Characterization of Watersheds on Fort Benning Military Reservation: Comparison of Field Data to Watershed Parameters

2010·19.9 MB·English

by  Stahl, Melinda Rosetta

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http://archive.org/details/characterizationOOstah

ColumbusStateUniversity
TheCollegeofScience
TheGraduatePrograminEnvironmentalScience
CharacterizationofWatershedsonFortBenningMilitaryReservation:
ComparisonofFieldDatatoWatershedParameters
AThesisin
EnvironmentalScience
By
MelindaRosettaStahl
SubmittedinPartialFulfillment
OftheRequirements
FortheDegreeof
MasterofScience
December2010

Ihavesubmittedthisthesisinpartialfulfillmentoftherequirementsforthe
degreeofMasterofScience.
^
Date MelindaRosettaStahl
WeapprovethethesisofMelindaRosettaStahlaspresentedhere.
Jn/*ri /2r^-^-
ate RogerBrown,AssociateProfessorof
Geology,ThesisAdvisor
Date
1 >f2Q/f
ate TroyJ*ell^r,AssistantProfessorof
EnvironmentalScience

ABSTRACT
Sixteenwatershedslocatedon FortBenning MilitaryInstallation inGeorgiawere
analyzed using both physically collected data and computer modeling data.
Physical data collected included total suspended solids (TSS) and grain size
analysisusingtheWolman PebbleCountmethod. Computermodelinganalyzed
the watersheds using ArcGIS 9.3 for comparison to physical data. Land use,
slope, andsoildatawereused inamodified revised universalsoil lossequation
(RUSLE) to create a soil erodibility index map. Wolman Pebble Count data
showedthatinhalfofthewatersheds,84%ofthesampledgrainswerelessthan
halfa millimeterin size. Watersheds studied were dominated by Nankin sandy
clayloamsoils,TrouploamysandsoilsandCowarts&Aileysoilstypes. Results
showedthatbaseflowTSSwasgreatestindisturbedandurbanizedcatchments.
The soil erodibility index maps produced in ArcGIS using the modified RUSLE
equationindicateareaswiththepotentialforhigherosionrates. Watershedsthat
hadthehighestpotentialforerosioncontainedlessthan55%forestcoverage.
Correlationanalysisindicated relationshipsbetweenthe D10and D50grain size
andtheslopesofthewatersheds. Relationshipswerealsoestablishedbetween
TSS, soil loss erodibility index, and land use classification factor. The results
suggest that the GIS/RUSLE model could be used for estimating soil loss;
however, other factors like unique land disturbance need to be included to
improveitsaccuracy.