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AQUEDUCT. Charles Iceland Use of Geo and Satellite Data. September 5, 2013. WATER. STRESS. Baseline Water Stress 2010. BWS = 2010 total withdrawals / mean( B a ) m ean (B a ) calculated using mean annual NASA GLDAS-2/NOAH runoff from 1950-2008 . Aqueduct water supply estimates.

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slide1

AQUEDUCT

Charles Iceland

Use of Geo and Satellite Data

September 5, 2013

water

WATER

STRESS

baseline water stress 2010
Baseline Water Stress 2010

BWS = 2010 total withdrawals / mean(Ba)

mean(Ba) calculated using mean annual NASA GLDAS-2/NOAH runoff from 1950-2008

aqueduct water supply estimates
Aqueduct water supply estimates
  • NASA Global Land Data Assimilation System (GLDAS) plays a key role:
      • GLDAS inputs include:
        • Temperature
        • Precipitation
        • Elevation
        • Wind speed
        • Water retention of soil
        • Etc.
      • GLDAS outputs include:
        • Soil moisture
        • Evapotranspiration
        • Runoff (surface and shallow groundwater)
  • GLDAS runoff values for period 1950-2010 are used to bias-correct runoff estimates from 6 GCMs
slide6

Change in total water supply

2040 relative to 1995 baseline

DRAFT

slide8

Change in inter-annual variability of water supply

2040 relative to 1995 baseline

DRAFT

slide10

Change in seasonal variability of water supply

2040 relative to 1995 baseline

DRAFT

projected water stress 2020
Projected Water Stress 2020

DRAFT

Water stress = 2020 projected total withdrawals / Ba

Ba calculated using median of 6 mean annual GCM runoff from 2015-2025

slide13

Change in water stress for 2020

relative to 2010 baseline

DRAFT

ground

GROUND-

WATER

slide15

Groundwater Stress

the ratio of groundwater withdrawal relative to the recharge rate to aquifer size; values above one indicate where unsustainable consumption could affect groundwater availability and dependent ecosystems

Data Sources:

Water Balance of Global Aquifers Revealed by Groundwater Footprint, Gleeson, T., Wada, Y., Bierkens, M.F.P., and van Beek, L.P.H., 1958-2000

slide16

GROUNDWATER DATA

Gravity Recovery and Climate Experiment (GRACE)

surface

SURFACE

WATER

slide18

The Global Reservoir and Lake Monitor (GRLM)

Charon Birkett, ESSIC/UMD

Curt Reynolds, USDA/FAS

A NASA/USDA sponsored program in collaboration with NASA/GSFC and the University of Maryland at College Park.

Additional lake databases and

web links.

LAKENET

Additional

3-D

imagery provided by USGS

Application of Satellite Radar Altimetry for surface water level monitoring.

Jason-2/OSTM

C.Birkett ESSIC/UMD

slide20

FLOOD

A COSTLY RISK

IS GROWING

BY 2050:

+2.0 BILLION vulnerable to flooding

+$70-100 BILLION/YR adaptation cost

Source: Munich Re, 2013. Topics Geo. Natural catastrophes 2012

slide21

LET’S BUILD

PREDICTIVE POWER

1KMFLOOD MAPS

RIVER FLOOD MODELS

LOSS ESTIMATES

SCENARIO ANALYSIS

PROBABILITY

OF LOSS

slide23

Near real-time

Global Agricultural Monitoring System (GLAM)

Correlates significant anomalies to drought conditions and shortfalls in crop production.

Famine Early Warning System Network (FEWS NET)

Provides early warning on emerging and evolving food security issues.

GLAM is a collaboration between NASA/GSFC, USDA/FAS, SSAI, and UMD Department of Geography

FEWS NET is funded by USAID – partners include NOAA, USGS, NASA, Chemonics, and USDA/FAS

slide24

Long-term projections for drought

  • Projections of changes in the frequency, duration and severity of drought relative to recent experience
  • Projections will be developed for multiple types of drought:
  • Soil moisture
  • Evapotranspiration deficit
  • Hydrological drought

Image: IPCC Fourth Assessment Report: Climate Change 2007

water1

WATER

QUALITY

slide26

WATER QUALITY

CHLOROPHYL

PHOSPHORUS

TURBIDITY

MODIS

250m+ / twice per day

1999-

LANDSAT

30m+ / 16 days + tasked

1972-

appendix

APPENDIX

SLIDES

aqueduct water supply estimates1
Aqueduct water supply estimates
  • NASA Global Land Data Assimilation System (GLDAS) plays a key role:
      • GLDAS inputs include:
        • Temperature
        • Precipitation
        • Elevation
        • Wind speed
        • Water retention of soil
        • Etc.
      • GLDAS outputs include:
        • Soil moisture
        • Evapotranspiration
        • Runoff (surface and shallow groundwater)
  • GLDAS runoff values for period 1950-2010 are used to bias-correct runoff estimates from 6 GCMs
  • Baseline
      • Supply = median of mean annual runoff from 6 bias-corrected GCMs for a window of time ending in 2010
  • Future
      • Supply = median of mean annual runoff from 6 bias-corrected GCMs for a window of time centered on 2020
bias correcting model runoff1
Bias-correcting model runoff
  • “quantilemapping” aka “cumulative distribution function matching” (Mason, 2007)
  • Bias correction occurs at the pixel level for each month
  • Based on generalized extreme value distribution (3 parameters)
  • Corrects for all moments, including location, spread, skew
  • Assumes stationarity of bias
example locations bias corrected raw runoff
Example locations bias-corrected raw runoff

GLDAS-2

Ensemble median

Runoff (m)

Year

11 yr running means

goals milestones
GOALS & MILESTONES
  • Objective: Project change (from baseline) in water risk for three Aqueduct Framework indicators
    • Water stress (Water withdrawal ratio)
    • Inter-annual variability
    • Seasonal (i.e., intra-annualor monthly) variability
  • Interim results: May 2013
    • Preliminary projections for 2020
    • One draft scenario of supply and demand
    • Six climate models; one initial condition per model
  • Final release: January 2014
    • Three time periods centered on 2020, 2030, and 2040
    • Three scenarios of supply and demand
    • Six climate models; multiple initial conditions per model
baseline water stress
Baseline Water Stress
  • Definition:
    • Total Annual Withdrawals / mean(Annual Available Blue Water)
    • Available Blue Water = accumulated runoff - accumulated consumptive use
  • Interpretation:
    • The degree to which freshwater availability is an ongoing concern.
    • High levels of baseline water stress are associated with:
      • Increased socioeconomic competition for freshwater supplies,
      • More reliance on engineered water supply infrastructure,
      • Heightened political attention to issues of water scarcity, and
      • Higher risk of supply disruptions.
change in water stress
Change in Water Stress
  • Definition:
    • Future Water Stress / Baseline Water Stress
  • Interpretation:
    • Estimated rate of change in water stress due to:
      • Changes in use due to population growth, economic development, and technology
      • Changes in supply due to climate change
    • High rates of change associated with:
      • Faster pace of socio-economic and technological change required to keep pace
choosing global climate models gcms
Choosing Global Climate Models (GCMs)
  • Select subset of 6 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5; to be used for IPCC AR5)
  • Selection criteria:
    • Availability: terms of use, parameter availability (runoff and evapotranspiration)
    • Quality for this purpose: best representations of historical runoff (not global mean temperature)
      • Long-term average
      • Standard deviation
    • Data provided by Alkama et al. (2013); evaluated 15 CMIP5 models against gauge data for 18 large basins.
example locations flow accumulated runoff b t
Example locations flow accumulated runoff (Bt)

GLDAS-2

Ensemble median

Runoff (m)

Year

11 yr running means

estimating water use previous work coca cola
Estimating water use: previous work (Coca-Cola)

Industrial Use

Domestic Use

Agricultural Use

$15,000

$60,000

$1,000

  • Domestic = f(population, GDP/capita) Adjusted R2=0.85
  • Industrial = f(GDP, GDP/Capita) Adjusted R2=0.70
  • Agricultural = f(population, GDP/Capita, ag land, %ag land under irrigation) Adjusted R2=0.90
  • Each sector responds differently to changing levels of economic development (GDP/Capita)
  • Cross-sectional analysis generally produces optimistic Kuznets curves
preliminary maps of projected change
Preliminary maps of projected change
  • Baseline
      • Supply = mean annual 1950-2008 runoff from GLDAS-2/NOAH current release
      • Demand = 2010 use
        • FAO Aquastat withdrawals by sector, estimated for 2010 using a mean of fixed and random effects models
        • consumptive use computed by consumptive use ratio (Shiklomanov and Rodda 2003)
  • Future
      • Supply = median of mean annual 2015-2025 runoff from 6 GCMs
      • Demand = projected change in 2010 use
        • change in scenario use by sector applied to baseline use

[2010 use] * [2020 scenario use] / [2010 scenario use]

  • Projected change maps are computed as future / baseline
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