Thabo Mofutsanyana

Draft Climate Change Plan

The table below provides a list of drafted climate change plan documents that are available for download for the Thabo Mofutsanyana District Municipality.

File Name	Year	Size (MB)	Type	Download
Thabo Mofutsanyana District Municipality CC Presentation	2016	12,980	Power Point	<a href="https://docs.google.com/presentation/d/1MYkbKkN3O9FR1i8OjE6me6iuCRaWDnX5udKEIncjuyA/export/pptx" target="_blank">Download</a>
Thabo Mofutsanyana District Municipality CC Response Plan	2016	3,634	WORD	<a href="https://drive.google.com/uc?export=download&id=0B98u4HJRN5rrbjgyV1VPNkVwRUk&resourcekey=0-ZSTHwUFcamgVyp3SG_9URA&rtpof=true&sd=true" target="_blank">Download</a>

Key Climate Hazards

Increasing temperatures

The figure below shows projected changes in annual average temperatures, highlighting increasing temperatures throughout the district for the period 2021-2050 under the RCP 8.5 scenario. By 2050, the district is projected to be affected by higher annual average temperatures, which will adversely affect water and food security. Evaporation rates will also likely increase and agricultural outputs may reduce.

Figure: Projected changes in annual average temperatures throughout Thabo Mofutsanyana over the period 2021-2050 under the RCP 8.5 scenario (CSIR 2019)

Increasing rainfall variability

The figure below shows projected shifts in annual average rainfall throughout the district between 2021-2050 under the RCP 8.5 scenario. Annual average rainfall amounts vary across the district. There is uncertainty regarding projected future rainfall.

Figure: Projected changes in annual average rainfall throughout Thabo Mofutsanyana over the period 2021-2050 under the RCP 8.5 scenario (CSIR 2019)

Increasing storms and flooding events

The figure below shows projected changes in the annual average number of extreme rainfall days throughout the district over the period 2021-2050 under the RCP 8.5 scenario. Increases in the number of rainfall days are likely to result in an increase in intense storms, and flooding events across the district.

Figure: Projected changes in the annual average number of extreme rainfall days throughout Thabo Mofutsanyana over the period 2021-2050 under the RCP 8.5 scenario (CSIR 2019)

Changing Biomes

The current delineation of biomes is depicted in the figure below, with the predicted shift in biomes shown in the following figure based on a high-risk scenario. The biomes have varying sensitivities to the projected impacts of climate change which are further exacerbated by issues such as the fragmentation of natural areas and unsustainable water usage rates.

Figure: The current delineation of biomes in Thabo Mofutsanyana (SANParks 2011a)

Figure: The predicted shift in biomes in Thabo Mofutsanyana using a high-risk scenario (SANParks 2011b)

Climate Change Vulnerability

A climate change vulnerability assessment is a way of identifying and prioritising impacts from climate change. The IPCC defines vulnerability as:

"Vulnerability to climate change is the degree to which geophysical, biological and socio-economic systems are susceptible to, and unable to cope with, adverse impacts of climate change"

Summary of Climate Change Response Plan

A vulnerability assessment lets you identify these adverse impacts of climate change that are most important to your area. The climate change vulnerability assessment process that is used in this toolkit identified the following indicators in the table below.

Theme	Indicator Title	Exposure	Exposure Comment	Sensitivity	Sensitivity Comment	Adaptive Capacity	Adaptive Capacity Comment
Agriculture	Change in grain (maize, wheat & barley) production	Yes	Maize, wheat, soya, and dry beans.	High	Basic need as a staple food. Job creation and contributing to the GDP.	Low	Grain SA, Free State Agricultural Unit, FSDOA, VKB OVK, ARC. Research. Limited financial support.
Agriculture	Change in Sorghum production	Yes	More towards the western boundary. Sugar graze for cattle lead towards higher eastern area	High	Staple foods, Job creation, Contribute to GDP.	Low	Subject for further research. No research currently taking place. No institutional support. Financial support is minimal.
Agriculture	Change in Soya Bean Production	Yes	Soya beans are already used as rotation crop. There is also an opportunity for new soya production areas.	High	Can be used for crop rotation purposes and nitrogen content Contributes to GDP.	Low	Grain SA, Free State Agricultural Unit, FSDOA, VKB OVK. Use information from DPO.
Agriculture	Change in other crop production areas (e.g. vegetables, nuts, etc.)	Yes	Potatoes, vegetables, sunflowers, dry beans, wheat, maize, and asparagus.	High	Basic staple foods. Creation of Jobs. Tense agriculture. Phakisa Programme. Nine Point Plan.	Low	Not enough capacity, Department of Agriculture should capacitate small scale farmers on the significance of sunflowers. Groundnuts are highly adaptable but can also do well under irrigation. The supply of the crop is decreasing due to the decrease in the number of producers. Drought is the limiting factor. Farmers should shift from producing under rainfed to irrigated. Land third stage.
Agriculture	Increased exposure to pests such as eldana, chilo and codling moth	Yes	Cherry production, vegetables, apple production	High	Apples are extremely important because of the export market. Agricultural tourism (e.g. cherry festival). Job creation	Low	FSDOA, FSAU, VKB OVK. AVCASA - educating farmers Fertilizers, Farm Feeds, Agricultural Remedies and Stock Remedies Act, 1947 (Act 36 of 1947) Responsible use of pesticide. No funding.
Agriculture	Increased risks to livestock	Yes	Small stock like sheep, big stock such as cows and game production.	High	Source protein and income. Performing of rituals. Job creation. Contributes to GDP.	Low	Red Meat Producers Organisation, Milk Producers Organisation, Pig Industry, Chicken Industry, OVK, Nestle, Clover SA, NERPO, SAPPO, SAPA, MPO and RPO.
Biodiversity and Environment	Loss of High Priority Biomes	Yes	Grassland and wetlands.	High	The predictions show that the Grassland Biome is being taken over by the Savanna Biome. Wildlife and domestic animals, dependant on grassland, are going to be negatively impacted. The livelihoods of local people will be affected.	Low	DESTEA, DLA Research - we have capacity but our projects are not focused on climate change adaptation. Financial support - totally lacking overall. Institutional capacity - totally lacking in most entities. Donors have narrow interests (which suits them) and do not necessarily focus on climate change.
Water	Decreased quality of drinking water	Yes	Currently, dams do not have their original capacity, due to siltation, e.g. Waden Dam. Kolla, Tshueue. Disposing of nappies in the Montsha River, which runs through the Montsha wetland.	High	Most rivers are not fenced. By-laws comment. Most areas do not have disposal facilities, e.g. disposable nappies and general waste in rural areas.	Low	Start enforcing available policies and legislative prescripts. National Environmental Management Act, Expanded Public Works Programmes, Clarra, Integrated Waste Management Act.
Water	Decreased water quality in ecosystem due to floods and droughts	Yes	Lack of water quality in the District Municipal Area due to inadequate sewage plants and infrastructure.	High	Children contracting waterborne diseases, due to the use of contaminated water from system for secondary uses, e.g. bathing and washing.	Low	We have policies but still lack skilled personnel and an adequate budget for the ageing infrastructure. Local municipalities.
Water	Less water available for irrigation and drinking	Yes	Availability of dams. Old infrastructure. Lack of maintenance.	High	Farmers have water rights. Drought has crippled both ground and surface water supplies.	Low	Cooperation between DWS and Local Municipalities.
Water	Increased impacts of flooding from litter blocking storm water and sewer systems	Yes	Lack of maintenance. Old infrastructure. Communities in low lying areas.	High	Litter occurs in wetlands and stormwater drainage areas. Drought and overgrazing are leading to wetland degradation.	Low	EPWP Programmes, Local Municipalities.

The CSIR Greenbook has also developed and refined a vulnerability assessment framework by collating relevant data into composite vulnerability indicators. Four local municipality level vulnerability indices were computed and are shown spatially below.

Socio-Economic Vulnerability

Social inequalities are the factors that affect the susceptibility and coping mechanisms of communities and households. Indicators for social vulnerability attempt to consider the sensitivity, response and recovery from the impacts of natural hazards. The CSIR Green Book has developed a socio-economic vulnerability index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the Socio-Economic vulnerability score of each municipality in the district visually.

Figure: Socio-economic vulnerability per local municipality in Thabo Mofutsanyana (Le Roux, van Huyssteen, et al. 2019)

Environmental Vulnerability

Environmental vulnerability describes the vulnerability and risk to the natural environment and the impacts on the ecological infrastructure of which surrounding settlements are dependent. The environmental risk of an area includes ecosystems, habitats, physical and biological processes (reproduction, diversity, energy ﬂows, etc). The CSIR Green Book has developed an Environmental Vulnerability Index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the environmental vulnerability score of each municipality in the district visually.

Figure: Environmental vulnerability per local municipality in Thabo Mofutsanyana (Le Roux, van Huyssteen, et al. 2019)

Physical Vulnerability

Physical vulnerability describes the physical fabric and connectedness of settlements (buildings and infrastructure) and focuses mainly on the conditions that exist before a hazard occurs and the expected level of resulting loss. The CSIR Green Book has developed a physical vulnerability index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the physical vulnerability score of each municipality in the district visually.

Figure: Physical vulnerability per local municipality in Thabo Mofutsanyana (Le Roux, van Huyssteen, et al. 2019)

Economic Vulnerability

Economic vulnerability describes the potential risks posed by hazards on economic assets and processes. Potential hazards can include job losses, increased poverty and interruptions in business activities. The CSIR Green Book has developed an economic vulnerability index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the economic vulnerability score of each municipality in the district visually.

Figure: Economic vulnerability per local municipality in Thabo Mofutsanyana (Le Roux, van Huyssteen, et al. 2019)

References

CSIR. 2019. ‘Green Book | Adapting South African Settlements to Climate Change’. Green Book | Adapting South African Settlements to Climate Change. 2019. www.greenbook.co.za.
Le Roux, A, E van Huyssteen, K Arnold, and C Ludick. 2019. ‘The Vulnerabilities of South Africa’s Settlements’. Green Book. 2019. https://pta-gis-2-web1.csir.co.za/portal/apps/GBCascade/index.html?appid=280ff54e54c145a5a765f736ac5e68f8.
SANParks. 2011a. ‘CCAB - Current Biome Delineations 2011 [Vector Geospatial Dataset]’. Available from the Biodiversity GIS website. http://bgis.sanbi.org/SpatialDataset/Detail/484
SANParks. 2011b. ‘CCAB - High Risk Scenarios - Biome Delineations 2011 [Vector Geospatial Dataset]’. Available from the Biodiversity GIS website. http://bgis.sanbi.org/SpatialDataset/Detail/486.