Foresight for Sustainable Water Futures in Sub-Saharan Africa: A Systematic Review

Abstract

The provision of clean and potable water and sanitation services remains a critical challenge in Sub-Saharan Africa (SSA). This is exacerbated by climate change, an ever-increasing population, urbanisation, industrialisation, and an increase in water demand, not least for agriculture. A sustainable water future requires more strategic planning and improved decision-making processes. To accomplish this, foresight plays a critical role. Foresight is the ability to study a system and its challenges, anticipate possible future trends, and make informed decisions that foster more desired futures. This paper presents a systematic review of the literature on the strategies or methodologies of foresight utilised to enhance decision-making and future planning for ensuring equitable and sustainable access to clean water in SSA amidst uncertainty and the evolving landscape of economic, social, and environmental challenges. The findings indicate that foresight research in most countries in SSA is in its early stages, is narrowly focused, uses foresight tools or approaches in isolation, and employs siloed approaches for overall decision-making. A transdisciplinary systems approach is recommended to support improved decision-making within sustainable water futures planning.

1. Introduction

The management of water resources is complex and fraught with risks and uncertainties. This is further amplified by increases in population and urbanisation, as well as the consequences of climate change. Traditionally, decisions on water resource management (WRM) are made based on historical trends of water abstraction, as well as on precipitation and run-off records and patterns [1]. However, due to complexities and the acceleration of unpredictable and unprecedented change, and the fact that the conditions that prevail today will not continue to prevail in the future [2], there is a need for a systems analysis approach that incorporates strategic foresight. Strategic foresight is a structured process for exploring alternative future states [3]. As opposed to historical precedence, which restricts thinking, foresight encourages imagination and the exploration of futures in uncharted territories [4]. By incorporating foresight and planning strategically, preparation for an uncertain water future can be embraced with flexibility and pluralism [2].

Foresight is defined as a process of exploring possible futures and their implications, identifying and avoiding challenges, envisioning desired futures, and identifying actions that promote the desired futures [4]. Over the years, foresight as a subject area has evolved, with several foresight tools and methodologies being developed by many organisations for exploring and planning for the future (see [3] for comprehensive information and a list of foresight tools and methodologies).

Foresight tools/approaches can be either quantitative (i.e., use simulation and modelling techniques) or qualitative (i.e., provide narratives of possible future pathways), and each approach comes both with its advantages and limitations [5]. As such, and in most cases, qualitative and quantitative approaches are combined for robust futures decision-making.

In the management of environmental issues, horizon scanning and scenario planning have been identified as the most common foresight tools used [4]. Horizon scanning is an approach for collecting and organising information and identifying and understanding emerging challenges and opportunities for policy and society [6]. On the other hand, scenarios involve the capacity to think creatively about the environment, economy, and society, envisioning future pathways and consequences, and the readiness to act upon this new knowledge in the face of uncertainty to make critical decisions [7]. Scenarios are not predictions and, therefore, should not be considered in terms of probability (i.e., the likelihood of occurring or not) [8]. Scenarios can be exploratory (divergent) or normative (convergent) [9]. Exploratory scenarios entail the creation of a range of plausible futures to understand how the different futures will play out, what will be the drivers of this change at play, and what will be the likely effects. In contrast, normative scenarios entail the creation of a vision of the future and the actions to be taken to get to that desired future.

Furthermore, for both qualitative and quantitative approaches, there is a debate about whether the foresight process should be expert-driven (involving individuals or groups of experts) or participatory (involving several stakeholders) [4,5]. The involvement of several stakeholders is believed to build trust and buy-in, in addition to capturing diverse voices and dimensions in the building of scenarios [4]. However, there is also the challenge of balancing different and often conflicting views in the face of time and resource constraints [10]. Notwithstanding this challenge, in strategic policy and decision-making, the views, engagement, and involvement of stakeholders are essential for better outcomes [5].

In the context of water resource availability and management, several foresight initiatives have been developed at the global and national scale by a host of international organisations or agencies, governments, civil society organisations or NGOs, and think tanks and academia. For example, building on the first study of global water availability by Shiklomanov [11], the World Water Vision report by the World Water Commission was launched in 2000, describing four global scenarios for the future of water resources up to 2035 [12]. The scenarios included ‘Business-As-usual’—a continuation of the present policies and trends that will lead to crisis, ‘Technology, Economics and Private Sector’—a focus on technology and market forces approach leading to the poorest countries lagging behind, ‘Value and Lifestyle’—a focus on sustainable and equitable development leading to closing the ‘equity’ gap91, and the final scenario, the ‘World Water Vision’, a combination of key elements from of all three scenarios that leads to improved water security [13]. However, since its development, this final scenario has not come to fruition, and since this time, other initiatives have evolved, such as the Water Futures and Solutions, developed by the International Institute for Applied Systems Analysis in partnership with the United Nations Educational Scientific and Cultural Organization (UNESCO) [1]. The purpose of this initiative was the development of an adaptable, resilient and robust framework for guiding decision-makers in dealing with the challenges and solutions to sustainable water resource management (SWRM) and in achieving the Sustainable Development Goals (SDGs) [14,15].

However, at a more detailed level, considering scale is essential for ensuring relevance and maximising impact in scenario development and water futures planning [4]. Therefore, several regional or national foresight tools, frameworks, or initiatives have been developed for more robust and granular futures decision-making. Examples include the SCENES project (Water Scenarios for Europe and for Neighbouring States), which developed a set of exploratory scenarios of four plausible futures (i.e., Economy First, Policy Rules, Fortress Europe and Sustainability Eventually) to assess, analyse and plan for Europe’s freshwater futures up to 2050 [16]. Batisha [17] developed the DEEPEST (Demographic, Ecological, Environmental, Political, Economic, Social, and Technological) holistic framework using horizon scanning and drivers of change to explore water visions and promote the planning and development of sustainable water futures in the ‘Arabsphere’ (of which Sub-Saharan Africa does not form a significant part). Examples at the national scale include a foresight study conducted by Lienert et al. [18], who developed three scenarios for a sustainable water sector in Switzerland. Another example is the ‘water foresight project’ in Egypt, which aimed to assess the challenges and steps required for better integrating foresight thinking in national strategic planning processes [19]. However, there is limited research on foresight and futures approaches for sustainable water futures in developing countries that need it the most for strategic planning in meeting their developmental goals [20].

In Sub-Saharan Africa (SSA), the design, planning and management of water resources and infrastructure is already fraught with numerous challenges [21,22]. These include but are not limited to lack of institutional capacity, lack of robust regulation, lack of technology and human capacity, poor governance structures, financial constraints, and corruption, to name a few. This is exacerbated by the complexities and uncertainties of population increase, climate change, freshwater availability, and uncontrolled urbanisation. There is a need for strategic thinking and foresight as they plan for both an unforeseen and unpredictable future. This paper aims, by conducting a systematic review of the literature, to assess the foresight strategies or methodologies that have been employed to promote better decision-making and futures planning for equitable and sustainable access to potable water in Sub-Saharan Africa in the face of uncertainty and evolving social, economic, and environmental challenges.

2. Methodology

To address the aim of this research, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) proposed guidelines [23] were followed, see Supplementary Materials.

2.1. Eligibility Criteria

The eligibility criteria for the inclusion of records in the review adhered to the PCC (Population/Problem, Concept, Context) framework, which is a variant of the PICO (Population, Intervention, Comparison, Outcome) framework [24].

2.2. Search Strategy

The search strategy was designed around the PCC framework, ensuring a balance between sensitivity and specificity, as shown in

Table 1. Search terms for the literature review.

Item No	Description	Search Terms
1	Problem Sustainable Water	(Sustainab * OR resilien * OR smart) AND (water)
2	Context Sub-Saharan Africa	“Sub-Saharan Africa” OR “low-income countr *” OR “developing countr *” OR Africa OR Angola OR Benin OR Botswana OR “Burkina Faso” OR Burundi OR Cameroon OR “Cape Verde” OR Chad OR “Central African Republic” OR “Democratic Republic of Congo” OR “Republic of Congo” OR Congo OR “DRC” OR “Cote D’Ivoire” OR Eswatini OR Eritrea OR “Equatorial Guinea” OR Ethiopia OR Gabon OR “The Gambia” OR Gambia OR Ghana OR Guinea OR Kenya OR “Guinea Bissau” OR Lesotho OR Liberia OR Madagascar OR Malawi OR Mali OR Mauritania OR Mauritius OR Mozambique OR Namibia OR Niger OR Nigeria OR Rwanda OR “Sao Tome and Principe” OR Senegal OR Seychelles OR “South Africa” OR “Sierra Leone” OR Somalia OR “South Sudan” OR Sudan OR Swaziland OR Tanzania OR Togo OR Uganda OR Zambia OR Zimbabwe
3	Concept Foresight	Foresight OR forecast * OR future * OR scenario OR vision OR backcast * OR “horizon scan *” OR “black swan” OR “wild card” OR roadmap OR “worldview” OR Delphi OR pathway OR “Theory of change” OR “causal layered” OR predict * OR trend *

* Allows for truncation.

.

2.3. Information Sources

The search was conducted in four databases (Web of Science, Scopus, ProQuest and Compendex) on the 24th of October 2023. The search was restricted to ‘Title’ and ‘Keywords’ to ensure that only relevant records were returned. For Web of Science and Scopus databases, the title and keywords filters are available. However, according to the Scopus Search Guide, ‘Keywords’ was defined as a combined field that searches the ‘AuthorKeywords’, ‘Indexterms’, ‘TradeName’, and ‘ChemicalName’ fields. For ProQuest and Compendex, field codes or search codes were used, respectively, as keywords could not be filtered directly. For ProQuest, the field code ‘IF’ was used, which filters keywords or identifiers, and for Compendex, the search code ‘CV’ was used, which filters for controlled terms or subject areas. For both databases (ProQuest and Compendex), these filters were the closest to the keyword filter.

2.4. Results from Databases

The search results from the databases are shown in

Table 2. Search results from the 4 databases.

Item No	Description	Web of Science	Scopus	ProQuest	Compendex
4	T = 1	18,004	12,105	34,851	43,846
5	T = 2	933,499	656,326	5,846,146	61,077
6	T = 3	3,076,516	2,261,716	12,076,779	837,882
7	K = 1	12,536	64,088	10,560	71,883
8	K = 2	278,734	995,879	841,514	6192
9	K = 3	906,677	2,996,953	1,312,075	696,555
10	4 OR 7	27,246	69,215	42,923	88,719
11	5 OR 8	1,045,903	1,214,361	6,219,731	64,696
12	6 OR 9	3,588,422	4,273,212	12,996,663	1,195,561
13	10 AND 11 AND 12	86	417	87	76

T = title; K = keywords or equivalent.

, which is an extension of Table 1. No additional filters were applied.

A total of 666 results were returned. These records were downloaded into the Endnote 20 software, and 182 duplicates were removed. The next screening stage removed non-English records and records deemed irrelevant (datasets, unpublished records, newspapers, etc.). The titles, abstracts and keywords were then assessed for relevance to the research question and the inclusion of all three concepts as per the inclusion criteria in the search strategy. A total of 369 records were excluded at this stage. An additional 9 records were removed for which full documents were unavailable. The remaining 32 records were included in the review. Four additional records were identified through snowballing, which, even though they were not directly related to water, included foresight for handling environmental and socio-economic change in Sub-Saharan Africa and, therefore, were included in the review. A total of 36 records were taken forward and read in their entirety for the review. Figure 1 shows a flowchart of the record selection process.

3. Results

A summary of the results is shown in Table 3 prior to elaboration in a more detailed discussion in the subsequent sections of the paper. These include author and year of publication (Section 3.1), country/region considered (Section 3.2), main themes covered by the paper (Section 3.3), scale (Section 3.4), foresight approach, foresight tool or methodology (Section 3.5 and Section 4), and time horizon (Section 3.6).

3.1. Year of Publication

While foresight as a field of study is argued to have been around since 1945 [25], others believe studies that consider the concept of foresight as a science and differentiate it from forecasting started in the early 1980s [26,27]. One of the first studies on foresight in global water availability by Shiklomanov dates back to 1998 [11]. However, as per Figure 2, which shows the trend in publication year for research in foresight in SSA, the earliest record of foresight in SSA was published in 2005. Nonetheless, there has been some growth in interest and, therefore, the number of publications in more recent years.

3.2. Country/Region

Considering that some papers covered developing countries in general, including countries in SSA, while others were focused on one or more countries in SSA specifically, it was difficult to compare country-specific output. Therefore, a regional perspective was considered based on a counting system. In other words, papers focused on developing countries or SSA in general were counted in four regions (i.e., Western, Eastern, Central, and Southern Africa), and papers that were specific to a region were counted in that individual region. Figure 3 provides an overview of the number of publications per region. Eastern (26 papers) and Southern Africa (21 papers) had more publications than Central (12 papers) and Western Africa (14 Papers), with no specific publication from Central Africa and only Benin and Niger being specifically featured from Western Africa. Ethiopia and South Africa had the highest number of publications, with a total of 9 and 8 specific publications, respectively.

Table 3. Summary of results from papers reviewed.

Author	Year	Country/Region	Main Theme	Scale	Foresight Approach	Foresight Tool or Methodology	Time Horizon
Jenkins et al. [28]	2005	Kenya	Group A	Local	Exploratory, Quantitative, Participatory	WEAP model	NA (Not Applicable)
Bengtsson et al. [29]	2005	Developing countries	Group A	Continental	Normative, Qualitative, Expert-driven	Trend analysis	NA
Ochola et al. [30]	2006	Africa	Group A	Continental	Exploratory, Qualitative Quantitative, Expert-driven	PoleStar, T21	NA
Brumbelow and Georgakakos [31]	2007	Kenya, Tanzania, Uganda	Group B	Regional	Exploratory, Quantitative, Expert-driven	GCMs	NA
Christoph et al. [32]	2008	Benin	Group A	Local	Exploratory, Quantitative, Expert-driven	IPCC SRES and a combination of different GCMs	2025
Cullis et al. [33]	2011	South Africa	Group A	Local	Exploratory, Quantitative, Participatory	GCMs	2050
Cinderby et al. [34]	2011	Tanzania	Group B	National	Exploratory, Qualitative, Participatory	GIS	NA
Spies [35]	2011	SSA	Group A	Continental	Normative, Qualitative, Expert-driven	Development planning	NA
Claassen et al. [36]	2013	South Africa	Group A	National	Exploratory, Qualitative, Participatory	Scenario development	2025
Strzepek et al. [37]	2013	Developing countries	Group A	Global	Exploratory, Quantitative, Expert-driven	GCM/SRES model combinations	2030, 2050, and 2080
Mantel et al. [38]	2015	South Africa	Group A	National	Exploratory, Quantitative, Expert-driven	WEAP model	2065
Slaughter et al. [39]	2016	South Africa	Group A	National	Exploratory, Quantitative, Expert-driven	WEAP model	2065
Rodina et al. [40]	2017	Southern Africa	Group A	National	Normative, Qualitative, Participatory	Resilience	NA
Hirpa et al. [41]	2018	Kenya	Group A	Local	Exploratory, Quantitative, Expert-driven	GCMs and WEAP model	2030/2080
Kahil et al. [42]	2018	Africa	Area C	Continental	Exploratory, Quantitative, Expert-driven	ECHO model	2050
Kanyerere et al. [43]	2018	SSA	Group A	Continental	Normative, Qualitative, Expert-driven	IWRM	NA
Gedefaw et al. [44]	2019	Ethiopia	Groups A and B	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2030/2050
Miraji et al. [45]	2019	Tanzania	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2035
Bekele et al. [46]	2019	Ethiopia	Groups A and B	Local	Exploratory, Quantitative, Expert-driven	GCMs: HadGEM2-ES, HBV model	2050
van Puijenbroek et al. [47]	2019	Developing countries	Group D	Global	Exploratory, Quantitative, Expert-driven	Shared socio-economic pathways	2050
Hughes [48]	2019	SSA	Group A	Continental	Exploratory, Quantitative, Expert-driven	Pitman models	NA
Alemu and Dioha [49]	2020	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2030
Amoo et al. [50]	2020	South Africa	Group A	Local	Exploratory, Quantitative, Expert-driven	System dynamics allocation	30 years/2050
Fuente et al. [51]	2020	SSA	Group D	Continental	Exploratory, Quantitative, Expert-driven	Monte Carlo and regression analysis	2050
Tadese et al. [52]	2020	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	GCM: HadGEM2	2050 and 2070
Aberilla et al. [53]	2020	Developing countries	Group C	Global	Exploratory, Quantitative, Expert-driven	Foresight and life cycle assessment	2030
Kitessa et al. [54]	2021	Ethiopia	Group C	Local	Exploratory, Quantitative, Expert-driven	Regression model: WEKA	2030 and 2050
Naidoo et al. [55]	2021	Southern Africa	Group C	Regional	Normative, Qualitative, Expert-driven	Theory of change	NA
Remilekun et al. [56]	2021	South Africa	Groups A and B	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2100
Johansson [57]	2021	SSA	Group A	Continental	Exploratory, Qualitative, Participatory	Scenario development	NA
Hamza and Getahun [58]	2022	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2060
Bellwood-Howard et al. [59]	2022	Ethiopia/Tanzania/Niger	Group A	Regional	Exploratory, Qualitative, Participatory	Multicriteria mapping	NA
Eshete et al. [60]	2022	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	GCMS and SWAT model	2050 and 2080
Saketa [61]	2022	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2035
Simukonda et al. [62]	2022	Zambia	Group A	National	Exploratory, Qualitative Quantitative, Expert-driven	Scenario development	2035
van Puijenbroek et al. [63]	2023	Developing countries	Group D	Global	Exploratory, Quantitative, Expert-driven	Shared socio-economic pathways	NA

Table 3. Summary of results from papers reviewed.

Author	Year	Country/Region	Main Theme	Scale	Foresight Approach	Foresight Tool or Methodology	Time Horizon
Jenkins et al. [28]	2005	Kenya	Group A	Local	Exploratory, Quantitative, Participatory	WEAP model	NA (Not Applicable)
Bengtsson et al. [29]	2005	Developing countries	Group A	Continental	Normative, Qualitative, Expert-driven	Trend analysis	NA
Ochola et al. [30]	2006	Africa	Group A	Continental	Exploratory, Qualitative Quantitative, Expert-driven	PoleStar, T21	NA
Brumbelow and Georgakakos [31]	2007	Kenya, Tanzania, Uganda	Group B	Regional	Exploratory, Quantitative, Expert-driven	GCMs	NA
Christoph et al. [32]	2008	Benin	Group A	Local	Exploratory, Quantitative, Expert-driven	IPCC SRES and a combination of different GCMs	2025
Cullis et al. [33]	2011	South Africa	Group A	Local	Exploratory, Quantitative, Participatory	GCMs	2050
Cinderby et al. [34]	2011	Tanzania	Group B	National	Exploratory, Qualitative, Participatory	GIS	NA
Spies [35]	2011	SSA	Group A	Continental	Normative, Qualitative, Expert-driven	Development planning	NA
Claassen et al. [36]	2013	South Africa	Group A	National	Exploratory, Qualitative, Participatory	Scenario development	2025
Strzepek et al. [37]	2013	Developing countries	Group A	Global	Exploratory, Quantitative, Expert-driven	GCM/SRES model combinations	2030, 2050, and 2080
Mantel et al. [38]	2015	South Africa	Group A	National	Exploratory, Quantitative, Expert-driven	WEAP model	2065
Slaughter et al. [39]	2016	South Africa	Group A	National	Exploratory, Quantitative, Expert-driven	WEAP model	2065
Rodina et al. [40]	2017	Southern Africa	Group A	National	Normative, Qualitative, Participatory	Resilience	NA
Hirpa et al. [41]	2018	Kenya	Group A	Local	Exploratory, Quantitative, Expert-driven	GCMs and WEAP model	2030/2080
Kahil et al. [42]	2018	Africa	Area C	Continental	Exploratory, Quantitative, Expert-driven	ECHO model	2050
Kanyerere et al. [43]	2018	SSA	Group A	Continental	Normative, Qualitative, Expert-driven	IWRM	NA
Gedefaw et al. [44]	2019	Ethiopia	Groups A and B	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2030/2050
Miraji et al. [45]	2019	Tanzania	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2035
Bekele et al. [46]	2019	Ethiopia	Groups A and B	Local	Exploratory, Quantitative, Expert-driven	GCMs: HadGEM2-ES, HBV model	2050
van Puijenbroek et al. [47]	2019	Developing countries	Group D	Global	Exploratory, Quantitative, Expert-driven	Shared socio-economic pathways	2050
Hughes [48]	2019	SSA	Group A	Continental	Exploratory, Quantitative, Expert-driven	Pitman models	NA
Alemu and Dioha [49]	2020	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2030
Amoo et al. [50]	2020	South Africa	Group A	Local	Exploratory, Quantitative, Expert-driven	System dynamics allocation	30 years/2050
Fuente et al. [51]	2020	SSA	Group D	Continental	Exploratory, Quantitative, Expert-driven	Monte Carlo and regression analysis	2050
Tadese et al. [52]	2020	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	GCM: HadGEM2	2050 and 2070
Aberilla et al. [53]	2020	Developing countries	Group C	Global	Exploratory, Quantitative, Expert-driven	Foresight and life cycle assessment	2030
Kitessa et al. [54]	2021	Ethiopia	Group C	Local	Exploratory, Quantitative, Expert-driven	Regression model: WEKA	2030 and 2050
Naidoo et al. [55]	2021	Southern Africa	Group C	Regional	Normative, Qualitative, Expert-driven	Theory of change	NA
Remilekun et al. [56]	2021	South Africa	Groups A and B	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2100
Johansson [57]	2021	SSA	Group A	Continental	Exploratory, Qualitative, Participatory	Scenario development	NA
Hamza and Getahun [58]	2022	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2060
Bellwood-Howard et al. [59]	2022	Ethiopia/Tanzania/Niger	Group A	Regional	Exploratory, Qualitative, Participatory	Multicriteria mapping	NA
Eshete et al. [60]	2022	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	GCMS and SWAT model	2050 and 2080
Saketa [61]	2022	Ethiopia	Group A	Local	Exploratory, Quantitative, Expert-driven	WEAP model	2035
Simukonda et al. [62]	2022	Zambia	Group A	National	Exploratory, Qualitative Quantitative, Expert-driven	Scenario development	2035
van Puijenbroek et al. [63]	2023	Developing countries	Group D	Global	Exploratory, Quantitative, Expert-driven	Shared socio-economic pathways	NA

3.3. Themes

The records reviewed covered a broad range of themes:

• Water Resource Management (Group A);
• Water for Agriculture and Industry (Group B);
• Food–Water–Energy Nexus (Group C);
• Sanitation and Wastewater Management (Group D).

3.4. Scale

Of the 36 papers examined in the review, 15 explored foresight at a local scale, 8 at a continental scale, 6 at a national scale, 4 at a global scale, and 3 at a regional scale. Figure 4 provides a visual representation of this distribution.

3.5. Foresight Approach, Tools, and Methodologies

All 36 studies focused on some form of scenario development and planning, with the primary areas of focus covered in four main themes (discussed in Section 4.3, Section 4.4, Section 4.5 and Section 4.6). This is expected, given that scenario development is one of the primary methodologies utilised in foresight analysis. More than 75% of the studies employed some form of modelling and simulation for scenario planning and to inform decision-making. In as much as quantitative analysis provides objectivity and rigour, research has argued that they also come with limitations relating to oversimplification and the risk of misinterpretation, especially in cases where data are limited [31]. The specific modelling tools and techniques will be discussed in detail in Section 4. In addition to a greater number of studies being quantitative, more studies were exploratory rather than normative, seeking to understand risks and sustainable pathways for the future. This might be because developing countries, particularly in SSA, require flexible and adaptive approaches for future planning and decision-making to deal with the increase in risk and uncertainties. Out of 36 studies, only 7 studies employed a participatory approach to futures thinking and scenario development. The remaining 29 studies were expert-driven.

3.6. Time Horizon

The most common timeline considered was 2050 (11 studies), closely followed by 2030 with 6 studies. This is not unexpected, considering these dates coincide with the global targets for reduction in CO₂ emissions and for achieving the Sustainable Development Goals [8].

4. Discussion

In the context of foresight and scenario development for sustainable development, an array of methodologies and approaches have been developed to understand existing systems, contemplate a range of potential futures, and strategise actions conducive to achieving more desirable outcomes [8]. These methodologies can be qualitative in nature, as previously mentioned, focusing on a range of future trajectories influenced by critical driving forces, or quantitative, involving the extrapolation from historical trends [4]. Over the course of the evolution of futures studies, two primary approaches have emerged: normative, which revolves around envisioning a preferred future state, and exploratory, which involves considering a diverse array of potential future scenarios. Herein, there is ongoing debate regarding whether foresight endeavours should be expert-driven or participatory integrating insights from a range of stakeholders [3]. This section delves into the examination of these methodologies alongside an exploration of the key themes and concerns to water security in SSA as highlighted in the literature reviewed.

4.1. Driver of Change

The world as we know it is changing, and it is essential to understand the driving forces (e.g., Economic, Environmental, Social, Governance, Organisational, Political, or Technological) acting in isolation or combination to be able to make informed decisions for the future (see [20] for more details on drivers of change). The studies reviewed covered a host of specific drivers for sustainable water futures in SSA. These include rapid and increasing growth in population, increasing urbanisation, and general improvements in lifestyle, all of which put additional strain and demands on limited (and ageing) infrastructure, not least in terms of increased demand for potable water. This is exacerbated by climate change and its effects on temperature and the hydrological cycle, which in turn lead to the added risk and more likely occurrence of floods and droughts. In addition, environmental and land degradation, deforestation, and poor sanitation and wastewater management practices threaten the quality of water and health, especially in rural communities. Therefore, there is a need for robust, inclusive decision-making (i.e., involving the voices of all stakeholders) and the promotion of equity, resilience, sustainability, and the long-term security of water futures.

4.2. Approaches to Foresight Analysis

Several frameworks and tools have been developed to facilitate the process of thinking strategically about the future in terms of water. For example, Cook et al. [4] summarised their approach as including the following six-step process: Scoping, Scanning, Forecasting, Visioning, Planning, and Acting. Similar stepped approaches have been proposed by other researchers, including the 10-step process for futures thinking for the built environment by Ratcliffe and Sirr [7] and the 7-step foresight process developed by Destatte [64]. The shared characteristics among these processes are the application of diagnosis, prognosis, and prescription practices for understanding complex systems, identifying challenges and proposing solutions [65].

In this current review, most of the studies being applied in SSA failed to follow all these proposed steps. It is believed that this is because studies tried to simplify the process and delve deeply into one or two of the outlined steps rather than covering the whole process. The two steps mostly employed were ‘Forecasting’ and ‘Visioning’, which involved identifying signals and trends (with the use of statistical or modelling tools) and making sense of these inputs via scenario planning and analysis. While it is essential to explore individual steps in greater detail, it is equally important to maintain and not lose sight of the overall process.

4.2.1. Normative vs. Exploratory Techniques

Five out of the 36 studies [29,35,40,43,55] used normative approaches, while the rest used exploratory techniques for scenario analysis. For the normative approach, a desired future is described, along with actions to be taken to get to that future. For example, for a more resilient and just water future in Southern Africa, Rodina et al. [40] proposed a seven-step approach for practitioners and researchers based on consultation with key stakeholders. In the same light, Naidoo et al. [55] developed a ‘Theory of Change’ that both integrates and operationalises more sustainably the water–food–energy nexus in South Africa. For studies that employed an exploratory technique, several plausible futures were explored using scenarios. This is exemplified in the work undertaken by Claassen et al. [36], where four scenarios were developed using the ‘axes of uncertainty’ approach [8]. The driving forces were based on the ability of the South African water sector to deal with complexity in the face of decision-making and the sustainability issues in meeting the demands of present and future generations. The four scenarios developed were ‘Wise Tortoise’—in which the sector can deal with complexity in decision-making and is sensitive to issues of sustainability; ‘Busy Bee’—decision-making fails to deal with complexity, but there is a keen sensitivity to sustainability issues; ‘Ignorant Ostrich’—decision-making fails to deal with complexity, and there is insensitivity to sustainability issues; and ‘Greedy Jackal’—decision-making deals with complexity, but resources are exploited unsustainably.

Each technique has its challenges and opportunities, and the choice depends on the issue at hand and the level of uncertainty in decision-making [4]. For example, normative techniques are best suited for goal alignment, identifying potential risks and developing mitigation strategies. On the other hand, exploratory techniques have the advantage of flexibility and the opportunity to explore a range of possible futures and inspire creativity and adaptability [3]. However, it is not an either-or situation. In most cases, both approaches are used simultaneously to plan strategically for the future. For example, van Vliet and Kok [16] developed a methodology that combines backcasting and exploratory scenarios to face uncertain water futures, which was tested with the SCENES (Water Scenarios for Europe and Neighbouring States) project and saw positive results.

4.2.2. Expert-Driven vs. Participatory

A debate has always existed on whether foresight activities should be conducted by only experts (in this case, water experts) or if the views of several stakeholder groups should be included, and if the latter, how bias can be mitigated in the process [66]. However, over the years, there has been an increase in the use of participatory approaches in foresight analysis and visioning exercises [57]. Nonetheless, fewer than 20% of the reviewed studies used participatory approaches. This might be due to the challenges in the resource requirements, the complexity of subjectivity and managing diverse views, or issues with power structures [10]. Notwithstanding their challenges, participatory techniques introduce diversity of ideas, encourage knowledge sharing, and build consensus and trust [57]. An example of the application of a participatory approach is the study by Cullis et al. [33], in which stakeholder engagement via workshops was conducted to look at the effects of climate change on water resource planning in South Africa. After using several modelling tools and studying the future effects of climate change on temperature and the hydrologic cycle, it was concluded by the stakeholders that adaptation and demand management strategies were favoured over the development of new infrastructure (or the ‘ribbon-cutting’ culture).

The remaining studies were mostly expert-driven, relying on the specialised knowledge and judgement of experts alone. This participation style, traditionally referred to as the ‘design and defend’ approach, also comes with a range of advantages and disadvantages. For example, engaging all stakeholders fosters open dialogue and enhances trust and sustainability, but it can also be time-consuming and resource-intensive, and there is the need to balance varying and conflicting interests [67]. Regardless of the approach used, for a just and sustainable water future, it is recommended that power dynamics be considered [57] and an adaptive system integrated for managing uncertainties [10].

4.2.3. Qualitative vs. Quantitative

The reviewed studies employed both qualitative and quantitative approaches for foresight analysis. As shown in Table 3, eight studies used qualitative techniques, 26 used a quantitative approach, and two studies combined both qualitative and quantitative techniques. Qualitative approaches are generally in the form of narratives or storylines of possible futures, while quantitative approaches use modelling and numerical analysis to quantify the way the future might unfold [68]. Typically, both methods are combined when a more holistic and detailed picture is required, an approach commonly referred to as SAS (Story and Simulation) [13]. Global examples for exploring and combining both qualitative and quantitative water-related scenarios include the World Water Vision [12], the IPCC shared socio-economic pathway scenarios [69] and the Global Environmental Outlook [70]. The Africa Environment Outlook 2 report [30] and the study by Simukonda et al. [62] both employed a SAS approach for foresight analysis.

The Global Scenario Group (GSG) provides narratives of five possible futures (Market Forces, Policy Reform, Fortress World, New Sustainability Paradigm and Eco-Communalism) that have formed the basis for qualitative scenario development [71]. Simukonda et al. [62] developed four scenarios for water supply strategies in Zambia based on the GSG scenarios. Other approaches to scenario development include the identification of the major drivers and the use of the ‘axes of uncertainty’ approach [8], as seen in the study by Claassen et al. [36] for South Africa’s sustainable water future.

With reference to Table 3, more than 77% of the studies reviewed used some form of computational technique for scenario analysis. The Water Evaluation and Planning (WEAP) system is the most utilised, with nine studies using it for their analysis. Other tools used include the Shared Socio-economic Pathways (SSPs) and General Circulation Models to assess and explore future socio-economic conditions and the implications for greenhouse gas emissions and for simulating climate systems.

Table 4. Computational tools used for quantitative scenario development.

Tools	Developer	Application
ECHO	Extended Continental-scale Hydro-economic Optimisation—developed by the Water programme at the International Institute for Applied Science Analysis (IIASA)	ECHO is used for understanding the complex interactions in the management of water resources and for designing sustainable pathways under various socio-economic and climate futures [42]
GCMs	General Circulation Models—the first model was developed by Norman Philip, followed by several other models, with the Hadley Centre for Climate Prediction and Research’s HadCM3 being one of the most recent	GCMs are used for representing the physical processes of the atmosphere and ocean and for simulating and studying the Earth’s climate system [31]
IPCC SRES	Special Report on Emissions Scenarios by the Intergovernmental Panel on Climate Change	A set of scenarios to explore different future projections of greenhouse gas emissions, atmospheric concentrations, and their impact on climate change [32]
Pitmans	Developed by A. J. Pitman, University of Witwatersrand	A conceptual hydrological model used for simulating water flow through a catchment [48]
PoleStar System	Developed by the Stockholm Environment Institute	A system used for synthesising resource, economic, and environmental information and for developing and examining alternative scenarios [30]
SSPs	Shared Socio-economic Pathways—developed as part of the 5th assessment report of the Intergovernmental Panel on Climate Change	A set of five scenarios that describe potential pathways of future socio-economic development for use in climate change research [47]
WEAP	Water Evaluation and Planning—developed by the Stockholm Environment Institute	A forecasting tool for conducting integrated water resource planning assessments [49]
WEKA	Waikato Environment for Knowledge Analysis—developed at the University of Waikato in New Zealand	A set of machine learning tools and algorithms for data mining tasks [54]

describes the modelling tools used and their applications.

However, for scenarios to be meaningful, several societal, technological, physical, and ecological aspects of the system under investigation must be shown [32].

Across the studies reviewed, especially with those utilising quantitative techniques, greater emphasis was placed on numerical analysis, with comparatively less attention given to the development of scenario narratives. In addition, where quantitative modelling is employed, a substantial amount of data are required; in the absence of this, an inaccurate representation of the system in question is gained. Moreover, it can also be based on several assumptions, some of which may be flawed [31]. In other words, for a data-sparse region like SSA, models developed are predicated on numerous assumptions with uncertainty, which might skew results and the final modelling outcome. For example, one of the limitations in the study on sustainable water supply and demand in Addis Ababa, Ethiopia, was the uncertainty inherent in both socio-economic and demographic assumptions [49]. Therefore, it is not surprising that the authors highlighted discrepancies in the model when compared to similar research in the field. In a similar study on sustainable water futures in Kenya, the validity of the model trends remained doubtful, and there was evidence that climate change models inaccurately forecast an increase in rainfall patterns for eastern Africa [41]. Regardless of the technique used for scenario development, it is essential that for strategic foresight and robust decision-making, an adaptive approach is incorporated [4].

4.3. Water Resource Management

SSA is at a crossroads in its water resource development [35]. There is the option of allowing a dystopian future to ensue or the opportunity to incorporate robust foresight and planning strategies for empowering a more sustainable future [35]. Therefore, it is not surprising that much recent research focuses on tapping into these opportunities, particularly for meeting Sustainable Development Goals (SDGs) and for achieving a resilient water future for SSA. Out of the 36 studies reviewed, 27 focused on WRM with sub-themes including river/basin/catchment management, asset and utility management (demand, supply and infrastructure), and policies, governance, or institutions.

Most countries in SSA experience challenges with water shortages and rationing, issues with water quality, an increase in demand, and general increased risk in water security. This can be attributed to drivers including population increase, urbanisation, deforestation, climate change, and the competition between and among sectors [72]. The reviewed studies under this theme mostly used models to try to understand future water demand requirements under various scenarios. The two prevalent themes focused on examining the impacts of climate change on water resource planning [33,46,60] and assessing long-term drought risk in relation to evapotranspiration and water availability [73]. In more than 90% of the studies, the future scenarios saw an increase in unmet water demand except for a study on the Abbay River basin in Ethiopia, which, surprisingly, had most future demand requirements met [58]. This might be because a limitation of the study was that the impact of climate change was not considered in all analyses due to data unavailability. The importance of asset management and ensuring that existing infrastructure is maintained, as well as the development of new infrastructure, was highlighted in the literature. Moreover, it was stated that this should be on a needs basis and not just for the ‘ribbon cutting’ [29]. In addition, demand management practices must be an integral part of a sustainable water future for SSA [49] coupled with robust policies and governance [35,36,43]. Notwithstanding this, in most of the studies, the scenarios developed include the business-as-usual case with a handful of other ‘what if?’ hypotheses. However, the narratives created therein lacked a complete storyline, making the scenario meaningless [32,68]. In addition, several studies combined and/or downscaled alternative models [32,33,56] to generate future scenarios, which increases the assumptions made and the uncertainty while also (potentially) leading to the introduction of bias [74].

4.4. Water for Agriculture and Industry

The agriculture sector has traditionally contributed significantly to freshwater withdrawals. In SSA, especially in rural areas, agriculture relies greatly on rainfall, making them vulnerable to the effects of climate change, including anticipated shifts in precipitation patterns and temperatures [20]. This is exacerbated by the fact that the population is increasing, meaning food production needs to increase to meet growing demands. The studies in this review sought to understand the effects of climate change and climate uncertainty on crop water demand, crop yield, irrigation, and the general availability of water resources for agricultural purposes. In the studies featured in this review, all future scenarios highlighted that water demand for competing uses would be unmet and be made worse by seasonality [31,34,44,46]. Recommendations include, but are not limited to, an integrated water resource planning and management approach [56], drip irrigation/irrigation technology [31,34], rainwater harvesting [34], water recycling [56], and the development of water storage schemes [34], in addition to incorporating adaptation and mitigation strategies [56].

4.5. Water–Food–Energy Nexus

With the projected increase in the future population of SSA [75], there is a need for increased food production to meet the needs of the people. In addition, therein energy is seen to play an integral role, both in the production of food and in the treatment of water. Understanding the interconnectedness between and among these sectors is essential for embracing resilience and meeting SDGs. There is a need to transition from siloed thinking to a transdisciplinary approach [76,77]. To address some of these challenges, Aberilla et al. [53] proposed a ‘synergen’ approach that simultaneously assesses the life cycle sustainability of water, cooking heat, and electricity supply to remote communities, both for now and in the future, considering various scenarios. Desalination and bioenergy were identified as sustainable sources for remote communities. However, these options are capital-intensive, and due to a lack of technology, policies, and expertise, local communities are less attractive to secure investment for such projects [53]. Some of the challenges highlighted in the literature for a practical and sustainable water–energy–food nexus integration include insufficient relevant data, lack of tools and technology, lack of funds, and the general lack of knowledge and expertise [78]. In a similar light, Naidoo et al. [55] developed a theory of change for operationalising the water–energy–food nexus as a means to better understand the linkages between and among the said resources and recommended dialogue among stakeholders and the design of cost-effective policies to foster the attainment of SDGs. In other cases, researchers have used modelling and simulation approaches to integrate the management of these resources [42]. Nonetheless, the practical application of the transdisciplinary nature of the nexus is lacking, especially in SSA [55], with some researchers questioning the whole concept of an integrated approach to managing multiple resources [79].

4.6. Sanitation and Wastewater Management

The availability and supply of clean potable water is one of the major challenges of the world today. This is particularly a challenge in SSA, where millions of people face significant sanitation, health and environmental challenges due to water pollution and scarcity [80]. With wastewater treatment still at its early stages of development in most countries across SSA, there is a need for research that inspires transformative action. However, in this current review, only three studies were centred around sanitation and wastewater treatment. Fuente et al. [51] used modelling and simulation to estimate WASH (Water Sanitation and Hygiene) related mortality and the economic losses related to poor access to sanitation and water infrastructure in SSA from 1990 to 2050. From their simulations, it was observed that WASH-related mortality varies vastly across countries in SSA. Countries in SSA were placed in four groups, with Groups 1 and 2 representing countries with high WASH mortality and, according to simulated trajectories, will not see a reduction in mortality rates if current patterns persist. Groups 3 and 4 represent countries with moderate to low mortality rates, and it is suggested that these will decline in some cases to negligible levels in the simulated period. However, a large proportion of the population of SSA live in countries in Groups 1 and 2, with only a small percentage living in the other two groups. For countries in Groups 1 and 2, it was recommended that WASH-related investment should remain a priority and require a sustained and long-term commitment. It was also shown that Groups 1 and 2 countries were mostly in Western Africa.

Similar trends were observed in the study by van Puijenbroek et al. [47] on wastewater nutrient discharge from households into surface water bodies. Considering income level indicated by protein consumption, access to sewage systems, and the presence of wastewater treatment facilities along with their efficiency in nutrient removal, scenarios were constructed using the five Shared Socio-economic Pathways (SSPs) spanning 1970 to 2050. The results indicate that for SSA, an increase in population and a reduction in water quality will require adequate wastewater treatment for nutrient removal. Primarily, the simulations show that for all developing countries, SDG 6.3 (wastewater treated safely by 2030) will merely be achieved in 2050 only under SSP scenarios 1, 2, and 5.

5. Conclusions

The world is changing, and humans cannot continue to do things the way they used to and expect different results. In addition, the world is now so connected that what is done in one area has adverse consequences in other regions and afar. In addition to existing challenges of water security in Sub-Saharan Africa, the projected exponential increase in population, urbanisation, and economic development is expected to put considerable pressure on limited resources and infrastructure, which is compounded by climate change and its consequences. There is a need for decision-makers to think strategically and creatively about the future and plan accordingly for a more desirable outcome.

This review paper has investigated research on foresight strategies or methodologies that have been employed to promote better decision-making and futures planning for equitable and sustainable access to potable water in Sub-Saharan Africa in the face of uncertainty and evolving social, economic, and environmental challenges. It has been shown that foresight research in SSA is in its early stages of popularity, and therein, countries are at different stages in the provision of water and sanitation services. The studies reviewed lacked inter-, multi-, or trans-disciplinarity, were expert-driven, and were adaptation-focused. Most of the studies were narrowly focused, utilising foresight tools or approaches in isolation and as part of siloed approaches for decision-making. In addition, the critical challenges in the water sector in SSA have not been addressed adequately within the reviewed studies. The challenges in the provision of water and sanitation services in SSA are not only limited to challenges with climate change and its effects on resources. Other challenges, including asset and infrastructure management, institutions and governance, and the general lack of expertise and technology, were not sufficiently addressed. To address these challenges, a transdisciplinary systems approach is recommended for futures planning and decision-making. This involves the integration and collaboration of multiple disciplines to address challenging issues in a holistic and comprehensive manner for the co-creation of knowledge and solutions. There is also the need for a paradigm shift towards comprehensive foresight techniques that integrate multiple methodologies, capacity building for foresight application and understanding the role of technological innovations.

That said, it should be noted that the PRISMA guidelines adopted by the researcher recommend utilising several reviewers or a group of stakeholders in conducting a systematic review. One of the limitations of this study is that the inclusion and exclusion criteria and screening of data, in this case, were conducted by a single researcher as part of a PhD research project. In addition, the review was limited to reports in the English language alone, and therefore, this might have incorporated a level of bias. However, only one non-English record was removed in this study. Lastly, the search was restricted to title and keywords only, and this means that there is the possibility that some records relating to the research concepts might have been overlooked.