Declan Conway, Emma Archer van Garderen, Delphine
Deryng, Steve Dorling, Tobias Krueger, Willem Landman,
Bruce Lankford, Karen Lebek, Tim Osborn, Claudia Ringler,
James Thurlow, Tingju Zhu & Carole Dalin
Climate and southern Africa's water–energy–
food nexus
Article (Accepted version)
(Refereed)
Original citation: Conway, Declan, Archer van Garderen, Emma , Deryng, Delphine, Dorling, Steve, Krueger, Tobias,
Landman, Willem, Lankford, Bruce, Lebek, Karen, Osborn, Tim, Ringler, Claudia, Thurlow, James, Zhu, Tingju and Dalin,
Carole (2015) Climate and southern Africa's water–energy–food nexus. Nature Climate Change, 5 (9). pp. 837-846. ISSN
1758-678X
DOI: 10.1038/nclimate2735
© 2015 Nature Publishing Group
This version available at: http://eprints.lse.ac.uk/63308/
Available in LSE Research Online: August 2015
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1
Climate and southern Africa's water-energy-food nexus
In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and
socioeconomic exposure to climate is high in vulnerable areas and in sectors with crucial economic importance.
Spatial co-dependence is high; climate anomalies can be regional in extent and trans-boundary river basins and
aquifers transect the region. There is strong evidence of the effects of individual climate anomalies, yet proven
associations between rainfall and Gross Domestic Product and crop production are relatively weak. Most nexus
studies for southern Africa have been motivated by climate change. Whilst uncertainties remain high, for the
southernmost countries the majority of climate models project decreases in annual precipitation, typically by as
much as 20% by the 2080s. These changes would propagate into reduced water availability and crop yields.
Recognition of spatial and sectoral interdependencies in the nexus should inform policies, institutions and
investments for enhancing water, energy and food security and thus support regional prosperity in this climate-
sensitive environment. Three key political and economic instruments that mediate nexus interactions in the
region could be strengthened for this purpose; the Southern African Development Community, the Southern
African Power Pool, and trade of agricultural products amounting to significant transfers of embedded water.
Introduction
Numerous challenges coalesce to make southern Africa emblematic of the connections between
climate and the water-energy-food nexus which has important economic influence throughout the
region. Physical and socioeconomic exposure to climate is high in vulnerable areas and sectors, such
as agriculture, but also in energy generation and mining. For example, almost 100% of electricity
production in the Democratic Republic of Congo (DRC), Lesotho, Malawi, and Zambia is from
hydropower. Hydropower further comprises a major component of regional energy security through
extensive sharing as part of the Southern African Power Pool (SAPP). The region’s population is
concentrated in areas exposed to high levels of hydro-meteorological variability
1
and Africa’s population
as a whole is projected to double by 2050
2
. Of the thirteen mainland countries and Madagascar (Table
1) that comprise the Southern African Development Community (SADC), six are defined as low income,
three as lower-middle income and four as upper-middle income, according to the World Bank
Classification (using 2012 GNI per capita). There are few quantified examples of the linkages between
climate and economic activity in the region, though economic modelling studies in Malawi and Zambia
indicate that the severe 1992 drought caused an approximately 7-9% drop in GDP and adversely
affected household poverty
3
. Importantly, southern Africa's economy is closely linked with that of the
rest of the African continent through trade of agricultural and other (frequently primary industry)
commodities, acting as an important potential buffer for climate-induced resource scarcity.
Climate variability has important consequences for resource management in the region including for
non-equilibrium production systems such as rangeland ecology
4
, irrigation
5
and lakes
6
. Hence, southern
Africa is a region where seasonal climate forecasts have potential benefit in areas where sustained
forecast skill is demonstrated. Seasonal climate forecasting has been the subject of many studies in
sub-Saharan Africa
7,8,9
; and the Southern African Regional Outlook Forum (SARCOF) provides advance
information about the likely character of seasonal climate. Yet uptake has been very limited, despite
over a decade of research on hydrological applications of seasonal forecasts
10
there is limited evidence
for their operational use in the water sector
9
. With ongoing climate change, annual precipitation levels,
2
soil moisture and runoff are likely to decrease, while rising temperatures could increase evaporative
demand in large parts of the region
11
(Figure 1).
The last decade has seen rapid growth in research and policy interest in natural resource scarcity, with
water-energy-food interdependencies increasingly framed as a nexus, or resource trilemma. The Bonn
Nexus conference in 2011
10
is notable in this process of recognising the complex interactions between
sectors and resource systems and the need to minimise the trade-offs and risks of adverse cross-
sectoral impacts
10,12
. The nexus is increasingly prominent on policy-makers’ agendas, partly in relation
to the post-2015 development agenda for the Sustainable Development Goals
13
. The private sector was
another early promoter of the nexus concept
14
due to growing associated risks affecting production
security along supply chains, such as (but not exclusively) for water
15
. In southern Africa, for example,
South African Brewers SABMiller are seeking better approaches to handling trade-offs between water,
energy and food by attempting to make business decisions through a resource nexus lens
16
. Strong co-
dependencies at a range of scales give rise to a large number of trade-offs and co-benefits, according
to the heterogeneous configurations of societal uses of water across river basins and aquifers. For
example, irrigation and other consumptive water uses may bring opportunity costs for downstream
energy generation and environmental sustainability such as in the Rufiji and Zambezi basins.
Development of new hydropower facilities can increase evaporation and alter river flow regimes,
particularly during low flow seasons. The region’s many transboundary basins require that trade-offs
among upstream and downstream water uses are reconciled between countries.
Previous nexus studies have concentrated on global interdependencies
17
, problem framing
18
or case
studies of trade-offs and co-benefits in specific systems such as islands
19
and irrigation and hydropower
production
20
. Here, we examine southern Africa’s nexus through a climate lens and modify Hoff’s nexus
framework
10
which integrates global trends (drivers) with fields of action, to highlight the role of climate
as a driver in southern Africa’s nexus (Figure 2). Climate encompasses average (i.e. 30-year)
conditions, variability over years to decades (i.e. as observed) and anthropogenic climate change. In
terms of the nexus, we consider the main elements of intra-regional linkages in water-energy-food at a
national level, while highlighting connections at the river basin scale and drawing attention to some of
the many examples of specific trade-offs and synergies. We base our review on published studies,
complemented by empirical analysis of available national-level data on climate, water resources, crop
production, trade and GDP. We first consider national-level exposure of water, energy and food
production to climate variability in aggregate economic terms and analyse the relationship between
inter-annual and multi-year climate variability and economic activity, focusing on GDP and agricultural
production. We then outline the potential for connecting areas with robust seasonal climate forecasting
skill in areas with socially and economically important nexus related activities, and summarise studies
that model the impact of anthropogenic climate change on elements of the nexus. Finally, we describe
three key intra-regional mechanisms for balancing nexus components and conclude by identifying
knowledge gaps in southern Africa’s climate and water-energy-food nexus.
National level exposure of nexus sectors to climate
3
We characterise exposure as the interaction between characteristics of the climate system (particularly
inter-annual rainfall variability) and a country’s dependence on climate-sensitive economic activities
such as the share of agriculture in GDP, the proportion of rain-fed agricultural land and the energy
contribution from hydroelectric sources (Table 1, Figure 3). South Africa’s GDP is larger than that of the
other 12 economies combined. The direct contribution of agriculture to the economy is lowest (<10%) in
South Africa, Botswana, Swaziland, Namibia, Angola and Lesotho, 13% in Zimbabwe, and over 20% in
the other countries. If agricultural processing were included in agricultural GDP, the shares would be
substantially larger in most, if not all, SADC countries. The share of cropland equipped for irrigation is
low in most of the region, with the exception of Madagascar, South Africa and Swaziland (Table 1). The
contribution of hydropower in energy production is very high overall (Figure 3), but varies considerably
across the region, from 1.5% of energy production in South Africa, over 30% in Madagascar, Swaziland
and Zimbabwe, to almost 100% in DRC, Lesotho, Malawi, and Zambia. Reliable electricity production is
at risk during prolonged droughts, and also during extreme flooding events, when dam safety is an
additional risk. Over 90% of South Africa's energy generation is coal-based
21
, well above the rest of the
region. Coal-fired power plants with wet cooling systems consume far more water than most other
energy technologies
22
. South Africa’s main energy utility Eskom uses about 2% of the country’s
freshwater resources, mainly for coal-fired power stations
23
. Coal mining and energy generation from
coal both substantially impact water quality and availability
24
. To reduce these impacts, Eskom has
implemented a dry-cooling system in two existing power stations and all new power stations will use
dry-cooling
23
, enabling a 15-fold reduction in water use of power stations.
Overall, there are strong contrasts (Table 1) in energy (8-84% of energy consumption imported) and
food (5-90% of cereal food imported) self-sufficiency, and in the sustainability of freshwater use,
expressed as freshwater withdrawals relative to total actual renewable water resources (TARWR) (0.1-
24%). Countries facing most water shortage, expressed as share of TARWR withdrawn (Table 1), are
South Africa (24%), Swaziland (23%), and Zimbabwe (21%), well within categories defined as
physically water-scarce (ratio larger than 20%
25
). We interpret this indicator with caution, noting its
failure to capture the complex spatial and temporal distribution of water, political-economic access,
differences in water needs and socioeconomic capacity to support effective water utilisation
26,27
. Sub-
national areas of high demand relative to availability include southern Malawi, Namibia and Botswana.
Low ratios of water withdrawal to TARWR (such as 0.05% in DRC
27
) could also indicate economic water
scarcity due to inadequate investments to harness and deliver water.
The cereal import dependency ratio (Table 1) reflects the importance of imports in the volume of grains
available for consumption in the country (i.e. Production + Imports - Exports). It is particularly high for
the small countries of Swaziland and Lesotho, and more strikingly so for larger nations like Botswana
(90%), Namibia (65%) and Angola (55%). Dependency ratios are lowest in Zambia and Malawi. Total
food aid received by the region (260,000 tons in 2012, Figure S1) was equivalent to about 2-3% of food
imported by the region from the rest of the world (9 million tons in 2008). Chronic and episodic food
insecurity remain important problems in the region. The causes of inadequate food access are multiple
and, at the household and individual level, they are dominated by poverty, environmental stressors and
conflict, often underpinned by chronic structural elements in the lives of communities, intensified by
4
sudden shocks which can be climate related such as decrease in cereal availability and food price
increases
28,29
.
Climate signals in the nexus
Multi-year rainfall variability in southern Africa is higher than in many other parts of the world
30
. Inter-
annual variability, expressed as the coefficient of variation (CoV), is not particularly high at national
scales: < 20% for most countries, except for the driest two countries Botswana and Namibia (Figure 3).
However, rainfall displays much greater local variability (local CoV exceeds 20% across much of the
SADC region), strong seasonality, and a range of longer periodicities from multi-annual to decadal
31
. At
the national level, long-term trends in rainfall between 1901 and 2012 are modest (the linear trend is
insignificant relative to the long-term average) without evidence of any clear spatial pattern (Table S1).
Linear trends during the last two decades show varied behaviour; three countries with wetting trends
above 20% of the long-term mean annual rainfall (Botswana, Namibia and Zambia) and Tanzania with a
drying trend of 21% (Table S1). National level analysis is likely to obscure local trends and trend results
are highly sensitive to the period chosen for analysis, particularly in regions with strong multi-annual
variability.
We use correlation analysis to explore the associations between annual rainfall and national economic
activity (GDP annual growth rate) and agricultural production (all cereals and maize - the most
significant crop in the region). Fifteen year sliding correlations are used to examine the temporal stability
of associations between variables (see SI Methods and data). There are no statistically significant
relationships between annual rainfall and GDP growth rate and none of the mean 15-year sliding
correlations are significant (Table 2). Correlation of rainfall with total production of cereals and maize
shows three countries with significant relationships at 1% level and three at 5% level (although for DRC,
it is negative and possibly spurious). The average sliding correlations are somewhat higher (but not
statistically significant, Table S2).
Time series data of hydropower production are not publically available and not easily comparable
between sites/countries, making it difficult to assess the importance of climate variability as a driver of
energy production fluctuations. Electricity insecurity is known to negatively affect total factor productivity
and labour productivity of small and medium-sized enterprises but the relationship is as yet not
straightforward, with differences between countries and measurement effects
32
. Studies of specific
events highlight what are major consequences of some drought-induced reductions in electricity
production
33
. Ref. 18 cites examples of drought impact on the Kariba Dam (Zambezi River basin),
during 1991-92, resulting in an estimated $102 million reduction in GDP and $36 million reduction in
export earnings; and Kenya where, during 2000, a 25% reduction in hydropower capacity resulted in an
estimated 1.5% reduction in GDP. A review of the economics of climate change in Tanzania profiled the
consequences of drought in 2003, which brought the Mtera dam reservoir levels close to the minimum
required for electricity generation
34
. This prompted Tanzania Electric Supply Company (TANESCO) to
approach a private provider to use gas turbine units at huge cost. A more recent World Bank estimate
![Table 2: National-level correlation coefficients between annual GDP percentage growth rate (calendar year) and rainfall (October year-1 to September current year). Mean, maximum and minimum correlations from 15-year sliding Correlations significant at 1% level are bold, and at 5% in italics. Sources: GDP [95], rainfall [37].](/figures/table-2-national-level-correlation-coefficients-between-2u9is9s8.webp)
![Table 1: Economic indicators and climate sensitive economic activities across water, energy and food. Sources: GDP (2012), [95]; Energy (2012), [99]; Water use (2000-2005), [77,100]; Food trade (2007- 2009), [96], Irrigation (1960-2005), [77,100].](/figures/table-1-economic-indicators-and-climate-sensitive-economic-l1wbdsmb.webp)