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Catchment-scale Storm Orientations and Rainfall Patterns in the Missouri River Basin

Undergraduate #238
Discipline: Ecology Environmental and Earth Sciences
Subcategory: Climate Change
Session: 1

Mohamed Layachi - City College of New York
Co-Author(s): Cesar Hincapie, City College of New York, New York,NY; Nasser Najibi, City College of New York, New York,NY; Dr. Naresh Devineni. City College of New York



This study addresses the directionality of storms as they transpose over the Missouri River Basin, and the increased risk of dam failure they pose. The Missouri River will serve as the foundation track that will set a precedent to compare to the storm tracks. The posit under review is that parallel oriented storm tracks with respect to the Missouri River’s main stem path bear the highest flood and dam failure risk, while the orthogonal tracks bear the least risk. Daily precipitation data obtained from the Global Historical Climatology Network (GHCN) covering the years 1900 to 2014 is used to detect major precipitation events. Visual representations of storm tracks will be composed and compared, in a statistical manner with respect to the rivers physical behavior. Through quantification and plotting of major daily precipitation patterns coupled with application of statistical analysis to said assessments, we will attempt to bridge the gap between the understanding of storm tracks, and aiding in flood preparations and dam failures.

Funder Acknowledgement(s): National Science Foundation

Faculty Advisor: Dr. Naresh Devineni, ndevineni@ccny.cuny.edu

Role: Every part within the abstract I did the research for. Apart from retrieving the data from GHCN which was the job of all of my mentors to provide me with the correct data and from there I went about filtering it and performing statistical analysis on the behavior of the storm tracks in relation to the Missouri River Basin.

Discipline: Ecology Environmental and Earth SciencesPresentation Type: PosterRegistration Type: UndergraduateSub-Category: Climate ChangeConference Year: 2019

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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