Draft Climate Change Plan
|Sarah Baartman District Municipality CC Background Indicators Presentation||2018||12,980||Power Point||Download|
|Sarah Baartman District Municipality CC Response Plan||2017||12,716||WORD||Download|
|Sarah Baartman District Municipality CC Response Plan Presentation||2018||12,980||Power Point||Download|
Key Climate Hazards
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.
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.
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.
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.
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.
Adaptive Capacity Comment
|Agriculture||Reduced food security||Yes||All local municipalities in the District.||High||Even though census stats reveal that only 14.17% of households are involved and dependent on agriculture, this figure could have increased over the years.||Low||There is not enough education and awareness for subsistence farmers, thus, there is insufficient community capacity. Subsistence farmers lack the financial means also. |
DRDAR can formulate a policy for subsistence farmers.
Emerging farmers associations need to be capacitated.
|Biodiversity and Environment||Increased impacts on environment due to land-use change||Yes||Ndlambe, SBDM (urbanisation, soil erosion)||High||Lots of development has happened since 1990 e.g. urbanisation, industrialisation, RDP houses.|
Agricultural activities, wind farms (Kouga Area)
|Low||All Local Municipalities. |
Economic Development takes precedence over these natural resources. Thus current structure in the LMs and District are not effective.
|Biodiversity and Environment||Loss of Priority Wetlands and River ecosystems||Yes||Kouga (encroachment, sand river)|
Baviaans (wetlands went dry)
|High||Places that used to be wetlands in the past have been developed.||Low||DEAT|
|Human Health||Increased Occupational health problems||Yes||All Local Municipalities, private sector such as construction companies||High||Majority of municipal workers.|
Farm workers work outside.
To develop policy on working under severe conditions.
|Human Settlements, Infrastructure and Disaster Management||Increased risk of wildfires||Yes||Blue Crane, SRVM, Makana, Ndlambe, Kouga, Koukamma, Beyers Naude.||High||As a result of: fynbos, alien vegetation, plantations (forestry).||Low||Policies are available.|
Institutional support from District.
Lack of funding.
Community capacity is low.
Research in terms of past fires.
|Water||Decreased quality of drinking water||Yes||Makana and Dr Beyers Naude Local Municipalities.||High||Kouga, Camdeboo and Blue Crane Route score medium but all the other municipalities score low and therefore sensitivity is high.||Low||DWA, SBDM.|
Limited financial capacity to implement new technologies.
Research and standard for policy formulation.
|Water||Decreased water quality in ecosystem due to floods and droughts||Yes||All Local Municipalities||High||All municipalities perform poorly||Low||DWS, SBDM|
Research and policy.
Improved process and focus over short to medium term is required.
|Cross Cutting||Poor communication and awareness on climate change||Yes||All Local Municipalities, private sector, public sectors, NGOs, etc.||High||0||Low||Increase human resources (low HK), upgrade infrastructure, increase awareness campaigns / education.|
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.
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.
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.
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.
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.
- 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.