(Original Dirdata/global/Global)
Datasets for 2050 are based on 'Scinario 2', which reflects both climatic change and population growth.
Accessibility Notice : Some datasets are derived from WRI CD-ROM datasets and you can reconstruct WRI data from them. Since WRI CD-ROM is neither free nor public-domain, such datasets are protected by password (symbol [P] is attached)
The script for showing this result is described below. Unit of discharge and withdrawal is km3/year
population(1000) Industry Agriculture Rws(%) W Domestic Total 1|AFRICA | 690550| 3616.5| 13.9| 9.1| 136.1| 159.1| 4.4| 2|SOUTH_AMERICA | 319214| 8789.3| 22.2| 13.1| 102.1| 137.4| 1.6| 4|NORTH_AMERICA | 454926| 3824.4| 80.5| 263.7| 315.8| 660.0| 17.3| 5|EUROPE | 688143| 2190.9| 59.7| 233.4| 139.2| 432.3| 19.7| 6|ASIA | 3469180| 9384.9| 142.4| 203.8|1697.4|2043.7| 21.8| 8|OCEANIA | 28164| 1679.6| 8.9| 0.4| 6.0| 15.4| 0.9|
Component |
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Total |
Industrial |
Domestic |
Indus. + Domes. |
Agricultural-1 (From WRI's cropland) |
Agricultural-2 (From Kassel Univ's irrigated area) |
Agricultural-2 (From Kassel Univ's irrigated area: B/W) |
Agricultural-3m (From Dr. Tan's EPIC result. Maximum Irr. water demand) |
Agricultural-3.2 (From Dr. Tan's EPIC result. Irrigation water requirement : Version 20021007) |
Agricultural-3.1 (From Dr. Tan's EPIC result. REAL irrigation water withdrawal) |
Agri. 3m minus 3 (From Dr. Tan's EPIC result. MAXIMUM minus REAL) Color and BW version |
Agri. 3m (Max. Irrigation withdrawal of Dr. Tan's EPIC result) Minus Agri.2 (WRI & Kassel) |
Agri. 3m (Max. Irrigation withdrawal of Dr. Tan's EPIC result) Minus River Discharge |
(Total Withdrawal - Desalinized water) / population
Total by Agricultural-2 (irrigated area method) |
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Total by Agricultural-3 (EPIC 'real' by Dr. Tan) |
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Only Agricultural-3 (EPIC 'real' by Dr. Tan) |
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Woking Directory : data/global/Global
Make Withdrawal Maps (for all components)
foreach YEAR (1995 2050) setenv YEAR2 `bin/year2.sh $YEAR` foreach ITEM ( domes${YEAR2} indus${YEAR2} irr${YEAR2} crop${YEAR2} DI${YEAR2} DIA${YEAR2}-1 DIA${YEAR2}-2 ) setenv BASE ${ITEM}_106m3 bin/asc2xyz --lack 0< XYZ/${BASE}.asc > XYZ/${BASE}.xyz bin/globalxyz2image.sh ${BASE} end end
Water Demand per capita
foreach YEAR ( 1995 2050 ) setenv YEAR2 `bin/year2.sh $YEAR` setenv TYPE '-2' setenv BASE DemandP${YEAR}${TYPE}_m3 bin/asc_calc XYZ/DIA${YEAR2}${TYPE}_106m3.asc \ '-' XYZ/desal${YEAR2}_106m3.asc \ '*' 1000000 \ '/' ../../ciesin/XYZ/glp${YEAR}agiC.asc \ > XYZ/${BASE}.asc bin/asc2xyz XYZ/${BASE}.asc XYZ/${BASE}.xyz bin/globalxyz2image.sh $BASE end
Continental Discharge and Water Use
setenv YEAR 1995 setenv YEAR2 `bin year2 $YEAR` setenv REGION_FILE_BASE ../../BaseMap/region_code4 setenv REGION_MAP_FILE ${REGION_FILE_BASE}.asc setenv REGION_LIST_FILE ${REGION_FILE_BASE}.txt foreach R ( 1 2 4 5 6 8 ) setenv REGION_NAME `bin/regionname.sh $R $REGION_LIST_FILE` if ( "$REGION_NAME" != "" ) then setenv RUNOFF `bin/calctotal_int ../../discharge/annual/XYZ/Ro.Mean1995_106m3.asc $REGION_MAP_FILE $R | awk '{print $3 / 1000}'` setenv POP `bin/calctotal_int ../../ciesin/XYZ/glp${YEAR}agiC.asc $REGION_MAP_FILE $R | awk '{print $3 / 1000}'` setenv INDUS `bin/calctotal_int XYZ/indus${YEAR2}_106m3.asc $REGION_MAP_FILE $R | awk '{print $3 / 1000}'` setenv DOMES `bin/calctotal_int XYZ/domes${YEAR2}_106m3.asc $REGION_MAP_FILE $R | awk '{print $3 / 1000}'` setenv IRR `bin/calctotal_int XYZ/irr${YEAR2}_106m3.asc $REGION_MAP_FILE $R | awk '{print $3 / 1000}'` setenv DIA `bin/calctotal_int XYZ/DIA${YEAR2}-2_106m3.asc $REGION_MAP_FILE $R | awk '{print $3 / 1000}'` echo $R $REGION_NAME $POP $RUNOFF $DOMES $INDUS $IRR $DIA |\ awk '{printf("%3d|%-15s|%10.0f|%7.1f|%6.1f|%6.1f|%6.1f|%6.1f|%6.1f|\n", \ $1, $2, $3, $4, $5, $6, $7, $8, $8 / $4 * 100.)}' else echo $R : no such region. skipped endif end
bin/asc_calc XYZ/epic_106m3.asc '-' XYZ/epic-real_106m3.asc \ 'where' XYZ/epic_106m3.asc '>' 0.0 > XYZ/epic-diff_106m3.asc
bin/asc_calc XYZ/Mean1990_106m3.asc '-' XYZ/epic_106m3.asc \ 'where' XYZ/epic_106m3.asc '>' 0.0 > XYZ/epic-deficit1995_106m3.asc