project that is critical to understanding increases in extreme climate events and thus transport of sediments to our inland waters. I liked your video – it was informative, well-organized and clearly presented the basic elements of your project. Good luck with your project.

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    Benjamin Abban

    Presenter
    May 22, 2012 | 01:21 p.m.

    Thanks Craig.

  • Further posting is closed as the competition has ended.

Icon for: Benjamin Abban

BENJAMIN ABBAN

University of Iowa
Years in Grad School: 2

Identifying Sources of Eroded Sediment Using a Bayesian Framework

The area of land contributing overland and subsurface flows to a river network is known its watershed. Soil erosion that occurs within a watershed may result in the loss of rich arable land and/or the degradation of surface water quality due to the transport of excessive amounts of sediment, and associated pollutants, into the river network. Erosion management is therefore necessary for sustaining agricultural productivity as well as aquatic ecosystems. Appropriate tools are often needed to identify critical erosion sources, or “hotspots”, so that suitable economic management actions may be taken. Examples of such tools include statistical models that allow for direct quantification of uncertainty in erosion source identification, which is important in decision making. This study presents one such model formulated within a Bayesian framework. The original framework was developed by Fox and Papanicolaou (2007), who applied it successfully to a watershed in Idaho to predict the relative erosion contributions from agricultural and forest land uses in the watershed. The current study seeks to extend the capabilities of the original framework to include the prediction of the dominant erosion processes that occur within the watershed. The proposed extensions, which can accommodate prior knowledge of erosion processes in the watershed, will provide watershed managers with invaluable information that will enhance their decision making.