Mpumalanga
Mpumalanga
Climate Change Information System
Climate Change Information System
Embedded Files
The Mpumalanga Climate Change Information System offers a series of decision support tools to inform policy and decision-making including a database of adaptation and mitigation actions undertaken by stakeholders across the province.
The Mpumalanga Climate Change Information System offers a series of decision support tools to inform policy and decision-making including a database of adaptation and mitigation actions undertaken by stakeholders across the province.
This is an online database of climate change adaptation and mitigation interventions. Please add information on past, current, and future climate change response efforts in Mpumalanga province.
Climate Change Services and Data
Climate Change Services and Data
Understand the implications of climate change in the province, explore climate data and climate change projections, and recent changes in land cover and carbon sinks.
Mpumamalanga Policy and Legislation
Mpumamalanga Policy and Legislation
Search and view a collection of documents relevant to planning and climate change response in Mpumalanga including Spatial Development Framework and Integrated Development Plans.
Mpumalanga Geospatial Data
Mpumalanga Geospatial Data
The conformal-cubic atmospheric model (CCAM) was used as the regional climate model, a variable-resolution globalclimate model (GCM) developed by the Common-wealth Scientific and Industrial Research Organisation (CSIRO) was used, Six GCM simulations of the Coupled Model Intercomparison Project Phase Five (CMIP5) and Assessment Report Five (AR5) of the Intergovernmental Panel on Climate Change (IPCC) for the emission scenarios described by Representative Concentration Pathway 8.5 (RCP 8.5) were used at a 8 km resolution. Future climate projections obtained at the 10th, 50th and 90th percentile.
The conformal-cubic atmospheric model (CCAM) was used as the regional climate model, a variable-resolution globalclimate model (GCM) developed by the Common-wealth Scientific and Industrial Research Organisation (CSIRO) was used, Six GCM simulations of the Coupled Model Intercomparison Project Phase Five (CMIP5) and Assessment Report Five (AR5) of the Intergovernmental Panel on Climate Change (IPCC) for the emission scenarios described by Representative Concentration Pathway 8.5 (RCP 8.5) were used at a 8 km resolution. Future climate projections obtained at the 10th, 50th and 90th percentile.
Metrics Available include:
Metrics Available include:
Agricultural drought as indicated by the consecutive dry days (cdd) index
Flooding as indicated by the consecutive wet days (cwd) index
Diurnal temperature range (dtr)
Number of precipitation days > 20mm (r20mm)
Maximum 5day precipitation > 5mm (rx5day)
Monthly maximum of daily min temperature (tnx)
Monthly maximum of daily man temperature (txx)
Carbon Sinks Atlas Data
Carbon Sinks Atlas Data
The 2020 National Terrestrial Carbon Sinks Assessment (NTCSA 2020) updates and improves on the original 2014 NTCSA (NTCSA 2014). in two important ways. Firstly, it is uses updated and improved datasets on which the assessment is based, and secondly it runs the assessment for three time periods, 1990, 2014 and 2018 allowing for the assessment of rates of change over these periods.
The 2020 National Terrestrial Carbon Sinks Assessment (NTCSA 2020) updates and improves on the original 2014 NTCSA (NTCSA 2014). in two important ways. Firstly, it is uses updated and improved datasets on which the assessment is based, and secondly it runs the assessment for three time periods, 1990, 2014 and 2018 allowing for the assessment of rates of change over these periods.
The terrestrial environmental carbon stock can be divided into carbon pools to aid with the estimation and reporting of terrestrial carbon stocks. The NTCSA2020 uses the same carbon pool breakdown as used in NTCSA 2014: i.e. Above Ground (AGW) and Below Ground (BGW) Woody biomass carbon, Above Ground (AGH) and Below Ground (BGH) Herbaceous biomass carbon, Litter biomass carbon as well as Soil Organic Carbon (SOC).
The terrestrial environmental carbon stock can be divided into carbon pools to aid with the estimation and reporting of terrestrial carbon stocks. The NTCSA2020 uses the same carbon pool breakdown as used in NTCSA 2014: i.e. Above Ground (AGW) and Below Ground (BGW) Woody biomass carbon, Above Ground (AGH) and Below Ground (BGH) Herbaceous biomass carbon, Litter biomass carbon as well as Soil Organic Carbon (SOC).
Extreme Rainfall Metrics
Extreme Rainfall Metrics
A total of 60 weather stations were used for the rainfall trend analysis spanning the period 1921-2015. An extreme rainfall trend analysis is also performed, based on rainfall extreme indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) (Wang and Feng, 2013). The base period, from which the annual index values of all indices are determined (except the annual maxima and minima) was selected as 1981 – 2010, which can be considered to be the present general norm for similar trend studies. The trends were tested for significance at the 95% confidence level.
A total of 60 weather stations were used for the rainfall trend analysis spanning the period 1921-2015. An extreme rainfall trend analysis is also performed, based on rainfall extreme indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) (Wang and Feng, 2013). The base period, from which the annual index values of all indices are determined (except the annual maxima and minima) was selected as 1981 – 2010, which can be considered to be the present general norm for similar trend studies. The trends were tested for significance at the 95% confidence level.
Food, Agriculture, and Water Sector Assessment
Food, Agriculture, and Water Sector Assessment
Food and agricultural sector vulnerability
Food and agricultural sector vulnerability
The Mpumalanga Province, which is the second smallest of the nine provinces in South Africa, contains almost half of the country's high potential arable land. The agricultural sector plays an essential role in stimulating economic development, supporting livelihoods, and securing food security for the people of Mpumalanga. Mpumalanga is one of South Africa’s most productive and important agricultural regions. Land utilized for commercial farming is about 90% of the total farmland whilst for small scale/emerging farming is less than 10%.
The Mpumalanga Province, which is the second smallest of the nine provinces in South Africa, contains almost half of the country's high potential arable land. The agricultural sector plays an essential role in stimulating economic development, supporting livelihoods, and securing food security for the people of Mpumalanga. Mpumalanga is one of South Africa’s most productive and important agricultural regions. Land utilized for commercial farming is about 90% of the total farmland whilst for small scale/emerging farming is less than 10%.
Water sector vulnerability
Water sector vulnerability
The Mpumalanga province depends mainly on surface water resources to fulfill its water requirements. Surface water, through rivers and dams contribute 65%, transfers from other sources to the province account for 19%, groundwater 6% and return flows from mining, industrial irrigation and urban settlements contribute 10% (SDF, 2019). Transfer schemes comprise Vaal, Olifants, and Usuthu linkages. The average rainfall for Mpumalanga is about 867 mm per year.
The Mpumalanga province depends mainly on surface water resources to fulfill its water requirements. Surface water, through rivers and dams contribute 65%, transfers from other sources to the province account for 19%, groundwater 6% and return flows from mining, industrial irrigation and urban settlements contribute 10% (SDF, 2019). Transfer schemes comprise Vaal, Olifants, and Usuthu linkages. The average rainfall for Mpumalanga is about 867 mm per year.
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