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Title: Demeter-W

Abstract

Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.

Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
Contributing Org.:
Battelle Memorial Institute, Pacific Northwest Division (PNNL)
OSTI Identifier:
1395243
Report Number(s):
Demeter-W; 005449MLTPL00
Battelle IPID 31249-E
DOE Contract Number:
AC05-76RL01830
Resource Type:
Software
Software Revision:
00
Software Package Number:
005449
Software CPU:
MLTPL
Open Source:
Yes
Usually used in conjunction with the GCAM software.
Source Code Available:
Yes
Other Software Info:
Open Source
Related Software:
The following Python packages are needed: NumPy (version 1.11) Scipy (version 0.18) Matplotlib (version 2.0) Pandas (version 0.19) configobj (version 5.0.6)
Country of Publication:
United States

Citation Formats

. Demeter-W. Computer software. https://www.osti.gov//servlets/purl/1395243. Vers. 00. USDOE Office of Science (SC). 27 Sep. 2017. Web.
. (2017, September 27). Demeter-W (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1395243.
. Demeter-W. Computer software. Version 00. September 27, 2017. https://www.osti.gov//servlets/purl/1395243.
@misc{osti_1395243,
title = {Demeter-W, Version 00},
author = {},
abstractNote = {Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.},
url = {https://www.osti.gov//servlets/purl/1395243},
doi = {},
year = {Wed Sep 27 00:00:00 EDT 2017},
month = {Wed Sep 27 00:00:00 EDT 2017},
note =
}

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