Climate Change Impacts on Water and Agriculture Sectors in Southern Africa: Threats and Opportunities for Sustainable Development

How does virtual water influence the water stress pattern in Africa? A research perspective from the perspectives of production and trade

Northern Africa has become the first region in the world to exhaust its water resources, with a 40 % decrease in per capita water availability south of the Sahara over the past decade. While adjusting production structures and consumption can regulate the supply-demand dynamics of water resources, the extent of the impact of virtual water-induced pressure on both the regional and national levels in Africa remains largely understudied. Applying the standard Penman formula, this research calculates the water footprint of eight cereal crops in 54 African countries from 1990 to 2021. By integrating corresponding data on cereal trade, the study analyzes changes in virtual water stress. The findings indicate a decline in the per-unit production and consumption water footprints for African cereals. However, the continuous expansion of cultivation areas contributes to a rising water stress. In comparison to 1990, the water stress for soybeans, sorghum, rice, maize, and cassava increased by 149.72 %, 146.88 %, 133.89 %, 123.30 %, and 90.8 %, respectively, in 2021. Only barley showed a reduction in water stress by 23.22 %. The study underscores the growing interconnectedness of virtual water trade (VWT) among African nations from 1990 to 2021, leading to a more balanced trade distribution. VWT has reduced water stress by 7.65 %, 2.08 %, and 1.8 % in Western, Central, and Northern Africa, respectively, while increasing pressure in Southern and Eastern Africa by 10.51 % and 1.01 %. The flow of virtual water in Africa is most influenced by spatial proximity, primarily occurring between adjacent countries or regions. Forecasts for water stress under the five scenarios of SSPs-RCP8.5 have been conducted, revealing a continuous increase in water stress across Africa. Furthermore, analysis of the SSP2-RCP8.5 scenario indicates that by 2030 and 2040, African cereal crops are projected to face virtual water resource stress increases of 7 % and 18.76 %, respectively, compared to 2020 levels. During the same period, Sierra Leone is anticipated to experience a growth rate in virtual water stress of approximately 1903.38 %. Consequently, altering crop cultivation structures and enhancing VWT are poised to alleviate water resource pressure, promoting the scientific management of agricultural water resources in Africa.

Testing the agriculture-induced Environmental Kuznets Curve with moderation effect of human capital and renewable energy: insights from BRICS economies

The surge in economic growth and increased agricultural output can augment societal well-being whilst proliferating environmental stressors. So, the study tests the validity of the "agriculture-induced Environmental Kuznets Curve hypothesis" (AEKC) by assessing the varied environmental proxies that have yet to be accounted for earlier in the case of BRICS economies. Furthermore, most studies have utilised "first-generation econometric approaches" as the "cross-sectional dependency" has not been deemed in estimation. On account of this, the research employed "second-generation CIPS and CADF unit root test", "Westerlund cointegration test", "fully modified ordinary least square" (FMOLS) and "dynamic ordinary least square" (DOLS) to test the validity of AEKC in "BRICS countries" for 30 years. A positive association between agriculture and "ecological footprint" has been found which evidences the presence of an "inverted U-shaped AEKC" in BRICS nations. Another finding shows that the favourable impact of agriculture towards climate change can be moderated by illustrating the interaction effect of "human capital" and "renewable energy" with "agriculture". Lastly, the investigation brings forth the policy repercussions and acumens for the BRICS governments and policymakers in halting climate change by using renewable energy in agriculture and building human capital.

Dataset of the suitability of major food crops in Africa under climate change

Understanding the extent and adapting to the impacts of climate change in the agriculture sector in Africa requires robust data on which technical and policy decisions can be based. However, there are no publicly available comprehensive data of which crops are suitable where under current and projected climate conditions for impact assessments and targeted adaptation planning. We developed a dataset on crop suitability of 23 major food crops (eight cereals, six legumes & pulses, six root & tuber crops, and three in banana-related family) for rainfed agriculture in Africa in terms of area and produced quantity. This dataset is based on the EcoCrop model parameterized with temperature, precipitation and soil data and is available for the historical period and until mid-century. The scenarios used for future projections are SSP1:RCP2.6, SSP3:RCP7.0 and SSP5:RCP8.5. The dataset provides a quantitative assessment of the impacts of climate change on crop production potential and can enable applications and linkages of crop impact studies to other socioeconomic aspects, thereby facilitating more comprehensive understanding of climate change impacts and assessment of options for building resilience.

Concentrations and health risks of selected elements in leafy vegetables: a comparison between roadside open-air markets and large stores in Johannesburg, South Africa

This study compared concentrations and health risks of selected elements (Al, As, Cd, Co, Cr, Cu, Hg, Ni, Pb, Zn) in leafy vegetables (coriander, lettuce, mint, spring onion, swiss chard) from roadside open-air markets (OM) and large stores (supermarkets: SM, vegetable markets: VM) in Johannesburg, South Africa. Along with washed leaves (OMW, SMW, VMW), unwashed OM leaves (OMUW) were assessed to investigate the contribution of deposition. The findings revealed that OMUW leaves had the highest concentrations of all elements. Furthermore, compared with washed leaves, OMUW leaves showed significantly higher (p < 0.05) mean concentrations of Cd, Hg, Ni and Pb, elements that typify the composition of polluted urban air. Bi- and multivariate analysis indicated anthropogenic origin of most elements in OM leaves and several in SMW and VMW leaves. Although only OMUW leaves exhibited hazard quotient above the safe threshold of 1 for Cd, Cr, As and Ni, hazard index exceeded this safe limit in all samples (OMUW (11.77) > OMW (1.83) > SMW (1.29) > VMW (1.01)). Determined cancer risk for Cd and As was greater than 1 × 10-6 in both washed and unwashed leaves, and the greatest cancer risk was estimated for OM leaves. Thorough washing of OM vegetables with water reduced non-carcinogenic risk (84%) and cancer risk (74‒87%) markedly. In conclusion, residents primarily relying on open-air markets for their regular leafy vegetable supplies might face far more severe lifelong health implications compared to customers of large stores in Johannesburg.

Understanding the connections between climate change, air pollution, and human health in Africa: Insights from a literature review

Climate change and air pollution are two interconnected global challenges that have profound impacts on human health. In Africa, a continent known for its rich biodiversity and diverse ecosystems, the adverse effects of climate change and air pollution are particularly concerning. This review study examines the implications of air pollution and climate change for human health and well-being in Africa. It explores the intersection of these two factors and their impact on various health outcomes, including cardiovascular disease, respiratory disorders, mental health, and vulnerable populations such as children and the elderly. The study highlights the disproportionate effects of air pollution on vulnerable groups and emphasizes the need for targeted interventions and policies to protect their health. Furthermore, it discusses the role of climate change in exacerbating air pollution and the potential long-term consequences for public health in Africa. The review also addresses the importance of considering temperature and precipitation changes as modifiers of the health effects of air pollution. By synthesizing existing research, this study aims to shed light on complex relationships and highlight the key findings, knowledge gaps, and potential solutions for mitigating the impacts of climate change and air pollution on human health in the region. The insights gained from this review can inform evidence-based policies and interventions to mitigate the adverse effects on human health and promote sustainable development in Africa.

First report of aeroponically grown Bambara groundnut, an African indigenous hypogeal legume: Implications for climate adaptation

Global agricultural production is currently limited by negative climate-related hazards such as drought, uneven rainfall and rising temperatures. Many efforts have been put in place by government and non-government agencies to mitigate the challenges of climate change in the sector. However, the approaches do not seem feasible due to the growing demand for food. With these challenges, climate-smart agricultural technologies such as aeroponics and underutilised crops have been projected as the future of agriculture in developing African countries to reduce the risk of food insecurity. In this paper, we present the cultivation of an underutilised indigenous African legume crop, Bambara groundnut, in an aeroponics system. Seventy Bambara groundnut landraces were cultivated in a low-cost climate-smart aeroponics system and in sawdust media. The results showed that Bambara groundnut landraces cultivated in aeroponics performed better than those cultivated in a traditional hydroponics (sawdust/drip irrigation) technique in terms of plant height and chlorophyll content, where the landraces cultivated in sawdust had a higher number of leaves than those cultivated in aeroponics. This study also demonstrated the feasibility of introducing a generic Internet of Things platform for climate-smart agriculture in developing countries. The proof-of-concept and the successful cultivation of a hypogeal crop in aeroponics can be useful for cost-effective adaptation and mitigation plans for climate change, particularly for food security in rural African agricultural sectors.

Prediction of monthly precipitation using various artificial models and comparison with mathematical models

Precipitation (PP) prediction is an interesting topic in the meteorology or hydrology field since it is directly related to agriculture, the management of water resources in hydrologic basins, and water scarcity. Selecting the right model to predict precipitation has always been a challenge because it could help researchers to use the proper model for their purposes. Accordingly, the performance of five artificial models (feed-forward neural network, cascade forward neural network, Elman neural network, multi-layer perceptron neural network, and radial basis neural network) and three mathematical models (Poisson regression model (PRM), quadratic model, and multiple linear regression) were evaluated for their ability to predict the monthly precipitation in Mediterranean coastal cities located in Eastern part of Mediterranean Sea for the first time. Twenty-seven Mediterranean coastal cities are considered case studies. For this aim, scenario 1 and scenario 2 with various input variables are proposed. Scenario 1 is developed using the number of months (MN), maximum temperature (Tmax), minimum temperature (Tmin), downward radiation (DR), wind speed (WS), vapor pressure (VP), and actual evapotranspiration (AE). Scenario 2 is developed by adding geographical coordinates (latitude, longitude, and altitude) to the global meteorological data to see the impact of geographical coordinates on the accuracy of the prediction of monthly precipitation. This study utilized the monthly data, which were obtained from TerraClimate for the period from 2010 to 2021. Based on the performance indexes, the PRM model performed best for the prediction of monthly precipitation in all selected locations compared to other models. Moreover, the results indicate that scenario 2 ([Formula: see text]) has shown higher prediction accuracy compared to scenario 1 ([Formula: see text]). In conclusion, PRM with the combination of [[Formula: see text]] had RMSE value that was lower by 12% relative to PRM with the combination of [[Formula: see text]]. Consequently, the PRM model can be recommended for modeling the complexity of interactions for precipitation-climate conditions-geographical coordinates and predicting precipitation.

Irrigation area, efficiency and water storage mediate the drought resilience of irrigated agriculture in a semi-arid catchment

We examined the effects of hydrological variables such as irrigation area, irrigation efficiency and water storage on the resilience of (mostly commercial) irrigated agriculture to drought in a semi-arid catchment in South Africa. We formulated a conceptual framework termed 'Water, Efficiency, Resilience, Drought' (WERD) and an accompanying spreadsheet model. These allow the resilience of irrigated agriculture to drought to be analysed via water accounts and a key resilience indicator termed Days to Day Zero (DDZ). This represents the number of days that a pre- and within-drought supply of catchment water available to irrigation is withdrawn down to zero in the face of a prolonged drought. A higher DDZ (e.g. >300 days) indicates greater resilience whilst a lower DDZ (e.g. <150 days) signals lower resilience. Drought resilience arises through land and water management decisions underpinned by four types of resilience capacities; absorptive, adaptive, anticipative and transformative. For the case study, analyses showed that irrigators, with currently approximately 23,000 ha under irrigation, have historically absorbed and adapted to drought events through construction of water storage and adoption of more efficient irrigation practices resulting in a DDZ of 260 days. However, by not fully anticipating future climate and water-related risks, irrigators are arguably on a maladaptive pathway resulting in water supply gains, efficiency and other practices being used to increase irrigation command areas to 28,000 ha or more, decreasing their capacity to absorb future droughts. This areal growth increases water withdrawals and depletion, further stresses the catchment, and reduces future DDZs to approximately 130 days indicating much lower drought resilience. Our approach, supported by supplementary material, allows stakeholders to understand the resilience consequences of future drought in order to; reconcile competition between rising water demands, consider new water storage; improve agricultural and irrigation planning; and enhance catchment governance.

A methodological tool for sustainability and feasibility assessment of indoor vertical farming with artificial lighting in Africa

African agriculture is bound to face challenges for its future food systems development and economic transformation. Indoor vertical farms with artificial lighting represent an opportunity that has been gaining relevance worldwide, thanks to their potential to enable high productivity rates, food quality and safety, year-round production, and more sustainable use of water and mineral nutrients. The present study assesses the potential for vertical farming technology integration within the African continent, targeting the countries where a more sustainable approach could be achieved. A deep analysis of each territory's major opportunities and challenges was built through an updated database of 147 development indicators from 54 African states. Countries such as South Africa, Seychelles, Egypt, Mauritius, Morocco, Tunisia, Algeria, Cape Verde, and Nigeria showed the best prospective for indoor vertical farming implementation. Moreover, Seychelles, South Africa, and Egypt resulted to be the countries where vertical indoor farming could be more sustainable.

Maize producers' vulnerability to climate change: Evidence from Makhuduthamaga Local Municipality, South Africa

Climate change is predicted to impact agricultural production and affect food security in poor communities of developing countries due to the likely negative impacts on rainfall characteristics. South Africa is one of the largest producers of maize crops in the Southern African Development Community (SADC) region. The majority of crop production is rainfed with precipitation received during the summer growing season. This study evaluated the impact of climate change on maize yields using trend and multiple regression analysis in northern South Africa. Exposure and vulnerability of maize farmers to the impacts of climate change were also evaluated. Rainfall characteristics showed variability of 20.35% with rain days standard deviation of 10.25 days and coefficient of variation of 18.57%. The results revealed a weak relationship between annual rainfall and rainy days, and annual rainfall and maize yields, both showed an r² and p-values of less than 0.5 and 0.005, respectively. The study found that variations in rainfall did not significantly influence variation in maize yields. Despite a clear fluctuation in yields, the results demonstrate a rising trend that can be attributed to agricultural practices such as the use of fertilisers and planting drought resistant cultivars as opposed to climate variables. The study further found that maize producers were proactively adapting to climate change, thus, reducing their vulnerability to its impacts.

Spatial and temporal patterns of agrometeorological indicators in maize producing provinces of South Africa

Climate change impacts on maize production in South Africa, i.e., interannual yield variabilities, are still not well understood. This study is based on a recently released reanalysis of climate observations (AgERA5), i.e., temperature, precipitation, solar radiation, and wind speed data. The study assesses climate change effects by quantifying the trend of agrometeorological indicators, their correlation with maize yield, and analyzing their spatiotemporal patterns using Empirical Orthogonal Function. Thereby, the main agrometeorological factors that affected yield variability for the last 31 years (1990/91–2020/21 growing season) in major maize production provinces, namely Free State, KwaZulu-Natal, Mpumalanga, and North West are identified. Results show that there was a significant positive trend in temperature that averages 0.03–0.04 °C per year and 0.02–0.04 °C per growing season. There was a decreasing trend in precipitation in Free State with 0.01 mm per year. Solar radiation did not show a significant trend. Wind speed in Free State increased at a rate of 0.01 ms⁻¹ per growing season. Yield variabilities in Free State, Mpumalanga, and North West show a significant positive correlation (r > 0.43) with agrometeorological variables. Yield in KwaZulu-Natal is not influenced by climate factors. The leading mode (50–80% of total variance) of each agrometeorological variable indicates spatially homogenous pattern across the regions. The dipole patterns of the second and the third mode suggest the variabilities of agrometeorological indicators are linked to South Indian high pressure and the warm Agulhas current. The corresponding principal components were mainly associated with strong climate anomalies which are identified as El Niño and La Niña events.

Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia

The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p < 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.

On-Farm Supplemental Irrigation of ‘Roja Lisa’ Cactus Pear: Pre- and Postharvest Effects

Opuntia species grow in arid and semiarid lands, where water for irrigation is scarce. However, supplemental irrigation can be a feasible strategy for commercial cactus pear orchards. From 2018 to 2020, a commercial cactus pear orchard was managed to validate the effect of supplemental irrigation on fruit yield, crop water use efficiency, fruit quality, and storability of ‘Roja Lisa’ cactus pear grown in the semiarid region of Mexico. The irrigation treatments were no irrigation and supplemental irrigation, with four replications. Crop water use was less and, therefore, water productivity greater in non-irrigated plants than in plants with supplemental irrigation. Mean fruit yield, mean fruit mass, and proportion of commercial fruit increased with supplemental irrigation. These differences were more pronounced in growing seasons with less rainfall. Fruit quality at harvest or after room temperature or cold storage was examined. Fruit mass loss rate was reduced in fruit receiving supplemental irrigation in both storage conditions. In addition, supplemental irrigation was consistent with water savings and food security programs in marginal areas: this irrigation strategy improved both pre- and postharvest some quality components of cactus pear fruit. Therefore, this irrigation strategy is suggested for cactus pear growers, depending on the availability of water for irrigation.

Risks of Climate Change on Future Water Supply in Smallholder Irrigation Schemes in Zimbabwe

Smallholder irrigation schemes (SISs) have been portrayed as a panacea to climate change adaptation. However, there is an emerging discourse that established schemes are becoming vulnerable to increased climate variability and change, particularly increased water stress. This paper reviews the existing knowledge on risks of climate change and variability in water supply in smallholder irrigation farming in Zimbabwe. In addition, this paper highlights adaptation options to climate change in SISs. Data for this review were collected systematically from peer-reviewed and published literature. The literature used for this study showed that SISs in Zimbabwe are beset with water stress, competing water needs and the outbreak of pests and diseases, which have been related with climate change and variability. Climate change is making Zimbabwe more arid through decreasing precipitation and warming. Droughts and floods are increasing in frequency and severity. Damage by floods is increasing exponentially, impacting environments, ecological systems and national economies. Climate change affects SISs’ productivity and decimates the livelihoods of scheme farmers. The review suggests that there is a need for increased adsorptive, adoptive and transformational capacity for SISs to obtain a new state of resilience from adverse effects of increased climate variability and change. This review recommends understanding and prioritizing solutions to vulnerability to climate change in SISs.

Resilience and Sustainability of the Water Sector during the COVID-19 Pandemic

The COVID-19 pandemic brought unprecedented socio-economic changes, ushering in a “new (ab)normal” way of living and human interaction. The water sector was not spared from the effects of the pandemic, a period in which the sector had to adapt rapidly and continue providing innovative water and sanitation solutions. This study unpacks and interrogates approaches, products, and services adopted by the water sector in response to the unprecedented lockdowns, heralding novel terrains, and fundamental paradigm shifts, both at the community and the workplace. The study highlights the wider societal perspective regarding the water and sanitation challenges that grappled society before, during, after, and beyond the pandemic. The premise is to provide plausible transitional pathways towards a new (ab)normal in adopting new models, as evidenced by the dismantling of the normal way of conducting business at the workplace and human interaction in an era inundated with social media, virtual communication, and disruptive technologies, which have transitioned absolutely everything into a virtual way of life. As such, the novel approaches have fast-tracked a transition into the 4th Industrial Revolution (4IR), with significant trade-offs to traditional business models and human interactions.

Informing Equitable Water and Food Policies through Accurate Spatial Information on Irrigated Areas in Smallholder Farming Systems

Accurate information on irrigated areas' spatial distribution and extent are crucial in enhancing agricultural water productivity, water resources management, and formulating strategic policies that enhance water and food security and ecologically sustainable development. However, data are typically limited for smallholder irrigated areas, which is key to achieving social equity and equal distribution of financial resources. This study addressed this gap by delineating disaggregated smallholder and commercial irrigated areas through the random forest algorithm, a non-parametric machine learning classifier. Location within or outside former apartheid "homelands" was taken as a proxy for smallholder, and commercial irrigation. Being in a medium rainfall area, the huge irrigation potential of the Inkomati-Usuthu Water Management Area (UWMA) is already well developed for commercial crop production outside former homelands. However, information about the spatial distribution and extent of irrigated areas within former homelands, which is largely informal, was missing. Therefore, we first classified cultivated lands in 2019 and 2020 as a baseline, from where the Normalised Difference Vegetation Index (NDVI) was used to distinguish irrigated from rainfed, focusing on the dry winter period when crops are predominately irrigated. The mapping accuracy of 84.9% improved the efficacy in defining the actual spatial extent of current irrigated areas at both smallholder and commercial spatial scales. The proportion of irrigated areas was high for both commercial (92.5%) and smallholder (96.2%) irrigation. Moreover, smallholder irrigation increased by over 19% between 2019 and 2020, compared to slightly over 7% in the commercial sector. Such information is critical for policy formulation regarding equitable and inclusive water allocation, irrigation expansion, land reform, and food and water security in smallholder farming systems.

Extreme Climate Shocks and Green Agricultural Development: Evidence from the 2008 Snow Disaster in China

Extreme climate shocks cause agricultural yield reductions and increase long-term climate risk, altering farmers’ long-term production decisions and affecting green agricultural development (GAD). We take the 2008 snow disaster in China as an extreme climate shock, calculate the GAD index by the entropy weighting method, and use the difference-in-difference method to study the extreme climate shock’s impact on GAD. The results show that: (1) Extreme climate shocks are detrimental to GAD, with the snow disaster decreasing China’s GAD level by 3.07%. (2) The impacts of extreme climate shocks are heterogeneous across climate and economic zones, with greater impact in humid and developed regions. (3) Extreme climate shocks affect GAD mainly by reducing farmers’ willingness to cultivate, and increasing energy consumption, fertilizer, and pesticide input. (4) Extreme climate shocks do not reduce agricultural yields in the long run. Still, they reduce the total value of agricultural production and decrease the quality of agricultural products expressed in terms of unit value. The findings of this study have policy implications for developing countries in coping with extreme climate shocks and promoting GAD.

Agricultural Land Transition in the “Groundnut Basin” of Senegal: 2009 to 2018

The study aims to reveal the transition features of agricultural land use in the Groundnut Basin of Senegal from 2009 to 2018, especially the impact of urbanization on agricultural land and the viewpoint of farmland spatiotemporal evolution. Integrated data of time series MCD12Q1 land-use images of 2009, 2012, 2015, and 2018 were used to provide a land transition in agricultural and urban areas through the synergistic methodology. Socio-economic data was also used to serve as a basis for the argument. The results highlight that: (1) Agricultural land increased by 14.53%, with a dynamic index of 1.45 from 2009–2018. (2) Over the same period, urbanization increased by 2.80%, with a dynamic index of 0.28. (3) In different regions, the transition of agricultural land in Kaffrine is most intense (expansion rate: 22.80%). The same situation of urbanization happened in Thiès Region with a value of 7.94%. Except for Thiès, agricultural land in other regions has not yet been subject to major pressure due to urbanization. Overall, the farming system in Groundnut Basin is an extensive model, the recommendations from the point of view of land-use planning and land law are necessary to ensure efficient agricultural land management in the area.

Transitional Pathways towards Achieving a Circular Economy in the Water, Energy, and Food Sectors

Achieving sustainable socio-economic development requires approaches that enhance resource use efficiencies and can address current cross-sectoral challenges in an integrated manner. Existing evidence suggests an urgent need for polycentric and transformative approaches, as global and local systems have come under strain. This study conducted a systematic literature review at the global level to assess the progress made towards achieving a circular economy between 2010 and 2020, a period covering the formulation of the Sustainable Development Goals (SDGs) and the initial five years of their implementation. The focus was on the potential of improved water and energy use efficiency, linking them to food production within the context of a circular economy. Identifying successes, opportunities, challenges, and pathways towards a circular economy from the literature review facilitated developing a conceptual framework to guide strategic policy formulations towards a more sustainable economy. A combination of transformative approaches is analysed in an integrated way in response to the 2030 global agenda on sustainable development. Thus, the study is informed by the initiatives to attain SDGs and mitigating negative environmental impacts due to waste and pollution. The premise is to enhance transformational change as a catalyst for employment creation and the attainment of a green economy while reducing waste. Transformative approaches have been identified to provide pathways towards global climate targets and protection of the environment from further degradation. They are a catalyst to achieve SDG 12 on ensuring sustainable consumption and production patterns.

Environmental Services: A New Approach Toward Addressing Sustainable Development Goals in Sub-Saharan Africa

The physical environment provides resources and specific types of environmental services relevant to the maintenance of human livelihoods globally and with specific reference to sub-Saharan Africa, including soils, food, and water systems. Previous studies on the shared nexus of such resources commonly view these as self-contained systems operating independent of their physical contexts provided by landscape-scale geomorphology and its related processes. This study critically examines the viewpoints adopted by such nexus studies with specific reference to sub-Saharan Africa, arguing that these studies are reductive, considering only the shared disciplinary overlap (nexus) and not their wider contexts, and are based on only a limited understanding of the workings of physical systems. This study argues that considering the attributes of the physical landscape and its provision of environmental services provides a broader and scientifically-informed context for understanding of interlinked issues such as relationships between soil–food–water systems. Framing such “nexus” studies in this wider context can derive a better understanding of the connections between different elements such as soil, food, and water, amongst others, and with respect to the United Nations' Sustainable Development Goals. The concept of environmental services is therefore a more powerful tool to examine both the connections between physical and human environmental processes and properties in sub-Saharan Africa, and to address overarching environmental issues such as land degradation, soil erosion loss, water scarcity, and impacts of climate change.

Climate Change, Land, Water, and Food Security: Perspectives From Sub-Saharan Africa

The current and projected warming of the earth is unequivocal with humans playing a strong role as both perpetrators and victims. The warming on the African continent is projected to be greater than the global average with an increased average temperature of 3–6°C by the end of the century under a high Representative Concentration Pathway. In Africa, the Sub-Saharan region is identified as the most vulnerable to the changing climate due to its very low capacity to adapt to or mitigate climate change. While it is common to identify studies conducted to assess how climate change independently impacts water, land, or food resources, very limited studies have sought to address the interlinkages, synergies, and trade-offs existing between climate change, water, land, and food (WLF) resources as a system in Sub-Saharan Africa (SSA). The climate change and WLF security nexus, therefore, seeks to address this shortfall in literature and subsequently serve as a relevant source of information for decision-making and policy implementation concerning climate change mitigation and adaptation. In this study, 41 relevant studies were selected from Web of Science, Google Scholar, ResearchGate, and institutional websites. We provide information on the independent relationships between climate change and WLF resources, and further discuss the existing inter-linkages between climate change and the WLF security in SSA using the nexus approach, with recommendations on how decision making and policy implementations should be done using the climate change and WLF security nexus approach.

Application of the Random Forest Classifier to Map Irrigated Areas Using Google Earth Engine

Improvements in irrigated areas' classification accuracy are critical to enhance agricultural water management and inform policy and decision-making on irrigation expansion and land use planning. This is particularly relevant in water-scarce regions where there are plans to increase the land under irrigation to enhance food security, yet the actual spatial extent of current irrigation areas is unknown. This study applied a non-parametric machine learning algorithm, the random forest, to process and classify irrigated areas using images acquired by the Landsat and Sentinel satellites, for Mpumalanga Province in Africa. The classification process was automated on a big-data management platform, the Google Earth Engine (GEE), and the R-programming was used for post-processing. The normalised difference vegetation index (NDVI) was subsequently used to distinguish between irrigated and rainfed areas during 2018/19 and 2019/20 winter growing seasons. High NDVI values on cultivated land during the dry season are an indication of irrigation. The classification of cultivated areas was for 2020, but 2019 irrigated areas were also classified to assess the impact of the Covid-19 pandemic on agriculture. The comparison in irrigated areas between 2019 and 2020 facilitated an assessment of changes in irrigated areas in smallholder farming areas. The approach enhanced the classification accuracy of irrigated areas using ground-based training samples and very high-resolution images (VHRI) and fusion with existing datasets and the use of expert and local knowledge of the study area. The overall classification accuracy was 88%.

Wetlands Management in Northern Greece: An Empirical Survey

Water management projects have an important role in regional environmental protection and socio-economic development. Environmental policies, strategies, and special measures are designed in order to balance the use and non-use values arising for the local communities. The region of Serres in Northern Greece hosts two wetland management projects—the artificial Lake Kerkini and the re-arrangement of Strymonas River. The case study aims to investigate the residents’ views and attitudes regarding these two water resources management projects, which significantly affect their socio-economic performance and produce several environmental impacts for the broader area. Simple random sampling was used and, by the application of reality and factor analyses along with the logit model support, significant insights were retrieved. The findings revealed that gender, age, education level, and marital status affect the residents’ perceived values for both projects and their contribution to local growth and could be utilized in policy making for the better organization of wetland management.