Draft Document: Climate Change Risk and Vulnerability Assessment for Rural Human Settlements

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Draft Document:

Climate Change Risk and Vulnerability

Assessment for Rural Human Settlements

Prepared by Link

d

_{Environment Services for the}

_{Department of Rural Development and}

Land Reform: Spatial Planning and Facilitation Directorate

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Status of this document

Our approach to the climate change risk and vulnerability assessment for rural human settlements has been ambitious and has gone somewhat beyond our initial proposal in that it amounts to original research, as opposed to simply collating existing research findings.

In undertaking the risk and vulnerability assessment, we have developed a conceptual model of climate change risks and vulnerability based on a complex set of climate change projections from existing models, composite indicators, and raw data from sources such as Stats SA. These have been translated into spatial maps using GIS tools.

This document provides a detailed description of the conceptual basis for the risk and vulnerability assessment using explanations and maps of the indicators used to build the model, as well as a description of the overall methodology.

In translating our conceptual model into a spatial model, we have inevitably had to make some compromises based on the availability of data, and at this point there are some indicators for which we are still trying to source spatial data. Further progress may be made in this regard prior to engaging stakeholders at the regional workshop.

In particular, the comparison of a mapping of risk and vulnerability in relation to a typology of human settlements is still underway, but we expect to present these results at the PSC meeting on the 17th and update this document at the same time.

However, we are already confident that we have useful outcomes in terms of the mapping of climate change risk and vulnerability with which to engage stakeholders. Further progress will amount to a refinement of the model and its spatial mapping, but is not likely to dramatically alter the findings presented in this document.

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Table of ContentsList of Abbreviations ... 5

List of Figures ... 5

1. Introduction ... 6

2. Methodology ... 8

2.1. Time scale... 8

2.2. Resolution ... 8

2.3. Weighting... 9

2.4. Outcomes ... 9

3. Hazard Exposure ... 9

3.1. Mean annual temperature change ... 9

3.2. Annual precipitation change ... 10

3.3. Extreme Weather ... 11

3.4. Sea-level rise ... 12

3.5. Ocean acidification ... 12

3.6. Aridity ... 13

3.7. Composite Mapping of Hazard Exposure ... 13

4. Sensitivity ... 14

4.1. Physical water scarcity ... 15

4.2. Irrigated cultivated land ... 16

4.3. Terrain slope ... 16

4.4. Growing period ... 17

4.5. Net Primary Production (rain fed) ... 18

4.6. Net Primary Production (irrigated) ... 19

4.7. Perennial rivers ... 20

4.8. Ground water availability ... 21

4.9. Land degradation ... 22

4.10. Crop diversification ... 23

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4.12. Composite Mapping of Sensitivity ... 24

5. Adaptive Capacity ... 25

5.1. Population age profile ... 26

5.2. Income ... 27

5.3. Employment ... 28

5.4. Gender ... 29

5.5. Access to basic services ... 30

5.6. Land Tenure status ... 32

5.7. Type of dwelling ... 33

5.8. HIV prevalence ... 34

5.9. Dependence on Agriculture ... 35

5.10. Composite Map of Adaptive Capacity ... 36

6. Vulnerability ... 37

6.1. Composite Mapping of Vulnerability ... 37

7. Typology of Rural Human Settlements ... 38

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List of Abbreviations

CO² Carbon Dioxide

°C degrees Centigrade

Cm centimetres

DRDLR Department of Rural Development and Land Reform DIRCO Department of International Relations and Cooperation

DWA Department of Water Affairs

FAO Food and Agriculture Organization

GIS Geographical Information Systems

GAEZ Global Agro-Ecological Zones

IIASA Institute for Applied Systems Analysis

IPCC International Panel on Climate Change

LGP Length of Growing Period

mm Millimetres

NPP Net Primary Production

RDI Radiative Dryness Index

SANBI South African National Biodiversity Institute

SCOR Scientific Committee on Oceanic Research

UNDP United Nations Development Programme

List of Figures

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1. Introduction

There is a natural amount of carbon dioxide (CO²) in the atmosphere, and this natural amount of carbon dioxide, together with other greenhouse gases, helps keeps the Earth at an average heat of 15°C and ensures a stable global climate in which any change tends to happen over very long time spans. However due to human activity, and particularly the combustion of fossil fuels, the natural balance of CO² in the atmosphere is being exceeded, causing the Earth to rapidly warm. This warming is resulting in changes to the earth’s climate that include rising sea levels, changes in precipitation patterns, and an increase in the frequency and intensity of extreme weather events. These global changes are known as climate change and threaten the way in which societies across the world relate to and live within the natural environment.

Across the world societies are preparing for the changes that climate change will bring and South Africa is no exception. Climate change presents a particular challenge to developing countries such as South Africa that already experience development problems such as poverty and lack of access to basic services. Changes in the climate will make already existing development challenges harder to resolve because resources will become scarcer as the demand for them from people who are at risk grows. There is therefore an urgent need to put appropriate plans in place now that will make people more resilient to climate change and enable them to not only survive climate change, but also to keep their livelihoods intact.

The changes which people must make to survive climate change and protect their livelihoods are commonly known as adaptation. In South Africa, the social and economic costs of climate change are already being incurred and are a growing threat to the achievement of South Africa’s sustainable development goals. Across the globe, due to the fact that they tend to rely more on natural systems, rural communities are the first to experience the effects of climate change and are likely to be the most severely affected. This is particularly true of developing countries such as South Africa. It is therefore critical to identify the rural human settlements most at risk from climate change, and to develop plans to reduce their vulnerability.

The central purpose of this report is to identify and understand the factors that increase climate change risks, and spatially map these risk factors in order to inform planning and assist in the development of relevant adaptation strategies at a regional and local level.

The impacts of climate change are not evenly borne across countries, communities and households. For a few, the net effects of climate change may be positive over certain time frames. For instance, growing periods for crops in some areas, particularly those in the large northern hemisphere land-masses bordering the arctic circle, are likely to increase. For most of Africa including South Africa, the net effect of climate change on growing periods is likely to be negative, however. Furthermore, the ability to respond effectively to climate change is sharply differentiated, with poor rural communities often being the least equipped to respond.

Modelling the impacts of climate change presents complex challenges and happens at different levels:

The physical impacts of climate change consist of changes such as increased temperature and changes to evaporation rates, precipitation patterns, ocean currents and prevailing winds.

The bio-physical impacts of climate change concern the interaction of the physical impacts of climate change with the bio-sphere i.e. living systems.

The social impacts of climate change are determined by the human consequences of changes to the environment due to climate change, as well as the socio-economic consequences of climate change mitigation actions.

It is commonly maintained by experts and endorsed by the United Nations Development Programme that climate change vulnerability is best understood as an outcome of the interrelationships between three related but different characteristics of a particular geographical location. These characteristics are hazard exposure, sensitivity and adaptive capacity. This relationship can best be understood in the following equation:

Hazard exposure x Sensitivity – Adaptive Capacity = Climate Vulnerability (UNDP 2010).

Hazard exposure can be defined as the physical impacts of climate change such as an incremental

rise in temperature, an increase in violent storms or changes in precipitation patterns. This exposure to the hazards of climate change can result in both gradual impacts such as declining crop yields

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Sensitivity can also be referred to as biophysical vulnerability and consists of the reactions of living

systems to hazard exposure. Sensitivity is measured by the reactions of a unit of analysis to the impacts of climate change. For instance, a 1°C incr ease in temperature may result in a quantifiable increase or decrease in the incidence of a particular plants species in a particular ecosystem. Equally, it may affect the geographical extent of a particular ecosystem (such as savannah).

Adaptive Capacity refers to the financial, physical, cultural and political ability of societies to make

the required changes needed to survive the adverse effects of climate change. Adaptive capacity is defined by how people experience and survive the the exposure to hazards. Further adaptive capacity is measured at the unit of analysis (the individual, household or community) and reflects the multi-stressors which these units experience; such as poverty, ill-health or unemployment. An adaptive capacity which is deemed high is usually experience by those with a low social vulnerability and vice versa.

The interaction between hazard exposure, based on climate change projections, and sensitivity, based on an analysis of bio-physical characteristics, can be understood as encompassing the risks posed by climate change. Vulnerability is therefore a product of the extent to which these risks are mitigated or exacerbated by the presence or absence of adaptive capacity.

The approach used in this study to modelling the interactions between hazard exposure, sensitivity and adaptive capacity in contributing towards vulnerability is illustrated in Figure 1. The figure introduces the indicators that were used to express the three interrelated components of climate vulnerability.

Source: Authors own

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2. Methodology

In this assessment the climate change vulnerability of rural human settlements is modelled using a Geographical Information System (GIS) to capture the spatial variability of the impacts of climate change in terms of hazard exposure and sensitivity, and the capacity of rural human settlements to respond to these.

2.1. Time scale

In terms of planning horizons, future values for the 2020s were used for indicators that include projected future values (primarily those relating to hazard exposure) because these are the earliest values available and are more realistic as a time horizon in planning for the DRDLR than the 2050s or the 2080s.

For indicators that have future values, the Hadley CM3 model with the A2 climate change scenario was used. The United Kingdom’s Meteorological Office developed this model and it is one of the models that is widely used by the international community, including the Intergovernmental Panel on Climate Change (IPCC). The A2 scenario was developed by the IPCC and describes a very heterogeneous world in the future, with an underlying theme of self-reliance and preservation of local identities. In this scenario, fertility patterns across regions converge very slowly, which results in continuously increasing global population. Economic development is primarily regionally oriented and per capita economic growth and technological change is more fragmented and slower than in other storylines.

2.2. Resolution

In principle, the GIS model determines the spatial distribution of communities’ vulnerability to climate change at ward level. Because many of the data sets used in this study are not compiled at ward level, this has meant in many cases that data has been averaged at the ward level (where the data is at a finer resolution than ward level) or downscaled to ward level.

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2.3. Weighting

Vulnerability to climate change is not directly measurable, so the approach adopted here is to express it as the net outcome of a weighting of composite indicators for hazard exposure, sensitivity and adaptive capacity.

The indicators within each composite indicator were scored according to individual criteria and the scores were summed to arrive at final scores for hazard exposure, sensitivity and adaptive capacity per ward. A municipal ward’s final score for vulnerability was calculated using the following weighting (based on the uncertainties in the data) for the composite indicators:

hazard exposure – 20%

sensitivity – 30%

adaptive capacity – 50%

The sections that follow describe each group and its indicators in more detail. The reasoning behind selecting these indicators and using wards as the final spatial unit is based on the main findings of the literature review of this study.

2.4. Outcomes

The primary outcome of this study is a spatial mapping of vulnerability in terms of areas of relatively high, medium, and low vulnerability to climate change. As such it provides a useful guide in terms of prioritising rural human settlements for resource allocation and planning for climate change adaptation. The implication is not, of course, that areas that have a relatively low risk do not need to plan for adaptation.

Vulnerability is location specific phenomenon, and simply knowing that a particular area is highly vulnerable to the impacts of climate change is only a starting point in terms of planning. For this reason, the spatial mapping of particular risk vectors and adaptive capabilities (or absence thereof) is an important part of the outcomes of this study. To this end this assessment includes:

Maps of the composite indices for hazard exposure, sensitivity and adaptive capability

Maps of the component indicators for each of these indices.

These resources can be used to obtain some level of insight into the particular threats and challenges facing specific communities. While beyond the immediate scope of this work, the approach adopted here could be potentially used to develop a ward-level adaptation planning tool for local government that exposes not just the overall vulnerability of settlements at ward level, but also the component factors that constitute vulnerability.

The sections that follow describe each composite index and its component indicators in more detail. The reasoning behind selecting these indicators and using wards as the final spatial unit is based on the main findings of the literature review of this study.

3. Hazard Exposure

In this assessment hazard exposure is defined as the physical impacts of climate change which can either happen over a prolonged period of time or through weather variability and weather related events. The indicators selected to measure the hazard exposure are: mean annual temperature change, annual precipitation change, climate extremes index, sea-level rise, ocean acidification and change in the aridity index. These indicators are further explained in the following sections.

3.1. Mean annual temperature change

Mean annual temperature can be described as the average temperature at any given location for the entire year. In South Africa, temperatures are largely affected by the elevation of any given location and its distance from the sea. The inland areas are highly elevated and they experience a warm summer with daily

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temperatures reaching 26-28 °C. These high areas al so experience cool winters with mean daily temperatures of around 0-2°C which also may be acco mpanied by frost. The temperature of the east coast is determined by the warm Mozambique current and the areas between East London and Mozambique are therefore warmer throughout the year. The northern parts of the coast are sub-tropical and experience a warm winter with daily minimums of around 9-10°C an d a hot summer with a maximum of 32°C. The interior which hold the Nam-karoo biome has more of an extreme climate than the rest of the country with daily maximum highs in the summer reaching 34 °C and mini mums in the winter sitting at around 6°C. The temperatures of the West Coast are influenced by the Benguela current and therefore the area experiences daily highs in the summer of around 32°C and daily winter minimum temperatures of around 6°C with no frost.

Under and A2 scenario there is a general consensus that South Africa’s coastal regions will warm by around 1-2°C by about 2050 and around 3-4°C by about 2100. Also, South Africa’s interior regions will warm by around 3-4°C by about 2050 and around 6-7°C by abou t 2100. Rising temperature is understood to be one of South Africa’s major impacts of climate change and therefore the change in mean annual temperature Is included in this study (Department of International Relations and Cooperation 2011).

Changes in the modelled mean annual temperature in the 2020s and the baseline values were scored by assigning marks using the absolute value of the percentage change. This is because adaptation is needed in all areas where the temperature changes, not only where it increases. Map 2 shows the differences between the mean annual temperature in the 2020s and the baseline from 1961 to 1990.

Map 2 : Mean annual temperature changes (°C) in Sou th Africa between the baseline of 1961-1990 the 2020s

Source: calculated from GAEZ data (Hadley CM3 model and A2 climate change scenario)

3.2. Annual precipitation change

Annual precipitation is the average amount of water, which is measured in mm, and falls from the clouds in a solid or liquid form at any given location during the course of the year. Currently South Africa has a mean annual rainfall of around 450mm and is therefore regarded as semi-arid. The country does however

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experience regional differences in rainfall patterns. Areas which border Namibia (the Richtersveld) may only receive less than 50 mm of rainfall while the mountains of the south west Cape can receive more than 600 mm of rainfall. Furthermore, South Africa experiences more below average rainfall years than above average and the annual potential evapo-transpiration may exceed annual precipitation by ratios of up to 20:1 (Palmer & Ainslee 2013).There are three major rainfall zones in South Africa: the winter rainfall region of the western, south western and southern Cape; the bimodal rainfall region of the Eastern Cape, and the summer rainfall region of the highveld and KwaZulu Natal (ibid).

Oncoming climate change will entail significant changes in rainfall patterns and this, coupled with increased evaporation, will result in significant changes in respect of water availability. Examining changes in annual precipitation averages therefore prove as useful indications as to which areas will experience the most environmental change in the future and overall vulnerability to climate change (DIRCO 2011). Changes in the precipitation mean baseline and modelled mean annual precipitation in the 2020s and values were scored by assigning marks using the absolute value of the percentage change. This is because adaptation is needed in all areas where the rainfall changes, not only where it increases. Map 3 shows the absolute percentage change in precipitation between the 2020s and the 1961-1990 baseline.

Map 3: Absolute percentage change in precipitation between the 2020s and the 1961 - 1990 baseline

3.3. Extreme Weather

A climate extremes index or incidence of extreme weather events has been selected in order to determine locations that are currently prone to and will be more prone to weather events in the future. In simple terms extreme climate is extremely bad or devastating weather. In South Africa this often takes the form of drought, flooding, frost and hail storms.

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3.4. Sea-level rise

Sea-level rise refers to the rising levels of the ocean which is contributed to by the expansion of the waters as the temperatures of the ocean rise and the melting of glaciers and ice sheets. Sea level rise therefore provides evidence that the temperature of the atmosphere is indeed increasing. The extent to which the waters of the sea will increase is unclear; however, the IPCCC estimates that over the course of the 21st Century, the seas could rise between 18 to 59 cm (IPCCC, 2007). The rising up of the oceans waters will have a detrimental effect on human populations that live in coastal areas as well as to marine ecosystems, and it is for this reason that sea level rise has been selected as a hazard exposure indicator because it will point towards wards where populations are at risk or may even have to be relocated.

Sea level rise scores were assigned to coastal municipal wards only, according to the length of its coast line and its population density. Map 5 displays this analysis. The reason for not using low lying land areas as an indication of areas that are vulnerable to sea level rise is because of data constraints.

Map 4: Population per length of coastline (displayed by ward)

Source: calculated from Statistics SA Census 2011

3.5. Ocean acidification

Ocean acidification refers to the continuous decrease in the pH levels of the Earth’s oceans which is caused by the dissolving of carbon dioxide into the waters of the oceans. It is estimated that up to 40% of carbon dioxide in the atmosphere is absorbed by the oceans and other large water bodies, and as this happens the acidity of the water increases as the water reacts with the carbon dioxide to form carbonic acid. It is estimated the oceans waters may have become up to 30% more acidic over the past 200 years and that this increasing acidity has negative effects for ocean eco-systems and for food chains (SCOR). Because of this detrimental effect of ocean acidification on marine food chains, ocean acidification has been selected as an indication of hazard exposure because it points out where communities which are reliant on the productivity of the ocean for their livelihoods are vulnerable to climate change.

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Scores for ocean acidification were assigned based on the relative importance of fishing in the GDP of the ward. (See Section 5.8 for a map of the relative contribution of agriculture, fisheries and forestry to the economy.) For this indicator only the coastal municipal wards were considered.

3.6. Aridity

The aridity index is the ratio between the annual precipitation and the potential evapotranspiration. This gives an indication of the dryness of the climate; that is whether the water balance is positive or negative at a given location. South Africa is already largely a dry country and in the process of climate change it is expected that some regions will become drier. As these regions become drier, agriculture and livestock farming will be impacted on negatively. This indicator therefore takes account of areas where rain fed agriculture and livestock agriculture will become more difficult in future as water deficit increases.

Changes in the modelled aridity index in the 2020s and the baseline values were scored by assigning marks to places where the index decreased in the future. Since a higher aridity index indicates more moisture compared to evapotranspiration, areas with a reduced future aridity index in the future (compared to the baseline) scored on this indicator. Therefore the areas in 7 below with negative values were assigned scores for this indicator.

Map 5: Aridity index changes in South Africa between the baseline of 1961-1990 the 2020s

3.7. Composite Mapping of Hazard Exposure

When the analysis of all of the selected indicators for hazard exposure (mean annual temperature change, annual precipitation change, climate extremes index, sea-level rise, ocean acidification and changes in the aridity index) is combined into a single composite map of hazard exposure, the map below is generated. In this map areas that have a high hazard exposure are clearly distinguished from areas that have a low hazard exposure. The map below shows that municipal wards along the coast will experience a high exposure to climate hazards, especially in the western coastal regions of the Northern Cape. Coastal municipal wards between the Western Cape and Eastern Cape also receive a high score in terms of the combined hazards. Municipal wards in the North West, Mpumulanga and Limpopo province receive a medium score in terms of climate hazard exposure.

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Map 6: Combined hazard scores

4. Sensitivity

Sensitivity can also be referred to as biophysical vulnerability and is defined as the biological and ecological reactions of ecosystems, biomes, sectors and countries to hazard exposure. Different physical environments will experience climate hazards differently and this difference determines their sensitivity to climate change. The sensitivity of different physical locations to climate hazards impacts the way in which humans use the environment because it indicates how productive and safe the land is. Sensitivity is measured at the unit of analysis which can be either a small ecosystem in a garden or an entire biome. The indicators selected to achieve a high level analysis of the sensitivity for rural human settlements in this assessment are: physical water scarcity by major river basin, irrigated cultivated land, terrain slope index, growing period, Net Primary Production (NPP) (rain fed), NPP (Irrigated), major perennial rivers, ground water availability, land degradation index, crop diversification index and ecological resilience. These indicators are discussed in greater detail throughout the rest of this section.

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4.1. Physical water scarcity

Rivers form a part of natural water courses and the hydrological cycle. Rivers are usually made up of fresh water which flows towards the ocean or to another body of water. Sometimes rivers dry before they can reach these other bodies of water. The water within a river is collected from precipitation and from the process of surface runoff, groundwater recharge, springs and the release of stored water such as natural ice. South Africa has several small rivers along the coast line which run into the sea, but none are navigable. There are only two major rivers in South Africa; the Limpopo River which is shared with Zimbabwe and the Orange (including its tributary river the Vaal) which runs across the centre of the country from the east to the west towards the Atlantic Ocean. Because South Africa is a dry country the levels of these rivers and the available amount of water is highly sensitive to climate change and therefore physical water scarcity by river basin is seen as an important indication of sensitivity to climate change especially for rural populations that are dependent on river water as their primary water resource.

A river basin constitutes the land area that is drained by a river and its tributaries. Physical water scarcity by major river basins refers to areas where there are negative water balances in the major basins. These values were modelled by the FAO and they expressed this negative balance in terms of the ratio between irrigation water that is consumed by plants through evapotranspiration and renewable fresh water resources. Renewable fresh water resources as well as net irrigation water requirements in the river basin are calculated through a water balance model, with information regarding climate, soils and irrigated agriculture as input data. Scores were assigned according to the classes.

Map 7: Physical water scarcity

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4.2. Irrigated cultivated land

Irrigation can be explained as the artificial application of water to the land or soil in order to assist with the cultivation of crops and the restoring of soils during times of insufficient rainfall. The process of irrigation can also assist in protecting crops from frost, in combating the growth of weeds, suppressing dust, and in preventing soil consolidation. The water source for irrigation can be groundwater, surface water from rivers or lakes, dams, desalinated water, waste water or drainage water. The quality of the water used in the irrigation process has a direct effect on the quality of the cultivated crops and on the productivity of the soil. Given South Africa’s dry climate, it is extremely reliant on irrigation for continued agricultural production. Irrigated lands are therefore extremely sensitive to reductions in available water.

This indicator was scored according to the percentage of an area that is irrigated – the higher the percentage, the higher the score.

Map 8: Irrigated, cultivated land in South Africa

Source: Global Agro-Ecological Zones (FAO and IIASA)

4.3. Terrain slope

The terrain, otherwise known as land relief, is the vertical and horizontal dimension of land surface. It is a common geographical term used to describe how the land is laid out and is usually expressed in terms of elevation, slope and the orientation of features. The terrain is important to consider because it can affect weather and climate patterns and also affects the distribution and quality of water. Furthermore a firm grasp of the terrain is important because it determines the suitability of the earth’s surface for human settlements, for example the flat plains have a better soil quality for the production of crops.

South Africa’s terrain falls into two major physiographic features: The interior plateau and the land between the plateau and the coast. The Great Escarpment forms the boundaries between these two regions. The Great Escarpment is the most prominent relief feature of the country and its height ranges from 1500 m

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above sea level at the Roggeveld scarp in the south-west to 3482 m above sea level in the Drakensburg Mountains. The plateau is characterized by wide plains and the escarpment forms the highest portion of the plateau. The plateau forms a part of the Southern part of the continuation of the great African plateau which stretches all the way to the Sahara Desert. The coastal area between the Great Escarpment and the coast varies in width from 80km to 240km in the east and in the south, and between 60 to 80 km in the west. Three sub-divisions of the coastal areas are recognized; the eastern plateau slopes, the Cape folded belt and the western plateau slopes. Because the lay out of the South African surface area has a direct impact on climate and water distribution, which impacts on rural human settlements and the livelihoods of human settlements it has been selected as an important indication of sensitivity to climate change.

Agriculture becomes more difficult as the slope increases and therefore this indicator scores higher for steeper slopes. Map 11 shows how the terrain slope varies across South Africa.

Map 9: Terrain slope across South Africa

Source: Global Agro-Ecological Zones (FAO and IIASA)

4.4. Growing period

The growing period, or the growing season, is a botanical term which refers to the period of the year when certain plants or crops can be grown. The growing period is determined by the climate, the elevation, the crop selection, the location, the temperature, daylight hours and rainfall amongst other features.

The rainfall seasonality of South Africa impacts growing periods throughout the country. In the north, east and along the coastal belt, summer seasonality encourages grass production and the main focus is cattle and sheep production. In the semi-arid central and western regions grasses and shrubs predominate, and this favours sheep and goat production (Palmer & Ainslee 2003). As agricultural production is critical for rural livelihoods in the form of food and job security the growing period is critical in maintaining the agricultural production balance and therefore that of rural livelihoods. Here, areas were looked for in which the growing period will shorten between the present and the 2020s. The number of growing period days (LGP) are

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calculated on the basis of average climatic parameters. LGP quantification is based on a water balance model comparing moisture supply from precipitation and soil moisture storage and reference evapotranspiration. Reference LGP assumes available soil moisture capacity of 100 mm per meter soil depth and a reference soil depth of one meter.

Changes in the modelled growing period in the 2020s and the baseline values were scored by assigning marks to those areas in which the growing period shortened.

Map 10: Difference in number of growing days per year between the baseline of 1961-1990 and the 2020s

4.5. Net Primary Production (rain fed)

Primary production is the production of organic compounds from carbon dioxide, this process can occur either through the process of photosynthesis of chemosynthesis. Almost all life on Earth relies on primary production because the process forms the basis of the food chain. The organisms that are responsible for primary production, and which sit at the bottom of the food chain, are primary producers or autotrophs. Primary producers are mainly plants in terrestrial ecosystems. Primary production can be determined in net or gross terms with net primary production accounting for losses such as cellular respiration. The Net primary production (NPP) is the total energy accumulated by an ecological unit. The NPP is the difference between the gross primary production and respiration. The NPP equation looks as follows:

The NPP of rain fed agriculture refers to the total production of agriculture which has relied on rainfall as its only water source. It was modelled by GAEZ ad a function of incoming solar radiation and soil moisture at the rhizosphere. Actual crop evapotranspiration (ETa) has a close relationship with NPP of natural vegetation as it is quantitatively related to plant photosynthetic activity which is also driven by radiation and water availability. For NPP estimates under natural, i.e rain-fed conditions, radiative dryness index (RDI) is

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calculated from prevailing net radiation and precipitation of a grid cell and ETa is determined by the GAEZ reference water balance.

Locations where the NPP reduced between the modelled 2020s values and the baseline received positive scores in the GIS model.

Map 11: Areas of reduced NPP under rainfed conditions between the 2020s and the baseline (1961-1990)

4.6. Net Primary Production (irrigated)

This indicator is similar to the previous one, but is applied to irrigated land. It was modelled by the FAO and the International Institute for Applied Systems Analysis (IIASA) in their GEZ system.

For an NPP estimate applicable under irrigation conditions, ETa = ETmax is assumed and a radiative dryness index of 1.375 is used, which maximises the approximation of the ratio between diffusion conditions of CO2 and sensible heat.

Locations where the NPP reduced between the modelled 2020s values and the baseline received positive scores in the GIS model.

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Map 12: Areas of increased NPP under irrigated conditions between the 2020s and the baseline (1961-1990)

4.7. Perennial rivers

A perennial river is one which has a continuous flow in all parts of its bed throughout the year if the year has a normal rainfall. This is in contrast to intermittent rivers which stop flowing or dry up during some months of the year. These definitions and boundaries between different rivers are however, blurred and are often subject to the definitions placed on them by local areas. About two-thirds of South Africa has non-perennial rivers and are therefore more sensitive to the erratic rainfall patterns and water shortages that climate change will bring (Rossouw et al. 2005). In this assessment the availability of perennial rivers is combined with major perennial rivers to find areas that have no alternative to rainfall.

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Map 13: Perennial rivers of SA and wards at least 5 km from a perennial river

Source: Own map from Statistics South Africa Census 2011 and Department of Water Affairs data

4.8. Ground water availability

Ground water refers to the water which is found below the Earth’s surface and which is stored in soil and rock and that supplies water to wells and springs. In South Africa 90% of the ground water occurs in hard rock that contains no porous spaces. In this hard rock the ground water is contained within faults and fissures. The ground water supplies that are found in hard rock are called secondary aquifers. In South Africa, the ground water that is not found in secondary aquifers is stored in primary aquifers which are found in spaces between sand grains in soils. Such aquifers are found in locations such as the Kalahari Desert (Ground water Division 2012).

Ground water contributes very little to the total water supply of South Africa at around 13%, yet at the same time, is an extremely vital water resource. Because of the dry nature of the country and the lack of perennial stream in the arid areas, ground water is an invaluable water resource. Irrigation for agriculture is the largest user of ground water in South Africa, but ground water also forms the major water supply of over many smaller towns and rural settlements. Because precipitation patterns are expected to change with climate change, many areas of the country will become more dependent on ground water as their primary source of water. Ground water will not only also become under threat then as demand increases, but settlements which are located in rapidly drying areas and which are not near to ground water sources, will be more sensitive to climate change. In this assessment ground water availability is combined with major perennial rivers to find areas that have no alternative to rainfall (Ibid).

Ground water availability was approximated through borehole yield, which was obtained from DWA. Areas with smaller yield scored higher on this indicator. The map below shows these scores that resulted from the spatial variation of borehole yield as it varies across South Africa; higher scores indicate less borehole yield.

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Map 14: Borehole yield as a measure of groundwater availability

Source: Own map from Department of Water Affairs data

4.9. Land degradation

Land degradation can be described as the process by which the quality of the environment is negatively impacted by human behaviour. This can be by one aspect of human behaviour or by multiple human activities. It can also be understood as an undesirable change made to the land caused by human activity. The extent of land degradation has serious impacts for agricultural and for human health. Desertification is also a form of land degradation in that it refers to the degradation of dry land areas also due to human activity. Desertification is commonly understood to mean the extension of desert but it actually means the destruction of productive land which is situated in dry areas. This destruction is mainly caused by overuse (Environmental Monitoring Group 2013).

Many features contribute towards land degradation, but the underlying cause is the placing of too much pressure on the land. One such form of this pressure is overgrazing and another is deforestation. It is estimated that up to 25% of South Africa’s land is already badly degraded (ibid.), and therefore land degradation constitutes a very big problem for the country of which 90% of the surface area is classified as arid. Much of this land degradation can be contributed to the history of apartheid in which land was unequally distributed. In the former homelands much of the land is degraded beyond repair because of over farming and overgrazing. This land degradation is a major reason behind the massive amounts of urbanization which the country is experiencing, in which people are moving to the cities in search of a better life and more opportunities (ibid). Land which is already degraded is fragile and is therefore more sensitive to climate change. On-going land degradation will be made worse by climate change and will threaten the livelihoods of rural population further. It is for this reason that land degradation has been chosen as an important indicator of sensitivity to climate change.

Erodabilty from EnpNat 2002 was used to compile this indicator, since erodability depends largely on the condition of the soil and vegetation. Higher erodability index values obtained higher scores on this indicator.

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Map 15: Erodability index

Source: EnpNat 2002

4.10. Crop diversification

Agricultural diversification refers to the cultivation of a multiplicity of different crops on the same land. The reasons for making use of crop diversification include reducing risk, responding to external shocks, increasing the capacity of the land to meet a growing need for cereals, to improve the quality of the soil and the ecosystem, increasing the income of small farms, surviving price fluctuation, mitigating the effects of changing weather, improving the fodder for livestock, to reduce dependence on external inputs, increasing community food security and responding to the impacts of climate change. Crop diversification is not the same as multiple cropping or succession planting in which different crops are grown in successive growing seasons, but rather aims to grow a mix of crops. These crops may also have complementary and higher market values than other crops such as fresh fruits and vegetables. In South Africa crop diversification has the potential to increase the resilience of rain fed subsistence farming to drought and therefore could play an important role in increasing the adaptive capacity and food security of rural human settlements in the country.

4.11. Ecological resilience

Ecological resilience refers to the capacity of an ecosystem or natural population to resist of recover from major changes in its structure and function after the negative effects of human activity have disturbed it. Furthermore ecological resilience refers to the ability of a natural ecosystem or population to recover without shifting to a different regime that will be difficult to reverse with human intervention.

This indicator is included to find areas where ecological services are compromised and therefore more sensitive to climate change. It was calculated from SANBI’s biogeographic nodes and their importance. These were identified as part of the National Biodiversity Assessment in 2004. Biogeographical nodes contain many ecological and evolutionary processes and are therefore more likely to be resilient to climate change.

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Map 16: Biogeographical nodes and their importance

Source: SANBI National Spatial Biodiversity Assessment 2004

4.12. Composite Mapping of Sensitivity

Combining all of the indicators of climate change sensitivity for rural human settlements (physical water scarcity by major river basin, irrigated cultivated land, terrain slope index, growing period, Net Primary Production (NPP) (rain fed), NPP (Irrigated), major perennial rivers, ground water availability, land degradation index, crop diversification index and ecological resilience) results in a composite map for sensitivity which can be seen in the map below. This map clearly shows which areas of the country are highly sensitive to climate change and which areas of the country are the least sensitive to climate change. Highly sensitive municipal wards are found in the western and central parts of the Northern Cape, the North West Province, Limpopo province, Mpumalanga province and dotted in parts of Kwazulu Natal. There are also some highly sensitive areas found in the Western Cape.

In comparison with the composite map of hazard exposure, the composite map of climate sensitivity shows a more diverse, location specific picture. This reflects the complexity of the eco-system characteristics that mediate how hazard exposure impacts on the bio-sphere.

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Map 17: Combined sensitivity score (without crop diversification index)

5. Adaptive Capacity

Adaptive capacity is defined as the resources, infrastructure and services available to people to respond to climate change and reflects the multiple stressors which they experience; such as poverty, ill-health or unemployment. Adaptive capacity can be thought of as the inverse of social vulnerability – a community with high adaptive capacity will have low levels of social vulnerability to climate change and vice versa.

The indicators chosen to express the adaptive capacity of rural human settlements in this assessment are as follows: population age profile, annual household income, employment status of household head, gender of head of households, access to basic services, tenure status, type of dwelling, HIV prevalence, % agriculture GDP and dominant crop areas. These indicators are explained and further discussed below.

For the purposes of simplicity in building the model of vulnerability, our approach has been to model lack of adaptation capacity, or social vulnerability. This means that areas that we have given high scores to areas that score low in the indicators for adaptive capacity – so an area with poor delivery of basic services scores high as being socially vulnerable to climate changes risks.

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5.1. Population age profile

The population of South Africa refers to all the inhabitants of the country and the age profile of the country refers to the average ages of the population. In July of 2012 the population of South Africa stood at 48, 810, 427. Census data shows that 28.4% of the population is between the ages of 0 and 14 years and 21% of the population is between the ages of 15 and 24 years; rendering the population of South Africa extremely young. A further 38% of the population is between the ages of 25 and 54 years of age. 7% of the population is between the ages of 55 and 64 years of age and 6% of the population is 65 years or older. The median age of the South African population is 25 years (Indexmundi 2013).

It is estimated that climate change will affect individuals within different population groups in different ways. Certain individuals within populations are more vulnerable to climate change as these groups include the sick, the elderly, children, native groups and groups who receive a low income. The reasons for this are that children and the elderly are more susceptible to illness and the stress which climate change will place on already difficult living conditions will make these groups even more so. As the temperatures in South Africa continue to rise, children and elderly populations will become vulnerable to severe heat stress. The expected decline in food security as agricultural productivity drops will lead to increased malnutrition which will have a contributing effect towards other diseases. Climate change and the increase in temperature, lack of water and decreased quality of water may encourage the spread of infectious diseases such as Gastro-enteritis. Areas which will become prone to flooding may attract mosquitoes and therefore the possibility for an increase in malaria cases may arise. Rural populations which live in close proximity with the environment, and often in rudimentary rural dwellings are more vulnerable from the increase in health related risks. These populations also often live far from sources of health care of the health care available in rural areas is substandard (EPA 2013).

A population which has a high proportion of individuals that are of a working/adult age therefore shows a stronger adaptive capacity than populations which have high levels of individuals who are children or elderly. Populations that have a high proportion of individuals that are of a working age will also be able to work to increase the resilience of their communities through planting food and climate proofing their dwellings. In this assessment, scores were assigned to municipal wards with high numbers of children and older people, or low numbers of young people compared to the national average and using the following classes: 0-14: child, 15-39: young, 40+: older. These scores are shown in the map below.

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Source: calculated from Statistics South Africa Census 2011 data

5.2. Income

The annual household income refers to the total amount of money that each household in South Africa earns per year. This income can be derived from formal or informal employment and constitutes any activity which a member of the household undertakes and that is rewarded in monetary terms.

The Income and Expenditure survey of 2010/2011 shows that household income expenditure and expenditure in South Africa is on the rise and according to the survey the average household consumption expenditure increased by 69,5% from the last survey. However, income and expenditure levels remain significantly varied across population groups with black households earning the least (StatsSA 2012). Households with a higher income are less susceptible to poverty and the multiple stressors that contribute to climate change vulnerability. Although poverty is not synonymous with climate change vulnerability, it is a major driver of climate vulnerability. It can therefore be deemed that households with higher annual incomes have a higher adaptive capacity than households with lower annual incomes. In this assessment scores were assigned to wards with high percentages of poor households and low percentages of high-income households compared to the national average. The following classes were used: low: 0 - R38 200, medium: R38 201 - R153 800, high: >R 153 800. 22 shows the resultant income scores by municipal ward – low scores indicate fewer low-income households and more high-income households.

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Source: Calculated from Statistics SA Census 2011 data

5.3. Employment

Employment status of the head of the household refers to whether the head of the household is employed, unemployed, a discouraged work seeker, in another form economically inactive or under the age of 15 years of age (in other words a child headed household). In South Africa the household is generally understood to be a dwelling with people who eat together and share resources and who stay in that dwelling for the majority of the time. The general understanding of the household head is the person who either owns or is in control of the property on which the dwelling sits, is the primary income provider within the household unit and has the decision making power on income and resource use and distribution (StatsSA 2013).

Because of the consensus that the head of the household has decision making power within the dwelling and specifically over the distribution of resources within the dwelling; it is deemed here that employment status of the head of the household is a valuable contributing factor towards adaptive capacity since the difference between employment and non-employment means a substantial difference in the availability of resources for climate change adaptation. In South Africa, the rounded off figures show that 42.26% of household heads are employed, that 11% of household heads are unemployed, that 5% of household heads are classified as discouraged work seekers, that 42% of household heads are not economically active in some way and that 0.3% of the household heads are below the age of 15 years of age (StatsSA, 2012). In this study, scores were assigned to wards with low percentages of employed people or high percentages of discouraged work-seekers, economically in active household heads, or child-headed households. The map below shows the resultant scores used in the model for each municipal ward.

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5.4. Gender

Gender inequalities exist in South Africa and these inequalities are often more severe in the rural area. In South Africa women already experience multiple stressors; such as unpaid work, child rearing, and insufficient access to basic services. Because climate change is expected to make already existing development challenges worse; households which are not represented by a male head may become more vulnerable in uncertain climatic periods. It is therefore assumed that households which are represented by a male figure will have a higher adaptive capacity. Furthermore, men may contribute toward the food security of the household in being able to contribute towards food production, are more likely to receive a higher wage in paid employment, may be more likely to find employment and could be able to contribute towards the climate proofing of settlements.

Municipal wards with the percentage female-headed households greater than two thirds of the national average scored on this indicator.

Map 21: Municipal wards where the proportion of female-headed households is greater than two thirds of the national average

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5.5. Access to basic services

This indicator uses access to basic water, electricity and sanitation services as a proxy for infrastructure in the GIS model. Many people remain marginalized from access to services such as piped water, electricity, basic sanitation, housing and roads. Communities with good infrastructure are more resilient and therefore less vulnerable to climate change. Therefore municipal wards with low levels of access to basic services compared to the national average score higher on this indicator.

Many rural households in South Africa are not connected to the electricity grid and therefore rely on other sources of energy such as wood, gas, dung, or paraffin. Having a reliable source of energy within dwellings is an important component of pulling people out of the deprivation trap. Access to energy within the household for lighting, cooking and heating is especially beneficial for women as they are most often charged with sourcing energy; which is unpaid work, and takes up energy and time which could be devoted elsewhere in activities such as food production. Households which have access to reliable energy sources such as gas, electricity, or solar will have a higher adaptive capacity than households which do not. Moreover, households which are reliant on wood as a primary energy source will contribute to the land degradation and the subsequent loss of land productivity through the cutting down of trees. Statistics from StatsSA show that the percentage of households connected to the main electricity grid has increased from 76,8% in 2002 to 82,7% in 2011. This increase in the connectivity of household to the electricity grid has meant a notable reduction in the number of households that rely on wood and paraffin as an energy source, especially in the Eastern Cape and Limpopo provinces (StatsSA, 2011).

Another basic service which may communities across South Africa are marginalized from is refuse removal. The removal of refuse refers to the removal of solid waste from close proximity of human dwellings and is mandated to local municipalities. Not only is the collection of solid waste a climate change hazard because of the methane that is released from waste during the anaerobic process of decomposition; but the build-up of waste near human settlements also presents serious threats to human health and safety. Waste, for example, can encourage the development of infectious diseases and can also encourage fires to break out.

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An abundance of waste in the close proximity of human settlements therefore poses a threat to the adaptive capacity of communities whilst adequate waste removal boosts the adaptive capacity of human settlements. South Africa has witnessed an increase in the number of households that have their refuse removed weekly by a local authority, and this increase has been from 52% in 1996 to 62% in 2011. Statistics from StatsSA also show that the number of households that rely on a communal refuse dump decreased from 2,2% in 2007 to 1,9% in 2011. The number of households that had no access to refuse removal whatsoever also decreased significantly from 9,7% to 5,4% with these results being taken from the 1996 and the 2011 Census respectively (StatsSA 2011).

Many households in South Africa are further marginalized from the access to a close supply of piped water. Not only does this result in household activities being centred on the collection of water (which is often a strenuous and timely task); but also means that households may rely on unsustainable and unclean water resources. The unsustainable use of water could feed into future climate vulnerability as it will contribute to the reduction of available water resources. The use of unclean water can lead to the spread of disease which will further lower the adaptive capacity of households. Settlements which have access to a water supply within the dwelling or in close proximity of the dwelling are therefore deemed to have a higher adaptive capacity.

There is great regional disparity in South Africa in terms of access to piped water supplies. Despite the fact that 89,5% of the country has access to piped water, these statistics were not reflected in rural provinces such as the Eastern Cape. The situation in the Eastern Cape has improved by around 10%, but still much work is required. South Africans nationwide have also become increasingly dissatisfied with the quality of the water that they are receiving in their households, with only 62, 1 % of the country being satisfied with the water which they are receiving (StatsSA 2012).

In South Africa the number of households with no access to toilets or which make use of bucket toilets has decreased from 12,6% in 2002 to 5,7% in 2011. The lack of access to toilets is most severely felt in the Eastern Cape, Limpopo and the Northern Cape provinces. StatsSA measures access to sanitation in the following categories; access to flush toilets which are connected to the sewage system, access to flush toilets with a septic tank, access to a chemical toilet, access to a pit toilet with ventilation, access to a pit toilet without ventilation, access to a bucket toilet and other types of toilets (StatsSA 2012). Improved sanitation is vital in protecting the health of communities and safeguarding communities from infectious diseases of which the incidence will increase as the climate continues to change in South Africa. Households that have access to adequate sanitation are therefore deemed to have a higher adaptive capacity than households which do not.

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Map 22: Combined score for access to basic services

5.6. Land Tenure status

Land Tenure refers to the conditions under which land or buildings are being occupied. StatsSA provides the following categories by which to measure tenure status: rented, owned but not yet paid off, occupied free of rent and other.

The linkages between climate change and land tenure are complicated and remain unclear. However, it is clear that the impacts of climate change will be felt through changes in natural ecosystems and the productivity of land. These changes will have detrimental effects for human settlements. Strengthening land tenure arrangements is a key feature then in building resilience to climate change especially for changing livelihood demands. Overall, securing land tenure rights over land and natural resources is a critical feature of building adaptive capacity (Quan & Dyer 2008). .

Broadly, four categories of land tenure exist in South Africa. Around 70% of the country is under freehold tenure (privately owned) and compromises commercial farming land. A further 14% of the land is allocated to communal areas with leasehold tenure, 10% of the land is conservation area and the remaining 6% of the land is used for mining, industrialization and urban development. Communal areas are mainly found in the former homelands of the Transkei, Ciskei, Bophutatswana, Kwa-Zulu, Lebowa, Venda and Gazankulu (Palmer & Ainslee 2013).

Communal land tenure is embedded within a range of social relationships which often means that the access of households to land is insecure. This is because the rights to land are determined by the societies normative values rather than by law. It is generally understood that households in the communal areas of South Africa land is distributed by the traditional authority, and that the land often does not correspond with the household need. Furthermore, the traditional authority has the right to take the land away from households and allocate it elsewhere. This insecure access to land creates vulnerability towards climate

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change. Also since the land is communally rather than privately owned there is little incentive to sustain the land for future increased productivity. It is therefore understood in this assessment that secure land tenure such as land ownership increases adaptive capacity while insecure land tenure decreases adaptive capacity (Kingwill 2003).

Communities with low levels of ownership compared to the national average scored higher on this indicator.

Map 23: Scores for tenure status

5.7. Type of dwelling

Type of dwelling refers to the type of structure in which people live. StatsSA defines dwelling by the following categories: house or brick/concrete block structure on a separate stand or yard or on a farm, traditional dwelling/hut/structure made of traditional materials, flat or apartment in a block of flats, cluster house in complex, townhouse (semi-detached house in a complex), semi-detached house, house/flat/room in backyard, informal dwelling (shack in backyard), informal dwelling (shack; not in backyard; e.g. in an informal/squatter settlement or on a farm, room/flatlet on a property or larger dwelling/servants quarters/granny flat, caravan/tent and other.

In the face of climate change it is necessary that housing is able to meet the demands of a changing environment and provide adequate shelter and safety for its inhabitants. Generally South Africa can expect a rise in temperature, a change in precipitation patterns and more severe weather events. Dwellings that are able to cope with these changes have a higher adaptive capacity than those that do not. Buildings which have a high adaptive capacity may include some of the following features: the incorporation protection against flooding and storms, efficient water systems for drought protection, making cool spaces available in the dwelling for protection against extreme heat, heat reflective surfaces and damp proofing to avoid places which are hospitable towards mosquitoes. Furthermore houses should be strategically placed to avoid flood plains and green spaces.

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There is no way in which dwelling types can be observed across South Africa since dissimilar dwelling types are usually located within one location. Therefore this assessment looked for areas with large proportions of informal dwellings as an indicator of a lower adaptive capacity.

Map 24: Municipal wards with a large proportion of informal dwellings

5.8. HIV prevalence

In South Africa the estimates prevalence of HIV in the population is 10,6%, amounting to approximately 5,38 million people living with HIV. In terms of the adult population which is from 15-49 years old, 16,6% of the population is infected with HIV. In 2011, it was estimated that 316 900 new infections occurred within the adult population (StatsSA 2011).

The impacts of HIV and climate change are perceived to be profoundly linked. Living with HIV and its associated illnesses is a major cause of vulnerability and to poverty in general. This is because the disease marginalizes individuals from communities, impedes their capacity for employment and decreases their ability to fulfil their basic needs. Further, families caring with for patients with HIV are made vulnerable through the required costs and time constraints. Communities therefore with a lower prevalence of HIV have a higher adaptive capacity than communities with a higher rate of HIV amongst the population. Women are especially vulnerable to the linkages between HIV and climate change; and the investments of education, health services and family planning services is likely to have a huge impact in building the resilience of women and subsequently children to climate change (UNAIDS).

The map below shows the HIV prevalence in 2011 by district municipality. These values were assigned to the municipal wards and scores assigned based on whether the prevalence in a municipal ward was above, more or less equal to, or greater than the national average.

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Map 25: HIV prevalence per district municipality, 2011

Source: Department of Health

5.9. Dependence on Agriculture

The agricultural GDP refers to the Gross Domestic Product of agriculture in South Africa and thus the total value of agriculture within the country’s borders in monetary terms over a specific time period.

In 2010, agriculture formed 2.48 % of the country’s total GDP. In this percentage agriculture includes: forestry, hunting, fishing and the cultivation of crops and livestock (Trading Economics 2012). Regions of the country that are large contributors towards this agricultural GDP will experience a diminishing productive capacity in the future and therefore will be more vulnerable to climate change. Areas which, on the other hand, have diverse sources of income, will be more able to adapt to the ill effects of climate change. The map below shows areas in which agriculture contributes towards a large percentage of the country’s economy.