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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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 . 2023
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 . 2023
License: CC BY
Data sources: Datacite
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Data produced for "Water Scarcity Challenges across Urban Regions with Expanding Irrigation"

Authors: Rathore, Lokendra Singh; Kumar, Mukesh; Naota Hanasaki; Mesfin M Mekonnen; Pushpendra Raghav;

Data produced for "Water Scarcity Challenges across Urban Regions with Expanding Irrigation"

Abstract

This archive includes the data and codes to produced results for the paper- Transition from Rain-fed to Irrigation-fed Agriculture in Rural Areas to Exacerbate Urban Water Scarcity. It contains 3 archive files: 1. H08_inputs_org: All the input files required for the simulation of the global hydrological model, H08 (/H08/map/org). It has the following files (for both scenarios S1, and S2) - a) AQUASTAT- industrial and domestic water use b) C05- GDP information for the countries c) FAO2009_Slop- data on slope d) GMIA5_S1- global map for irrigated areas version 5 for scenario 1 e) GMIA5_S2- global map for irrigated areas version 5 for scenario 2 f) GRanD- Global Reservoir and Dam (GRanD) database g) GSWP2_Albedo- albedo data h) GSWP23_SoilType- soil type data i) IGRAC- groundwater use for domestic and industrial sector j) IIASA_SSP- socio economic pathways data k) K14- explicit aqueduct data l) M08- crop distribution data m) OneGeology- geology units offshore n) R08- cropland and pastureland data o) WFDEI- flow direction p) DS02- irrigation data 2. Codes: Jupyter notebook consisting of the python codes for post-processing, and a folder named files_req with the required files for the notebook. 3. Outputs: This includes 4 archives a) arcgis_outputs- post-processing model results' shapefiles and rasters; ArcMap documents of CAD difference; and other outputs b) CAD_S1_S2- Raster files of monthly CAD for scenarios S1 (named as S12) and S2; raster files of total water abstraction from renewable water sources; and raster files of total water demand. c) diff_cad_21- Raster files of difference in CAD (CAD_S2 - CAD_S1) for with and without considering environmental flow requirements. e) urban_results_excel- Excel files of CAD comparison in S1 and S2; excel file of monthly water demand and abstraction in S1 and S2.

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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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