published: 10 March 2022
Frontiers in Water | www.frontiersin.org 1March 2022 | Volume 4 | Article 825854
Tendai Polite Chibarabada,
WaterNet Trust, Botswana
Texas A&M Energy Institute,
Texas A&M University, United States
Gareth B. Simpson
This article was submitted to
Water and Human Systems,
a section of the journal
Frontiers in Water
Received: 30 November 2021
Accepted: 02 February 2022
Published: 10 March 2022
Simpson GB, Jewitt GPW, Becker W,
Badenhorst J, Masia S, Neves AR,
Rovira P and Pascual V (2022) The
Water-Energy-Food Nexus Index: A
Tool to Support Integrated Resource
Planning, Management and Security.
Front. Water 4:825854.
The Water-Energy-Food Nexus Index:
A Tool to Support Integrated
Resource Planning, Management and
Gareth B. Simpson 1,2
*, Graham P. W. Jewitt2,3 , William Becker 4, Jessica Badenhorst 1,
Sara Masia 3,5 , Ana R. Neves 6, Pere Rovira 7and Victor Pascual 7
1Jones & Wagener (Pty) Ltd., Pretoria, South Africa, 2Centre for Water Resources Research, University of KwaZulu-Natal,
Pietermaritzburg, South Africa, 3IHE Delft Institute for Water Education, Delft, Netherlands, 4BlueFox Data Consulting, Ispra,
Italy, 5CMCC Foundation – Euro-Mediterranean Centre on Climate Change, Impacts on Agriculture, Forests and Ecosystem
Services Division, Sassari, Italy, 6Joint Research Centre, Competence Centre on Composite Indicators and Scoreboards,
Ispra, Italy, 7OneTandem SL, Barcelona, Spain
The call for measuring synergies and trade-offs between water, energy, and food
is increasing worldwide. This article presents the development and application of a
country-level index that has been calculated for 181 nations using open databases.
Following an assessment of 87 water-, energy-, and food-related indicators, 21 were
selected to constitute the Water-Energy-Food (WEF) Nexus Index. In this article, the WEF
Nexus Index is utilized to assess the Southern African Development Community, where it
demonstrates that food security is an area of concern, while the potential for beneﬁcially
exploiting water resources and energy projects exists in several countries. Water for
agriculture could be achieved through the drought-prooﬁng of rainfed agriculture and
systematic irrigation development, with energy as the critical enabler. Neither the
composite indicator nor the WEF nexus approach is the panacea that will solve all
the signiﬁcant development or environmental challenges facing humanity. However,
they could contribute to integrated resource management and policy-making and are
complementary to the Sustainable Development Goals. In this study, the methodology
set out by the Joint Research Centre’s Competence Center on Composite Indicators and
Scoreboards has been followed. A set of visualizations associated with the WEF Nexus
Index have been compiled in an interactive website, namely www.wefnexusindex.org.
Keywords: WEF, nexus, composite indicator, SDGs, SADC, open data
The global demand for resources such as water, energy and food is expected to escalate
dramatically in the forthcoming decades (Beddington, 2009; World Economic Forum, 2011;
National Intelligence Council, 2012; WWF and SABMiller, 2014). The increasing demand is being
driven by a worldwide population growth not only in number but also in consumption patterns,
primarily due to a burgeoning middle class and urbanization (FAO, 2018). While much economic
development has occurred over the past two and a half centuries, there has been a marked disparity
in this growth. In the world’s least developed countries:
•the agricultural sector utilizes 71 and 30% of the global water withdrawals and energy,
respectively (Mohtar and Daher, 2012; FAO, 2014);
Simpson et al. Water-Energy-Food Nexus Index
•one-third of all food produced globally is either lost or wasted
•10% of the globally available freshwater is utilized in energy
production (WWAP, 2020), while domestic uses constitute
14% of water utilization (World Economic Forum, 2011);
•the bioenergy sector utilizes 1% of all food produced (Garcia
and You, 2016);
•in 2011, only 13% of the energy generated globally originated
from renewable sources (Hoﬀ, 2011); and
•4% of all energy generated is utilized for the abstraction,
conveyance and treatment of water (WWAP, 2020), while total
industrial withdrawals account for 16% of today’s global water
demand (World Economic Forum, 2011).
This disparity has resulted in global eﬀorts to support initiatives
to achieve resource securities for the “bottom billion,” which is
that portion of the “world’s population living on <US$1.25 per
day” (UNESCO, 2014). A further stressor is that the international
supply chain system must deliver products and resources on a
planet where predominant risks include extreme weather events,
natural disasters, and resource depletion (World Economic
Forum, 2018). This has been demonstrated in the outworking of
the COVID-19 pandemic.
The 2008 ﬁnancial crisis raised concerns about resource-
eﬃcient management and the consequent feedback on
the environment, livelihoods and economic development
(Beddington, 2009, 2010; Rockstrom et al., 2009). Salam
et al. (2017) argue that the disparity between future
availability and demand will not be closed through an
increased supply but rather through eﬀective demand-side
management and policy interventions. Since 2011, signiﬁcant
attention has been given to the water-energy-food (WEF)
nexus in the academic, policy, regulatory and development
communities (Simpson and Jewitt, 2019a). The Bonn2011
Conference (Hoﬀ, 2011) and the World Economic Forum’s
publication Water Security: The Water-Food-Energy-Climate
Nexus (World Economic Forum, 2011) were inﬂuential in
The word nexus means to “connect” (De Laurentiis et al.,
2016), although its application is varied. The view that
water resources, energy generation, and food production are
interdependent is not novel (Allouche et al., 2015; Muller, 2015;
Wichelns, 2017). Sušnik (2018) argues that the earliest global
study on a nexus was the publication The Limits of Growth
(Meadows et al., 1972) in 1972. One of the main goals of the nexus
approach is to reduce or avoid trade-oﬀs resulting from policy
development in institutional “silos” (Belinskij, 2015). The WEF
nexus approach has, however, not been without criticism. Cairns
and Krzywoszynska (2016) considered it to be a “buzzword,”
and several recent publications have argued that the approach
has not lived up to its potential (Albrecht et al., 2018; FAO,
2018; Galaitsi et al., 2018). These critiques have emphasized the
need for a migration from “nexus thinking” to “nexus doing”
(McGrane et al., 2018). The imperative to integrate qualitative
and quantitative nexus assessments has been highlighted in
recent literature (FAO, 2018; Galaitsi et al., 2018; Allouche et al.,
2019; Hoﬀ et al., 2019; Simpson and Jewitt, 2019b).
Salam et al. (2017) argue that the interconnections between
the Sustainable Development Goals (SDGs) emphasize the need
for nexus thinking. El Costa (2015) suggested that since the SDGs
seek to incorporate multiple development goals, identifying
targets at the nexus of various sectors can be instrumental in
yielding a less complicated SDG framework. Internationally, the
WEF nexus has become accepted as a mechanism for facilitating
progress toward the relevant sector-related SDGs, i.e., SDGs 2,
6, and 7 (Simpson and Jewitt, 2019a). The WEF nexus approach
is, therefore, recognized as a promising tool for achieving the
relevant sector-related SDGs and holds promise for the guidance
of development initiatives aligned with Nationally Determined
Contributions (NDCs) of the Paris Agreement.
Ringler et al. (2013) suggested that the SDGs present a crucial
test for implementing the nexus approach at an international
level. Yet to date, no country is on track to achieve all the
goals by 2030 (Sachs et al., 2018). Furthermore, if the nexus is
to be utilized as a lens for sustainable development, then any
conceptual framework developed for the WEF nexus must also
address the global disparity in access to resources, i.e., equity,
together with environmental rights (Biggs et al., 2015; de Grenade
et al., 2016).
While there has been a considerable eﬀort to develop tools to
monitor progress toward the SDGs (Sachs et al., 2019), there is
less progress in assessing trade-oﬀs between diﬀerent SDGs or
resource sectors such as those represented by a nexus within the
SDGs, e.g., the WEF nexus. One means of assessing a multifaceted
system where parameters are quantiﬁed with diﬀerent units of
measurement (de Loë and Patterson, 2017; Wichelns, 2017) is
through the development of a composite indicator (or index),
which results “when individual indicators are compiled into a
single index on the basis of an underlying model” (OECD, 2008).
The aim of this work is to introduce a composite indicator that
allows a stakeholder to quantify and monitor the WEF nexus
interlinkages at a national level. Following an assessment of 87
globally applicable water-, energy-, and food-related indicators,
21 were selected to constitute the WEF Nexus Index, which was
calculated for 181 countries.
This article presents the WEF Nexus Index with its application
to the Southern African Development Community (SADC). The
SADC nations share many natural resources and have complex
political and social systems that inﬂuence the availability and
access to these resources. The SADC region is an ideal case
study for applying the WEF Nexus Index due to the inherent
opportunities and threats to sustainable development and the
potential for policy interventions.
In this study, the methodology set out by the Joint Research
Centre’s Competence Center on Composite Indicators and
Scoreboards (JRC:COIN) has been followed (Saisana et al.,
2018). The JRC:COIN have been involved in over 60
statistical audits of composite indicators, amongst others, the
Environmental Performance Index (Yale University, Columbia
University), the Multidimensional Poverty Assignment Tool
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Simpson et al. Water-Energy-Food Nexus Index
(UN International Fund for Agricultural Development), the
Global Competitiveness Index (World Economic Forum), and
the Corruption Perceptions Index (Transparency International)
(Saisana et al., 2018).
The JRC:COIN’s methodology consists of 10 steps (OECD,
2008; Saisana et al., 2018). Initially, a conceptual framework
needs to be developed for the context under assessment. This
framework is subsequently utilized to guide the selection of a
set of relevant and available indicators. These indicators are
normalized, weighted and aggregated, thereby yielding a unitless
index that represents the context being appraised. An index
is complementary to the underlying data, representing it in a
coherent manner. The index also provides an access point to the
complex data set upon which it is based, thereby enabling the
identiﬁcation of patterns and trends. Indices must be developed
sensibly and transparently and used responsibly, since they can
be misused (Saisana et al., 2018). However, they have been shown
to be valuable decision making and policy tools.
Development of the Framework
According to the JRC:COIN, the ﬁrst step in forming a composite
indicator is the development of a framework for the system under
assessment (Saisana et al., 2018). To this end, the anthropocentric
WEF nexus framework, presented in Figure 1, was utilized as
the basis for the WEF Nexus Index’s construction. The basis of
this framework’s development was a consideration of what lies
at the center of this nexus. It was concluded that humanity lies
at its center. At the core of this framework is, therefore, human
society, i.e., Anthropos (Greek for human), with its insatiable
demand for resources. Globally, access to resources such as water,
energy and food is not equitable, hence the inclusion of three
water-, energy-, and food-related SDGs in this framework. Each
SDG has targets that “are universally applicable and aspirational”
(UN Water, 2018). The framework also reﬂects the priorities of
the global South in achieving both access to and provision of
resources (Simpson et al., 2020).
Further, water, energy, and food are ultimately obtained from
the natural resource base (Rockström and Sukhdev, 2016) and the
ﬂow of resources from the environment to the source of demand,
i.e., humans, is therefore the dominant driver within this system.
These resources are procured from the environment in manners
that are either renewable or non-renewable. In addition, the
climate and environment are managed and regulated through
sound (or poor) governance and policies, as shown by the two
intermediate layers within the proposed framework. At the core
of this framework is “access” and “demand” related to the three
core resource sectors, i.e., “leave no one behind” and managing
the global supply chain system. This proposed framework is
especially applicable to the developing world due to its emphasis
on SDGs 2, 6, and 7, as well as the all-encompassing role of
governance and policy that promotes sustainable development
and the protection of the environment.
The environment, land, and climate are represented by the
outer layers of this framework since, in many cases, planetary
boundaries are being tested or even exceeded (Steﬀen et al.,
2018). The framework also demonstrates that while humanity
is at the center of the global supply chain system, they are also
custodians of the governance and policies related to these three
Selection of Indicators
The second stage of the JRC:COIN methodology in the
development of a composite indicator is the selection of the
indicators that will constitute the index. Figure 2 shows that,
for a given context (e.g., the WEF nexus), indicators and
indices are developed from data to yield information that can
ultimately be used for decision- and policy-making and the
interactions between these aspects. These decisions and policies
will then be based on ﬁrm knowledge, founded on veriﬁable
information, which will limit knee-jerk decisions and conjecture.
As information is developed, it can, in turn, inﬂuence the
data collection and indicators for reﬁning the process. Other
quantitative and qualitative studies can augment the information
generated, and various feedback loops can improve and optimize
the data gathering process. These studies could include socio-
economic and institutional indicators, models or surveys.
Based on the framework shown in Figure 1, the WEF Nexus
Index has three equal pillars representing water, energy and food
(refer to Figure 3). Each of these resource sectors, in turn, have
“access” and “availability” sub-pillars. The “access” component
of the WEF nexus relates to the urgent need for worldwide
distributional justice, i.e., equitable access to resources. This
is the perspective from which the WEF Nexus Index was
developed (Simpson et al., 2020). While equitable access to
resources is essential, the physical availability thereof is of equal
importance. Therefore, the energy-access sub-pillar includes
an access indicator, two indicators that represent renewable
energy consumption and output, and an indicator related to
CO2emissions per capita. This is because this pillar relates to
SDGs 7 and 13, i.e., access to modern energy that addresses
Internationally, data are collected by various organizations
such as national statistical oﬃces, government departments,
non-governmental organizations and international organizations
such as the World Bank, International Energy Agency (IEA),
Food and Agriculture Organization of the United Nations (FAO)
and the World Health Organization (WHO). A global search
of these databases resulted in a list of 87 water-, energy-,
and food-related indicators that were subsequently reviewed for
both relevance and data availability at a national scale via a
rigorous and iterative process. For an indicator to be included
in an index, at the indicator level, at least 65% of countries
should have valid data. Similarly, and at the country level, at
least 65% of indicators should have valid data (Saisana et al.,
Selection criteria included relevance, added value, data
availability, and reliability, together with a correlation analysis to
identify possible aggregation issues or double-counting (Simpson
et al., 2020). If the correlation of the indicators was too high,
taken to be equal to or >0.92 in this study, then this constituted
double-counting, i.e., eﬀectively including the same variable
twice (OECD, 2008). In this case, one of the highly correlated
indicators was omitted from the WEF Nexus Index.
Frontiers in Water | www.frontiersin.org 3March 2022 | Volume 4 | Article 825854
Simpson et al. Water-Energy-Food Nexus Index
FIGURE 1 | The Anthropocentric WEF nexus framework (from Simpson et al., 2020).
FIGURE 2 | From data to decision making; modiﬁed from Segnestam (2002) and Waas et al. (2014).
Details of each indicator evaluated, and a rationale for its
inclusion or exclusion in the WEF Nexus Index is provided in
Addendum A. One of the challenges experienced in the selection
of indicators is that there are very few indicators that measure the
linkages between the constituent sectors, i.e., “nexus” indicators
that measure water for energy, water for food, energy for water,
etc. Where these “nexus” or “integrated” indicators do exist, they
are invariably reported by too few countries to form part of the
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Simpson et al. Water-Energy-Food Nexus Index
FIGURE 3 | Schematic layout of the WEF Nexus Index, with its constituent pillars, sub-pillars, and indicators.
index. These indicators could, however, form part of an in-depth
study for countries that do report these parameters.
Both the anthropocentric WEF nexus framework and the
selection of indicators to form the WEF Nexus Index were
presented at various forums during this project to facilitate
stakeholder/expert engagement. These interactions proved to be
beneﬁcial in obtaining vital input on both the interpretation of
the framework and the ﬁnal selection of indicators. The forums
that the conceptual framework and indicators were presented
•A Research-on-Tap Seminar entitled “Toward a Water-
Energy-Food Nexus Index” at the University of KwaZulu-
Natal’s Center for Water Resources Research on 25 April 2019,
in Pietermaritzburg, South Africa,
•A workshop entitled the “Development of the Water-
Energy-Food Nexus Index and its application to South
Africa and the South African Development Community
(SADC): From Theory to Practice” at the Water
Research Commission in Pretoria, South Africa, on 10
•A presentation at the 2019 European Climate Change
Adaptation Conference in Lisbon, Portugal, on 30 May
2019, entitled the “Development of the Water-Energy-
Food Nexus Index and its application to South Africa
•A lunchtime seminar at IHE Delft Institute for Water
Education, Delft, The Netherlands on 5 June 2019,
entitled the “Development of the Water-Energy-Food
Nexus Index and its application to South Africa and
•A JRC:COIN Open Day in Ispra, Italy, on 7 June 2019,
entitled the “Development of the Water-Energy-Food
Nexus Index and its application to South Africa
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Simpson et al. Water-Energy-Food Nexus Index
The outcome of this analysis and stakeholder/expert engagement
was that a set of 21 indicators were selected to compose the WEF
Nexus Index, the structure of which is presented in Figure 3.
Adequate data is available for the index to be calculated for
The water-access sub-pillar represents SDG 6 (access to at
least basic drinking water and sanitation services) and the
degree of IWRM (which is an indicator of good governance in
terms of water resources management). The energy-access sub-
pillar includes both access to electricity (SDG indicator 7.1.1)
and two indicators that appertain to the degree of renewable
energy consumption (SDG indicator 7.2.1) and implementation,
as well as CO2emissions (which is an indicator of the degree
of dependence on fossil fuels). These indicators have been
aggregated because SDG 7 appertains to access to aﬀordable,
reliable, sustainable and modern energy for all, and not simply
“access to energy.”
The food-access sub-pillar includes, amongst others, SDG
indicators 2.1.1 (prevalence of undernourishment), 2.2.1
(percentage of children under 5 years of age who are stunted)
and FAO indicator 4.8 (prevalence of obesity in the adult
population). The food-accessibility sub-pillar includes FAO
indicators 1.1 (average dietary energy supply adequacy), 1.2
(average value of food production) and 1.4 (average protein
supply), and the cereal yield in kilograms per hectare.
The latest available data (in August 2019) was utilized for the
calculation of the WEF Nexus Index, with the reference year
varying between indicators, as presented in Addendum A.
Data Treatment and Normalization
Following the selection of indicators, missing data were
imputed where appropriate or necessary in accordance with the
JRC:COIN guidelines. One case of imputation was for levels
of undernourishment in high-income countries. Here, average
values reported by UNICEF were utilized, e.g., the average
prevalence of undernourishment in high-income countries is
1.2% (Sachs et al., 2018). All indicators were then normalized
to transform them into a uniform scale: [0:100] (OECD, 2008).
This is standard practice in composite indicator construction,
since not only are the indicators measured in diﬀerent units,
but their values vary markedly, e.g., the indicator Percentage of
children under 5 years of age who are aﬀected by wasting varies
from 0.3 to 22.7%, whereas the Renewable internal freshwater
resources per capita vary from 2.5 to 519 265 cubic meters. In
this project, the min-max method was utilized to normalize the
data (Saisana et al., 2018; Simpson et al., 2020). Where there
was no data for an indicator, shallow imputation was applied,
whereby it “calculates the sub-pillar score by taking the mean
only over the indicators that have data” (Becker et al., 2019). This
is the same as substituting the missing value with the normalized
mean of the other indicators in the aggregation group (e.g., pillar
Outliers were treated in particular cases. This practice is
necessary since outliers “generally spoil basic descriptive statistics
such as the mean, the standard deviation, and correlation
coeﬃcient, thus causing misinterpretation” (Saisana et al., 2018).
Where the skewness and kurtosis of an indicator’s data set
exceeded the generally accepted range, i.e., |<2| and |<3.5|,
respectively, a process of either Winsorisation (where there are
ﬁve or fewer outliers) or a Box-cox transformation (if the number
of outliers exceeds ﬁve) was adopted (Saisana et al., 2018). This is
described in more detail in Simpson et al. (2020).
Weighting and Aggregation of Indicators
The sub-pillar scores were obtained by determining the weighted
arithmetic average of the indicators in each sub-pillar. Pillar
scores were calculated using the arithmetic average of the
corresponding sub-pillar scores, and the ﬁnal index score was an
arithmetic average of the pillar scores. Equal weighting was used
at the pillar level to preserve the multi-centric philosophy of the
WEF nexus approach, such that each resource sector has equal
importance (Allouche et al., 2015; Benson et al., 2015; Owen
et al., 2018). Given that some sub-pillars contain more indicators
than others and the fact that some indicators in a sub-pillar have
stronger weightings than others, the ﬁnal weight of each indicator
in the overall index is unequal. The ﬁnal weights, per aggregation
level, are presented in Addenda B,C.
The arithmetic mean was used for aggregation despite
its known property of compensability. Compensability refers
to the extent to which a decrease in one indicator can be
compensated for by an increase in another indicator. If the
indicators are summed, i.e., using the arithmetic mean, there is
a higher degree of compensability than if they are multiplied,
i.e., using the geometric mean. This is because the latter
method “penalizes” lower scores in indicators to a greater extent
than the former method. The use of the arithmetic mean to
calculate the WEF Nexus Index was, nevertheless, prefered
because there is a reasonable degree of substitutability between
constituent indicators and utilizing the arithmetic mean is
easier to understand than the geometric mean. This method of
aggregation was also adopted in the development of the SDG
Index (Sachs et al., 2016, 2018).
The WEF Nexus Index has been calculated for the 181 nations
that had suﬃcient data for 2019, as presented in Figure 4. The
ﬁve highest-ranking countries are Iceland, Canada, Norway, New
Zealand, and the United States of America, respectively, while
the ﬁve lowest-ranking countries are Eritrea, South Sudan, Chad,
Somalia and Haiti. Amongst the 20 highest-ranking nations
for the index are 12 Organization for Economic Co-operation
and Development (OECD) countries. While the 20 highest-
ranking nations are predominantly developed countries, four
South American and three Asian countries are on this list. The
four South American countries in the top 20 are Brazil, Uruguay,
Columbia, and Paraguay. The three Asian nations are Bhutan,
Hong Kong and Lao. While no African countries feature in the 20
highest-ranking nations for the index, it is striking that 17 of the
lowest-ranking countries are from Africa. Based on this ﬁnding,
an in-depth analysis of the WEF Nexus Index is presented for
the SADC. A dashboard for all the 181 countries, with their rank,
is presented in Addendum D. The 21 indicators calculated for
the 16 SADC nations are presented graphically in Supplementary
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Simpson et al. Water-Energy-Food Nexus Index
FIGURE 4 | WEF Nexus Index world map with a focus (in glyphs) on selected countries (interactive website at https://www.wefnexusindex.org/). Latest available data
as of August 2019.
Figures S1–S21 in Addendum E. In Addendum F, the untreated
indicator data (e.g., from the World Bank, International Energy
Agency, and FAO) for the 21 indicators that constitute the WEF
Nexus Index are presented.
SADC Case Study
The purpose of this case study is to demonstrate how the WEF
Nexus Index, and its hierarchically structured constituents, can
be utilized in a systematic analysis for a region. By exploring the
underlying pillars, sub-pillars and indicators, the SADC nation’s
status in terms of access to and availability of water, energy
and food becomes evident and emphasizes the remaining work
required for this region to attain the SDGs and NDCs. Table 1
presents the median WEF Nexus Index values and ranks for the
16 SADC nations, together with the median and average values.
The two highest-ranking SADC nations, in terms of the
WEF Nexus Index, are Seychelles and Mauritius, with global
ranks of 64th and 89th, respectively. The two lowest-ranking
SADC countries are Madagascar and Botswana, 175th and
The average water, energy, and food pillar scores for the SADC
countries are 50.4, 52.3, and 42.3, respectively. The energy pillar
is, therefore, the highest-ranking pillar of the three, on average,
while the food pillar scores the lowest, on average, for the SADC
nations. The nation with the highest pillar value is Comoros
(energy pillar =74.9), with Seychelles having the highest value
for the water pillar (74.7), and Mauritius (61.0) having the highest
value for the food pillar, highlighting the relatively good access
and supply of these resources to those nations populations.
Seven nations have food pillar values below 40. South Africa,
Mauritius, Comores, and Seychelles have relatively high index
values. Interestingly, for Mauritius, the energy pillar is the lowest
of any of the nations, yet the food pillar is the highest. In the lower
ranking countries, food is generally the lowest ranking pillar, with
the exception of Tanzania (where water is the lowest).
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Simpson et al. Water-Energy-Food Nexus Index
TABLE 1 | WEF Nexus Index, ranks, pillar and sub-pillar values for 16 SADC countries.
Country WEF Nexus
Angola 46.9 148 45.9 50.9 43.9 30.5 61.2 51.0 50.7 69.4 18.4
Botswana 41.8 171 46.8 40.0 38.5 55.2 38.5 48.0 32.0 59.9 17.1
Comoros 55.9 99 50.3 74.9 42.4 42.1 58.6 74.9 – 68.3 16.4
Congo, Dem. Rep. 45.4 160 47.8 52.2 36.3 21.6 74.0 55.1 49.2 68.4 4.3
Eswatini 52.6 124 46.3 66.7 44.9 53.9 38.6 66.7 – 71.9 17.9
Lesotho 47.4 144 44.7 53.5 43.9 43.2 46.2 53.5 – 73.3 14.6
Madagascar 40.6 175 44.5 46.2 31.3 23.6 65.3 46.2 – 49.4 13.1
Malawi 45.8 156 45.6 48.3 43.6 44.0 47.1 48.3 – 71.5 15.7
Mauritius 58.2 89 72.6 41.0 61.0 84.2 60.9 69.3 12.6 85.4 36.6
Mozambique 46.5 152 47.2 53.0 39.3 33.9 60.4 54.9 51.1 63.8 14.7
Namibia 42.3 169 48.6 38.4 39.8 54.4 42.8 60.3 16.4 65.2 14.4
Seychelles 61.5 64 74.7 63.2 46.4 78.0 71.5 63.2 – 78.1 14.8
South Africa 55.1 108 55.4 57.7 52.3 71.2 39.6 54.7 60.6 68.6 35.9
Tanzania 44.9 162 43.2 47.8 43.7 33.5 52.9 50.8 44.7 68.3 19.0
Zambia 45.5 159 48.0 53.1 35.3 39.2 56.9 58.6 47.5 56.5 14.1
Zimbabwe 42.7 167 44.5 49.7 34.0 49.7 39.3 55.7 43.7 57.3 10.7
Average 48.3 140.4 50.4 52.3 42.3 47.4 53.4 57.0 40.9 67.2 17.4
Median 46.1 154 47.0 51.5 43.0 43.6 54.9 55.0 46.1 68.3 15.2
Access to basic drinking water and sanitation services has
improved across the region since 1990 (Zimbabwe is one
exception) (World Bank, 2018). However, our study shows
that only Mauritius and Seychelles exceed the global median
value1for these two indicators (Supplementary Figures 1, 2 in
Addendum E). There is, therefore, much work remaining within
this region to achieve SDG 6 by 2030, with the median levels
of access to at least basic drinking water and sanitation services
for the SADC nations being 67.2 and 39.4%, respectively. In
contrast, regarding the degree of Integrated Water Resources
Management (IWRM) implementation, i.e., SDG indicator
6.5.1 (Supplementary Figure 3 in Addendum E), eight nations
have values that exceed the global median (45.0), illustrating
the relatively strong adoption of IWRM principles within
several SADC countries’ policies, institutions, management tools
The annual freshwater withdrawals as a percentage of the
total internal resources is a vital sustainability indicator, as
evidenced by its inclusion as an oﬃcial SDG indicator (6.4.2).
Six SADC nations have withdrawal levels that exceed the global
median value (7.7%), with Mauritius, South Africa, Eswatini,
and Zimbabwe having levels that exceed 25% (Supplementary
Figure 4 in Addendum E). Eight SADC countries2have annual
freshwater withdrawal rates that are <5% of their internal
resources. The potential to utilize freshwater beneﬁcially in these
countries is evident when it is considered that Angola, Comoros,
the DRC, Lesotho, Mozambique and Zambia only utilize 0.5,
1The global median value relates to the median calculated for a particular indicator
for the 181 nations included in this study.
2Angola, Comoros, DRC, Lesotho, Madagascar, Mozambique, Namibia, and
0.8, 0.08, 0.8, 0.9, and 2% of their annual freshwater resources,
respectively. The renewable freshwater resources per capita in
ﬁve of these countries exceed the global median (Supplementary
Figure 5 in Addendum E), which suggests that not only is
freshwater underutilized, but it is relatively abundant. It must be
noted that, due to the signiﬁcant ﬂows in these nations, these river
systems have relatively high environmental ﬂow requirements
(Supplementary Figure 6 in Addendum E), with those in the
DRC being the most signiﬁcant (982 million m3/yr). The average
precipitation depths for the SADC countries are presented in
Supplementary Figure 7 in Addendum E, with seven nations
receiving, on average, a rainfall depth that equals or exceeds the
global average rainfall depth of 1,028 mm per annum, although
with high seasonality.
SDG 7 is the aspirational goal of ensuring access to aﬀordable,
reliable, sustainable and modern energy for all. The global
median level of access to electricity (SDG indicator 7.1.1) is
100%. Seychelles provides access to electricity for their entire
population, while only 11% of Malawi’s populace have access
to electricity (Supplementary Figure 8 in Addendum E). The
average and median levels of access to electricity within the
SADC countries are 57 and 55%, respectively. In terms of
renewable energy consumption (SDG indicator 7.2.1), an average
of 55.6% of the total ﬁnal energy consumed is classiﬁed as
being renewable for SADC nations (Supplementary Figure 9 in
Addendum E). Similarly, on average, 56.1% of the total electricity
output is renewable (Supplementary Figure 1 in Addendum E);
the global median value is 30.9%. Countries with low levels of
renewable electricity output include Botswana and South Africa
(0.03 and 2.3%, respectively), highlighting their dependence on
coal-ﬁred power stations (World Bank, 2018). Six SADC nations
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Simpson et al. Water-Energy-Food Nexus Index
have renewable electricity output levels that exceed 80% of
the total electricity output and renewable energy consumption
levels that exceed 80% of the total ﬁnal energy consumption.
Hydropower is the dominant electricity source in these countries.
Many SADC nations have very low CO2emissions, with the
median value for these 16 nations being 0.9 metric tons per capita
per annum (Supplementary Figure 11 in Addendum E). South
Africa is a notable exception. In 2014 it emitted nine tons of CO2
per capita, and 3 years later was the fourteenth highest net emitter
of CO2globally (Fleming, 2019).
Electric power consumption per capita levels in the SADC
countries are generally signiﬁcantly below the global median
(2,584 kWh/capita), with South Africa being the only exception.
The electric power consumption levels per capita are instructive
because they provide context for renewable electricity output
levels. For example, the DRC has a renewable electricity output
level of 99.8% of the total electricity output, but the electric power
consumption in this nation is only 109 kWh per capita, which is
signiﬁcantly below the global median of 2,584 kWh per capita.
The indicator “Energy imports, net (% of energy use)”
provides an indication of a nation’s independence in terms of
energy supply, which provides a perspective of energy security.
Because many nations generate surplus energy and export that
additional capacity, these countries have negative values for
this indicator (Supplementary Figure 13 in Addendum E). The
indicator, therefore, measures both imports and exports of
energy—for example, Angola and Mozambique export energy,
the former to a large degree.
As noted above, the food pillar is generally the lowest scoring
in the SADC region. A deeper analysis highlights that the
prevalence of undernourishment in SADC countries exceeds the
global median value for all but two nations, namely Mauritius
and South Africa (Supplementary Figure 14 in Addendum E;
there is no data for this indicator for Seychelles, Comoros and
the DRC). Similar patterns are evident in the percentage of
children under 5 years of age aﬀected by wasting and stunting
(Supplementary Figures 15, 16 in Addendum E, respectively).
These concerning levels are supported indirectly by assessing
obesity in the SADC nations, with South Africa being the only
nation to exceed the global median (Supplementary Figure 17 in
Addendum E). In terms of the availability of food, two critical
indicators are the cereal yield (kg/ha) and the average value
of food production (I$/capita3)—Supplementary Figures 19, 21
in Addendum E, respectively. While three nations (Madagascar,
Mauritius and South Africa) have cereal yields that exceed the
global median (3,032 kg/ha), many of the remaining SADC
nations have very low crop yields. None of the 16 SADC
nations has an average value of food production that exceeds the
global median. This is reﬂected in the indicators related to the
prevalence of undernourishment and the percentage of children
under 5 years of age who are stunted (median values of 26.3 and
33.8%, respectively, for the SADC nations). The median values
3International dollars per capita: An international dollar could purchase, in the
cited country, a comparable amount of goods and services that a US$ would
acquire in the United States of America. This term is generally utilized in
conjunction with Purchasing Power Parity (PPP) data.
for these indicators for the 181 countries assessed are 6.5 and
Whilst the high-level comparative analyses above are
illustrative, an important aspect of the WEF Nexus Index is that
it provides an entry point for deeper analysis and identiﬁcation of
opportunities to address the higher level issues identiﬁed, rather
than an endpoint or target.
Analysis of Index Construction
In order to provide context and a degree of validation to
the index, it has been compared with the well-known Human
Development Index (HDI), and both cluster and sensitivity
analyses have been performed. Furthermore, there has been
a strong eﬀort in providing interactive visualization tools for
Comparison With Human Development Index
While there is a medium-to-strong correlation between the HDI
and the WEF Nexus Index (R2=0.57; Supplementary Figure
22 in Addendum E), these two indices represent contrasting
facets of development (UNDP, 2018a,b). The former combines
indicators relating to health, education and income (providing
a nexus perspective of, amongst others, SDGs 3, 4, 8). The
latter presents sustainable development in terms of access to
and availability of water, energy and food. These three crucial
resource sectors directly represent four of the 17 SDGs, i.e., 2, 6,
7, and 13. The two indices can, therefore, be beneﬁcially utilized
by diﬀerent academics, non-governmental organizations, policy-
and decision-makers to inform their areas of research, interest or
responsibility. The medium-to-strong correlation is constructive.
If the HDI and WEF Nexus Index were weakly correlated, then
they would not both be oﬀering a perspective on sustainability.
The existence of the one does not, therefore, nullify the need for
A k-means clustering algorithm was applied to the 181 countries’
WEF Nexus Index values, thus allowing the countries to be
grouped according to these values. The analysis yielded two
clusters, i.e., countries with WEF Nexus Index values lower
than the global median and those with values higher than
the global median index, as presented in Figures 5A,B. From
Figure 5A, it is evident that while the median for the food
pillar is the lowest and the water pillar the highest, countries
with a WEF Nexus Index value above the median do not
necessarily rank highly for all three resource sector pillars.
Figure 5B presents the correlation between the various pillars,
which is generally poor. This lack of correlation is anticipated
since the pillars represent independent resource sectors. The
two sectors that are most strongly correlated are the water
and food pillars.
Like any composite indicator or model, the WEF Nexus Index
has uncertainties in the underlying data and the methodological
decisions made in its construction. Here, a sensitivity analysis is
performed to investigate the eﬀects of these uncertainties, using a
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Simpson et al. Water-Energy-Food Nexus Index
FIGURE 5 | (A) Plot of the pillar and WEF Nexus Index values vs. the median pillar/index value for the 181 countries assessed, and (B) Scatter plots of the WEF
Nexus Index pillars, water vs. energy, water vs. food, and food vs. energy (orange indicates countries with WEF Nexus Index values above the global median while
blue indicates values below the global median index value).
Monte Carlo analysis to estimate conﬁdence intervals on country
ranks and a global sensitivity analysis to ascertain the individual
contribution of each input’s uncertainty (Becker, 2021).
Three key uncertainties were chosen to be
1. The aggregation method: By default, the WEF Index is
aggregated using an arithmetic mean. However, it could be
argued that the water, energy and food components of the
nexus are not fully compensable; therefore, the geometric
mean could be a plausible alternative for the last level
2. The normalization method: The index is normalized using a
min-max approach. Plausible alternatives could be a “distance
to maximum” approach (each indicator is normalized with
the distance to the maximum country value) or using “z-
scores” (indicators are normalized to have the same mean
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Simpson et al. Water-Energy-Food Nexus Index
3. The weighting: By default, indicators have ﬁxed weights, as
described elsewhere in the article. Here, the assumption is
relaxed by allowing indicators to vary randomly within ±25%
of their nominal values.
While this list is not exhaustive, it provides a summary of some
of the important methodological uncertainties. Strictly speaking,
an uncertainty analysis quantiﬁes the uncertainties in the outputs
of a system, while a sensitivity analysis apportions this output
uncertainty to individual inputs. Here, the output is considered
as the ranks of the index. The WEF Nexus Index was re-run 2,000
times in a Monte Carlo analysis, each time randomly selecting an
aggregation method, normalization method, and a random set of
weights within the prescribed limits. Each time, the ranks were
recorded for each nation.
Figure 6 shows the 90% conﬁdence intervals of the ranks
of the WEF Nexus Index (countries are not labeled due to a
large number of points). There is a moderate but manageable
amount of uncertainty in the ranks of the countries. The average
diﬀerence between nominal and median rank is 2.86 places. As is
typical in composite indicators, the top and bottom nations are
relatively stable, whereas there is more variation in the middle-
Next, a global sensitivity analysis was run following the
methodology of Saisana et al. (2005). This method uses a Monte
Carlo approach to estimate variance-based sensitivity indices;
speciﬁcally, the ﬁrst-order index, which measures the individual
contribution of each input to the output uncertainty, and the
total order index, which measures the contribution of each input
including interactions with other inputs (Saisana et al., 2005;
Saltelli et al., 2008).
The sensitivity indices were estimated by re-running the WEF
Nexus Index calculation 5,000 times according to a Monte Carlo
design. The results are shown in Figure 7, where each sensitivity
index includes bootstrapped conﬁdence intervals.
The results show that the most sensitive assumption is
the normalization method, followed by the weights and the
aggregation method. This means that, at least in terms of the
ranks and the alternatives investigated here, the WEF Nexus
Index is robust to the aggregation method and essentially
robust to its weights. The normalization method is somewhat
more sensitive, and this may also be because three alternatives
Open Science and Visualization
An essential part of this project is the communication of the
WEF Nexus Index. Now, more than ever, visualizing data in an
engaging manner is vital for the acceptance and dissemination
of public data, making it more accessible and understandable
(Shneiderman, 1996; van Wijk, 2005). Data visualization is the
discipline that studies how to interpret and understand graphics
and charts that represent complex data (Tufte, 1983). Its primary
design principles have been applied in a set of visualizations
compiled in an interactive website associated with the WEF
Nexus Index, namely www.wefnexusindex.org.
The website, published to disseminate the WEF Nexus Index,
provides data at hierarchical levels. First, it oﬀers a global view of
the main index, as well as its three main pillars (water, energy and
food), utilizing an interactive globe. The globe includes a novel
legend that combines a classical color legend with a strip plot,
which graphically presents the distribution of the selected index
At the same level of visualization and complementary to
the globe are visualizations comprising glyphs. These glyphs
represent the WEF Nexus Index and its pillars by country. These
glyphs can be compared and sorted in order to facilitate a WEF
nexus analysis. Further, each country has a dedicated page that
provides more details for that nation, such as the availability and
access sub-pillar values, a radar chart, global rankings, a scatter
plot of accessibility and access (which highlights correlations),
together with the untreated indicator values themselves.
The purpose of utilizing a case study is to demonstrate how the
WEF Nexus Index and its pillars, sub-pillars and indicators can
be utilized as a catalyst for WEF nexus assessments. The set of
16 radar charts in Figure 8 presents the six sub-pillars (where
available) per SADC nation. From these graphs, it is evident
that access to and availability of water, energy and food is both
constrained and varied within the region.
Through an integrated analysis, it has been noted that the
lowest pillar for the SADC nations, on average, is the food pillar.
Secondly, the lowest sub-pillar, on average, is the food-availability
sub-pillar. Thirdly, the low value of the food-availability sub-
pillar can be attributed principally to the low cereal yields and a
low average value of food production within this region (refer to
indicators 19 and 21 in Addendum D). At a very high level, this
would suggest that critical interventions are needed to enhance
access to and availability of food through the use of the available
water and energy. In this regard, UN Water (2018) state that Sub-
Saharan Africa experiences the highest level of food insecurity,
aﬀecting almost 30% of the population. Schreiner and Baleta
(2015) suggest that the agricultural potential of countries like
Zambia could be exploited for the beneﬁt of the entire region.
While this is true, it is ironic that fertile countries such as Zambia
experience high levels of undernourishment (World Bank, 2018).
Eight SADC nations have annual freshwater withdrawal levels
of <5% of their total internal resources, i.e., low levels of
withdrawal. If this available water could be utilized beneﬁcially
for food production, be it through the drought-prooﬁng of
rainfed agriculture (Bossio et al., 2011) or a “steady positive
trend in irrigation development” (Van der Zaag, 2010)—or,
ideally, both—it could go a long way in addressing food
security concerns in the region. Such actions must be married
with endeavors to boost nutrient balances (through suitable
fertilizer addition), access to markets, agricultural training
and research (Van der Zaag, 2010; Mueller et al., 2012; Lu
and Tian, 2017). In terms of synergies, there is a clear
opportunity to produce more food through the utilization of
available water resources in several SADC countries. This will
enhance food security and reduce levels of malnourishment,
wasting and stunting, while increasing the values of the
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Simpson et al. Water-Energy-Food Nexus Index
FIGURE 6 | 90% conﬁdence intervals on ranks of the WEF Nexus Index. The gray bars are the 90% conﬁdence intervals. Countries are ordered according to their
nominal rank. The green point is the median rank across the uncertainty analysis.
FIGURE 7 | First order (Si) and total order (STi ) sensitivity indices of input assumptions plotted as mean (dot) and 90% conﬁdence intervals by bootstrapping.
water and food pillars. A trade-oﬀ is that more energy will
Energy is required to eﬃciently pump, treat, convey and
irrigate water. All the SADC countries, except Seychelles, have
electricity access levels below the median global value, with half
the populations in nine of these nations having no electricity
access. Electrical power consumption per capita is low when
compared to the global average of 2,584 kWh/capita. RES4Africa
and Enel (2019) state that the WEF nexus “oﬀers an innovative
perspective on bridging the energy access gap by considering
energy as an enabler for development.” From a nexus perspective,
there are clear opportunities for energy systems to be developed
beneﬁcially to use the available water to facilitate enhanced
agricultural development and food security. This philosophy
is aligned with the United Nation’s Deputy Secretary-General,
Amina Mohammed, who stated that “sustainable energy is the
golden thread that links most of the SDGs and the pledge to leave
no one behind” (Mohammed, 2018).
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Simpson et al. Water-Energy-Food Nexus Index
FIGURE 8 | Radar graphs of the sub-pillars for the 16 SADC nations.
The SADC countries share an energy grid, termed the
Southern African Power Pool (SAPP), and several nations within
the zone export and import power from each other to meet their
local demand (Mabhaudhi et al., 2016). A paradox in Africa is
that some nations, such as Angola and Mozambique, have their
populaces languishing with low levels of access to electricity and
limited electric power consumption per capita, yet they export
energy (the former, signiﬁcantly), illustrating the potential trade-
oﬀ of increased supply to local populations against lower foreign
earnings. Another seeming contradiction is that a nation such
as South Africa exports energy, yet it has struggled with rolling
power-cuts for over a decade. Mauritius, Botswana and Namibia
are three SADC nations that rely on energy imports.
Hydropower forms a signiﬁcant component of the regional
energy supply with widespread sharing within the SAPP. Conway
et al. (2015) note that almost 100% of electricity production
in the DRC, Lesotho, Malawi and Zambia is generated by
means of hydropower. Regarding energy in SADC, “challenges
include low tariﬀs, poor project preparation, issues with power
purchase agreements, and absent regulatory frameworks that
stunt investment and ﬁnancing in the energy sector” (Schreiner
and Baleta, 2015). A great opportunity results from Southern
Africa being endowed with signiﬁcant potential in terms of solar
and wind power generation (Gies, 2016). However, although
recognized as opportunities in most of the region’s NDCs, the
prevalence of coal-ﬁred stations which are not yet at the end of
their design life in South Africa means signiﬁcant rigidity in the
energy production system. Thus, any “policy-driven transition
to a low carbon and climate resilient society must take into
account and emphasize its overriding priority to address poverty
and inequality” (DEA, 2016). In other words, the SDGs must be
A project that has been touted to transform the SADC region
is the development of the vast hydropower potential of the
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Simpson et al. Water-Energy-Food Nexus Index
Inga Falls in the Congo River. The Grand Inga Dam Project,
which has been discussed for half a century, could produce 40
GW of hydroelectric power, more than one-third of the total
electricity currently generated in Africa (Sachs, 2015). Political
and technical obstacles have, until now, limited the development
of this project.
The need to address resource planning in an integrated
manner is evident when the water resources in the region are
assessed. The national boundaries within SADC were determined
politically and not hydrologically, and 85% of the region’s
water resources are transboundary (Mabhaudhi et al., 2016).
SADC coordinates transboundary water cooperation in 15
basins across Southern Africa (UN Water, 2013). These shared
basins present opportunities for cooperation to enhance socio-
economic security and ensure further progress in achieving the
SDGs. However, the availability of resources within the region is
not evenly distributed. Over 70% of SADC’s freshwater resources
are shared between two or more member states (Schreiner and
Baleta, 2015). The ratiﬁcation of SADC’s revised protocol on
shared watercourses together with the establishment of various
river basin organizations, has promoted cooperation and the
sharing of beneﬁts from these basins (Claassen, 2013). Hoﬀ
(2011) explained that one of the early nexus analyses focussed on
the Zambezi River basin. This integrated project included the co-
development of hydropower, new irrigation schemes and other
water-related sectors, including wetlands and their ecosystem
services. More recent analyses of the basin highlight the critical
trade-oﬀs between hydropower generation and irrigation, where
optimisation of one occurs at the expense of the other, and the
recommendation that increasing eﬃciency of dryland production
is an essential aspect of a WEF nexus guided strategy (Payet-
Burin et al., 2019).
Kurian and Kojima (2021) argue that “Composite indicators
can enable integrative modeling of trade-oﬀs by incorporating
information about biophysical, socio-economic and institutional
dimensions” of a context under assessment, e.g., water reuse
or drought adaption. They are concerned that the WEF nexus
context is too narrow in order to adequately inform policy
making, and propose the broader context of the environment-
development nexus. The WEF Nexus Index can form part of the
environment-development nexus studies, highlighting relatively
rapidly, on a national level, where interventions, or further
assessments are required. The context of the WEF Nexus Index
is, however, integrated resource security. Kurian and Kojima
(2021) also note that “A composite index can also be useful
to compare insitutional responses of diﬀerent regions within a
country or diﬀerent countries in response to a global goal.” To
this end, by updating the WEF Nexus Index each year, until 2030,
a critical measure of the nexus of a subset of SDGs can be assessed
Beneﬁts of the WEF Nexus Index
A composite indicator, or index, by its nature, provides an
integrated perspective of the context under analysis, e.g., the
WEF nexus. This is true even if the composite indicator
is not constituted of “nexus” indicators. Rather, the OECD
(2008) emphasizes that a “composite indicator should ideally
measure multi-dimensional concepts which cannot be captured
in a single indicator, e.g., competitiveness, industrialization,
sustainability,” i.e., an index provides a nexus perspective which
individual indicators cannot oﬀer. However, it cannot—nor is
it designed to—provide detailed insight into every aspect of its
Thus, the WEF Nexus Index, together with its associated
visualization website (www.wefnexusindex.org), presented in this
work can be used to (i) draw attention to an issue, (ii) allow
a hierarchical dataset to be explored, and (iii) facilitate global
comparisons. The index serves as a gateway to the underlying
pillars, sub-pillars, and indicators (as demonstrated for SADC).
While a nation’s unitless index value is not signiﬁcant on its
own, the ranking of 181 countries demonstrates national progress
in terms of integrated resource management and security. It
also facilitates benchmarking against other nations, be they
geographically or socio-economically similar, or a top performer
like Iceland. The gap between this value and the SADC nation’s
index values highlights the disparity in integrated resource
management and security globally. However, the fact that Iceland
and Canada are the only countries that have index values that
exceed 80 indicates that no country has achieved complete water,
energy and food security. In this regard, rather than being an end
in itself, the WEF Nexus Index is a tool that provides an entry
point for further in-depth analyses.
Assessments of the hierarchical dataset can be utilized to
ascertain focus areas for synergistic eﬀorts, such as the SAPP or
the Zambezi Watercourse Commission (ZAMCOM). Providing a
quantiﬁcation of a subset of the SDGs could assist policy-makers
in avoiding the trade-oﬀs that result from a silo approach, e.g.,
pursuing fossil-fuel-based energy security in South Africa at the
expense of water and food security (and the loss of biodiversity)
(Simpson et al., 2019). The WEF Nexus Index can, therefore,
serve as a tool to inform water-for-food, food-for-energy, energy-
for-water, water-for-energy, energy-for-food, and food-for-water.
Condensing a nation’s integrated resource management status
into a single number is complex (Daher and Mohtar, 2015;
Garcia and You, 2016; Wicaksono et al., 2017; McGrane et al.,
2018; Simpson and Jewitt, 2019a). The WEF Nexus Index does
not consider political and social impacts to resource security
due to the lack of suﬃcient data for the countries analyzed
and the challenge of linking these indicators to the sub-pillars
within the index. Social and political issues directly inﬂuence
natural resource availability and management by determining
the amount and quality of resources available to the population,
particularly when resources are exported to neighboring nations.
The trade of resources between countries constitutes complex
interactions and an essential consideration in resource security
that may be added to the WEF Nexus Index when the data
The wide range of WEF Nexus Index values indicates the extent
to which water, energy, and food security diﬀer on a global
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Simpson et al. Water-Energy-Food Nexus Index
scale. The relatively strong correlation between the HDI and
the WEF Nexus Index indicates that although these two indices
are measuring diﬀerent aspects of sustainable development, they
The results of the sensitivity analysis related to the
uncertainties in the index’s construction show that the most
sensitive assumption is the normalization method, followed by
the weights and the aggregation method. The cluster analysis
indicates that there is a clear separation of nations between
those with WEF Nexus Index values above the global median
and those below, with the divide aligned between high income,
technologically advanced and low income, technologically
underdeveloped countries. Of the pillars, water and food security
are most strongly correlated.
Within the SADC, food security is a signiﬁcant concern.
Eight of these nations have annual freshwater withdrawal
rates that are <5% of their internal resources, and rainfall
depth in several countries is above the global median. This
indicates that if this available water could be utilized beneﬁcially
for food production, be it through the drought-prooﬁng
of rainfed agriculture or irrigation development—or both—
it could contribute signiﬁcantly to addressing food security
concerns in the region. The enhancement of access to reliable,
modern, renewable, aﬀordable energy is a critical enabler of any
development, agricultural or otherwise.
Based on the constituent indicators, the WEF Nexus Index is
a function of the national resource base (e.g., land, water and
fossil fuels), governance and service delivery, and the degree
of the energy transition to renewable sources, consumption
and self-suﬃciency. The proposed WEF Nexus Index is not a
“silver bullet” aimed at solving development and environmental
challenges facing humanity. Rather it is a tool that can be added
to the sustainability toolbox that is being developed and utilized
to create “the future we want” reﬂected both in the SDGs and the
NDCs of the Paris Agreement.
DATA AVAILABILITY STATEMENT
The datasets presented in this study can be found in online
repositories. The names of the repository/repositories and
accession number(s) can be found at: http://dx.doi.org/10.17632/
GS wrote the manuscript in consultation with GJ, who supervised
the project. WB and AN provided input into the development
of the WEF Nexus Index. WB developed the sensitivity analysis
and contributed to the ﬁnal manuscript. JB assisted with the
selection of indicators and in the literature review of the
WEF nexus in South Africa and contributed to the ﬁnal
manuscript. PR and VP developed the data visualizations and
cluster analysis, described the philosophy, and importance
of visualization in this study. SM contributed to the ﬁnal
manuscript. All authors contributed to the article and approved
the submitted version.
This work is based on the research supported by the
Water Research Commission (Project Number K5/2959)
and the National Research Foundation (Grant Number:
114692), both of South Africa, and the Ministry of
Foreign Aﬀairs of the Netherlands through the WEF-
Tools project of the Partnership Programme for Water
and Development (DUPC2) under Activity Number
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/frwa.
Addendum A | The indicator selection table, which presents the 87 indicators
reviewed in the development of the WEF Nexus Index, as well as their deﬁnitions,
source, data adequacy, reference year, and a motivation of why each indicator
was, or was not, included in the composite index.
Addendum B | Detailed description of the selection and weighting of indicators.
Addendum C | A table presenting the conceptual framework associated with the
WEF Nexus Index’s composition. This table includes the index, pillars, sub-pillars,
and indicators with each of their weights, forms of aggregation, and directions.
Addendum D | A dashboard developed from the treated data. The published
data for the 21 indicators have been treated by normalizing each of the data sets
[using the min-max method (OECD, 2008; Saisana et al., 2018)] so that they
conform to a range from 0 to 100. The normalizing of the data is also necessary to
ensure that each indicator’s data set is unitless such that it can be combined in
the composite indicator. The data treatment includes the minimizing of the
distorting effect of outliers on the data using statistical methods, which are
described in this article. The dashboard has different colors for the treated data for
each indicator in the following ranges: 0–25%; 25–50%; 50–75%; and 75–100%.
Addendum E | Supplementary Figures S1–S21, which are graphical plots of each
indicator for the 16 SADC nations included in this assessment.
Addendum F | The untreated indicator data table includes the published data
(e.g., by the World Bank, IEA, and FAO) for the 21 indicators that constitute the
WEF Nexus Index, for the 181 nations that have adequate data.
Albrecht, T. R., Crootof, A., and A., S. C. (2018). The water-energy-food nexus:
a systematic review of methods for nexus assessment. Environ. Res. Lett.
13:043002. doi: 10.1088/1748-9326/aaa9c6
Allouche, J., Middleton, C., and Gyawali, D. (2015). Technical veil, hidden
politics: interrogating the power linkages behind the nexus. Water Alternatives
8, 610–626. Available online at: https://www.water-alternatives.org/index.php/
Allouche, J., Middleton, C., and Gyawali, D. (2019). The Water-Energy-Food
Nexus: Power, Politics, and Justice. Abingdon: Routledge. doi: 10.4324/9781315
Becker, W. (2021). Composite Indicator Development and Analysis in R With
COINr. Available online at: https://bluefoxr.github.io/COINrDoc/
Frontiers in Water | www.frontiersin.org 15 March 2022 | Volume 4 | Article 825854
Simpson et al. Water-Energy-Food Nexus Index
Becker, W., Benavente, D., Dominguez Torreiro, M., Moura, C., Neves, A., Saisana,
M., et al. (2019). COIN Tool User Guide. Luxembourg: Publications Oﬃce of the
Beddington, J. (2009). Food, Energy, Water and the Climate: A Perfect Storm of
Global Events? London: Government Oﬃce for Science.
Beddington, J. (2010). Food security: contributions from science to a
new and greener revolution. Philos. Trans. R. Soc. B 365, 61–71.
Belinskij, A. (2015). Water-energy-food nexus within the framework of
international water law. Water 7, 5396–5415. doi: 10.3390/w7105396
Benson, D., Gain, A. K., and Rouillard, J. J. (2015). Water governance in
a comparative perspective: from IWRM to a ’Nexus’ approach? Water
Alternatives 8, 756–773. Available online at: https://www.water-alternatives.
Biggs, E. M., Bruce, E., Boruﬀ, B., Duncan, J. M. A., Horsley, J., Pauli,
N., et al. (2015). Sustainable development and the water–energy–food
nexus: a perspective on livelihoods. Environ. Sci. Policy 54, 389–397.
Bossio, D., Jewitt, G., and van der Zaag, P. (2011). Smallholder system innovation
for integrated watershed management in Sub-Saharan Africa. Agric. Water
Manage. 98, 1683–1686 doi: 10.1016/j.agwat.2011.07.006
Cairns, R., and Krzywoszynska, A. (2016). Anatomy of a buzzword: the emergence
of ‘the water-energy-food nexus’ in UK natural resource debates. Environ. Sci.
Policy 64, 164–170. doi: 10.1016/j.envsci.2016.07.007
Claassen, M. (2013). Integrated water resource management in South Africa. Int. J.
Water Governance 1, 323–338. doi: 10.7564/13-IJWG12
Conway, D., van Garderen, E. A., Deryng, D., Dorling, S., Krueger, T., Landman,
W., et al. (2015). Climate and southern Africa’s water-energy-food nexus. Nat.
Clim. Chang. 5, 837–846. doi: 10.1038/nclimate2735
Daher, B. T., and Mohtar, R. H. (2015). Water-energy-food (WEF) Nexus Tool
2.0: guiding integrative resource planning and decision-making. Water Int. 40,
748–771. doi: 10.1080/02508060.2015.1074148
de Grenade, R., House-Peters, L., Scott, C. A., Thapa, B., Mills-Novoa,
M., Gerlak, A., et al. (2016). The nexus: reconsidering environmental
security and adaptive capacity. Curr. Opin. Environ. Sustain. 21, 15–21.
De Laurentiis, V., Hunt, D. V. L., and Rogers, C. D. F. (2016). Overcoming food
security challenges within an Energy/Water/Food Nexus (EWFN) approach.
Sustainability 8, 1–23. doi: 10.3390/su8010095
de Loë, R. C., and Patterson, J. J. (2017). Rethinking water governance: moving
beyond water-centric perspectives in a connected and changing world. Nat.
Resour. J. 57, 75–99. Available online at: https://digitalrepository.unm.edu/nrj/
DEA (2016). South Africa’s Intended Nationally Determined Contribution (INDC).
Department of Environmental Aﬀairs. Available online at: https://www4.
El Costa, D. (2015). Conceptual Frameworks for Understanding the Water,
Energy and Food Security Nexus. Working Paper Report Number:
E/ESCWA/SDPD/2015/WP. Beirut: Economic and Social Commission for
Western Asia (ESCWA).
FAO (2014). The Water-Energy-Food Nexus A New Approach in Support of Food
Security and Sustainable Agriculture. Rome: Food and Agriculture Organization
of the United Nations.
FAO (2018). Water-Energy-Food Nexus for the Review of SDG 7. New York, NY:
Food and Agriculture Organization.
Fleming, S. (2019). Chart of the Day: These Countries Create Most of the World’s
CO2 Emissions. World Economic Forum. Available online at: https://www.
weforum.org/agenda/2019/06/chart-of-the-day- these-countries- create-most-
of-the- world-s-co2-emissions/ (accessed June 17, 2019).
Galaitsi, S., Veysey, J., and Huber-Lee, A. (2018). Where is the Added Value? A
Review of the Water-Energy-Food Nexus Literature. Somerville, MA: Stockholm
Garcia, D. J., and You, F. (2016). The water-energy-food nexus and process
systems engineering: a new focus. Comput. Chem. Eng. 91, 49–67.
Gies, E. (2016). Can wind and solar fuel Africa’s future? Nature 539, 20–22.
Hoﬀ, H. (2011). Understanding the Nexus. Background Paper for the Bonn2011
Conference: The Water, Energyand Food S ecurity Nexus. Stockholm: Stockholm
Hoﬀ, H., Alrahaife, S. A., El Hajj, R., Lohr, K., Mengoub, F. E., Farajalla, N., et al.
(2019). A nexus approach for the MENA region - from concept to knowledge
to action. Front. Environ. Sci. 7, 48. doi: 10.3389/fenvs.2019.00048
IRENA (2015). Renewable Energy in the Water, Energy & Food Nexus. Abu Dhabi:
International Renewable Energy Agency.
Kurian, M., and Kojima, U. (2021). “A data light approach to monitoring
the environment-development Nexus,” in Boundary Science: Re-imagining
Water-Energy-Food Interactions in the Context of a Data Light Approach to
Monitoring the Environment-Development Nexus, eds M. Kurian and U. Kojima
(Cambridge, MA: Elsevier), 75–118.
Lu, C., and Tian, H. (2017). Global nitrogen and phosphorus fertilizer use for
agriculture production in the past half century: shifted hot spots and nutrient
imbalance. Earth Syst. Sci. Data 9, 181–192. doi: 10.5194/essd-9-181-2017
Mabhaudhi, T., Mpandeli, S., Madhlopa, A., Modi, A. T., Backeberg, G., and
Nhamo, L. (2016). Southern Africa’s water-energy nexus: towards regional
integration and development. Water 8, 235. doi: 10.3390/w8060235
McGrane, S. J., Acuto, M., Artioli, M., Chen, P.-Y., Comber, R., Cottee, J., et al.
(2018). Scaling the nexus: towards integrated frameworks for analysing water,
energy and food. Geogr. J. 185, 1–13. doi: 10.1111/geoj.12256
Meadows, D. H., Meadows, D. L., Randers, J., and Behrens, W. W. III. (1972). The
Limits to Growth. New York, NY: Universe Books.
Mohammed, A. (2018). Sustainable Energy ‘Golden Thread’ Linking 2030 Agenda
with Pledge to Leave No One Behind, Especially Rural Women, Deputy Secretary-
General Tells Side Event. New York, NY: United Nations.
Mohtar, R. H., and Daher, B. (2012). Water, Energy, and Food: The Ultimate Nexus,
2nd Edn. West Lafayette, IN: Taylor & Francis.
Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., R amankutty, N., and Foley, J.
A. (2012). Closing yield gaps through nutrient and water management. Nature
490, 254–257. doi: 10.1038/nature11420
Muller, M. (2015). The ’Nexus’ as a step back towards a more coherent water
resource management paradigm. Water Alternatives 8, 675–694. Available
online at: https://www.water-alternatives.org/index.php/all-abs/271- a8-1-4/
National Intelligence Council (2012). Global Trends 2030: Alternative Worlds.
Washington, DC: National Intelligence Council.
OECD (2008). Handbook on Constructing Composite Indicators: Methodology and
User Guide. Paris: Organisation for Economic Co-operation and Development.
Owen, A., Scott, K., and Barrett, J. (2018). Identifying critical supply chains and
ﬁnal products: an input-output approach to exploring the energy-water-food
nexus. Appl. Energy 210, 632–642. doi: 10.1016/j.apenergy.2017.09.069
Payet-Burin, R., Kromann, M., Pereira-Cardenal, S., Strzepek, K. M., and Bauer-
Gottwein, P. (2019). WHAT-IF: an open-source decision support tool for
water infrastructure investment planning within the water-energy-food-climate
nexus. Hydrol. Earth Syst. Sci. 23, 4129–4152. doi: 10.5194/hess-23-4129-2019
RES4Africa and Enel (2019). Africa’s Future Counts - Renewables & the Water-
Energy-Food Nexus in Africa. Rome: RES4Africa.
Ringler, C., Bhaduri, A., and Lawford, R. (2013). The nexus across water, energy,
land and food (WELF): potential for improved resource use eﬃciency? Curr.
Opin. Environ. Sustain. 5, 617–624. doi: 10.1016/j.cosust.2013.11.002
Rockstrom, J., Steﬀen, W., Noone, K., Persson, A., F. S., Chapin, I., et al. (2009).
Planetary boundaries: exploring the safe operating space for humanity. Ecol.
Soc. 14, 32. doi: 10.5751/ES-03180-140232
Rockström, J., and Sukhdev, P. (2016). How Food Connects all the SDGs.
Stockholm: Stockholm Resilience Centre.
Sachs, J., Schmidt-Traub, G., Kroll, C., Durand-Delacre, D., and Teksoz, K. (2016).
SDG Index & Dashboards - Global Report. New York, NY: Bertelsmann Stiftung
and Sustainable Development Solutions Network (SDSN).
Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., and Fuller, G. (2018). SDG
Index and Dashboards Report 2018: Global Responsibilities - Implementing
the Goals. Paris: Bertelsmann Stiftung and Sustainable Development
Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., and Fuller, G. (2019).
Sustainable Development Report 2019. New York, NY.
Sachs, J. D. (2015). The Age of Sustainable Development. New York, NY: Columbia
Frontiers in Water | www.frontiersin.org 16 March 2022 | Volume 4 | Article 825854
Simpson et al. Water-Energy-Food Nexus Index
Saisana, M., Alberti, V., Alvarez, M., Becker, W., Caperna, G., Cocco, C., et al.
(2018). 16th JRC Annual Training on Composite Indicators and Scoreboards.
Ispra: Joint Research Centre: Competence Centre on Composite Indicators
Saisana, M., Saltelli, A., and Tarantola, S. (2005). Uncertainty and sensitivity
analysis techniques as tools for the quality assessment of composite
indicators. J. R. Stat. Soc. Ser. A 168, 307–323. doi: 10.1111/j.1467-985X.2005.
Salam, P. A., Pandey, V. P., Shrestha, S., and Anal, A. K. (eds.). (2017). “The need
for the nexus approach,” in Water-Energy-Food Nexus: Principles and Practices
(Hoboken, NJ: John Wiley & Sons, Inc), 1–10.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., et al.
(2008). Global Sensitivity Analysis: The Primer. West Sussex: John Wiley & Sons.
Schreiner, B., and Baleta, H. (2015). Broadening the lens: a regional perspective
on water, food and energy integration in SADC. Aquatic Procedia 5, 90–103.
Segnestam, L. (2002). Indicators of Environment and Sustainable Development:
Theories and Practical Experience. Washington, DC: The World Bank
Shneiderman, B. (1996). “The eyes have it: a task by data type taxonomy
for information visualizations,” in Proceedings 1996 IEEE Symposium on
Visual Languages (Boulder, CO: IEEE).
Simpson, G. B., Badenhorst, J., Berchner, M., Jewitt, G. P. W., and Davies,
E. (2019). Competition for land: the water-energy-food nexus and coal
mining in Mpumalanga province, South Africa. Front. Environ. Sci. 7, 1–12.
Simpson, G. B., and Jewitt, G. P. W. (2019a). The development of
the water-energy-food nexus as a framework for achieving resource
security: a review. Fron. Environ. Sci. 7, 1–9. doi: 10.3389/fenvs.2019.0
Simpson, G. B., and Jewitt, G. P. W. (2019b). The water-energy-food nexus
in the anthropocene: moving from ‘nexus thinking’ to ‘nexus action’.
Curr. Opin. Environ. Sustain. 40, 117–123. doi: 10.1016/j.cosust.2019.
Simpson, G. B., Jewitt, G. P. W., and Badenhorst, J. (2020). The Water-Energy-
Food Nexus Index and its application to South Africa and the Southern
African Development Community. WRC Report no. 2959/1/19. Water Research
Commission, Pretoria. Availableonline at: http://wrcwebsite.azurewebsites.net/
Steﬀen, W., Rockstrom, J., Richardson, K., Lenton, T. M., Folke, C., Liverman,
D., et al. (2018). Trajectories of the earth system in the anthropocene.
Proc. Natl. Acad. Sci. U.S.A. 115, 8252–8259. doi: 10.1073/pnas.181014
Sušnik, J. (2018). Data-driven quantiﬁcation of the global water-
energy-food system. Resourc. Conserv. Recycl. 133, 179–190.
Tufte, E. (1983). The Visual Display of Quantitative Information. Cheshire, CT:
UN Water (2013). Water Security and the Global Water Agenda. UN-Water
Analytical Brief. Hamilton, ON: United Nations University.
UN Water (2018). Sustainable Development Goal 6: Synthesis Report on Water and
Sanitation. New York, NY: United Nations.
UNDP (2018a). 2018 Statistical Annex - Human Development Reports. Available
online at: hdr.undp.org/sites/default/ﬁles/2018_statistical_annex_all.xlsx.
United Nations Development Programme.
UNDP (2018b). Human Development Indices and Indicators 2018 Statistical
Update. New York, NY: United Nations Development Programme.
UNESCO (2014). United Nations World Water Development Report 2014: Water
and Energy. Paris: UNESCO. p. 230.
Van der Zaag, P. (2010). Viewpoint – Water variability, soil nutrient heterogeneity
and market volatility – why sub-Saharan Africa’s Green Revolution
will be location-speciﬁc and knowledge-intensive. Water Alternatives
3, 154–160. Available online at: https://www.water-alternatives.org/index.
van Wijk, J. (2005). The value of visualization. IEEE Visual. 5, 79–86.
Waas, T., Hugé, J., Block, T., Wright, T., Benitez-Capistros, F., and Verbruggen,
A. (2014). Sustainability assessment and indicators: tools in a decision-
making strategy for sustainable development. Sustainability 6, 5512–5534.
Wicaksono, A., Jeong, G., and Kang, D. (2017). Water, energy, and food nexus:
review of global implementation and simulation model development. Water
Policy 19, 440–462. doi: 10.2166/wp.2017.214
Wichelns, D. (2017). The water-energy-food nexus: is the increasing attention
warranted, from either a research or policy perspective? Environ. Sci. Policy 69,
113–123. doi: 10.1016/j.envsci.2016.12.018
World Bank (2018). Indicators. Data. Available online at: http://data.worldbank.
org/indicator/ (accessed March 1, 2019)
World Economic Forum (2011). Water Security: The Water-Energy-Food-Climate
Nexus. Washington, DC: World Economic Forum.
World Economic Forum (2018). The Global Risks Report 2018 - 13th Edition.
Geneva: World Economic Forum.
WWAP (2020). United Nations World Water Development Report 2020: Water and
Climate Change. Perugia: UNESCO.
WWF and SABMiller (2014). The Water-Food-Energy Nexus: Insights into Resilient
Development, 20. Available online at: http://assets.wwf.org.uk/downloads/
Conﬂict of Interest: GS and JB are employed by Jones & Wagener (Pty) Ltd.
WB is employed by BlueFox Data Consulting. PR and VP are employed by
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