Nutrient Explorer Application Default Datasets From LAGOS-NE And National Nutrient Inventories
U.S. Environmental Protection Agency
@usgov.epa_gov_nutrient_explorer_application_default_datasets_4c6da922
U.S. Environmental Protection Agency
@usgov.epa_gov_nutrient_explorer_application_default_datasets_4c6da922
This dataset contains the default data provided with the Nutrient Explorer Downloadable application (SI: https://cfpub.epa.gov/si/si_public_record_Report.cfm?Lab=CPHEA&dirEntryId=358039), which is used for testing out the features and capabilities of the app. The dataset is based off of LAGOS-NE, lake total nitrogen and total phosphorus concentration data from lakes in the Northeast United States and is combined with a number of explanatory variables such as geology, land use, climate, nutrient inputs, and lake characteristics. Portions of this dataset are inaccessible because: The *.RData format is not allowed to be uploaded on ScienceHub (see above response). They can be accessed through the following means: The *.RData files can be accessed when the user downloaded the NutrientExplorer application zip files on the ScienceInventory link: https://cfpub.epa.gov/si/si_public_record_Report.cfm?Lab=CPHEA&dirEntryId=358039.
The user need to have RStudio installed to open the application and be able to use the RData files. Format: Some of the data files associated with the Nutrient Explorer application are in the *.RData format, which can not be uploaded to ScienceHub. These files include hydrologic unit (HU8) watershed shapefiles and some datasets similar to the *.csv files uploaded here containing variables used for testing out the application's features.
This dataset is associated with the following publication:
Pennino, M., M. Fry, R. Sabo, and J. Carleton. Nutrient Explorer: An analytical framework to visualize and investigate drivers of surface water quality. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 170: 105853, (2023).
Organization: U.S. Environmental Protection Agency
Last updated: 2024-05-25T12:31:33.325755
Tags: lake-water-quality, multilinear-regression, nitrogen-and-co-pollutants, phosphorus, random-forest-modeling
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