Cover
Title Page
CONTRIBUTORS
PREFACE
ACKNOWLEDGMENTS
Part I: Overview of the Changes in the Terrestrial Water Cycle
1. 1 Macroscale Hydrological Modeling and Global Water Balance
  1. 1.1. INTRODUCTION
  2. 1.2. COMPONENTS OF TERRESTRIAL HYDROLOGICAL CYCLES
  3. 1.3. GLOBAL WATER BALANCE IN EARLY ERA
  4. 1.4. MACROSCALE MODELING FOR WATER CYCLE IN NATURE
  5. 1.5. CLIMATE CHANGE AND HUMAN IMPACT
  6. 1.6. INTERNATIONAL COLLABORATION AND CAPACITY BUILDING
  7. 1.7. PROSPECTS FOR GLOBAL HYDROLOGY AND MODEL DEVELOPMENT
  8. REFERENCES
2. 2 Historical and Future Changes in Streamflow and Continental Runoff
  1. 2.1. INTRODUCTION
  2. 2.2. STREAMFLOW AND RUNOFF DATA
  3. 2.3. HISTORICAL CHANGES IN STREAMFLOW AND RUNOFF
  4. 2.4. MODEL‐PROJECTED FUTURE CHANGES IN RUNOFF AND STREAMFLOW
  5. 2.5. SUMMARY
  6. ACKNOWLEDGMENTS
  7. REFERENCES
3. 3 Changes in the Global Terrestrial Water Cycle
  1. 3.1. INTRODUCTION
  2. 3.2. DEVELOPMENT OF LONG‐TERM RETROSPECTIVE WATER BUDGET DATA SET
  3. 3.3. ASSESSMENTS OF THE RETROSPECTIVE WATER BUDGET
  4. 3.4. CONCLUSIONS AND DISCUSSIONS
  5. ACKNOWLEDGMENTS
  6. REFERENCES
Part II: Human Alterations of the Terrestrial Water Cycle
1. 4 Human‐Induced Changes in the Global Water Cycle
  1. 4.1. INTRODUCTION
  2. 4.2. MACROSCALE WATER MANAGEMENT MODELS AND INTERCOMPARISONS
  3. 4.3. GLOBAL CONSUMPTIVE USE OF WATER
  4. 4.4. RESERVOIR CONTRIBUTIONS TO GLOBAL LAND SURFACE WATER STORAGE VARIATIONS
  5. 4.5. CONCLUSIONS
  6. ACKNOWLEDGMENTS
  7. REFERENCES
2. 5 Impacts of Groundwater Pumping on Regional and Global Water Resources
  1. 5.1. INTRODUCTION
  2. 5.2. HUMAN WATER USE AND GROUNDWATER PUMPING
  3. 5.3. DIRECT AND INDIRECT CLIMATE IMPACTS ON GROUNDWATER RESOURCES
  4. 5.4. GLOBAL AND REGIONAL ESTIMATES OF GROUNDWATER DEPLETION
  5. 5.5. GROUNDWATER DEPLETION AND SEA‐LEVEL RISE
  6. 5.6. FUTURE PROJECTIONS OF GROUNDWATER DEPLETION AND THE SUSTAINABILITY OF HUMAN WATER USE
  7. 5.7. A WAY FORWARD
  8. REFERENCES
3. 6 Land Use/Cover Change Impacts on Hydrology in Large River Basins
  1. 6.1. INTRODUCTION
  2. 6.2. EXAMINED VARIABLES
  3. 6.3. APPROACHES
  4. 6.4. LAND COVER CHANGE IMPACTS
  5. 6.5. OUTSTANDING ISSUES
  6. 6.6. CONCLUSIONS
  7. ACKNOWLEDGMENTS
  8. REFERENCES
Part III: Recent Advances in Hydrological Measurement and Observation
1. 7 GRACE‐Based Estimates of Global Groundwater Depletion
  1. 7.1. INTRODUCTION
  2. 7.2. GLOBAL GROUNDWATER CHANGES
  3. 7.3. SUMMARY
  4. 7.4. DISCUSSION
  5. ACKNOWLEDGMENTS
  6. REFERENCES
2. 8 Regional‐Scale Combined Land‐Atmosphere Water Balance Based on Daily Observations in Illinois
  1. 8.1. INTRODUCTION
  2. 8.2. DATA
  3. 8.3. THEORY AND METHODOLOGY
  4. 8.4. RESULTS
  5. 8.5. CONCLUSIONS
  6. REFERENCES
Part IV: Integrated Modeling of the Terrestrial Water Cycle
1. 9 Drivers of Change in Managed Water Resources
  1. 9.1. INTRODUCTION
  2. 9.2. MODELING FRAMEWORK
  3. 9.3. REGIONAL APPLICATION: DOMAIN, FORCING, AND EXPERIMENTAL APPROACH
  4. 9.4. APPLICATION IN THE CONTEXT OF GLOBAL CHANGE
  5. 9.5. DISCUSSION AND CONCLUSION
  6. ACKNOWLEDGMENTS
  7. REFERENCES
2. 10 Modeling the Role of Vegetation in Hydrological Responses to Climate Change
  1. 10.1. INTRODUCTION
  2. 10.2. ADVANCES IN HYDROLOGICAL MODELING
  3. 10.3. MODEL EXPERIMENT
  4. 10.4. HYDROLOGICAL MODELING RESULTS
  5. 10.5. DISCUSSION AND CONCLUSIONS
  6. ACKNOWLEDGMENTS
  7. REFERENCES
3. 11 Estimating Virtual Water Contents Using a Global Hydrological Model
  1. 11.1. INTRODUCTION
  2. 11.2. BASIS
  3. 11.3. APPLICATIONS: OBJECTIVE AND METHODS
  4. 11.4. RESULTS AND DISCUSSION
  5. 11.5. CONCLUSIONS
  6. ACKNOWLEDGMENTS
  7. REFERENCES
Index
End User License Agreement

List of Tables

Chapter 01
1. Table 1.1 Global Water Balance in mm yr^–1 by Different Studies
Chapter 04
1. Table 4.1 Parameterization of Human Impacts in the Hydrologic Models
2. Table 4.2 Comparisons of Previous Estimates (km³) about Irrigation Withdrawal, Irrigation Consumption, Total Withdrawal, and Total Consumption
Chapter 05
1. Table 5.1 Global Estimates of Groundwater Pumping (km³ yr^–1)
2. Table 5.2 Total and Nonrenewable Groundwater Abstraction (km³ yr^–1) over Major Groundwater Users for 1960, 2010, and 2099
3. Table 5.3 Comparison of Estimated Sectoral Water Use (Withdrawal and Consumption) to Other Estimates (km³ yr^‐1)
Chapter 06
1. Table 6.1 LUCC Impact Studies Reviewed and the Changes of Streamflow Metrics after LUCC
Chapter 07
1. Table 7.1 A Summary of the Amount of Groundwater Depletion for 10 Regions
Chapter 08
1. Table 8.1 The 10‐Year (2004–2013) Long‐Term Average of Precipitation, Soil Moisture (SM) at Top 175 cm, and GW Depth at the 12 ICN Stations
2. Table 8.2 The 10‐Year (2004–2013) Mean Annual Cycles and Interannual Variability of Precipitation, Evaporation, Runoff, Atmospheric Vapor Convergence, SM (0–175 cm), GW depth, and Precipitable Water
Chapter 09
1. Table 9.1 Correlation Coefficients between GCAM and USGS Based on State‐Level Water Demand Estimates by Sector
2. Table 9.2 Percent Change in Annual Discharge of the Simulated Regulated Flow with Respect to the Simulated Natural Discharge
3. Table 9.3 Relative Supply Deficit over the Three Regions of Interest and Future Periods
4. Table 9.4 Covariances of Supply Deficit with Inflow and Water Demand
5. Table 9.5 The Sensitivity Analysis of Water Resources with Respect to Changes in Natural Flow Demand
Chapter 11
1. Table 11.1 Major Countries Producing Four Crops in 2000
2. Table 11.2 List of Commodities and Their Yield Ratio, Price Ratio, and Content Ratio
3. Table 11.3 The Mean, Standard Deviation, and Slope of Precipitation and Potential and Actual Evapotranspiration for Four Crops
4. Table 11.4 The Mean, Standard Deviation, and Slope of Total, Green, and Blue Water Consumption for Four Crops
5. Table 11.5 The Mean, Standard Deviation, and Slope of Time Series of Crop Yield for Four Crops for the Globe and United States
6. Table 11.6 The Mean, Standard Deviation, and Slope of the Time Series of Virtual Water Contents for Four Crops
7. Table 11.7 Regions

List of Illustrations

Chapter 01
1. Figure 1.1 Global hydrological fluxes (1000 km³ yr^–1) and storages (1000 km³) with natural and anthropogenic cycles are synthesized from various sources. Vertical arrows show annual precipitation and evapotranspiration over ocean and land with major landscapes (1000 km³ yr^–1). Parentheses indicate the area (million km²)
2. Figure 1.2 Global distribution of long‐term (1979–2013) annual mean of (a) precipitation (mm yr^–1) from the GPCC [Schneider et al., 2014], (b) evapotranspiration (mm yr^–1), (c) runoff (mm yr^–1), (d) river discharge (m³ yr^–1), (e) groundwater recharge (mm yr^–1), and (f) soil wetness (‐) from off‐line hydrological simulations by Ensemble Land Surface Estimator (ELSE)
3. Figure 1.3 Global water balance and partitioning between the components of evapotranspiration (E_transp: transpiration, E_canop: interception‐loss, and E_soil: evaporation from bare soil) and runoff (R_surf: surface runoff, R_sub: base flow) based on the estimation by Kim and Oki [2014].
4. Figure 1.4 Schematic diagram for (a) terrestrial water balance, (b) atmospheric water balance, and (c) combined atmosphere–land surface water balance corresponding to equations (1.1), (1.2), and (1.3), respectively
5. Figure 1.5 Atmospheric water balance approach using (a) annual vapor‐flux convergence (mm yr^–1) from European Centre for Medium‐Range Weather Forecast (ECMWF) global analysis [Hoskins, 1989] based on Oki et al. [1995] to estimate (b) annual mean evapotranspiration (mm yr^–1) for 1989–1992 as a residual of (a) and precipitation corresponding to the period.
6. Figure 1.6 Basinwise validation for a macroscale hydrological simulation using the gauged Global Runoff Data Center (GRDC) discharge and the observed TWSA by GRACE. It shows (a) seasonal variations of GRDC discharge (black solid line), simulated discharge (red solid line), and runoff without routing (gray dashed line); (b) seasonal variations of GRACE observed TWSA (black solid line), simulated TWSA with river storage (red solid line), simulated TWSA without river storage (gray dashed line), and the major water storage components in TWS; and (c) interannual variations of relative TWS: the GRACE observation (black dot), simulation with river storage (red solid line), and simulation without river storage (gray dashed line). Gray crosses and shade, green circles and shade, and blue triangles and shade in (b) and (c) represent the individual storage component of snow water, soil moisture, and river storage, respectively
7. Figure 1.7 (a) The ratio of blue water to the total evapotranspiration during a cropping period from irrigated cropland (the total of green and blue water). The ratios of (b) streamflow, (c) medium‐size reservoirs, and (d) nonrenewable and nonlocal blue‐water withdrawals to blue water
Chapter 02
1. Figure 2.1 Distributions of the 9009 GRDC stations with monthly streamflow data. Colors indicate the record ending years in (a) and the record length in years in (b)
2. Figure 2.2 Global runoff data base, temporal distribution of river discharge data. Time series of number stations with river discharge data included in the GRDC data base as of December 2013
3. Figure 2.3 Distribution of the farthest downstream gauge stations (dots) with varying length of record of streamflow available during 1948–2013 for world’s 925 largest rivers included in Dai et al. [2009].
4. Figure 2.4 Time series of yearly (October–September) mean streamflow rate (in km³ yr^–1) from observations (thick solid line) and estimated using basin‐mean PDSI or precipitation (thin solid line) at the farthest downstream station for world's first six largest rivers, with the river name (station name) shown on top of each panel. Also shown (dashed line) is the basin‐averaged precipitation anomaly (right ordinate, normalized by its standard deviation). The correlation r(D,P) between the thick solid and dashed lines is also shown.
5. Figure 2.5 Same as Figure 2.4, but for world's next largest rivers. Time series of yearly (October–September) mean streamflow rate (in km³ yr^–1) from observations (thick solid line) and estimated using basin‐mean PDSI or precipitation (thin solid line) at the farthest downstream station for world's second six largest rivers, with the river name (station name) shown on top of each panel. Also shown (dashed line) is the basin‐averaged precipitation anomaly (right ordinate, normalized by its standard deviation). The correlation r(D,P) between the thick solid and dashed lines is also shown.
6. Figure 2.6 Linear trends of yearly (October–September) streamflow during 1948–2012 for world's largest 200 rivers plotted as a function of the 1948–2012 mean flow rate of the corresponding river. The trend is expressed in percentage of the mean per decade, with the statistically significant trends (at 5% level) denoted by stars and insignificant ones by open circles. Only 55 of the 200 rivers show significant trends, with 26 of them being positive and 29 being negative.
7. Figure 2.7 (a) Long‐term (1949–2012) trends (in 0.1 mm/day per 50 years) of October–September mean runoff inferred from records of downstream river flow rates. Blank areas do not have runoff into the oceans or do not have enough observations. (b) Long‐term (1950–2012) trends (in 0.1mm/day per 50 years) of annual precipitation from rain gauge observations.
8. Figure 2.8 (a) Yearly time series of October–September mean total continental discharge (in Sv or 1 × 10⁶ m³ s^–1, excluding that from Greenland and Antarctica) for 1949–2004 (thick solid line) estimated based on streamflow observations from 925 world's largest rivers [from Dai et al., 2009], and for 2005–2012 (thin solid line) estimated based on updated streamflow data for 264 of world's largest rivers and a linear regression with the think solid line. The dashed line is the October–September mean precipitation averaged over global (60^°S–75^°N) land areas. (b) Same as (a) except the dashed line is the Nino3.4 (170^°W–120^°W, 5^°S–5^°N) SST index.
9. Figure 2.9 Multimodel mean long‐term percentage changes from 1970–1999 to 2070–2099 (under a moderate RCP4.5 scenario) over land in annual (a) precipitation, (b) soil moisture content in the top 10 cm layer, (c) surface evapotranspiration, and (d) total runoff from 31–33 CMIP5 models. The stippling indicates at least 80% of the models agree on the sign of change. The change patterns are similar to those shown by Collins et al. [2013].
10. Figure 2.10 Multimodel ensemble averaged long‐term changes from 1970–1999 to 2070–2099 (under the moderate RCP4.5 scenario) over land in annual (a) sc_PDSI_pm, (b) potential evapotranspiration (PET) based on the Penman‐Monteith equation, (c) precipitation (P) vs. PET ratio (×100), and (d) runoff ratio (×100) estimated using data from the 14 CMIP5 models (12 for panel d). For reference, a sc_PDSI_pm value below –1 is considered drought and below –3 is considered severe to extreme drought for current climate [Palmer, 1965]. The sc_PDSI_pm and PET were computed for each model run and then averaged over the 14 models
11. Figure 2.11 Time series of the changes (in percentage of the 1950–1979 mean) in globally (60°S–75°N) averaged land annual precipitation (P, black line), total runoff (R, blue), evapotranspiration (ET, magenta), and runoff ratio (R/P, red). The 1950–1979 mean for the global land P, R, ET, and R/P are 2.340, 0.709, 1.690, and 0.303, respectively
12. Figure 2.12 Relative change (difference of future [2071–2100] and past [1971–2000], divided by past) in percentage of multimodel means of (a) long‐term mean stream flow (Qm), (b) high flow (Q5), and (c) low flow (Q95) under the RCP8.5 scenario. The flow rates were simulated by a high‐resolution river routing model forced by the daily runoff fields from 11 CMIP5 models, and the simulated flow rates were then averaged to derive the multimodel mean shown here
Chapter 04
1. Figure 4.1 Percentage of area equipped for irrigation
2. Figure 4.2 Estimated mean annual potential irrigation water consumption (km3 year–1), 1985–1999
3. Figure 4.3 (a) Mean annual (1985–1999) potential irrigation water consumption for the five models, and (b) coefficient of variation of the model means
4. Figure 4.4 Monthly mean global potential irrigation water consumption, 1985–1999
5. Figure 4.5 Ensemble mean monthly streamflow and evapotranspiration for naturalized and human impact simulations in the (a, b) Indus River basin and (c, d) Colorado River basin. Simulation results represent the control period (1971–2000), and the period representing a +2K global temperature rise compared to preindustrialized levels
6. Figure 4.6 Location of river basins and 166 simulated reservoirs (blue dots give reservoir capacities in km3)
7. Figure 4.7 Reservoir storage and variation range comparisons between model‐simulated and satellite‐estimated results for 23 global reservoirs
8. Figure 4.8 Simulated seasonal variation of reservoir storage compared with combined SWE and soil‐moisture storage variation for 32 major river basins.
9. Figure 4.9 Mean seasonal reservoir storage variations compared with seasonal SWE and soil moisture in five continents (a–e) and Northern (f) and Southern (g) Hemisphere.
Chapter 05
1. Figure 5.1 Conceptual representation of climate, groundwater, and pumping
2. Figure 5.2 Historical trends of global human water use and groundwater abstraction (1900–2010).
3. Figure 5.3 Present global human water use intensity (year 2010).
4. Figure 5.4 Present global groundwater abstraction rate (year 2010).
5. Figure 5.5 Global diffuse groundwater recharge from (a) Döll and Fiedler [2008] and (b) Wada et al. [2010], and the difference (a)–(b).
6. Figure 5.6 Global irrigation return flow to groundwater system.
7. Figure 5.7 Global groundwater depletion for the year 1960 and 2010.
8. Figure 5.8 Historical and future trends of global groundwater depletion rates.
9. Figure 5.9 Historical and future trends of the contribution of global groundwater depletion to sea‐level rise.
10. Figure 5.10 Global average nonsustainable water use (BlWSI) (dimensionless) for (a) surface water, (b) groundwater, and (c) the total at a subbasin scale (except Antarctica and Greenland; 1960–2010).
11. Figure 5.11 (a) Future global human water use intensity (year 2099) (million m³ yr^‐1) and (b) the relative change (%) from the present (2010) (Fig. 5.3) to the future (a).
12. Figure 5.12 Future trends of global human water use and groundwater abstraction.
13. Figure 5.13 Global average nonsustainable water use (BlWSI) (dimensionless) for (a) surface water, (b) groundwater, and (c) the total at a subbasin scale (except Antarctica and Greenland) (2069–2099).
14. Figure 5.14 Estimated trends of consumptive blue water use, surface water overabstraction, nonrenewable groundwater abstraction (km³ yr^‐1) (left y‐coordinate), and Blue Water Sustainability Indicator (BlWSI) (dimensionless) (right y‐coordinate) over the period 1960–2099.
Chapter 06
1. Figure 6.1 Scatter plots between (a) deforested coverage and relative annual streamflow change, (b) afforested coverage and relative annual streamflow change, (c) converted agricultural coverage and relative annual streamflow change, and (d) urbanized coverage and relative peak flow change.
Chapter 07
1. Figure 7.1 Eight aquifers reviewed in this study. (a) GRACE total water storage changes averaged from three data‐processing centers (The Center for Space Research [CSR], GeoForschungsZentrum [GFZ], and Jet Propulsion Laboratory [JPL]) with 24 months running average from 2003 to 2013; (b) sum of snow, soil moisture, and canopy water from four GLDAS models (including CLM, Mosaic, VIC, and Noah) simulations; (c) groundwater changes (GRACE minus GLDAS). The shaded colors indicate the one standard deviation uncertainty from three GRACE datasets and four GLDAS model outputs. Modified from Famiglietti [2014].
Chapter 08
1. Figure 8.1 (a) Location of 19 Illinois Climate Network (ICN) stations (circles); 12 of them used in this study with complete data coverage are marked in green. The 11 USGS streamflow stations are marked in black squares. (http://www.isws.illinois.edu/warm/weather/). (b) Time series of daily soil moisture (Sm) at top 175 cm and groundwater (GW) depth at 12 ICN stations and their state averages from 2004 to 2013.
2. Figure 8.2 The 2004–2013 daily time series of state‐average SM content at six depths with the blue solid lines denoting the corresponding long‐term (2004–2013) average.
3. Figure 8.3 The 2004–2013 monthly time series of state‐average convergence, precipitation, streamflow, SM at top 175 cm and GW depth with the blue solid lines denoting the corresponding long‐term (2004–2013) average.
4. Figure 8.4 GRACE‐derived land water storage variations in Illinois (2003–2013), the unit is mm/month. Comparisons between applying DDK filter versus applying 340 km Gaussian filter (GF) and P3M10 decorrelation (P3M10) for the data from four processing centers: CSR, GFZ, GRGS, and JPL. See the text for details.
5. Figure 8.5 Averaging kernels used in this study to obtain Illinois regional‐averaged total land water storage variations.
6. Figure 8.6 The comparison between the land water storage (TWS) using different soil depths in (a) monthly timescale, (b) annual mean, and (c) annual time series.
7. Figure 8.7 Monthly time series of the correction term for double counting in TWS derivation and GW depth (H). The 1.75 m level is denoted by the red solid line.
8. Figure 8.8 The comparison between the 10 yr (2004–2013) TWS from GRACE, derived TWS without correction for double counting, corrected TWS and TWS averaged among the 12 ICN stations (local) in (a) monthly timescale and (b) annual mean. The 1:1 relationship between corrected TWS and from GRACE is shown in (c).
9. Figure 8.9 The comparison between the land water storage change (d(TWS)/dt), derived from GRACE and from TWS averaged among the 12 ICN stations (local) in (a) monthly timescale, (b) annual mean, and (c) annual time series.
10. Figure 8.10 The 10 yr (2004–2013) mean annual cycles and interannual variability of land water balance components (P: precipitation; R: runoff; E: evaporation; d(TWS)/dt: monthly change of TWS; d(TWS_sm)/dt: monthly change in SM storage; and d(TWS_gm)/dt: monthly change in GW storage).
11. Figure 8.11 The 10 yr (2004–2013) mean annual cycles and interannual variability of atmospheric water balance components (P: precipitation; C: convergence; E: evaporation; dW_a/dt: monthly change of precipitable water).
12. Figure 8.12 The 10 yr (2004–2013) mean annual cycles and interannual variability of combined water balance components (C: convergence; R: total runoff;d(TWS)/dt: monthly change of land water storage; and dW_a/dt: monthly change of precipitable water).
13. Figure 8.13 The comparison between the 10 yr (2004–2013) C reanalysis data (C_raw) and that derived from LWB approach using GRACE and in situ data in monthly timescale, annual mean cycle, and annual time series.
14. Figure 8.14 The comparison of different monthly d(TWS)/dt estimates: from LWB approach using GRACE and in situ data and from AWB approach using C reanalysis data in monthly timescale, annual mean cycle, and annual time series.
15. Figure 8.15 The comparison between the land water storage change, d(TWS)/dt, derived from daily and monthly averaged SM and H, using forward and backward differencing.
16. Figure 8.16 The comparison of different evaporation (E) estimates: from LWB approach using GRACE and in situ data and from AWB approach using convergence data in monthly timescale, annual mean cycle, and annual time series.
17. Figure 8.17 Plots of different evaporation (E) estimates: from LWB approach versus AWB approach and between LWB approach using GRACE and in situ data. The solid line is the 1:1 line and the dashed line denotes the best fit line by linear regression.
Chapter 09
1. Figure 9.1 Schematic of the system. The paper describes and evaluates the coupling of the water demand model with the water resources model (red). Publicly available datasets processed for the experiments are in grey. Models are in blue
2. Figure 9.2 Flow chart of the water resources model
3. Figure 9.3 GRanD reservoir database by type of operating rules over the three regions of the Midwest: Missouri, upper Mississippi, and Ohio. Flow is validated at the outlet of the three regions: Missouri at Hermann (06934500), upper Mississippi at Grafton (05587450), and Ohio at Metropolis (03611500)
4. Figure 9.4 Simulated natural (dashed) and regulated (solid) flow (left column) and relative change in flow due to regulation (right column) over the three midwestern regions: Missouri, upper Mississippi, and Ohio for the historical (1984–1999)
5. Figure 9.5 Time series of simulated historical and future (B1) mean annual regulated and natural flow for the outlets of the Missouri, upper Mississippi, and Ohio river basins
6. Figure 9.6 Average relative change in the future periods relative to the historical period for multiple variables for the Missouri, upper Mississippi, and Ohio river basins and the entire Midwest. Values for regulated flow, demand, and supply are indicated by the y‐axis on the left, and values for supply deficit are indicated by the y‐axis on the right.
7. Figure 9.7 Annual total water demand (left) and actual water supply (center) in cubic meters, and fractional water supply deficit for the historical and future periods for the B1 scenario
8. Figure 9.8 Covariances between supply deficit and natural flow (blue) and demand (red) for all three regions for different time periods and emission scenarios. Filled markers represent value statistically significant at 0.1 level. Actual values are presented in Table 9.4.
9. Figure 9.9 Elasticities of supply, supply deficit, and regulated flow with respect to changes in natural flow and demand, for 2030s, 2050s, and 2080s and A2 and B1 emissions scenarios, for the three regions and the Midwest.
Chapter 10
1. Figure 10.1 Evolution of hydrological model. (a) First generation: empirical and lumped models; (b) second generation: distributed hydrological models; (c) third generation: distributed biosphere‐hydrological model.
2. Figure 10.2 The GEO‐3 regions and the selected eight global basins.
3. Figure 10.3 Comparison of DBH monthly runoff and UNH/GRDC observations at selected global major basins during 1986–1995. Grey areas denote the standard deviation for each month during the period.
4. Figure 10.4 Differences of runoff between EXP1 and EXP2 (EXP2‐EXP1) for seasons and annual. MAM: spring, JJA: summer, SON: autumn, DJF: winter.
5. Figure 10.5 Differences (EXP2‐EXP1) of relative global runoff changes (%) in EXP1 and EXP2 versus increment of atmospheric CO₂ concentration during 2020–2050 compared to present day. Grey area denotes the ranges of the 25th and 75th values of relative runoff changes in global grids.
6. Figure 10.6 (a) Projected mean relative discharge changes during 2020–2050 with constant atmosphere CO₂ concentration (EXP1), and (b) the differences of annual mean discharge between the two experiments (EXP2‐EXP1).
Chapter 11
1. Figure 11.1 Annual precipitation (thick line), and potential and actual evapotranspiration (dotted and thin lines) that come in or go out from cropland of wheat, maize, rice, and soy for three major producing countries. (a)–(d) show the global average. (e)–(p) show the individual countries with the largest production.
2. Figure 11.2 Total (thick line), green (dotted line), and blue (thin line) water consumption for wheat, maize, rice, and soy for the globe and three major countries.
3. Figure 11.3 The crop yield of wheat, maize, rice, and soy for the globe and three major producing countries. Thick, dotted, and thin lines show GDHY [Iizumi et al., 2013], GDHY‐det, and H08 simulation, respectively. The numbers indicate the correlation coefficient of H08 with GDHY and GDHY‐det, respectively.
4. Figure 11.4 Virtual water contents of four crops for the globe and major producing countries. Thick, dotted, and thin lines show total, green, and blue VWC, respectively.
5. Figure 11.5 Spatial distributions of virtual water contents of total (green + blue) water for (a) maize, (b) rice, (c) soybean, and (d) wheat. The United States and China are subdivided into states and provinces, respectively.
6. Figure 11.6 Spatial distributions of virtual water contents of green water for (a) maize, (b) rice, (c) soybean, and (d) wheat.
7. Figure 11.7 Spatial distributions of virtual water contents of blue water for (a) maize, (b) rice, (c) soybean, and (d) wheat.
8. Figure 11.8 Global total trade flows among regions. The numbers shown on the arc are regions listed in Table 11.6. The beam indicates the flow; the beams on the right‐hand side of each arc indicate export (the beams are connected to the arc), and those on the left‐hand side are import (note the gap between the end of the beams and the arc). The area of the circle reflects the total volume of flows.
9. Figure 11.9 Global total virtual water flows among regions. See Figure 11.8 for details.
10. Figure 11.10 Global blue virtual water flows among regions. See Figure 11.8 for details.

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187 Surface Ocean–Lower Atmosphere Processes Corinne Le Quèrè and Eric S. Saltzman (Eds.)
188 Diversity of Hydrothermal Systems on Slow Spreading Ocean Ridges Peter A. Rona, Colin W. Devey, Jérôme Dyment, and Bramley J. Murton (Eds.)
189 Climate Dynamics: Why Does Climate Vary? De‐Zheng Sun and Frank Bryan (Eds.)
190 The Stratosphere: Dynamics, Transport, and Chemistry L. M. Polvani, A. H. Sobel, and D. W. Waugh (Eds.)
191 Rainfall: State of the Science Firat Y. Testik and Mekonnen Gebremichael (Eds.)
192 Antarctic Subglacial Aquatic Environments Martin J. Siegert, Mahlon C. Kennicut II, and Robert A. Bindschadler
193 Abrupt Climate Change: Mechanisms, Patterns, and Impacts Harunur Rashid, Leonid Polyak, and Ellen Mosley‐Thompson (Eds.)
194 Stream Restoration in Dynamic Fluvial Systems: Scientific Approaches, Analyses, and Tools Andrew Simon, Sean J. Bennett, and Janine M. Castro (Eds.)
195 Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record‐Breaking Enterprise Yonggang Liu, Amy MacFadyen, Zhen‐Gang Ji, and Robert H. Weisberg (Eds.)
196 Extreme Events and Natural Hazards: The Complexity Perspective A. Surjalal Sharma, Armin Bunde, Vijay P. Dimri, and Daniel N. Baker (Eds.)
197 Auroral Phenomenology and Magnetospheric Processes: Earth and Other Planets Andreas Keiling, Eric Donovan, Fran Bagenal, and Tomas Karlsson (Eds.)
198 Climates, Landscapes, and Civilizations Liviu Giosan, Dorian Q. Fuller, Kathleen Nicoll, Rowan K. Flad, and Peter D. Clift (Eds.)
199 Dynamics of the Earth’s Radiation Belts and Inner Magnetosphere Danny Summers, Ian R. Mann, Daniel N. Baker, and Michael Schulz (Eds.)
200 Lagrangian Modeling of the Atmosphere John Lin (Ed.)
201 Modeling the Ionosphere‐Thermosphere Jospeh D. Huba, Robert W. Schunk, and George V Khazanov (Eds.)
202 The Mediterranean Sea: Temporal Variability and Spatial Patterns Gian Luca Eusebi Borzelli, Miroslav Gacic, Piero Lionello, and Paola Malanotte‐Rizzoli (Eds.)
203 Future Earth ‐ Advancing Civic Understanding of the Anthropocene Diana Dalbotten, Gillian Roehrig, and Patrick Hamilton (Eds.)
204 The Galápagos: A Natural Laboratory for the Earth Sciences Karen S. Harpp, Eric Mittelstaedt, Noémi d’Ozouville, and David W. Graham (Eds.)
205 Modeling Atmospheric and Oceanic Flows: Insightsfrom Laboratory Experiments and Numerical Simulations Thomas von Larcher and Paul D. Williams (Eds.)
206 Remote Sensing of the Terrestrial Water Cycle Venkat Lakshmi (Eds.)
207 Magnetotails in the Solar System Andreas Keiling, Caitríona Jackman, and Peter Delamere (Eds.)
208 Hawaiian Volcanoes: From Source to Surface Rebecca Carey, Valerie Cayol, Michael Poland, and Dominique Weis (Eds.)
209 Sea Ice: Physics, Mechanics, and Remote Sensing Mohammed Shokr and Nirmal Sinha (Eds.)
210 Fluid Dynamics in Complex Fractured‐Porous Systems Boris Faybishenko, Sally M. Benson, and John E. Gale (Eds.)
211 Subduction Dynamics: From Mantle Flow to Mega Disasters Gabriele Morra, David A. Yuen, Scott King, Sang Mook Lee, and Seth Stein (Eds.)
212 The Early Earth: Accretion and Differentiation James Badro and Michael Walter (Eds.)
213 Global Vegetation Dynamics: Concepts and Applications in the MC1 Model Dominique Bachelet and David Turner (Eds.)
214 Extreme Events: Observations, Modeling and Economics Mario Chavez, Michael Ghil, and Jaime Urrutia‐Fucugauchi (Eds.)
215 Auroral Dynamics and Space Weather Yongliang Zhang and Larry Paxton (Eds.)
216 Low‐Frequency Waves in Space Plasmas Andreas Keiling, Dong‐Hun Lee, and Valery Nakariakov (Eds.)
217 Deep Earth: Physics and Chemistry of the Lower Mantle and Core Hidenori Terasaki and Rebecca A. Fischer (Eds.)
218 Integrated Imaging of the Earth: Theory and Applications Max Moorkamp, Peter G. Lelievre, Niklas Linde, and Amir Khan (Eds.)
219 Plate Boundaries and Natural Hazards Joao Duarte and Wouter Schellart (Eds.)
220 Ionospheric Space Weather: Longitude and Hemispheric Dependences and Lower Atmosphere Forcing Timothy Fuller‐Rowell, Endawoke Yizengaw, Patricia H. Doherty, and Sunanda Basu (Eds.)

Geophysical Monograph Series

Terrestrial Water Cycle and Climate Change

Natural and Human‐Induced Impacts

CONTRIBUTORS

PREFACE

ACKNOWLEDGMENTS

Part I
Overview of the Changes in the Terrestrial Water Cycle