North West

This page provides a summary of key provincial climate change issues and links to district level climate change information. Click on the links on the right for more information on each of the District Municipalities in the Province.

Climate Change Strategy

The North West province is in the process of developing an integrated climate change strategy adressing both mitigation and adaptation.

Provincial Overview

The North West Province is the fourth smallest province in South Africa, covering an area of 102,881 km2. It lies at the centre of the Northern border of South Africa and shares a border with neighbouring Botswana. The Province is known for its rich natural resources, which include minerals such as platinum and chromium, as well as its rich wildlife and has a comparative advantage over the other provinces in the mining and agriculture sectors. The North West is also home to a number of internationally recognised fossils found at a number of different sites. The capital of North West is Mahikeng (formerly known as Mafikeng) (North West Provincial Department: Department, Rural, Environment and Agricultural Development, 2015).

The North West Province is made up of four municipalities as shown in the Figure 1 below: Dr Ruth Segomotsi Mompati, Ngaka Modiri Molema, Bojanala Platinum, and Dr Kenneth Kaunda. Based on the 2011 Census, the North West’s total population is 3,509,953, with 65% of the population is accommodated in rural areas. The climate in the province varies considerably with the areas in the east being much wetter than those in the west. The province is dominated by a flat savanna and grassland landscape, which is home to rich biodiversity and agriculture, with hills and ridges dividing up this landscape. Some of the more iconic of these include the Magaliesberg and Pilanesberg ridges, and the Vredefort Dome. The Kalahari Desert lies to the west of the province (North West Provincial Department: Department, Rural, Environment and Agricultural Development, 2015).

Figure: North West province and its municipalities

Greenhouse Gas Data

Electricity Sales

There are a range of sources of Greenhouse Gas (GHG) emissions at the provincial and district level. One of the main sources of GHGs is from electricity. Although the GHGs associated with the generation of electricity is recorded at a national level, provinces and municipalities typically record the GHGs associated with the sale of electricity.  The map below is a summary of the GHGs from the sale of electricity in the province. This data is sourced from Stats SA for the provinces and divided into district data by the proportion of houshold numbers in the district.

Figure: Total electricity sales (GgCO2e) in North West

Liquid Fuel Sales

A second major source of GHGs is from the sale of liquid fuels. This includes jet fuel, aviation gasoline, diesel, furnace oil, LPG, paraffin and petrol. The map below is a summary of the GHGs from the sale of liquid fuels in the province. Each fuel is converted to Gigagram Carbon Dioxide equivalent (GgCO2e) using specific emission factors from the Intergovernmental Panel on Climate Change Emission Factor Database. 

Figure: Total liquid fuel sales (GgCO2e) in North West

Key Climate Hazards

Increasing temperatures

The figure below shows projected changes in annual average temperatures, highlighting increasing temperatures throughout the province for the period 2021-2050 under the RCP 8.5 scenario. By 2050, the province 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 North West 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 province between 2021-2050 under the RCP 8.5 scenario. Annual average rainfall amounts vary across the province. There is uncertainty regarding projected future rainfall.

Figure: Projected changes in annual average rainfall throughout North West 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 province 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 province.

Figure: Projected changes in the annual average number of extreme rainfall days throughout North West 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 North West (SANParks 2011a)
Figure: The predicted shift in biomes in North West using a high-risk scenario (SANParks 2011b)

Climate Change Vulnerability

The CSIR Greenbook has 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 province visually.

Figure: Socio-economic vulnerability per local municipality in North West (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 province visually.

Figure: Environmental vulnerability per local municipality in North West (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 province visually.

Figure: Physical vulnerability per local municipality in North West (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 province visually.

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

References