Cities are complex and evolving systems with various factors playing key roles, e.g., population increase, the migration of population, the availability of resources, and the flexibility of policies. Consumers’ socioeconomic status is also an important aspect that needs to be studied in the context of a self-reliant urban city in its resource consumption. In this regard, the association between water–food and socio-economic attributes was analyzed based on the consumer-centric approach for the Hyderabad Metro Development Authority (HMDA) region, India. In this study, the embedded water content in food consumption was estimated and analyzed for nine food groups and twelve economic classes of the HMDA region. The middle economic classes were found to correspond to ~80% of embedded water content in the HMDA region, followed by the upper and lower economic classes. Except for cereals, per capita, the water consumption of all food groups increased with the spending power of the economic class. The green, blue, and grey consumption water footprints (WFs) suggested that much of the water that is being consumed in the HMDA region is precipitation-driven, followed by surface and groundwater resources. Limited water resources, water resource variability, climate change consequences including future climate projections, uncertainty in data, WF estimates, and region’s future growth imply a detailed study in drafting policies to become a self-reliant region.

Over the next few years, Tunisia will face a growing scarcity of water. The concept of a food consumption water footprint has been recently applied to expand knowledge about water management and to respond to problems of food insecurity. In this study, following the Water Footprint Network (WFN) method, we assessed and analysed the food consumption water footprint of Tunisian households by geographical location and by group of food products. We used results from national food surveys to collect the quantities of food consumed and the WFN database containing water footprints of food products specific to Tunisia. We found that the average water footprint for the main consumed food groups has increased by 31% during recent decades, from 1208 m³/capita/year in 1985 to 1586 m³/capita/year in 2010. Despite the decline in cereal consumption in Tunisia, the food water footprint has continued to rise as a result of increased consumption of animal source products. This increase is associated with regional variations in food choices that imply large differences in water footprints. Urban diets present higher water footprints than rural diets proportionally to higher standards of living. This study provides a new perspective on the water footprint of food consumption in Tunisia by using dietary data at the household level and demonstrated significant variability in water footprints due to different food consumption modes, and socio-economic and geographic characteristics. Future food consumption trends will likely create more pressure on water resources, especially in Tunis city and coastal areas of Tunisia. Special measures related to price policies, sensitization of consumers, and changes in production systems may have to be taken by policy makers to reduce the water footprint in order to improve food security strategies and water management in Tunisia.

Water and food are facing increased demands from larger and more affluent populations thus necessitating a coordinated and effective management of limited natural resources. In this study, we present an optimization model developed for optimal resource allocation towards sustainable water and food security under nutritional, socio-economic, agricultural, environmental, and natural resource constraints. The core objective of this model is to maximize the composite water-food security status by defining an optimal water and agricultural policy that ensures nutritional guidelines while still maintaining food-preferences. This policy transforms optimum food demands into optimum cropping options given the water and land footprints of each crop or agricultural product. The model performance is evaluated with a hypothetical regional case study testing a wide spectrum of cases from the water-stressed to the land-stressed extremes thus showing the model's ability to suggest fundamentally different policy approaches. Results demonstrated the sensitivity of adopted water and food security definitions in shaping water and agricultural policies, thus reinforcing the need for agreements amongst the wide range of stakeholders at global scale.

Poorer countries often face a severe trade-off: the need to improve socio-economic conditions is hard to balance with the maintenance of key ecological processes. As a case study, we select Colombia, a Latin American country with almost 10% of its inhabitants living in extreme poverty. We elaborate a water–food–labour (WFL) nexus grounded on a sub-national Environmentally Extended Input–Output (EEIO) analysis to assess the virtual water trade (VWT) and virtual informal labour (VIL) flows across administrative departments and economic sectors related to domestic trade. The main results are the following: high cross-departmental resource interdependence both in terms of VWT and VIL, rich departments highly depend on the resources of their neighbouring trading partners, extreme poverty conditions shown by economically isolated departments, and considerable income inequality in the food production sectors. Moreover, departments that are net exporters of virtual water suffer from water stress that might be exacerbated by future high rainfall variability due to climate change. These results suggest that strategies to attain sustainable development goals (SDGs) must deal with the biophysical constraints and the economic and political feasibility of the proposed solutions. In this vein, we argue that a holistic framework, grounded on quantitative analyses, is necessary to support informed policy decisions for the simultaneous achievement of multiple (possibly contrasting) goals. Moreover, severe spatial imbalances call for local policy responses coordinated at the national level.

Recent years have shown increased awareness that the use of the basic resources water, food, and energy are highly interconnected (referred to as a ‘nexus’). Spatial scales play a major role in nexus analyses, and can be related to the physical characteristics and dependencies between nexus resources. In fact, water, food and energy are very different in terms of absolute magnitude of production, as well as in the extent to which they are traded. The differences in trade extent can partly be explained by physical differences: high value, high density, geographically concentrated resources are traded more. We show how input-output dependencies are more relevant at local to national scales, whereas the continental and global scales are important due to physical and virtual trade. We combined various insights into an overview of which spatial scales are most relevant for each nexus resource, based on physical characteristics, input-output dependencies, virtual trade, and potential future changes due to socio-economic trends, climate change impacts and climate change mitigation.

The current study introduces a conceptual socio-hydrological-based framework for the water-energy-food (WEF) nexus. The proposed conceptual framework aims to investigate how farmers' dynamic agricultural activities under different socio-economic conditions affect the WEF systems. The WEF nexus model has been integrated with an Agent-Based Model, reflecting the farmers’ agricultural activities. Furthermore, the agent-based model benefits from Association Rule Mining to define farmer agents’ agricultural decision-making in various conditions. The processes within the WEF nexus are simultaneously physical, socio-economic, ecological, and political. Indeed, there are interrelated interactions among the mentioned processes in ways that have not yet been properly delineated and mapped. Thus, to obtain sustainable outcomes, the current study investigates trade-offs among natural resources and social systems in the WEF nexus approach. The proposed socio-hydrological WEF nexus framework may provide more in-depth future insights for policy-makers through capturing bidirectional feedbacks among farmers and WEF systems. In other words, the proposed framework can help policymakers to capture the dynamic impacts of agricultural activities by farmers on the WEF nexus, which may vary due to different socio-economic conditions.

Water, energy, food, and environment are highly interconnected, with intricate dependencies and multiple uncertainties involved in agricultural system. This paper presents a novel water-energy-food-environment nexus (WEFEN) optimization model for sustainable development of agriculture. The developed model incorporates stochastic multi-objective programming, triangular fuzzy numbers, fuzzy credibility-constrained programming, mixed-integer programming, non-linear programming, and Stewart model into a general optimization framework. The model is capable of (1) balancing the tradeoffs among socio-economic, resources, and environmental concerns; (2) generating valid WEFEN management solutions achieving the targets of maximum net economic benefit, maximum renewable energy production, minimum water footprint, and minimum carbon footprint simultaneously; (3) dealing with complexities and uncertainties existed in agricultural WEFEN systems. The model was applied to the Zhanghe irrigation district to give policy-makers insights into what efforts should be made towards sustainable agricultural management. Flexible alternatives were generated under different scenarios and sensitivity analyses were conducted. Results highlighted the significance of improvement of internal water storage capacity, reasonable farmland management, and compromise decision preferences. The proposed methodology is applicable for other agriculture-centered regions suffering from multifold resources and environment crisis.

Water, energy and food are three essential resources for the socio-economic system, and they are interlinked. The coordination of their internal relations is worth studying. We conduct a coordination evaluation method to assess the water-energy-food nexus (WEF Nexus) in China’s provinces. By combining the coupling model and the coupling coordination model, we measure the comprehensive evaluation index and coupling coordination degree of China’s 30 provinces from 2005 to 2017. First, the results show the provincial comprehensive evaluation index had a slow upward trend. The comprehensive evaluation index of the southern region was higher than that of the north, and the eastern was higher than the west. Second, the coordination degree of WEF Nexus in China’s 30 provinces has reached high level in the horizontal coupling stage, and the overall degree of coupling coordination was on the rise. In 2017, the WEF Nexus coupling coordination degree of most provinces reached 0.700 or more, which was intermediate-coordinated. In the six years, the 30 provinces have experienced five types of coupling coordination degree: near coordinated, barely coordinated, primary coordinated, intermediate-coordinated, and well-coordinated.

The water–climate-food security nexus is uniquely vulnerable in Central Asia, a region replete with transboundary water conflicts, shortages in land and water resources and high sensitivity to climate change. Using a water balance for the Amu Darya River Basin, we present a synthetic evaluation of future water use, crop yields, land and water productivities for the period 2016 to 2055 in Ahal, Dashoguz, Lebap, and Mary provinces in Turkmenistan. Modeled fut socio-economic scenarios include food security and diet change (FSD), export-oriented sustainable adaptation (ESA) and business as usual (BAU). Results show that water requirements and water deficits during growing seasons will exhibit a decreasing trend from 2016 to 2055 in most provinces under all three scenarios. Crop yields and land and water productivities will likely increase in the four provinces under both the FSD and ESA scenarios. Mary province had the highest mean income and losses of irrigated agriculture, with an annual average value of about 7 × 108 USD/year and 1.5 × 103 USD/year, respectively. Ahral province showed the largest annual mean land and irrigation water productivities for all three scenarios, up to about 800 USD/ha/year and 0.40 USD/m3/year respectively. Results obtained from this study provide tools to assist resource managers to identify vulnerabilities in the nexus of water, land and climate to ensure food security, water management, and sustainable development.