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Library Impacts of Land Use Characterization in Modeling Hydrology and Sediments for the Luxapallila Creek Watershed, Alabama and Mississippi

Impacts of Land Use Characterization in Modeling Hydrology and Sediments for the Luxapallila Creek Watershed, Alabama and Mississippi

Impacts of Land Use Characterization in Modeling Hydrology and Sediments for the Luxapallila Creek Watershed, Alabama and Mississippi

Resource information

Date of publication
December 2008
Resource Language
ISBN / Resource ID
AGRIS:US201301538969
Pages
139-151

The Hydrological Simulation Program - Fortran (HSPF), interfaced with the Better Assessment Science Integrating Point and Nonpoint (BASINS), was used to evaluate the impact of land use (as characterized by different land use/land cover (LU/LC) datasets) on hydrology and sediment components of the Luxapallila Creek watershed. The 1,770 km 2 watershed is located in Alabama and Mississippi. Simulation of the watershed processes were tested at the hillslope and at the watershed outlet for the period between 1985 and 2003. Three LU/LC databases were used: the Geographic Information Retrieval and Analysis System (GIRAS), the Moderate Resolution Imaging Spectroradiometer land cover product (MODIS MOD12Q1), and the National Land Cover Dataset (NLCD). The two main land use categories revealed by the three LU/LC databases were forest and agricultural lands. Whereas forest cover mechanisms were the main source of water loss in hydrology simulation, agricultural land was the main source of sediment export in sediment modeling. Land use datasets of coarser spatial resolution (MODIS and GIRAS) produced larger HSPF estimations for sediment fraction values than land use datasets identifying smaller percentages of those agricultural land cover classes (NLCD). Differences in agricultural land characterization among the land use datasets showed that sediment predictions were more sensitive than streamflow predictions to the scale and resolution of land use datasets. Choosing the right land use dataset will impact the modeling of sediments and, potentially, other water quality constituents that are related with agricultural activities.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Diaz-Ramirez, Jairo N.
Alarcon, Vladimir J.
Duan, Zhiyong
Tagert, Mary Love
McAnally, William
Martin, James L.
O'Hara, Charles G.

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