Fig 1.
Black contours delineate Assessment Sub Regions (ASRs) defined for the Water Resource System (WRS) within the IGSM-WRS framework. The color shading indicates the economic regions that are resolved in the Emissions Prediction and Policy Analysis (EPPA) model.
Fig 2.
Schematic of connections between components of the IGSM framework and the WRS.
Within the IGSM, the EPPA model produces economic projections, calculating population and GDP for each ASR. These determine municipal and industrial demands for water. Climate results from MESM are projected longitudinally via pattern scaling with archived GCM data. CLM determines runoff, and CliCrop calculates irrigation demands. Water demands and surface-water supply are fed into the WSM to optimize the routing of water across all ASRs. The resultant routing is then analyzed via water stress indicators.
Fig 3.
Schematic of the delta method for producing the future climate forcing.
The procedure is applied for six near-surface meteorological variables (near-surface air temperature, wind speed and specific humidity at the lowest atmosphere level, total precipitation, shortwave and longwave radiation). The IGSM monthly precipitation is partitioned into 3-hourly based on the observed number of precipitation events within that month and amount of precipitation per each event in the derived 3-hourly baseline precipitation time series.
Fig 4.
Year 2000 global distribution of population (in millions).
Population is projected onto the Assessment Sub Regions (ASRs) of the WRS (Water Resource System) water-management network of river basins. Black contours denote political boundaries.
Fig 5.
Regions used in the Gaussian Quadrature summary statistics with 2.5° longitude by 2.0° latitude HFD grids.
Colored polygons denote the 5 regions used for the Gaussian Quadrature thinning, based on the Koeppen-Geyger Climatic Zones. Black lines are the political boundaries of China, India, and Pakistan.
Fig 6.
Distribution of the 14 Climate Moisture Index (CMI) statistics used in the Gaussian Quadrature thinning procedure.
The solid lines show the values for the full 6,800-member ensemble. Dashed lines are the Gaussian Quadrature subset distributions for comparison. The solid vertical lines on the CMI plots (a to e) show the baseline CMI values.
Fig 7.
Baseline unmet water requirement (%) for the study region at the ASR level.
Unmet requirement is defined as total consumptive use divided by the total water requirement.
Fig 8.
Distribution of water stress index by ASR, as simulated by IGSM-WRS from the baseline climate run.
Fig 9.
Baseline annual runoff by ASR (in billion cubic meters per year).
Fig 10.
Percentage change in runoff across all ensemble members.
Each point in the line represents one of the 551 members with appropriate weights from the Gaussian Quadrature (Section 2.3). The percent change in runoff represents a weighted-averaged result for the entire domain of study region (Fig 1)—such that for every member's result in the distribution shown, each ASR's runoff has been weighted by its population (Fig 3).
Fig 11.
Runoff change patterns (in %) around the 10th, 50th, and 90th percentile.
Two are shown for each percentile, based on the mean runoff change for the region (the metric used in Fig 10). Top label shows the percentile (left) and the GCM name (right.)
Fig 12.
Changes in ASR runoff (%) calculated point-wise by ASR.
These are changes in decadal averaged ASR runoff from the baseline to the future scenarios averaged over 2041–2050 for the 10th, 50th, and 90th percentiles.
Fig 13.
Baseline irrigation requirement (in billion cubic meters)
Fig 14.
As in Fig 9, but shown for percentage change in irrigation requirement across all ensemble members.
Each point in the line represents one of 551 climate scenarios.
Fig 15.
Irrigation requirement change patterns (in %) around the 10th, 50th, and 90th percentile, two each based on the mean irrigation requirement change for the region.
Top label shows the percentile (left) and GCM name (right.)
Fig 16.
Changes from baseline in irrigation requirement (%) calculated point-wise by ASR, showing changes in decadal averaged ASR irrigation requirement from the baseline to the future scenarios averaged over 2041–2050 for the 10th, 50th, and 90th percentiles.
Fig 17.
Baseline domestic water requirement (in billion cubic meters).
Fig 18.
As in Fig 13, but for percent change in domestic requirement for the region for all scenarios.
Each point in the line represents one of 400 growth scenarios. Percent change for each ASR in each scenario is weighted by population.
Fig 19.
Domestic water requirement change by region (in %) around the 10th percentile, median, and 90th percentile, two each, similar to the metric used in Fig 18.
Top label shows the percentile.
Fig 20.
Changes from baseline in domestic water requirement (%) calculated point-wise by ASR, changes are based on the baseline (Fig 16) to the future scenarios averaged over 2041–2050 and shown for the 10th, 50th, and 90th percentiles for each ASR.
Fig 21.
Baseline industrial water requirement (in billion cubic meters).
Fig 22.
Mean change in industrial requirement for the region for all scenarios.
Each point in the line represents one of 400 growth scenarios. Percent change for each ASR in each scenario is weighted by population.
Fig 23.
Industrial requirement change (in %) around the 10th percentile, median, and 90th percentile, two each, based on the mean industrial requirement change for the region (the metric used in Fig 22).
Top label shows the percentile.
Fig 24.
As in Fig 19, but for industrial water requirement shown for the 10th, median, and 90th percentiles for each ASR.
Fig 25.
Exceedance changes in ASR UWR (%).
Changes are based on the baseline (Fig 6) to the future scenarios averaged over 2041–2050 and shown for the 10th, 50th, and 90th percentiles for each ASR.
Fig 26.
Exceedance changes in decadal averaged WSI (unitless).
Changes are based on the baseline (Fig 7) to the future scenarios averaged over 2041–2050 and shown for the 10th, 50th, and 90th percentiles for each ASR.
Fig 27.
Map of major political regions showing the aggregate frequency distributions of water stress.
Fig 28.
Frequency distributions of changes in decadal averaged Unmet Water Requirement (UWR, left column) and water stress index (WSI, right column) for 2041–2050 against the baseline result aggregated over major socio-economic regions (Fig 28) and weighted by population.
Mean baseline value shown above each figure. Results are shown for the Just Growth, Just Climate, and Climate and Growth ensemble scenarios. In addition, a distribution for the Baseline result is also provided that depicts the range of UWR and WSI decadal-averaged changes that would result from internal variability of the climate forcing (see text for details).
Fig 29.
Map of major basins used to show the aggregate frequency distributions of water stress.
Fig 30.
Frequency distributions of changes in decadal averaged Unmet Water Requirement (UWR, left column) and water stress index (WSI, right column) for 2041–2050 against the baseline result aggregated over selected basins (Fig 30) and weighted by population.
Mean baseline value shown above each figure. Results are shown for the Just Growth, Just Climate, and Climate and Growth ensemble scenarios. In addition, a distribution for the Baseline result is also provided that depicts the range of UWR and WSI decadal-averaged changes that would result from internal variability of the climate forcing (see text for details).
Fig 31.
Population exposed to water stress based on UWR classifications using the 2041–2050 mean.
Grey bars represent the number of people in each class in the baseline scenario (set to year-2000 value); the box-and-whisker plots show the distributional characteristics of the three ensemble scenarios.
Table 1.
Matrix of populations’ (in millions) exposure to water stress.
Shaded gray cells show the population remaining in the UWR class relative to the Baseline result. The off-diagonal cells denote population shifts by 2050 across the various UWR classes; population shifts between classes are depicted by their location within the table matrix. Each cell provides the 10th [left, bracketed], 50th (center), and 90th [right, bracketed] percentile results.
Fig 32.
Population exposed to water stress based on WSI classifications using the 2041–2050 mean.
Grey bars represent the number of people in each class in the baseline scenario (set to year-2000 value); the box-and-whisker plots show the distributional characteristics of the three ensemble scenarios.
Table 2.
Matrix of populations’ (in millions) exposure to water stress.
Shaded gray cells show the population remaining in the WSI class relative to the Baseline result. The off-diagonal cells denote population shifts by 2050 across the various WSI classes; population shifts between classes are depicted by their location within the table matrix. Each cell provides the 10th [left, bracketed], 50th (center), and 90th [right, bracketed] percentile results.
Table 3.
Water-stressed population increase (in millions and percent).
Based on a threshold of 10% for unmet requirement (UWR) and 0.6 for WSI. Each cell provides the 10th percentile [left bracketed value], median (center in bold type), and 90th percentile [right bracketed value] results.