Low-cost houses make up the majority of the homes in townships (racially segregated areas which are usually underdeveloped) in South Africa and there has been limited research on the indoor temperatures experienced by residents of these homes. As a developing nation the price and availability of construction materials, often takes precedence over the potential thermal efficiency of the house. Occupants of low-cost houses are particularly vulnerable to climatic changes which may increase the likelihood of exposure to extreme temperatures in South Africa. This study focused on the relationship between indoor and ambient temperature in two study areas namely; Kathorus in Gauteng and Wakkerstroom in Mpumalanga. Three housing types were included in the study (government funded apartheid era houses, government funded post-apartheid houses and informal houses (shacks)). Temperature data loggers were installed in each home, in each area, from June 2017 to July 2018. Ambient temperature data were collected for the period June 2017 to July 2018. The houses studied were built with different materials which affect their thermal efficiency. The study also included semi-structured interviews where occupant’s perspectives on housing could be surveyed. Household temperatures in Kathorus and Wakkerstroom, both in the warmer and colder months fluctuated substantially throughout the day. There was an 8 °C, 9 °C and 14 °C fluctuations in daily indoor temperatures of apartheid-era, post-apartheid and shacks houses, and daily outdoor fluctuations of 5–15 °C, with higher fluctuations measured in Wakkerstroom. Generally, ambient and indoor temperatures were correlated but showed high variability. Indoor data for the winter months were less well correlated. Data showed that residents are subjected to extreme temperatures and these are expected to increase. The householder’s perceptions of thermal comfort were often not related to indoor temperature readings but to behavioural changes including the use of warm clothes and wood burning stoves. The study’s findings suggest that a majority of low-cost houses are thermally inefficient especially for those built in the post-apartheid era and shacks. With these houses showing a clear link between ambient and indoor temperature fluctuations. The occupants of these homes are poor and vulnerable to health risks which could be exacerbated by temperature fluctuations. Small changes such as installation of ceilings and use of insulation could make a large difference in these houses.

The reconnaissance drought index (RDI) for the Setsoto municipality of the Free State province in South Africa was calculated for the period between 1985 and 2019 at 3 month (October–December), 6 month (October–March), and 12 month (October–September) intervals. Rainfall and minimum and maximum temperature data from four weather stations (Clocolan, Ficksburg, Marquard, and Senekal) were used for this study to characterize drought using “DrinC” software together with the Mann Kendall test with Sen’s slope to detect drought trends and the rate of change. Extreme, severe, and moderate droughts were recorded for all the stations, with RDIs ranging from −3.6 to −1.0 at different temporal scales. The years 1991, 1994, 2006, 2011, and 2015 were highlighted using the RDI 3, 6, and 12 month calculations. Results showed that the yield decreased either in the year of the drought or in the subsequent year, due to the exact timing of the low-rainfall events in the season and soil moisture storage. Yields were low, on average 2.5 tons ha⁻¹ year⁻¹, with high variability. Optimal growing conditions are essential in the early part of the season, October–December, for maximizing yield; if droughts are experienced at this time then the yield is more greatly impacted than if the droughts occur later in the season. Spatial analysis shows a large variability of drought patterns across the Municipality, over the years, with the 3 month RDI values giving a more detailed picture of this variability than the 6 and 12 month RDI values.

Understanding the interactions of the social and biophysical drivers of land degradation is crucial for developing adaptive management actions for future sustainability. A research-praxis project, the ‘Tsitsa Project’ (TP), applies a social-ecological systems (SES) approach where researchers, natural resource managers, and residents collaborate to support sustainable livelihoods and improved natural resource management for the degraded Tsitsa River Catchment (TRC) in South Africa. A system diagramming approach was coupled with findings from interviews, workshops, literature, and two conceptual frameworks. Data inputs were qualitatively integrated to provide a systemic snapshot of how the context-specific social and biophysical drivers are interlinked and how they interact, revealing multiple processes that operate simultaneously to cause and exacerbate land degradation. Physical and climatic variables, changes in land use and cover, and overgrazing were identified as key factors leading to degradation. Additionally, poverty and disempowerment were also important. While little can be done to influence the physical aspects (steep topography and duplex soils) and climatic variables (extreme rainfall and drought), carefully planned changes in land use and management could produce dual-benefits for improving landscape conditions and sustainable livelihoods. This analysis will inform integrated planning processes to monitor, avoid, reduce and reverse land degradation.

The majority of people in South Africa eat maize, which is grown as a rain-fed crop in the summer rainfall areas of the country, as their staple food. The country is usually food secure except in drought years, which are expected to increase in severity and frequency. This study investigated the impacts of rainfall and minimum and maximum temperatures on maize yield in the Setsoto municipality of the Free State province of South Africa from 1985 to 2016. The variation of the agroclimatic variables, including the Palmer stress diversity index (PSDI), was investigated over the growing period (Oct–Apr) which varied across the four target stations (Clocolan, Senekal, Marquard and Ficksburg). The highest coefficients of variance (CV) recorded for the minimum and maximum temperatures and rainfall were 16.2%, 6.2% and 29% during the growing period. Non-parametric Mann Kendal and Sen’s slope estimator were used for the trend analysis. The result showed significant positive trends in minimum temperature across the stations except for Clocolan where a negative trend of 0.2 to 0.12 °C year⁻¹ was observed. The maximum temperature increased significantly across all the stations by 0.04–0.05 °C year⁻¹ during the growing period. The temperature effects were most noticeable in the months of November and February when leaf initiation and kernel filling occur, respectively. The changes in rainfall were significant only in Ficksburg in the month of January with a value of 2.34 mm year⁻¹. Nevertheless, the rainfall showed a strong positive correlation with yield (r 0.46, p = < 0.05). The overall variation in maize production is explained by the contribution of the agroclimatic parameters; the minimum temperature (R² 0.13–0.152), maximum temperature (R² 0.214–0.432) and rainfall (R² 0.17–0.473) for the growing period across the stations during the study period. The PSDI showed dry years and wet years but with most of the years recording close to normal rainfall. An increase in both the minimum and maximum temperatures over time will have a negative impact on crop yield.

Exploratory modelling of the impact of gold mining on groundwater in a strategic water area of South Africa was undertaken. A systems dynamics (SD) model was developed to simulate the impact of gold mining on water quality, focusing on groundwater contamination risk, within the context of competing developmental priorities around water resource development and the socio-economic gains from gold mining. The model also identified interventions to minimise the impacts by the year 2040. The study area was the Blyde River Catchment (BRC), which is part of the Olifants Water Management Area in South Africa. This area is an important contributor, currently and in the future, to freshwater flows and groundwater in the Olifants River Catchment, which is one of South Africa’s most economically important catchments. The model development process included a causal loop diagram­–based problem conceptualisation, followed by the drawing of stock-flow diagrams and the determining of model parameters based on a combination of background literature, data from environmental impact assessments, and from the national Department of Water and Sanitation. The model showed the potential environmental risks of gold mine wastewater production and interventions to minimise these risks. The most effective intervention identified to reduce the risk of groundwater contamination was the development and use of synthetic-lined tailings dams. The baseline simulation result of sulphate loading of 5430 t/year can be reduced by 3070 t/year to give a simulated sulphate load of 2270 t/year in 2040 using this intervention. In comparison, the simulated wastewater recycling intervention only reduced the sulphate load to 4630 t/year and the wastewater treatment interventions to 3420 t/year. This project contributes to the exploratory modelling of an understudied region of the Olifants River Catchment that is a crucial provider of freshwater flows to the Olifants, which is threatened by increasing gold mining in the upper BRC. The SD model highlighted the importance of protecting the dolomitic aquifers in the BRC for the long term sustainability of the catchment, which is particularly important if groundwater development occurs.