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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Input Runoff Data for RAPID Model Pre-Processor (RRR) from GLDAS-v.2.1

Authors: Sikder, Md. Safat; David, Cédric H.;

Input Runoff Data for RAPID Model Pre-Processor (RRR) from GLDAS-v.2.1

Abstract

This database can be used as the input runoff files in the RAPID model [David et al., 2011] pre-processor (RRR). The runoff files were acquired/derived from the GLDAS-v.2.1 [Rodell et al., 2004] LSM outputs, available at; http://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/OTF/HTTP_services.cgi The GLDAS-v.2.1 outputs (from NOAH Land Surface Models) are available in 1º, 0.25º with 3-hour temporal resolution. The database contains the following files; GLDAS.2.1_NOAHres_3H_yyyy.tar.gz (Note: res = 10 or 025; yyyy = 2000 to 2009) Note: These runoff data were used by Sikder et al. [2019] to assess the performance of available global LSM runoffs in South and Southeast Asian river basins. Other necessary links associated with this database: RAPID model: https://github.com/c-h-david/rapid RAPID model pre-processor (rrr): https://github.com/c-h-david/rrr GLDAS outputs: https://disc.gsfc.nasa.gov/datasets?keywords=GLDAS References: David, C. H., D. R. Maidment, G. Y. Niu, Z. L. Yang, F. Habets, and V. Eijkhout [2011], River network routing on the NHDPlus dataset, J. Hydrometeorol., 12, 913–934, https://doi.org/10.1175/2011JHM1345.1 Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, et al. [2004], The global land data assimilation system, Bull. Am. Meteorol. Soc. 85, 381–394, https://doi.org/10.1175/BAMS-85-3-381 Sikder, M. S., C. H. David, G. H. Allen, X. Qiao, E. J. Nelson, and M. A. Matin [2019], Evaluation of Available Global Runoff Datasets Through a River Model in Support of Transboundary Water Management in South and Southeast Asia, Front. Environ. Sci., 7:171, https://doi.org/10.3389/fenvs.2019.00171

{"references": ["David, C. H., D. R. Maidment, G. Y. Niu, Z. L. Yang, F. Habets, and V. Eijkhout [2011], River network routing on the NHDPlus dataset, J. Hydrometeorol., 12, 913\u2013934, https://doi.org/10.1175/2011JHM1345.1", "Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, et al. [2004], The global land data assimilation system, Bull. Am. Meteorol. Soc. 85, 381\u2013394, https://doi.org/10.1175/BAMS-85-3-381", "Sikder, M. S., C. H. David, G. H. Allen, X. Qiao, E. J. Nelson, and M. A. Matin [2019], Evaluation of Available Global Runoff Datasets Through a River Model in Support of Transboundary Water Management in South and Southeast Asia, Front. Environ. Sci., 7:171, https://doi.org/10.3389/fenvs.2019.00171"]}

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Keywords

Land Surface Model, Hydrology, River Flow, River Routing Model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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