Input Runoff Data for RAPID Model Pre-Processor (RRR) from GLDAS-v.2.0

Main Authors: Sikder, Md. Safat, David, Cédric H.
Format: info dataset Journal
Bahasa: eng
Terbitan: , 2020
Subjects:
Online Access: https://zenodo.org/record/3630703
Daftar Isi:
  • 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.2.0 [Rodell et al., 2004] LSM outputs, available at; http://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/OTF/HTTP_services.cgi The GLDAS-v.2.0 outputs (from NOAH Land Surface Models) are available in 1o, 0.25o with 3-hour temporal resolution. The database contains the following files; GLDAS.2.0_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