Understanding Socioeconomic Risk and Vulnerability to Climate Change–Induced Disasters: The Case of Informal Settlements in KwaZulu-Natal,South Africa

Abstract

This study employs a qualitative research approach to spatially delineate the risk and vulnerability of informal settlements in KwaZulu-Natal, South Africa. This comes after devastating floods that occurred in KwaZulu-Natal, South Africa, in April 2022. This disaster emphasised the necessity for South Africa to proactively address natural hazards by implementing risk reduction strategies rather than attempting to mitigate the impact after the damage has occurred. Evidence indicates that the risk and vulnerability associated with climate-induced disasters, such as flooding, are exacerbated by socioeconomic factors, including housing shortages, which compel individuals to construct dwellings in flood-prone areas. Opportunities exist to enhance the understanding of disaster risk reduction in Africa, and South Africa in particular, through science-informed initiatives employing spatial techniques, including geographic information systems, hazard exposure mapping, and socioeconomic risk and vulnerability mapping. These techniques are crucial for humanitarian planning focused on long-term risk reduction, early recovery, shelter, reconstruction, and psychosocial support for climate change disaster recovery. Furthermore, an understanding of the nature and location of areas with high disaster risk, such as flooding, is essential for the formulation of disaster risk reduction strategies, including early warning systems.

Introduction

South Africa is faced with a housing crisis, resulting in the proliferation of informal settlements in urban areas (Cinnamon and Noth, 2023). Informal settlements are residential areas that do not comply with local authority requirements for conventional (formal) townships. They are, typically, unauthorised and are invariably located upon land that has not been proclaimed for residential use (HDA, 2013). Also referred to as ‘shacks’, they are ‘structures which are made of rudimentary materials (wood, cardboard, metal sheets, mud, etc.) without any building plans approved, often on land that has been illegally occupied’ (HDA, 2013). These informal settlements are largely lacking in terms of proper roads, sanitation, and storm water drainage systems. Some are located on flood lines, wetlands, and in environmentally sensitive areas prone to landslides. In such settlements, services are very basic or not available at all. The number of informal settlements is expected to rise worldwide, particularly in developing countries, as a result of rapid urbanisation (World Bank, 2022), yet they remain unprioritised in planning, policymaking and development (Cinnamon and Noth, 2023). This renders such settlements vulnerable to climate-induced disasters such as flooding.

The city of eThekwini, in the KwaZulu-Natal (KZN) province of South Africa, is one such area that has been adversely affected by floods, with devastating effects on most of its sprawling informal settlements. A study of the city’s topography indicates that some of the vacant land in which informal settlements are encroaching falls under the 50- or 100-year flood lines (McDonald et al., 2004). Flood lines physically demarcate areas that could flood within a certain time interval. The time interval is computed on average qualification and could be 50 or 100 years. Living within areas demarcated as flood lines is not only illegal but also unsafe. These flood lines fall along river and stream floodplains. In eThekwini Municipality, informal settlements have also been built on slopes and low-lying areas, such as those in Prospecton, Isipingo, Sibongile, Ntuzuma and uMlazi, among others. Other informal settlements have been established along the coastline, placing the inhabitants at risk of the advancing sea line and high tides (Figure 1).

Figure 1.

Examples of (a) informal settlements built on a floodplain, (b) and (c) sloppy terrain and (d) along coastlines.

Informal settlements are part of urbanism and urban sprawl in developing countries their temporal and spatial characterisations, and the use of local knowledge systems in understanding their occurrence is highly fragmented. This is not only because of the rate at which they sprout, which, in some instances, is overnight, but also because data that is specific to their characteristics is scarce (Membele et al., 2022). Informal settlements remain as sites of hazard and risk mitigation for major health and environmental challenges, and are a depiction of ‘spatial inequality’ in the country (Strauss, 2019). It is against this background that this research aims to spatially characterise the socioeconomic risk exposure of vulnerable settlements to climate-induced disasters in eThekwini Municipality in KZN. This is important for the formulation of targeted policy interventions such as disaster risk reduction strategies and urban planning.

Literature review

Spatial inequality and informal settlements in South Africa

Some researchers argue that informal settlements are a result of spatial inequalities perpetuated by the apartheid ¹ legacy in South Africa (Hartnack and Liedeman, 2017; Turok et al., 2017). In the 1940s, the need for jobs in urban areas resulted in internal and international migration into urban areas in South Africa, resulting in widespread housing shortages (Hartnack and Liedeman, 2017). The government of the time responded by enacting a series of influx-control legislation, like the Black (Urban Areas) Consolidation Act 25 of 1945, together with the Regulations Concerning the Control and Supervision of Urban Black Residential Areas. ² These pieces of legislation, however, did not require the Minister to consider the adequacy, location or the quality of the housing spaces created in terms of the Act. The influx resulted in the uncontrolled proliferation of settlements close to places of work in urban and mining areas (Marutlulle, 2021). This resulted in a stark divide among the largely Black urban working class and other races whose demarcated residential areas were more formally controlled in terms of the provision of basic services and housing (Dovey and King, 2011; Turok et al., 2017).

Other researchers argue that better regulation is needed to eradicate such injustices, of which information settlements are a manifestation (Turok et al., 2017). Turok et al. (2017) point out that regulations meant to address inequalities tend to be ‘burdensome’ and not responsive to socioeconomic needs of the most vulnerable. There remains a spatial dislocation between formal and informal settlements and activities, rendering those living in high density, and particularly informal settlements, more vulnerable. Years after the abolition of apartheid policies, informal settlements dwellers still have poor adaptive capabilities to disasters (Turok et al., 2017). And still, a much larger portion of these informal settlements remains outside the fringes of city development, perpetuating their exposure to climate change–induced risks such as floods, mudslides and landslides (Brown-Luthango et al., 2017).

Natural disasters and risk mitigation

The negative effects of naturally disasters are intrinsically more pronounced in areas where vulnerable communities live (Brown-Luthango et al., 2017). The World Bank (2018) notes that natural disasters in South Africa, including floods, storms and droughts significantly affect people’s day-to-day activities, including their livelihoods, and at times cause significant loss to life and a disruption of agricultural activities. Studies reveal the vulnerability of farmers particularly in drought prone areas where livelihoods are further negatively affected by high food costs, decreased income households, and increased agricultural input costs, and recently, by recurring flood events (European Commission’s Directorate-General for European Civil Protection and Humanitarian Aid Operations (ECHO), 2022; Mthembu and Zwane, 2017; Vogel and Swilling, 2018).

In addition, literature suggests that vulnerability plays a major role in determining the impacts of climate-induced disasters. For instance, in South Africa, flood risks are a major concern especially in KwaZulu-Natal, Eastern Cape, Limpopo and North West provinces, which have been identified as the most vulnerable (Munyai et al., 2021). Lack of housing, one of the challenges facing government, compels poor people to building rudimentary housing on land not zoned for human settlements, such as slopy land and floodplains (Sguazzin and Siwele, 2022). As a result, the poor are the worst affected by natural disasters, as has been seen in similar communities in Mozambique, Zimbabwe and Malawi where cyclone Idai caused high casualties among the most vulnerable populations whose exposure to risk was exacerbated by poor residential structures in which they reside (Phiri et al., 2021). Besides housing issues, the socioeconomically disadvantaged communities also have limited access to information, thus increasing their risk exposure. Communication and early warning systems on impending disasters, and civic education on how to avert disaster risk, is often in forms that the poor have limited access to, such as radio, television and social media (Mavhura, 2020; World Weather Attribution, 2022). In addition, lack of climate knowledge by disaster risk officials and a lack of clear policy on averting and dealing with the adverse effects of climate-induced disasters worsen the situation. There is also failure to consider local and indigenous knowledge in disaster management by government officials. Poor infrastructure and lack of planning exacerbate the effects of climate change–induced disasters such as floods in vulnerable communities (Ngcamu, 2022).

Researchers, therefore, concede that communities be made aware of the adverse impacts of climate change, that locally available knowledge be enhanced and applied, and that clear policies be well-outlined to improve social inclusion in cases of disaster to address informal settlement issues well. These policies could be informed by empirical studies based on geographic data, spatial analysis, thematic mapping and remote sensing, and integrated with local knowledge systems where possible (Anwana and Owojori, 2023; Ngcamu, 2022; Pedzisai et al., 2023). In addition, more stringent disaster awareness measures considering the socioeconomic variations within the province have to be considered (Bopape et al., 2021).

The use of GIS in disaster risk management

Besides local knowledge systems used mainly by communities in South Africa and the global south in general, new technologies in predicting climate events have been used the world over in understanding and responding to climate change–induced disasters. This includes strides in artificial intelligence (AI), earth observation techniques such as remote sensing and geographic information systems (GIS) (Tomaszewski, 2015). GIS, remote sensing and earth observation are great contributors to researching, predicting, addressing preventing, reducing and managing catastrophic incidents such as floods, drought and frost (Manfré et al., 2012). These technologies also prove valuable in producing maps and analysis without the need for in situ observation (Hofmann et al., 2015). They also give urban planners and policy-makers information about land use changes over time, infrastructural and built-environment features and estimates of population and socioeconomic attributes (Liu et al., 2019). GIS also offer capabilities to comprehend the interplay between hazard exposure and social vulnerability, which is a crucial component of the hazard mitigation planning process. The modelling and simulation functionalities of GIS enable decision-makers to evaluate response and recovery strategies during non-emergency periods and assess near real-time scenarios during an ongoing event (Liu et al., 2019). It is, therefore, advisable for government officials to be trained and equipped with skills for using AI and digital tools such as GIS and remote sensing in preparing them for responding to climate-induced disasters (Abid et al., 2020; Mahmud et al., 2022).

Even though GIS and remote sensing studies have been conducted in South Africa, few delve into spatiotemporal effects of informal settlement invasion into high-risk environments such as floodplains. For example, Cinnamon and Noth (2023) used GIS to understand and spatially characterise informal settlements’ disaster risk exposure in Cape Town. The research involved identifying the locations and spatial distribution of informal settlements and conducting a land cover classification analysis and time series temporal change detection analysis to examine overall spatiotemporal patterns in the development of informal areas and to reveal periods of growth and decline in the proportion of built-up land within individual settlements. The study reported an increase in informal land use in Cape Town between 2000 and 2020, including land not zoned for settlements and environmentally sensitive areas. Other studies (e.g. Matarira et al., 2023) have used GIS tools such as the Google Earth Engine (GEE) platform to assess land use and landcover change (LULCC), which can be valuable in tracking real-time changes in informal settlement encroachments. GIS has also been used to explain the spatial injustice phenomenon, where residential segregation represents significant dimensions in the historical development of the settlement patterns of South Africa’s urban poor, which have strong links to colonialism and apartheid (Strauss, 2019). This underscores the efficacy of GIS in understanding disaster risk exposure of informal settlements and spatial inequality. These studies could be complemented by qualitative studies such as these, to give a quick overview of the effects of climate-induced disasters soon after their occurrence, particularly noting the time and scale at which informal settlements develop. In this study, choropleth mapping, rather than spatial analysis, is used to characterise informal settlements against risk vulnerability, using the overlay technique since a qualitative approach is adopted.

Theoretical framework

This study situates socioeconomic risk and vulnerability through the use of two indices: The Socioeconomic Risk Index (SERI) and the WorldRiskIndex (WRI). Both these indices have been used to understand risk exposure and complement spatial data such as that from GIS and remote sensing (Weller, 2023). The SERI marks the quality of life of an individual, considering indicators such as dwelling type, education, housing and mobility, which all determine individuals’ socioeconomic status. However, the WRI is a tool used to assess and estimate the disaster risk of a country. It takes into consideration both external and internal factors, such as threats by natural hazards such as cyclones, floods, droughts and sea level rise and societal conditions. These indices, therefore, complement each other in terms of understanding socioeconomic risk and vulnerability in our area of study.

The SERI, developed by the University of Manitoba in 2006, in particular, has a spatial bearing, and so in useful in South Africa with a strong divide in socioeconomic structure based on the social engineering of the country as a consequence of the apartheid legacy (Dlamini and Weir-Smith, 2022). The index also emphasises the spatial differences between high-density and low-density suburbs, as well as informal settlements within an environment, as these have differing dimensions of vulnerability. The WRI, developed, jointly by the United Nations University Institute for Environment and Human Security (UNU-EHS) and Bündnis Entwicklung Hilft and first published in 2011 (Birkmann and Welle, 2016), measures both internal (e.g. socioeconomic) and external (e.g. topographic) characteristics affecting risk vulnerability. The WRI is therefore akin and complementary to the SERI, and these indices are therefore both used to measure levels of inequality within communities in informal settlements in KZN because of their methodological similarities.

The WRI, in addition, synthesises various concepts of hazard, exposure, and vulnerability, which are the leading causes of disaster risk (Weller, 2023). The WRI and SERI note that risks depend not only on the occurrence, intensity, and duration of natural events but that socioeconomic factors also play a role in determining their effects on society. This means that theoretically, every society has the capability to develop coping mechanisms to address the effects of such disasters, and that their coping mechanisms determine the intensity of their effects (Weller, 2023). The framework is depicted in Figure 3.

The theoretical framework situates disaster risk in terms of external and internal risks. In the study area, external risk is determined by the location and nature of informal settlements, which renders communities more vulnerable to flood events, while internal factors are those relating to individual exposure (based on household and individual preconditions). This is explained in light of relevant literature in the next section.

Study area

The focus of the study is KwaZulu-Natal, the second largest province in South Africa (Figure 2). KZN is also the second most densely populated province in the country, with 131 people per square kilometre (Statistics South Africa (Stats SA), 2023). Black Africans comprise the bulk of the population at approximately 11 million, followed by Indians/Asians at 1.2 million, then Whites at 514,000 (Stats SA, 2022).

Figure 2.

The location in KwaZulu-Natal province, South Africa.

In terms of housing, the needs in the province have increased exponentially in the past few years as a result of rapid urbanisation. The State of South African Cities Report (2016) reports that 40% of global expansion is taking place in informal settlements, which seems to be the case with KZN. For instance, the province estimated a 75% increase in the number of people living in informal settlements between 2011 and 2016, placing the burden on planners to cater to the influx through the provision of more formal housing or the formalisation of informal settlements. In 2020, provincial estimates placed the number of households living in informal settlements at 400,000, housing approximately 700,000 to 1 million people.

In terms of climate, KZN has a varied climate due to its diverse topography. Inland KZN is generally colder than the coastline, which is subtropical in nature. The temperatures are higher on average between January and March (approximately 28°C max. 21°C min). This drops to 23°C maximum with a minimum of 11°C between June and August. The annual average rainfall is 1009 mm (measured in Durban) (South African Weather Service (SAWS), 2022).

Approach

A qualitative, descriptive approach is adopted in this study. The research uses the Socioeconomic Risk Index (SERI) data obtained from GeoTerraImage (GTI), GIS data on informal settlements obtained from the KZN Informal Settlement Programme (ISP) database and secondary data, such as that from Statistics South Africa. The GTI and ISP data are overlaid with publicly available GIS topographic data to depict areas of vulnerability. GTI periodically calculates the SERI for South Africa, with SERI values ranging from high – medium – low. Areas of high socioeconomic risk are those that are susceptible to environmental, household, and individual preconditions which place them at risk of poor health. SERI is linked to socioeconomic status (SES), with people of low SES being more vulnerable to risk and shock factors (Williams et al., 2019).

The informal settlement data, although not updated to 2023/2024, give an indication of the location and spread of informal settlements in the province. The database comprises a spreadsheet containing GIS data and data on the informal settlements (e.g. location, services, nature of land occupied) as well as proposed interventions and time frames for these interventions. The most recent dwelling count is based on 2007 aerial photographs. Choropleth maps are constructed using ArcGIS Pro to depict informal settlement location in relation to topography and risk exposure in terms of risk indices.

Results and discussion

Socioeconomic risk and vulnerability

Population vulnerability, according to the WRI, is determined by factors such as socioeconomic development, deprivation and societal disparities (Figure 3). The likelihood and extent of adverse effects are determined by vulnerability through susceptibility and ability to cope: whose effects are a function of exposure, sensitivity and adaptive capacity. Data pertaining to KZN indicate that informal settlements are more vulnerable to climate change–induced disasters as they are mostly built on land unsuitable for human habitation (Lefulebe et al., 2014; Williams et al., 2019). Census 2023 data, however, show a positive trend where there has been a decline in the number of people living in informal settlements. Census data rely on a proxy for the description of informal settlements based on dwelling type, namely those who live in an ‘informal dwelling/shack, not in backyard e.g. in an informal/squatter settlement’. Census data from 2011 also indicate that of those households in KwaZulu-Natal who lived in areas categorised as Informal Settlements then, 43% lived in shacks, not in backyards. A further 34% of households in these areas live in formal dwellings, 14% live in traditional dwellings and 7% live in shacks in backyards. Conversely, the data indicate that 35% of all households in KwaZulu-Natal who live in shacks, not in a backyard, do not live in EAs categorised as Informal Settlements. 17% live in EAs categorised as Urban Settlements, and 10% live in Tribal Settlement EAs. The adaptive capacities of these settlements are based on their SES (HDA, 2012). Conversely, Matarira et al. (2023), on a study of LULCC in eThekwini municipality, found that generally, the intensity of gain in informal settlements is higher than the loss.

Figure 3.

The theoretical framework adopted in the study.

GIS data and remote sensing images indicate that informal settlements were the most affected by floods that destroyed several settlements in the province in 2022 (JBA Risk Management, 2022). In addition, this information indicates that geographic location, physical condition, urban design, and management all play vital roles in the losses experienced in a region (JBA Risk Management, 2022). South African Weather Service (SAWS) (2022) data also reported on rainfall over four times the average amount for April in 2022. Media on the ground reported on poor infrastructure, urban sprawl and a lack of resources being responsible for the severe effects of the floods, with many of the homes affected being flimsily built and lacking adequate drainage systems, which means that they offer little protection from the elements (BBC, 2022). This relates to high-risk exposure as per the WRI, and societal exposure as per the SERI.

The United Nations International Strategy for Disaster Reduction (ISDR) (2007) notes that the magnitude and intensity of climate-induced natural disasters are largely determined by the socioeconomic status of households and the changing physical characteristics of areas they occupy (e.g. poor land use planning/building on unsuitable land, poorly managed urbanisation, changing demographic structures, natural resource dependency, etc). These factors can potentially increase a system’s exposure to the impact brought on by a hazard. The National Disaster Management Centre in South Africa also adopts this definition of vulnerability as outlined in the Disaster Management Act (16 of 2015). These factors referred to in this definition would normally include the characteristics of the built environment, a community or an individual (humans), as well as environmental, agricultural and economic elements that are exposed to natural hazards and risks. Therefore, as defined by the KZN ISP, informal settlements fall under those whose response to hazards and coping strategies are minimal, as they are of low SES (HDA, 2012).

Spatially characterising risk and vulnerability

Informal settlement data from the KZN ISP were overlaid with GTI SERI data to determine the risk exposure of informal settlements. The SERI ranges from 1 (very low socioeconomic vulnerability) to 5 (very high socioeconomic vulnerability). The maps below have been drawn to classify risk exposure from high, medium to low. Figure 4 shows that the majority of settlements in coastal areas fall under low SERI, for example, La Lucia, Umbilo, Manzimtoti and Umgababa, among others. These are affluent areas occupied by residents of relatively high SES. Other relatively low SERI areas are along the highway, the route that links KZN to other inland provinces such as Gauteng. While very few areas are of high SERI along the coast, Phoenix Beach has areas of high SERI (Figure 4).

Figure 4.

The socioeconomic risk index and informal settlements in KZN.

The inland areas of the province have a sizable portion of areas classified as medium to high SERI. This indicates that these areas are more vulnerable to shocks, such as climate-induced floods. Areas like Ndwedwe, Kwashange, Inanda, Kwdabeka and Mabagani, among others, fall under high levels of SERI, indicating their relatively higher risk of exposure to socioeconomic risk and climate change–induced shocks. Map overlays also indicate that high SERI areas such as Zwelitsha, Amawoti, Inanda and Inchanga, among others, also have high encroachments of informal settlements. Informal settlements are, however, seen to be encroaching to high SES areas such as Marianhill, Monclaire and Isiphingo, among others. This is a common occurrence in the province and the country in general, where urbanisation and immigration have resulted in housing shortages, and increased competition for land (Matarira et al., 2023).

Figure 5(a) to (d) depicts overlays between the SERI, informal settlements and rivers in selected areas within KZN. Figure 5(a) shows the informal settlement Sthumba, built in close proximity to the Mngeni River. Similarly, Figure 5(b) shows informal settlements such as Intake Road, Katshi and Progress Place, all built along river floodplains, as have informal settlements such as Lilian Ngoyi and Savanna Place (Figure 5(c)) and Lotus Park informal settlement (Figure 5(d)). Notably, Dakota Beach informal settlement (Figure 5(d)) is located right on the coast, and is an area of moderately high socioeconomic risk index.

Figure 5.

(a) to (d): The socioeconomic risk index, informal settlements and rivers in KZN.

Low socioeconomic status, combined with unfavourable living conditions such as building along floodplains, are exacerbated by communities’ lack of adaptive capacities when faced with disasters. Williams et al. (2019) used participatory mapping to understand coping and adaptive capacities in areas of high socioeconomic risk in eThekwini municipality. The WRI lists coping capabilities as societal shock, state and government, and health capabilities as components of exposure and vulnerability of a society. Communities of low SES and high SERI have relatively lower capabilities of building resilience in the face of climate-induced societal shocks such as floods (Williams et al., 2019). Informal settlements, largely built in areas not formally zoned for human settlement, are not well prepared for shocks, rendering them more vulnerable. State and government, however, need to have policies in place and the necessary funding to increase the coping capabilities of informal settlements. In South Africa, the Department of Human Settlements has embarked on a programme of formalising informal settlements, which is devolved to district and provincial levels, such as the ISP in KZN. In a similar vein, health capabilities are relatively low in areas of high SERI and low SES. The HDA, in its KwaZulu-Natal State of Informal Report (2012), stated that out of the 670 informal settlements in KwaZulu-Natal at that time, only one of them had a hospital.

In terms of adaptive capacities, the WRI lists education and research, health and dependency capabilities, and investment capacities as components of exposure and vulnerability. Various municipalities within the province have in place response plans, such as the Harry Gwala District Climate Change Vulnerability Assessment and Response Plan (Harry Gwala District Municipality, 2018), which recognises that ‘adaptation is regarded as inevitable and a necessary response to the changes that are projected to take place in the District’ (p. 7). Through research and the building of indicators, areas of high exposure and vulnerability are identified, indicating the province’s investment in mitigating the negative effects of climate change, such as floods.

Topographic risk and exposure

The KZN terrain renders the setting up of informal settlements risky, as it mainly comprises of undulating land and a high stream density. The main rivers in the province include Elands, Drakensberg, Umbilo, Umngeni, Amanzimtoti, Molteno, Elliot, Mzimkhulu, Pholela, Mkhomazana, Umkomaas, Nhlathimbe, Nzinga, Mooi, Bushmans, Tugela, Klip, Beaufort, Busi, Blood, Mkuze, Pongola, Mfolozi and Mhlathuze rivers, among others. Figure 6 shows the rivers and streams within the province. During the 2022 floods, several rivers, including the Amanzimtoti, Umbilo and Umgeni, overflowed, causing widespread damage to informal settlements and other riverside communities (Floodlist, 2022).

Figure 6.

Rivers and streams in KwaZulu-Natal.

Organisations such as Placemarks tracked the destruction caused by the 2022 floods, depicting how settlements built along floodplains were affected by the floods. The organisation noted that the most affected areas were townships and informal settlements often built in areas vacated by urban sprawl, on steep slopes, in the bed of rivers and streams or in other areas at risk. The image below is but one captured by Placemarks to indicate the effects of building on floodplains, and the effects of the floods. The image shows what happened in an informal settlement on the Mlazi River; where it is estimated that over 150 homes were destroyed during the 2022 floods (Figure 7).

Figure 7.

Image showing housing along the Umngeni floodplain, before and after flooding.

The growth of informal settlements into vulnerable topography is also confirmed by remote sensing studies, such as that by Matarira et al. (2023). The authors used the GEE to assess LULCC, and reported on the spatial growth of informal settlements with a total net gain of 3%. Intensity analysis results at the category level revealed that informal settlements were actively losing and gaining land area within the period, with yearly gain and loss intensity of 72% and 54%, correspondingly, compared to the uniform intensity of 26%. While the growth of informal settlements avoided water bodies during 2021–2022, there was an observed systematic transition process between informal settlements and other urban land (Matarira et al., 2023).

The Council for Scientific and industrial Research (CSIR) has developed an Environmental Risk Index that addresses the potential risks through effective planning and interventions that will reduce the vulnerabilities within settlements, and strengthen the ability of these settlements to cope with potential hazards. In addition, the importance of profiling vulnerability and proactively strengthening the resilience of cities and human settlements has been highlighted as an international priority (Sendai Framework for Disaster Risk Management 2015–2030, the New Urban Agenda and the Sustainable Development Goals) and national priority (South African Disaster Management Amendment Act, Act No. 16 of 2015, and the National Climate Change Response Policy of 2011). The CSIR Index is specific on physical vulnerability, which relates to the built environment, its fabric, and built structures (buildings and infrastructure) and focuses mainly on the conditions that exist before a hazard occurs (exposed elements and their characteristics) and the expected degree of loss which results from the occurrence of a hazard of a given magnitude. Environmental vulnerability, however, refers to vulnerability and risk to the natural environment and, in the case of settlements the impacts on the ecological infrastructure on which such settlements are dependent.

Therefore, the severity and impact of flooding is dependent not only on the topography or terrain of an area, but also on how communities are able to cope and adapt to the shock, based on their levels of susceptibility. The vulnerability of informal settlements in KZN in increased by their exposure to settling in land not zoned for human habitation, hence the high death rate in these areas during the 2022 floods (JBA Risk Management, 2022).

Recommendations of the study

This study highlights that vulnerable groups in high-risk areas, predominantly informal settlements, are found to be less prepared for disasters. Intense and frequent flooding due to climate change has caused significant damage in informal settlements, exacerbated by a lack of disaster preparedness. Spatial inequities, which are a legacy of apartheid, still persist, and new policies should be emphatic in reversing disparities in the country. To ensure that the effects of climate changed induced disasters such as flooding are minimised, policies should be developed based on, among others: (1) local government’s inability to prioritise climate change interventions; (2) municipal officials’ lack of knowledge regarding climate change; (3) lack of climate change knowledge and literacy among vulnerable communities, (4) the need for planners to consider local knowledge systems in disaster response planning and (5) taking into account nuanced socioeconomic and spatial variations in disaster planning and response strategies.

Practical steps could be taken in developing the above policy responses, and these could include, among others: (1) conducting holistic investigations by municipal planners and communities to assess risks, hazards, and effects of disasters in disaster prone areas; (2) developing, implementing, and enforcing by-laws to manage unplanned urbanisation and influence provincial and national governments to enact legislation to manage sporadic immigration that result in the growth of informal settlements; (3) benchmarking integrated knowledge management systems applied in other developing countries where communities have built houses in high-risk areas (floodplains, wetlands and hilly slopes), (4) prioritising in-person educational programmes on local climate knowledge, disaster prevention, preparedness, response, and recovery, involving planners and communities, (5) integrating GIS into disaster management programmes and (6) developing communication strategies that ensure the early warning systems reach the most vulnerable members of society.

Conclusion

This study has demonstrated the risk and vulnerability exposure of informal settlements in KwaZulu-Natal to climate-induced disasters such as floods. The floods that affected the province in 2022 exposed the vulnerability of informal settlements to climate change–induced shocks, and their lack of adaptive capabilities. Literature and reports pertaining to the floods indicate that most of the informal settlements in the province are built on topography not suitable for habitation, increasing their risk and vulnerability exposure. This is also demonstrated by data from the KZN ISP and GTI, which shows that these informal settlements are of high socioeconomic risk. These areas also have lower resources to respond to risk, since their low socioeconomic status also lowers their resilience.

The study adopted a qualitative research methodology to demonstrate the exposure of informal settlements to climate change–induced disasters such as floods, using choropleth maps. Results also show that internal (such as socioeconomic status) and external factors (such as physical location of settlements) play a significant role in determining exposure to climate change–induced disasters such as flooding. Indeed, our results show the juxtaposition of affluence and inequality in the province, which may further drive discontent among those of lower SES. The disastrous effects of the floods lead us to infer the unpreparedness of authorities for disaster events, their failure to understand and effectively respond to climate change events, and a disconnect between communities and city authorities in disaster risk mitigation and response. Moreover, there are opportunities to use techniques such as GIS in predicting, addressing preventing, reducing and managing such events. Therefore, the study recommendations focus on developing policies aimed at addressing structural inequalities and response strategies in the province through targeted legislation, policies and programmes to lessen the impacts of future flooding events in the province. Without these efforts, populations will become more vulnerable, less resilient, and more exposed to risk, resulting in greater social instability and protest. However, political will is required if such policies are to be formulated and implemented, as studies have shown the decades-long persistence of delayed response by authorities to issues affecting the poor, a phenomenon referred to as spatial injustice (Harrison, 1992; Strauss, 2019).

Our study has limitations which should be considered in interpreting the results, though. The KZN ISP data is dated 2012, and informal settlements, by their nature, are dynamic, and changes within a 10-year gap may be substantial and complex. Recent Stats SA data, for example, show a decrease in the number of informal settlements since the last census count in 2011, while a recent LULCC (Matarira et al., 2023) found an increase in the total amount of land occupied by informal settlements during 2021-2022. More recent informal settlement data is therefore required to get more nuanced results. In addition, as a result of data non-availability, the GIS analysis used in this study is descriptive and does not go into more detailed spatial analysis, such as buffering and distance analysis. This would provide more detail and enable modelling likely scenarios of informal settlement location and topography. Nevertheless, the study has managed to build a context of specific informal settlements in the area, and how this may relate to their risk exposure, vulnerability and resilience, which is required for policymaking and human settlement planning.