The document discusses developing a Groundwater Risk Index (GRI) to assess groundwater depletion risk conditions in the Middle East and North Africa region. It first summarizes conducting a regional groundwater resource assessment using groundwater storage reserves estimates and groundwater storage change data. It then outlines developing the GRI using indicators for groundwater reserves, storage change, governance, food security, and groundwater extraction costs. The GRI is computed by weighting and aggregating the normalized indicators. Results show varying degrees of risk and rank changes between countries from 2003 to 2014. A sensitivity analysis examines the robustness of results to excluding individual indicators and using different normalization schemes.

1. Advisor: Adam Milewski
Committee: Eugene Yan
Jeffrey Mullen
Marshall Shepherd
AN INTEGRATED ASSESSMENT OF GROUNDWATER
SCARCITYAND RISK CONDITIONS IN THE ARAB
MIDDLE EAST AND NORTH AFRICA REGION
Khalil Lezzaik

2. Groundwater Storage
Reserves
Groundwater
Storage Change Groundwater
Scarcity
Assessment
Overview
Governance
Government Effectiveness
Regulatory Quality
Rule of Law
Control of Corruption
Food
Security Affordability
Accessability
Nutritional Profile
Groundwater
Extraction
Cost
WTD Lift Energy
Energy Costs
2
The integration of current and gridded remote sensing (e.g.
GRACE) and modelled datasets, with distributed GIS
models is capable of producing accurate assessments and
characterizations of groundwater scarcity and risk conditions,
especially in data scarce regions.

3. 3
Outline
 Introduction (Motivation, Research Questions, Research Objectives)
 Regional Groundwater Resource Assessment
 Groundwater [Depletion] Risk Index Development
 Groundwater Risk Index Sensitivity Analysis
 Conclusion

4. 4
Motivation
“ The next war in the Middle East will be fought over water, not politics.”
Boutros Boutros-Ghali, UN Secretary-General (1992-1996)
“ The wars of the 21st century will be fought over water…”
Ismail Serageldin, World Bank Vice President (1993-1998)
“ …people think the only place, there is potential conflict over water is the Middle East, they
are wrong, it is a problem all over the world.”
Kofi Annan, UN Secretary-General (1996-2006)
“ Whiskey is for Drinking. Water is for Fighting.”
Mark Twain

5. 5
Motivation
“ Aquifer depletion is already a significant issue facing the global population…that will be
exacerbated by climate change and population growth”
Lester Brown, Earth Policy Institute
“ Global ground water supplies, crucial for sustaining agriculture, are being depleted at an
alarming rate with dangerous security implications…
…Further declines in groundwater availability may well trigger more civil uprising and
international violent conflict in the already-water stressed region of the world”
Jay Famiglietti, NASA Scientist

6. 6
6
Motivation
Global Discharge Network
Temporal Distribution
Global Water Stress
Global Water Availability

7. 7
7
Research Questions
 Can the development and use of distributed GIS models parametrized with current gridded
datasets, and remote sensing datasets, such as the Gravity Recovery and Climate
Experiment’s (GRACE) gravimetric datasets, provide better quantitative assessments of
groundwater resources in the MENA region than currently available assessments?
 What are the drivers behind groundwater risk in arid environments such as the MENA
region? Is groundwater risk determined by either physical hydrogeological systems, social-
adaptive factors, or both?

8. 8
8
Research Objectives
 Evaluating and estimating regional groundwater resources in the MENA region by
integrating modeled groundwater reserves estimates with groundwater storage changes
 Developing and constructing a Groundwater Risk Index (GRI) designed for assessing and
visualizing the spatio-temporal vulnerability of MENA countries to groundwater depletion
 Testing the robustness of GRI’s results by conducting a sensitivity analysis to examine the
impact of different methodological choices on GRI country performance.

9. 9
9
Outline
 Introduction (Motivation, Research Questions, Research Objectives)
 Regional Groundwater Resource Assessment
 Groundwater [Depletion] Risk Index Development
 Groundwater Risk Index Sensitivity Analysis
 Conclusion

10. 10
10
Regional Groundwater Resource Assessment – Review
Results: Renewable water
resources.
Model: PCR-GLOBWB,
parameterized with climatic,
ET, soil, land cover,
topographic data.
Limitations: Does not
Account for non-renewable
groundwater resources.
“The 2 most striking regional
hydrological phenomena in
the MENA region are the
extreme scarcity of renewable
water resources and the
predominance of fossil
groundwater resources” –
Burdon et al., 1982.

11. 11
11
Regional Groundwater Resource Assessment – Methodology
1
Groundwater
Storage
Reserves
(GWR)
2
Groundwater
Storage
Changes
(GWSC)

12. 12
Regional Groundwater Resource Assessment – GWR (1)
12
12
Fan et al., 2013
Water Table Depth (WTD)
Laske et al., 2013
Sedimentary Thickness (SDT)
Hsat = SDT-WTD
Lithological Classification
Hartmann and Moosdorf, 2012
Effective Porosity values
McWhorter and Sunada, 1977
Assign effective
porosity values
to distributed
lithological
units (φe)
GWR =Hsat . ϕe

13. 1313
13
Regional Groundwater Resource Assessment – GWSC (2)
Δ GWS/dt = Δ TWS – Δ LSP {SM + SW + CW}
Process and Analyze
GRACE dTWS data
from JPL, CSR, and GFZ
centers.
To minimize uncertainty
an ensemble GRACE
product was used.
[Sakumura et al., 2014]
Spatio-temporal land
surface parameters (LSP)
generated by GLDAS Land
surface models, integrated
with observation and
satellite-based data.
LSP are used to isolate
dGWS from dTWS
GRACE measurements.
Δ GWS/dt: groundwater storage anomaly; Δ TWS: terrestrial water storage;
Δ LSP: land surface parameters;
SM: soil moisture; SW: snow water; CW: canopy water

14. 1414
14
Regional Groundwater Resource Assessment – Results (GWR)
 GWR reserves
estimates based on
aquifer saturated
thickness and effective
porosity
 Min and Max GWR
estimates, to account
for margin of error,
are a function a range
of effective porosity
values.
 GW Reserves are
lowest in and around
Precambrian outcrops.
 Alternatively, they are
highest in the deep
sedimentary basins of
the Saharan and
Arabian aquifer
systems

15. 1515
15
Regional Groundwater Resource Assessment – Results (GWSC)
 Very clear association between
groundwater declines and
major urban and demographic
concentrations
 Indications of possible
groundwater recharge in
aquifer systems categorized as
“non-renewable”:
1) GRACE/GLDAS Uncertainties
2) Diffuse recharge [Goncalves et
al. 2013]
3) Groundwater flow [Ahmed et al.,
2011]
Muscat

16. 1616
16
Regional Groundwater Resource Assessment – Results (GWSC)
 Negligible changes in groundwater
reserves between 2003 and 2014
 Consistent with GWSC results,
largest declines underlie urban and
demographic concentrations
 Quantitatively, there is no short-term
threat to groundwater supplies.
Lezzaik, K.A., and A.M. Milewski (2015), A Quantitative Assessment of Groundwater Resources in the Middle East
and North Africa Region, Journal of Arid Environments (Submitted).

17. 1717
17
Groundwater Storage
Reserves
Groundwater
Storage Change Groundwater
Scarcity
Assessment
Governance
Government Effectiveness
Regulatory Quality
Rule of Law
Control of Corruption
Food
Security Affordability
Accessability
Nutritional Profile
Groundwater
Extraction
Cost
WTD Lift Energy
Energy Costs

18. 1818
18
Outline
 Introduction (Motivation, Research Questions, Research Objectives)
 Regional Groundwater Resource Assessment
 Groundwater [Depletion] Risk Index Development
 Groundwater Risk Index Sensitivity Analysis
 Conclusion

19. 1919
19
Groundwater Risk Index (GRI) - Review
What is a Composite Index?
A multi-dimensional tool, formed from a grouping of indicators or variables that are combined
in a standardized way, intended to assess concepts are relative, dimensionless and non-
measurable in nature.
Examples:
Body Mass Index (BMI) University Ranking Human Development Index

20. 2020
20
Groundwater Risk Index – Purpose and Objective
 To shift the focus of the public, policy-makers, and academics on groundwater
depletion risk and its causes, from a purely physical perspective to a more multi-
dimensional viewpoint that accounts for the role of political and socio-economic
criteria in determining environmental risks
 To provide an assessment tool that addresses the limitations of existing water indices,
that primarily focus on surface water scarcity and stress assessments, and disregard
the groundwater risk assessments.
 To develop a tool designed at evaluating and pinpointing hotspots that are highly
susceptible to groundwater depletion and the associated adverse effects.

21. 2121
21
Define phenomenon being
measured and selection of
variables into a
meaningful composite
indicator
Theoretical
Framework and
Component Selection
Imputation of
Missing Data
Estimation of missing
data to provide complete
datasets, using multiple
Imputation and alternate
datasets
Normalization
Render data comparable,
in a manner consistent
with theoretical
framework and data
properties
Weighting and
Aggregation
Selection of weighting
and aggregation methods,
along the lines of the
theoretical framework and
data properties
Groundwater Risk Index – Design and Development

22. 2222
22
Define phenomenon being
measured and selection of
variables into a
meaningful composite
indicator
Theoretical
Framework and
Component Selection
Imputation of
Missing Data
Estimation of missing
data to provide complete
datasets, using multiple
Imputation and alternate
datasets
Normalization
Render data comparable,
in a manner consistent
with theoretical
framework and data
properties
Weighting and
Aggregation
Selection of weighting
and aggregation methods,
along the lines of the
theoretical framework and
data properties
Groundwater Risk Index – Design and Development
GW
Reserves
Governance
Food
Security
Groundwater
Extraction
Cost
GW
Storage
Change
GRI = w1GWR + w2GWSC + w3GOV + w4FS + w5GWEC
GW
Reserves

23. Groundwater Risk Index – Governance Indicator
2323
23
Reallocation
Mechanisms
Accountability
and Corruption
Control Over
Water Rights
Groundwater
Depletion
Governance Indicators:
 Freedom House
 Worldwide Governance Indicators
 International Country Risk Guide
 Transparency International

24. Groundwater Risk Index – Governance Indicator
2424
23
Reallocation
Mechanisms
Accountability
and Corruption
Control Over
Water Rights
Groundwater
Depletion
Governance Indicators:
 Freedom House
 Worldwide Governance Indicators
 International Country Risk Guide
 Transparency International
Voice and Accountability
Government Effectiveness
Regulatory Quality
Rule of Law
Control of Corruption
GI =
1
𝑁 1
𝑁
Gov 𝐷𝑖𝑚

25. 2525
24
Groundwater Risk Index – Food Security Indicator
Affordability
(40%)
Availability
(44%)
Nutritional
Diversity
(16%)
 Proxy measure of societies’ capacity to engage in external
virtual water trade.
 Inverse relationship between food security and
groundwater depletion.
 Reliance on virtual water trade already a reality in the
MENA Region.
Subindicators Data Sources
Affordability  Gross Domestic Product per Capita (PPP, USD)
 World Bank Database (http://data.worldbank.org/indicators/)
 United Nations Statistical Division (http://unstats.un.org/unsd/)
Availability
 Average Food Supply per Capita
(calories/day/person)
 Volatility of Domestic Agricultural Production
(CV)
 Food and Agriculture Organization Database
(http://faostat.fao.org/)
Nutritional Profile
 Percent of energy from non-staples
 Modified Shannon Entropy
 Remans, Roseline, et al. "Measuring nutritional diversity of
national food supplies." Global Food Security 3.3 (2014): 174-182.

26. 2626
25
Groundwater Risk Index – GW Extraction Cost Indicator
(1)
Vdiesel/kwh:
Fuel heat * Heat Rate
Diesel amount for GW extraction:
Vdiesel/kwh * (2)
(3)
Monetize GW extraction
using country-level pump
(real) price for diesel fuel
 Asymmetrical and skewed energy – water nexus: groundwater abstraction, conveyance,
and distribution is heavily reliant on fossil fuel energy resources.
 Groundwater abstraction in the MENA region is one of the most energy intensive
processes.
 Energy implications on water demand and consequent groundwater extraction.

27. 2727
26
Define phenomenon being
measured and selection of
variables into a
meaningful composite
indicator
Theoretical
Framework and
Component Selection
Imputation of
Missing Data
Estimation of missing
data to provide complete
datasets, using multiple
Imputation and alternate
datasets
Normalization
Render data comparable,
in a manner consistent
with theoretical
framework and data
properties
Weighting and
Aggregation
Selection of weighting
and aggregation methods,
along the lines of the
theoretical framework and
data properties
Groundwater Risk Index – Design and Development
Imputation of Missing Data:
1. using alternative datasets
2. multiple imputation
Min-Max Normalization [0, 100]:
1. ease of interpretation
2. preserves relationship between original data
Weighting and Aggregation:
1. Equal Weighting
2. Additive Arithmetic Mean (GRI = 1
𝑛
𝑤 𝑛 𝑞 𝑛)

28. 2828
27
Groundwater Risk Index – Results

29. 2929
28
Groundwater Risk Index – Results
Most RiskLeast Risk
Average normalized scores of final GRI results between 2003 and 2014

30. Groundwater Risk Index – Results
3030
29
Bump Graph Displaying Annual Temporal Changes in Groundwater Risk Ranking between 2003 and 2014
+ 2
+ 1
+ 1
+ 2
- 4
+ 3
- 2
+2
- 2
- 2
+ 1
+ 3
+ 1
- 3
- 2
- 1
Kuwait (R: 2  6, -4 )
Syria (R: 12  15, -3)
 Varying degrees of rank change:
Jordan (R: 2  6, +3 )
Yemen (R: 12  15, +3)
 Relatively stable period between 2003 and 2007, with heightened changes afterwards.

31. 3131
30
Groundwater Risk Index – Results
Average spatial variations in groundwater depletion risk in the MENA region between 2003 and 2014. Pie charts
reflect the impact of individual indicators on groundwater risk outcomes in MENA countries.

32. 3232Lezzaik, K., A. Milewski, and J. Mullen (2016), The Groundwater Risk Index: Development and Application in the Middle East and
North Africa Region, Earth-Science Reviews. 31
Groundwater Risk Index – Results
 Fundamental key points:
1. Groundwater allocations are an ineffective determinant of groundwater risk conditions.
2. A combination of efficient governance and developed high income economy is the best prescription to
mitigating groundwater depletion.
3. Centrality of governance in groundwater risk determinations.
A typology of
MENA countries
based on: (1)
hydrological
systems, and (2)
political economies

33. 3333
3032
Outline
 Introduction (Motivation, Research Questions, Research Objectives)
 Regional Groundwater Resource Assessment
 Groundwater [Depletion] Risk Index Development
 Groundwater Risk Index Sensitivity Analysis
 Conclusion

34. 3434
3033
Groundwater Risk Index – Sensitivity Analysis (SA)
Construction of composite indices involves stages where judgements have to be made.
 Sources of Sensitivity:
1. Indicator Selection
 One-Factor-at-a-time (OFAT), involves:
1. Change/remove one input variable/methodological choice, while keeping others constant,
2. Run model or function,
3. Compare resultsmodified with resultsoriginal
2. Normalization Scheme 3. Aggregation Method
 GRI sensitivity assessments are based on:
∆ scorec= scoreoriginal,c – scoremodified,c
∆ rankc= rankoriginal,c – rankmodified,c
∆ scorec represents score change for country c; scoreoriginal, c represents original GRI score for country c; and scoremodified,c represents modified GRI
score for country c; ∆ rankc represents rank shift for country c; scoreoriginal, c represents original GRI rank for country c; and scoremodified,c
represents modified GRI rank for country c.

35. 3535
3034
Groundwater Risk Index – Sensitivity Analysis (SA)
 Inclusion/Exclusion of individual indicators:
1. Exclusion of an individual indicator
2. Execute the composite index
3. Examine Δ in country rank and score
GRIoriginal = GWR + GWSC + GOV + FS + GWEC
GRImodified = GWR + GWSC + GOV + FS + GWEC
 Run GRI using the following normalization Schemes:
Min-Max Normalization
(baseline)
𝑥𝑖 − 𝑥 𝑚𝑖𝑛
𝑥 𝑚𝑎𝑥 − 𝑥 𝑚𝑖𝑛
Standardization (z-score)
𝑥𝑖 − 𝑚𝑒𝑎𝑛
𝑠𝑡𝑑
Reference to Distance
𝑥𝑖
𝑥 𝑟𝑒𝑓
 Run GRI using the following aggregation methods:
Additive Arithmetic Aggregation
(baseline)
1
𝑛
𝑞 𝑐
Multiplicative Geometric Aggregation
(𝑞 𝑐 )1/𝑛

36. 3636
3035
Groundwater Risk Index – Sensitivity Analysis
35
Sensitivity Analysis ALG EGY IRQ IPT JOR KWT LEB LIB MOR OMN QTR SDA SYR TUN UAE YMN
Subindicator
Exclusion/Inclusion
GRI excl. GWR 35 41 27 72 50 59 46 31 53 49 77 41 31 48 55 31
GRI excl. GWSC 29 32 19 74 43 63 44 24 47 42 70 32 27 41 59 22
GRI excl. GOV 35 35 31 61 39 52 48 36 47 36 58 32 37 39 48 32
GRI excl. FS 32 34 25 67 46 53 46 25 49 44 59 35 31 42 59 32
GRI excl. GWEC 37 39 28 67 46 58 45 34 42 49 66 45 37 43 63 28
Normalizati
onScheme
Min - Max 33 36 26 68 45 56 46 30 47 44 66 37 33 43 56 29
Z - Score 19 26 0 100 51 72 36 4 46 54 99 35 12 43 81 7
Indicization 23 28 0 100 57 58 36 6 51 58 91 40 12 46 88 14
Aggregation
Method
Arithmetic Mean 33 36 26 68 45 56 46 30 47 44 66 37 33 43 56 29
Geometric Mean 25 29 17 65 36 32 44 18 41 33 33 23 25 35 44 22
GRIOriginal Score 34 36 26 68 45 56 47 30 47 44 66 37 33 43 56 29
GRIOriginal Rank 12 11 16 1 7 4 6 14 5 8 2 10 13 9 3 15
GRIModified Score 30 34 20 74 46 56 44 24 47 45 69 36 28 42 61 25
GRIModified Rank 12 11 16 1 6 4 8 15 5 7 2 10 13 9 3 14
Δ GRI Score 4 2 6 -6 -1 0 3 6 0 -1 -3 1 5 0 -5 4
Δ GRI Rank 0 0 0 0 1 0 -2 -1 0 1 0 0 0 0 0 1
ALG (Algeria); EGY (Egypt); IRQ (Iraq); IPT (Israel and Palestinian Territories); JOR (Jordan); KWT (Kuwait); LEB (Lebanon); LIB (Libya); MOR (Morocco); OMN (Oman); QTR (Qatar); SDA (Saudi
Arabia); SYR (Syria); TUN (Tunisia); UAE (United Arab Emirates); YMN (Yemen).
 Aggregating sources of sensitivity using arithmetic averaging displays:
1. Modified GRI values are negligibly different than original baseline values in both score and rank terms
2. The robustness of GRI and its insensitivity to the aforementioned methodological alternatives
3. Did not affect overall analysis of groundwater risk in the MENA region using typological interpretation
Lezzaik, K.A., and A.M. Milewski (2016), Sensitivity Analysis of the Groundwater Risk Index in the Middle East and
North Africa Region, Water Resources Research (Submitted).

37. Outline
 Introduction (Motivation, Research Questions, Research Objectives)
 Regional Groundwater Resource Assessment
 Groundwater [Depletion] Risk Index Development
 Groundwater Risk Index Sensitivity Analysis
 Conclusion
3036

38. Conclusion
 Groundwater is unevenly distributed, with 75% of the reserves occurring in deep
sedimentary basins underlying four MENA countries.
 Largest declines in groundwater storage occurred along coastal areas with urban and
demographic concentrations.
 Groundwater storage changes are negligible, and present no short term threat to
groundwater reserves.
Groundwater Scarcity Assessment
3037

39. Conclusion
Groundwater Risk Assessment
 Groundwater endowments are consistently indeterminant of groundwater depletion
risk, unlike governance and economic factors
 Groundwater risk is best mitigated by a combination of good governance and high-
income economies, that provides the capacity to select and implement different
solutions to groundwater scarcity
 Overall, GRI is insensitive to alternative methodological choices, with exception to
aggregation methods.
3038

40. 3039
Conclusion
Scientific Contribution and Broader Implications
Results of our uniquely constructed groundwater scarcity assessment and
developed Groundwater Depletion Index (GRI), highlight and contribute to:
 The role of global integrated datasets and GIS systems in advancing out
understanding and knowledge of groundwater systems in data scarce regions.
 The shifting of discourse on water sector problems from solely the scientific
and technological sphere, to a multidisciplinary approach that formulates
groundwater issues through the integration of hydrological assessments with
non-water sectors solutions, such as governance, international trade, and
energy.

41. Thank You
Questions?
3039

42. Back Up Slides

43. Groundwater Risk Index – Indicator Selection (SA)
 Inclusion/Exclusion of individual indicators:
1. Exclusion of an individual indicator
2. Execute the composite index
3. Examine Δ in country rank and score
Country
GRI original GRI excl. GWR GRI excl. GWSC GRI excl. GOV GRI excl. FS GRI excl. GWEC
Scores Rank Score Rank Score Rank Score Rank Score Rank Score Rank
Israel and PT 68.1 1 72.2 2 (-1) 73.7 1 60.8 1 67.2 1 67.2 1
Qatar 66 2 77 1 (+1) 70.2 2 58.3 2 58.8 2 66 2
UAE 56.4 3 55.1 4 (-1) 59.4 4 (-1) 48.2 4 (-1) 58.7 3 62.8 3
Kuwait 55.8 4 58.8 3 (+1) 62.6 3 (+1) 51.8 3 (+1) 53.1 4 57.7 4
Morocco 47.3 5 52.5 5 46.5 5 47.1 6 (-1) 48.7 5 42 10 (-5)
Lebanon 46.5 6 45.5 9 (-3) 44.3 6 48.2 5 (+1) 46.2 6 45.4 7 (-1)
Jordan 44.8 7 50.2 6 (+1) 43 7 39.3 7 46 7 46 6 (+1)
Oman 44.2 8 49 7 (+1) 42.2 8 36.3 10 (-2) 44.1 8 49.3 5 (+3)
Tunisia 42.5 9 48.1 8 (+1) 40.7 9 39.3 8 (+1) 41.8 9 42.9 9
Saudi Arabia 36.9 10 40.8 11 (-1) 32.4 10 31.9 15 (-5) 34.8 10 44.7 8 (+2)
Egypt 36.2 11 40.8 10 (+1) 31.5 11 35.4 12 (-1) 34.1 11 38.6 11
Algeria 33.5 12 34.6 12 28.6 12 34.7 13 (-1) 32.4 12 36.7 12
Syria 32.6 13 31 13 27.2 13 36.6 9 (+4) 30.9 14 (-1) 36.6 13
Libya 29.8 14 30.8 14 23.6 14 35.6 11 (+3) 25.4 15 (-1) 33.6 14
Yemen 28.9 15 30.6 15 21.7 15 32.2 14 (+1) 31.7 13 (+2) 27.7 15
Iraq 25.6 16 26.7 16 18.6 16 30.5 16 24.7 16 27.6 16

44. Groundwater Risk Index – Normalization Scheme (SA)
 Run GRI using the following normalization Schemes:
Min-Max Normalization
(baseline)
𝑥𝑖 − 𝑥 𝑚𝑖𝑛
𝑥 𝑚𝑎𝑥 − 𝑥 𝑚𝑖𝑛
Standardization (z-score)
𝑥𝑖 − 𝑚𝑒𝑎𝑛
𝑠𝑡𝑑
Reference to Distance
𝑥𝑖
𝑥 𝑟𝑒𝑓
Country
Minimum - Maximum Normalization
(GRI original)
Z -Score Standardization Indicization (divide by largest)
Score Ranking Quantile Rank Score Ranking Quantile Rank Score Ranking Quantile Rank
Israel and PT 68.1 1 75th
or higher 2.4 1 75th
or higher 47.4 1 75th
or higher
Qatar 66 2 75th
or higher 2.3 2 75th
or higher 41.6 2 75th
or higher
UAE 56.4 3 75th
or higher 1.7 3 75th
or higher 40 3 75th
or higher
Kuwait 55.8 4 75th
or higher 1.4 4 75th
or higher 20.9 4 75th
or higher
Oman 44.2 8 50th
to 74th
0.7 5 (+3) 50th
to 74th
20.3 5 (+3) 50th
to 74th
Jordan 44.8 7 50th
to 74th
0.6 6 (+1) 50th
to 74th
20.2 6 (+1) 50th
to 74th
Morocco 47.3 5 50th
to 74th
0.4 7 (-2) 50th
to 74th
16.1 7 (-2) 50th
to 74th
Lebanon 46.5 6 50th
to 74th
0.1 9 (-3) 25th to 49th 6.9 10 (-4) 25th to 49th
Tunisia 42.5 9 25th
to 49th
0.3 8 (+1) 50th to 74th 13.1 8 (+1) 50th to 74th
Saudi Arabia 36.9 10 25th
to 49th
0 10 25th
to 49th
9 9 25th
to 49th
Egypt 36.2 11 25th
to 49th
-0.3 11 25th
to 49th
1.7 11 25th
to 49th
Algeria 33.5 12 25th
to 49th
-0.6 12 25th
to 49th
-1.5 12 25th
to 49th
Syria 32.6 13 24th
or lower -0.8 13 24th
or lower -8.7 14 (-1) 24th or lower
Yemen 28.9 15 24th
or lower -1 14 (+1) 24th
or lower -7 13 (+2) 24th or lower
Libya 29.8 14 24th
or lower -1.1 15 (-1) 24th
or lower -12.4 15 (-1) 24th or lower
Iraq 25.6 16 24th
or lower -1.3 16 24th
or lower -16.3 16 24th or lower

45. Groundwater Risk Index – Aggregation Method (SA)
 Run GRI using the following aggregation methods:
Additive Arithmetic Aggregation
1
𝑛
𝑞 𝑐
Multiplicative Geometric Aggregation
(𝑞 𝑐 )1/𝑛
Country
Weighted Arithmetic Mean (GRIoriginal) Weighted Geometric Mean
Score Rank Quantile Rank Score Rank Quantile Rank
Israel and PT 68.1 1 75th or higher 65.2 1 75th or higher
UAE 56.4 3 75th or higher 44.3 2 (-1) 75th or higher
Qatar 66 2 75th or higher 33.2 7 (+5) 50th to 74th
Lebanon 46.5 6 50th to 74th 43.7 3 (-3) 75th or higher
Kuwait 56 4 75th or higher 32.4 9 (+5) 25th to 49th
Morocco 47.3 5 50th to 74th 40.7 4 (-1) 75th or higher
Jordan 44.8 7 50th to 74th 36.5 5 (-2) 50th to 74th
Tunisia 42.5 9 25th to 49th 34.9 6 (-3) 50th to 74th
Oman 44.2 8 50th to 74th 33.2 8 50th to 74th
Egypt 36.2 11 25th to 49th 29.4 10 (-1) 25th to 49th
Saudi Arabia 36.9 10 25th to 49th 22.5 13 (+3) 24th or lower
Algeria 33.5 12 25th to 49th 24.9 12 25th to 49th
Syria 32.6 13 24th or lower 25.3 11 (-2) 25th to 49th
Yemen 28.9 15 24th or lower 22.5 14 (-1) 24th or lower
Libya 29.8 14 24th or lower 17.6 15 (+1) 24th or lower
Iraq 25.6 16 24th or lower 17.1 16 24th or lower

46. Groundwater Risk Index – Sensitivity Analysis
Sensitivity Analysis ALG EGY IRQ IPT JOR KWT LEB LIB MOR OMN QTR SDA SYR TUN UAE YMN
Subindicator
Exclusion/Inclusion
GRI excl. GWR 35 41 27 72 50 59 46 31 53 49 77 41 31 48 55 31
GRI excl. GWSC 29 32 19 74 43 63 44 24 47 42 70 32 27 41 59 22
GRI excl. GOV 35 35 31 61 39 52 48 36 47 36 58 32 37 39 48 32
GRI excl. FS 32 34 25 67 46 53 46 25 49 44 59 35 31 42 59 32
GRI excl. GWEC 37 39 28 67 46 58 45 34 42 49 66 45 37 43 63 28
Normalizati
onScheme
Min - Max 33 36 26 68 45 56 46 30 47 44 66 37 33 43 56 29
Z - Score 19 26 0 100 51 72 36 4 46 54 99 35 12 43 81 7
Indicization 23 28 0 100 57 58 36 6 51 58 91 40 12 46 88 14
Aggregation
Method
Arithmetic Mean 34 36 26 68 45 56 46 30 47 44 66 37 33 43 56 29
Geometric Mean 25 29 17 65 36 32 44 18 41 33 33 23 25 35 44 22
GRIOriginal Score 34 36 26 68 45 56 47 30 47 44 66 37 33 43 56 29
GRIOriginal Rank 12 11 16 1 7 4 6 14 5 8 2 10 13 9 3 15
GRIModified Score 30 34 20 74 46 56 44 24 47 45 69 36 28 42 61 25
GRIModified Rank 12 11 16 1 6 4 8 15 5 7 2 10 13 9 3 14
Δ GRI Score 4 2 6 -6 -1 0 3 6 0 -1 -3 1 5 0 -5 4
Δ GRI Rank 0 0 0 0 1 0 -2 -1 0 1 0 0 0 0 0 1
ALG (Algeria); EGY (Egypt); IRQ (Iraq); IPT (Israel and Palestinian Territories); JOR (Jordan); KWT (Kuwait); LEB (Lebanon); LIB (Libya); MOR (Morocco); OMN (Oman); QTR (Qatar); SDA (Saudi
Arabia); SYR (Syria); TUN (Tunisia); UAE (United Arab Emirates); YMN (Yemen).
 Aggregating sources of sensitivity using arithmetic averaging displays:
1. Modified GRI values are negligibly different than original baseline values in both score and rank terms
2. The robustness of GRI and its insensitivity to the aforementioned methodological alternatives
3. Did not affect overall analysis of groundwater risk in the MENA region using typological interpretation

47. Study comparison of groundwater storage capacity in the Arabian Aquifer System,
Nubian Aquifer System, and Northwestern Sahara Aquifer system.

48. Country WTD (meters)
WTD+GWSC
(meters)
Δ
Algeria 48.11 48.22 0.22%
Egypt 67.99 68.31 0.47%
Iraq 17.47 16.90 -3.26%
Israel 34.67 35.10 1.23%
Jordan 32.01 31.85 -0.51%
Kuwait 20.23 20.54 1.54%
Lebanon 35.77 34.89 -2.45%
Libya 47.69 47.83 0.31%
Morocco 53.36 53.98 1.16%
Oman 25.42 24.00 -5.59%
Saudi Arabia 30.53 30.79 0.85%
Syria 22.52 22.52 0.02%
Tunisia 34.89 34.77 -0.33%
United Arab Emirates 21.96 22.25 1.33%
Yemen 52.06 51.16 -1.73%

49. Mus
cat

50. Groundwater Depletion Effects
The social and economic impacts of groundwater depletion are directly tied to the
environmental effects it effects:
 Greater capital investments in well construction and pumping plants
 Imposes economic costs on different societal sectors, especially farmers
 Optimizes conflict conditions
 Damage public infrastructure and private property
 Generates societal instability, conflict and migration waves

51. “Annual recharge variations were also estimated and vary
between 0 and 4.40 km3 yr-1 for the period 2003-2010. These
values correspond to a recharge between 0 and 6.75 mm yr-
1…which is consistent with the expected weak and sporadic
recharge in this semi-arid environments.”

52. “Stable Isotope contents in the groundwater and springs indicate their
recharge sources to be the seasonal monsoon airmasses from the
Indian ocean and Arabian Sea”

53. “ Detailed measurements of the soil retention capacity and the inflow
to the karst yield a yearly groundwater recharge of 44 mm over the last
16 years, contributing significantly to the aquifer”

69. WGI Criticisms

72. 2003
WECG Food S. Gov GWR GWSC
2004
WECG Food S. Gov GWR GWSC
2005
WECG Food S. Gov GWR GWSC
WECG - -0.03 -0.07 0.11 -0.17 WECG - -0.04 -0.08 0.11 -0.24 WECG - -0.04 -0.04 0.11 -0.18
Food S. -0.03 - 0.45 0.04 -0.03 Food S. -0.04 - 0.41 0.04 -0.10 Food S. -0.04 - 0.33 0.02 -0.06
Gov -0.07 0.45 - 0.00 -0.08 Gov -0.08 0.41 - 0.01 -0.08 Gov -0.04 0.33 - 0.01 -0.13
GWR 0.11 0.04 0.00 - 0.02 GWR 0.11 0.04 0.01 - 0.02 GWR 0.11 0.02 0.01 - 0.08
GWSC -0.17 -0.03 -0.08 0.02 - GWSC -0.24 -0.10 -0.08 0.02 - GWSC -0.18 -0.06 -0.13 0.08 -
2006
WECG Food S. Gov GWR GWSC
2007
WECG Food S. Gov GWR GWSC
2008
WECG Food S. Gov GWR GWSC
WECG - -0.06 -0.03 0.11 -0.02 WECG - -0.06 -0.03 0.10 0.02 WECG - -0.09 0.01 0.11 0.17
Food S. -0.06 - 0.28 0.02 -0.23 Food S. -0.06 - 0.33 0.00 -0.15 Food S. -0.09 - 0.35 0.00 0.01
Gov -0.03 0.28 - 0.01 -0.22 Gov -0.03 0.33 - 0.00 -0.21 Gov 0.01 0.35 - -0.01 0.05
GWR 0.11 0.02 0.01 - 0.05 GWR 0.10 0.00 0.00 - -0.01 GWR 0.11 0.00 -0.01 - -0.01
GWSC -0.02 -0.23 -0.22 0.05 - GWSC 0.02 -0.15 -0.21 -0.01 - GWSC 0.17 0.01 0.05 -0.01 -
2009
WECG Food S. Gov GWR GWSC
2010
WECG Food S. Gov GWR GWSC
2011
WECG Food S. Gov GWR GWSC
WECG - -0.06 -0.08 0.10 0.14 WECG - -0.04 -0.02 0.10 0.13 WECG - -0.04 0.00 0.09 0.15
Food S. -0.06 - 0.36 0.00 0.08 Food S. -0.04 - 0.37 -0.02 0.00 Food S. -0.04 - 0.40 -0.03 0.11
Gov -0.08 0.36 - -0.03 0.10 Gov -0.02 0.37 - -0.03 -0.06 Gov 0.00 0.40 - 0.00 0.04
GWR 0.10 0.00 -0.03 - -0.02 GWR 0.10 -0.02 -0.03 - -0.07 GWR 0.09 -0.03 0.00 - -0.04
GWSC 0.14 0.08 0.10 -0.02 - GWSC 0.13 0.00 -0.06 -0.07 - GWSC 0.15 0.11 0.04 -0.04 -
2012
WECG Food S. Gov GWR GWSC
2013
WECG Food S. Gov GWR GWSC
2014
WECG Food S. Gov GWR GWSC
WECG - 0.04 0.05 0.10 0.06 WECG - -0.02 0.10 0.10 0.04 WECG - -0.01 0.05 0.09 0.02
Food S. 0.04 - 0.28 0.00 0.13 Food S. -0.02 - 0.23 -0.01 0.17 Food S. -0.01 - 0.29 -0.01 0.20
Gov 0.05 0.28 - -0.01 0.14 Gov 0.10 0.23 - -0.01 0.16 Gov 0.05 0.29 - -0.01 0.16
GWR 0.10 0.00 -0.01 - -0.02 GWR 0.10 -0.01 -0.01 - 0.00 GWR 0.09 -0.01 -0.01 - 0.01
GWSC 0.06 0.13 0.14 -0.02 - GWSC 0.04 0.17 0.16 0.00 - GWSC 0.02 0.20 0.16 0.01 -
12 Year
Average
WECG Food S. Gov GWR GWSC
WECG - -0.04 -0.01 0.10 0.01
Food S. -0.04 - 0.34 0.00 0.01
Gov -0.01 0.34 - -0.01 -0.01
GWR 0.10 0.00 -0.01 - 0.00
GWSC 0.01 0.01 -0.01 0.00 -