wri's aqueduct global water risk mapping: data & methodology

PAUL REIG, TOM PARRIS, AND FRANCIS GASSERT February 20, 2013

AQUEDUCT DATA & METHODOLOGY

AGENDA

Introduction

Modeling Water Supply and Demand – Tom Parris

Aqueduct Indicators – Paul Reig

Aggregation and scoring – Francis Gassert

Q&A

Photo: NOAA

RISKS TO: GOVERNMENTSCOMPANIES INVESTORS

DETAILED, COMPARABLE, GLOBAL WATER RISK INFORMATION

Photo: NASA

UNDERSTANDING RISK: AQUEDUCT FRAMEWORK

Baseline water stress

Inter-annual variability

Seasonal variability

Flood occurrence

Drought severity

Upstream storage

Groundwater stress

Physical Risk: QUANTITY

Overall Water Risk

Media coverage

Access to water

Threatened amphibians

Regulatory & Reputational Risk

Return flow ratio

Upstream protected land

Physical Risk: QUALITY

WHERE WE PILOT TESTED: KEY BASINS

HOW WE EVOLVED: GLOBAL MAPPING

BUILDING ON SCIENCE: EXPERT REVIEWERS

CDP Water Disclosure Project

Ceres

Columbia University

Deloitte Consulting LLP

Global Adaptation Institute

Global Water Strategies

Nanjing University

National Geographic

Pacific Institute

The Nature Conservancy

The World Bank

US Environmental Protection Agency

University of Michigan at Ann Arbor

University of North Carolina Chapel Hill

University of Virginia

Water Footprint Network

World Business Council for Sustainable Development

Yale University

DATA: SELECTION CRITERIA

Step 1: Literature review

Step 2: Public domain & global coverage

Step 3: Comparative analysis to evaluate: granularity, time coverage source

Step 4: Selection of data source

MODELING WATER SUPPLY AND DEMAND

Tom Parris | Vice President | ISciences

UNDERSTANDING RISK: AQUEDUCT FRAMEWORK

Baseline water stress

Inter-annual variability

Seasonal variability

Flood occurrence

Drought severity

Upstream storage

Groundwater stress

Physical Risk: QUANTITY

Overall Water Risk

Media coverage

Access to water

Threatened amphibians

Regulatory & Reputational Risk

Return flow ratio

Upstream protected land

Physical Risk: QUALITY

OVERVIEW

Catchments

Demand: Withdrawals & consumptive use

Source: Runoff

Flow accumulation

Supply: Total and available blue water

Flow accumulator

Total blue water (Bt)

Available blue water (Ba)

Hydrologically connected catchments

Runoff Withdrawals & consumptive use

MODELING: WATER SUPPLY AND DEMAND

Catchments

Global Drainage Basin Database (GDBD; n=73074)

Aggregated to <100,000 km2 target

Mean area = 8804 km2 (n=14998)

CATCHMENTS

1. Source data: withdrawals by sector (agricultural, domestic, and industrial) reported by country (FAO), baselined to 2010

2. Spatially disaggregate by sector Agricultural withdrawals disaggregated by Global Map of Irrigated Areas

(2000) Domestic withdrawals disaggregated by Gridded Population of the World

(2010) and Nighttime Lights (2010) Industrial withdrawals disaggregated by Nighttime Lights (2010)

3. Multiply each sector by consumptive use ratio

4. Re-aggregate to basins and sum sectoral consumptive and total withdrawals

WATER DEMAND: BASELINE 2010

Withdrawal Disaggregation Methodology WATER DEMAND: INPUT DATA

Sector Variable Source

All sectors Water withdrawals FAO Aquastat Pacific Institute

GDP World Bank

Population World Bank Average annual precipitation FAO Aquastat Total renewable water supply FAO Aquastat

Sectoral water withdrawal ratio Calculated

Agricultural Irrigated area FAOSTAT

FAO Aquastat Freydank & Siebert 2008

Agricultural land area World Bank

Industrial CO2 emissions World Bank Electricity, total net generation Energy Information Administration

Coal production Energy Information Administration Refinery Processing Gain Energy Information Administration

Domestic Urban population World Bank

Start with reported national withdrawals (FAO Aquastat) by sector (domestic, industrial, agricultural) (black points)

Project using two random and two fixed effects regression models (light points)

Withdrawals reported 2008-2010 were not modeled (vertical dashed line)

Average four models to estimate national withdrawals for 2010 (dark red points)

Regressions explained 94-99% of the total variation.

WATER DEMAND: BASELINE TO 2010

Withdrawal Disaggregation Methodology

1. Input data: withdrawals by sector (agricultural, domestic, and industrial) reported by country (FAO), baselined to 2010

2. Spatially disaggregate by sector Agricultural withdrawals disaggregated by Global Map of Irrigated

Areas (2000) Domestic withdrawals disaggregated by Gridded Population of the

World (2010) and Nighttime Lights (2010) Industrial withdrawals disaggregated by Nighttime Lights (2010)

3. Multiply each sector by consumptive use ratio

4. Re-aggregate to basins and sum sectoral consumptive and total withdrawals

WATER DEMAND: DISAGGREGATION

Global Map of Irrigation Area

WATER DEMAND: AGRICULTURE

Nighttime Lights (2010)

WATER DEMAND: INDUSTRY

Gridded Population of the World

(2010)

Nighttime Lights (2010)

WATER DEMAND: DOMESTIC

Total withdrawals (Ut) are the sum of agricultural, domestic, and industrial withdrawals

𝑈𝑡 = 𝑈𝑎𝑎𝑎 + 𝑈𝑑𝑑𝑑 + 𝑈𝑖𝑖𝑑

WATER DEMAND: TOTAL WITHDRAWALS

1. Input data: withdrawals by sector (agricultural, domestic, and industrial) reported by country (FAO), baselined to 2010

2. Spatially disaggregate by sector Agricultural withdrawals disaggregated by Global Map of Irrigated Areas

(2000) Domestic withdrawals disaggregated by Gridded Population of the World

(2010) and Nighttime Lights (2010) Industrial withdrawals disaggregated by Nighttime Lights (2010)

3. Multiply each sector by consumptive use ratio

4. Re-aggregate to basins and sum sectoral consumptive and total withdrawals

WATER DEMAND: CONSUMPTIVE USE

Consumptive use (Ct) is the sum of sectoral use times the sectoral consumptive use ratio (cr) (Shiklomanov and Rodda 2003)

𝐶𝑡 = 𝑈𝑎𝑎𝑎 × 𝑐𝑐𝑎𝑎𝑎 + 𝑈𝑑𝑑𝑑 × 𝑐𝑐𝑑𝑑𝑑 + 𝑈𝑖𝑖𝑑 × 𝑐𝑐𝑖𝑖𝑑

WATER DEMAND: CONSUMPTIVE USE

evaluated 4 datasets (UNH/GRDC, CFSR, MERRA-Land, GLDAS-2)

GLDAS-2, 1°, NOAH monthly (summed to annual)

1948-2008 (used 1950-2008)

directly resampled to 1km without interpolation

WATER SOURCE: RUNOFF

Runoff Precipitation minus

evapotranspiration, loss to groundwater, and increase in soil moisture.

Total Blue Water (Bt) Accumulated runoff Equivalent to naturalized flow.

MODELING: FLOW ACCUMULATION runoffa

runoffb Bta

Btb

Runoff Precipitation minus evaporation,

transpiration, deep groundwater recharge, and change in soil moisture

Total Blue Water Accumulated runoff Equivalent to naturalized flow

Available Blue Water (Ba) Upstream runoff minus consumptive

use, plus runoff Loosely equivalent to surface water

and shallow groundwater

MODELING: FLOW ACCUMULATION runoffa

runoffb Baa

Bab

consumptive useb

consumptive usea

Total blue water (Bt) is the sum of naturalized (uninhibited) runoff

WATER SUPPLY: TOTAL BLUE WATER

Available blue water (Ba) is the sum of upstream runoff minus consumptive use

WATER SUPPLY: AVAILABLE BLUE WATER

AQUEDUCT’S WATER RISK INDICATORS

Paul Reig | Aqueduct Project | WRI

UNDERSTANDING RISK : AQUEDUCT FRAMEWORK

Baseline water stress

Inter-annual variability

Seasonal variability

Flood occurrence

Drought severity

Upstream storage

Groundwater stress

Physical Risk: QUANTITY

Overall Water Risk

Media coverage

Access to water

Threatened amphibians

Regulatory & Reputational Risk

Return flow ratio

Upstream protected land

Physical Risk: QUALITY

𝐁𝐁𝐁𝐁𝐁𝐁𝐁𝐁 𝐰𝐁𝐰𝐁𝐰 𝐁𝐰𝐰𝐁𝐁𝐁 =𝑇𝑇𝑇𝑇𝑇 𝑤𝑇𝑇𝑤𝑐 𝑤𝑤𝑇𝑤𝑤𝑐𝑇𝑤𝑇𝑇𝑤 (2010)

𝑀𝑤𝑇𝑀 𝑇𝑎𝑇𝑤𝑇𝑇𝑎𝑇𝑤 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

SUPPLY AND DEMAND INDICATORS

𝐈𝐁𝐰𝐁𝐰𝐁𝐁𝐁𝐈𝐁𝐁 𝐯𝐁𝐰𝐁𝐁𝐯𝐁𝐁𝐁𝐰𝐯 =𝑆𝑇𝑇𝑀𝑤𝑇𝑐𝑤 𝑤𝑤𝑎𝑤𝑇𝑇𝑤𝑇𝑀 𝑇𝑜 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

𝑀𝑤𝑇𝑀 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

SUPPLY AND DEMAND INDICATORS

𝐒𝐁𝐁𝐁𝐒𝐁𝐁𝐁 𝐯𝐁𝐰𝐁𝐁𝐯𝐁𝐁𝐁𝐰𝐯 =𝑆𝑇𝑇𝑀𝑤𝑇𝑐𝑤 𝑤𝑤𝑎𝑤𝑇𝑇𝑤𝑇𝑀 𝑇𝑜𝑜𝑇𝑀𝑇𝑤𝑇𝑜 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

𝑀𝑤𝑇𝑀 𝑜𝑇𝑀𝑇𝑤𝑇𝑜 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

SUPPLY AND DEMAND INDICATORS

𝐔𝐔𝐁𝐰𝐰𝐁𝐁𝐔 𝐁𝐰𝐒𝐰𝐁𝐬𝐁 =𝑈𝑈𝑤𝑇𝑐𝑤𝑇𝑜 𝑤𝑇𝑇𝑐𝑇𝑠𝑤 𝑐𝑇𝑈𝑇𝑐𝑤𝑇𝑜

𝑀𝑤𝑇𝑀 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

Data: Lehner et al. GRanD

SUPPLY AND DEMAND INDICATORS

𝐔𝐔𝐁𝐰𝐰𝐁𝐁𝐔 𝐔𝐰𝐒𝐰𝐁𝐩𝐰𝐁𝐩 𝐁𝐁𝐁𝐩 = 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 𝑜𝑐𝑇𝑜 𝑈𝑐𝑇𝑇𝑤𝑐𝑇𝑤𝑤 𝑇𝑇𝑀𝑤𝑤 1950 − 2008

𝑀𝑤𝑇𝑀 𝑇𝑇𝑇𝑇𝑇 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 1950 − 2008

SUPPLY AND DEMAND INDICATORS

Data: IUCN, UNEP

SUPPLY AND DEMAND INDICATORS

𝐑𝐁𝐰𝐈𝐰𝐁 𝐟𝐁𝐒𝐰 𝐰𝐁𝐰𝐁𝐒 =𝑈𝑈𝑤𝑇𝑐𝑤𝑇𝑜 𝑀𝑇𝑀𝑐𝑇𝑀𝑤𝑏𝑜𝑈𝑇𝑤𝑎𝑤 𝑏𝑤𝑤 (2010)

𝑀𝑤𝑇𝑀 𝑇𝑎𝑇𝑤𝑇𝑇𝑎𝑇𝑤 𝑎𝑇𝑏𝑤 𝑤𝑇𝑇𝑤𝑐 (1950 − 2008)

UNDERSTANDING RISK : AQUEDUCT FRAMEWORK

Baseline water stress

Inter-annual variability

Seasonal variability

Flood occurrence

Drought severity

Upstream storage

Groundwater stress

Physical Risk: QUANTITY

Overall Water Risk

Media coverage

Access to water

Threatened amphibians

Regulatory & Reputational Risk

Return flow ratio

Upstream protected land

Physical Risk: QUALITY

Indicator Data Source Scale

Flood occurrence Brakenridge, Dartmouth Flood Observatory Polygons

Drought severity Sheffield and Wood 1 degree raster

Groundwater stress Gleeson et al. Major aquifers

Media coverage Google Country

Access to water WHO, UNICEF Country

Threatened amphibians IUCN Red List Polygons

OTHER INDICATORS

AQUEDUCT’S WATER RISK FRAMEWORK

Francis Gassert | Aqueduct Project | WRI

UNDERSTANDING RISK : AQUEDUCT FRAMEWORK

Baseline water stress

Inter-annual variability

Seasonal variability

Flood occurrence

Drought severity

Upstream storage

Groundwater stress

Physical Risk: QUANTITY

Overall Water Risk

Media coverage

Access to water

Threatened amphibians

Regulatory & Reputational Risk

Return flow ratio

Upstream protected land

Physical Risk: QUALITY

ENABLING COMPARABILITY : THRESHOLDS

Thresholds: 1. Create categories for communication 2. Enable scoring and aggregation

Thresholds determined using: existing literature governmental or intergovernmental guidelines range and distribution of indicator values expert judgment

NORMALIZING AND SCORING

Values mapped over thresholds using continuous functions

0.1 1

0.2

2

0.4

3

0.8

4

Raw value (r) :

Score :

0

5

𝑜BWS 𝑐 = min(5, max(0,ln 𝑐 − ln 𝑇1

ln 𝑎𝑇𝑤𝑤 + 1 ))

PUTTING IT TOGETHER : AGGREGATION

PUTTING IT TOGETHER : AGGREGATION

Weighted average For each region (j):

Re-normalize to display full range of relative values Final displayed “overall water risk” (sj):

𝑤𝑗 = 5𝑇𝑗 − min(𝑇)

max 𝑇 − min(𝑇)

𝑇𝑗 =∑𝑥𝑖𝑗𝑤𝑖∑𝑤𝑖

𝑜𝑇𝑐 𝑤 𝑤𝑀 {𝑇𝑇𝑇 𝑤𝑀𝑤𝑤𝑐𝑇𝑇𝑇𝑐𝑤 𝑤𝑤𝑤𝑐𝑤 𝑥𝑖𝑗 ≠ 𝑀𝑏𝑇𝑇}

0% 25% 50% 75% 100%

WRI Default

Agriculture

Food & Beverage

Chemicals

Electric power

Semi-conductor

Oil & Gas

Mining

Construction Materials

Textile

UNIQUE USERS : TAILORED WEIGHTING

Quantity Quality Regulatory and reputational

BALANCING INDICATORS : SETTING WEIGHTS

Exposure to risk varies– users can set own weights

Default weights set by: WRI water expert panel Corporate disclosure documentation Industry leader review

PUBLICATIONS

Aqueduct Global Maps 2.0:

http://www.wri.org/publication/aqueduct-metadata-global

Aqueduct Water Risk Framework:

http://www.wri.org/publication/aqueduct-water-risk-framework

Aqueduct Data and Methodology: in prep

Thank you for joining!

CONTACT US

Paul Reig | preig@wri.org Francis Gassert | fgassert@wri.org

WRI.org/Aqueduct