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WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions

The WEPPcloud interface is a new online decision-support tool for the Water Erosion Prediction Project (WEPP) model that facilitates data preparation and model runs, and summarizes model outputs into tables and maps that are easily interpretable by users. The interface can be used by land and water...

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Autores principales: Dobre, Mariana, Srivastava, Anurag, Lew, Roger, Deval, Chinmay, Brooks, Erin S., Elliot, William J., Robichaud, Peter R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130536/
https://www.ncbi.nlm.nih.gov/pubmed/35647243
http://dx.doi.org/10.1016/j.dib.2022.108251
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author Dobre, Mariana
Srivastava, Anurag
Lew, Roger
Deval, Chinmay
Brooks, Erin S.
Elliot, William J.
Robichaud, Peter R.
author_facet Dobre, Mariana
Srivastava, Anurag
Lew, Roger
Deval, Chinmay
Brooks, Erin S.
Elliot, William J.
Robichaud, Peter R.
author_sort Dobre, Mariana
collection PubMed
description The WEPPcloud interface is a new online decision-support tool for the Water Erosion Prediction Project (WEPP) model that facilitates data preparation and model runs, and summarizes model outputs into tables and maps that are easily interpretable by users. The interface can be used by land and water managers in United States, Europe, and Australia interested in simulating streamflow, sediment and pollutant loads from both undisturbed and disturbed (e.g. post-wildfire or post-treatment such as thinning or prescribed fires) forested watersheds. This article contains full hydrologic model runs for 28 forested watersheds in the U.S. Pacific Northwest with the WEPPcloud online interface. It also includes links to repositories with the individual model runs, a table containing default model parameters for disturbed conditions, and figures with model outputs as compared to observed data. The data in the repositories include all the raw data input and output from the model as well as the processed data, which can be accessed through tables and shapefiles to provide additional insights into the model outputs. Lastly, the article describes how the data are organized and the content of each folder containing the data. These model runs are useful for anyone interested in modeling forested watersheds with the WEPPcloud interface.
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spelling pubmed-91305362022-05-26 WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions Dobre, Mariana Srivastava, Anurag Lew, Roger Deval, Chinmay Brooks, Erin S. Elliot, William J. Robichaud, Peter R. Data Brief Data Article The WEPPcloud interface is a new online decision-support tool for the Water Erosion Prediction Project (WEPP) model that facilitates data preparation and model runs, and summarizes model outputs into tables and maps that are easily interpretable by users. The interface can be used by land and water managers in United States, Europe, and Australia interested in simulating streamflow, sediment and pollutant loads from both undisturbed and disturbed (e.g. post-wildfire or post-treatment such as thinning or prescribed fires) forested watersheds. This article contains full hydrologic model runs for 28 forested watersheds in the U.S. Pacific Northwest with the WEPPcloud online interface. It also includes links to repositories with the individual model runs, a table containing default model parameters for disturbed conditions, and figures with model outputs as compared to observed data. The data in the repositories include all the raw data input and output from the model as well as the processed data, which can be accessed through tables and shapefiles to provide additional insights into the model outputs. Lastly, the article describes how the data are organized and the content of each folder containing the data. These model runs are useful for anyone interested in modeling forested watersheds with the WEPPcloud interface. Elsevier 2022-05-10 /pmc/articles/PMC9130536/ /pubmed/35647243 http://dx.doi.org/10.1016/j.dib.2022.108251 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Dobre, Mariana
Srivastava, Anurag
Lew, Roger
Deval, Chinmay
Brooks, Erin S.
Elliot, William J.
Robichaud, Peter R.
WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
title WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
title_full WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
title_fullStr WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
title_full_unstemmed WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
title_short WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
title_sort weppcloud hydrologic and erosion simulation datasets from 28 watersheds in us pacific northwest and calibrating model parameters for undisturbed and disturbed forest management conditions
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130536/
https://www.ncbi.nlm.nih.gov/pubmed/35647243
http://dx.doi.org/10.1016/j.dib.2022.108251
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