Pressures from growing demands and shrinking supplies have reached a critical junction in major global resources, particularly water, energy, and food (WEF). Recognizing the complex interaction across those highly interconnected resources, the nexus concept evolved to boost efficiencies across all nexus pillars. Several modeling efforts tried to capture the complexity of this problem, but most attempts captured only one or two nexus pillars, remained localized to fixed case-studies or applications, or used simulations to assess pre-defined scenarios rather than solving for optimum solutions under defined objective function and constraints. Here, we present an optimization model for water, energy, and food nexus resource management and allocation at a regional scale. The model was successfully validated using a hypothetical case study to test its efficiency under several resource availability scenarios and different policy targets. The results enhanced the understanding of the interlinkages among the nexus sectors by demonstrating the sensitivity of the WEF nexus to adopted strategies. For example, imposing food variety constraints changed water consumption by an order of magnitude and more than doubled energy requirements. Moreover, adopting renewable energy may cause increased demands for land, but can significantly cut CO₂ emissions. The model serves as an effective decision-making tool that enables policy makers to assess multiple WEF sources and recommends the optimum resource allocation under various policy, technology, and resource constraints.

Allocation and management of agricultural land is of emergent concern due to land scarcity, diminishing supply of energy and water, and the increasing demand of food globally. To achieve social, economic and environmental goals in a specific agricultural land area, people and society must make decisions subject to the demand and supply of food, energy and water (FEW). Interdependence among these three elements, the Food-Energy-Water Nexus (FEW-N), requires that they be addressed concertedly. Despite global efforts on data, models and techniques, studies navigating the multi-faceted FEW-N space, identifying opportunities for synergistic benefits, and exploring interactions and trade-offs in agricultural land use system are still limited. Taking an experimental station in China as a model system, we present the foundations of a systematic engineering framework and quantitative decision-making tools for the trade-off analysis and optimization of stressed interconnected FEW-N networks. The framework combines data analytics and mixed-integer nonlinear modeling and optimization methods establishing the interdependencies and potentially competing interests among the FEW elements in the system, along with policy, sustainability, and feedback from various stakeholders. A multi-objective optimization strategy is followed for the trade-off analysis empowered by the introduction of composite FEW-N metrics as means to facilitate decision-making and compare alternative process and technological options. We found the framework works effectively to balance multiple objectives and benchmark the competitions for systematic decisions. The optimal solutions tend to promote the food production with reduced consumption of water and energy, and have a robust performance with alternative pathways under different climate scenarios.

This study proposes a performance appraisal framework for agricultural water distribution systems based on the Water-Food-Energy Nexus perspective. To analyze and evaluate agricultural water distribution systems with this framework, various methods of improving the operational management were developed and tested under the conventional and water shortages in operational scenarios. The Water-Food-Energy Nexus indicators were then calculated for performance appraisal of the water distribution systems in a study area, located in central Iran. The results indicated that by upgrading the manual operation to an automatic control system, gave the best results from the nexus indicators perspectives. The Bayesian Network model was used to present a probabilistic approach that could assist managers and decision-makers in evaluating the performance of the system, based on the nexus perspective. For this purpose, various configurations of the Bayesian Network structures were developed based on an export-oriented approach, and the most appropriate model was determined for the test case. The calibration and validation process of the selected configuration approved a high accuracy in fulfilling the objective of the study. The developed framework can be employed as a decision support model to prioritize options for modernizing agricultural water distribution systems.

The water–energy–food nexus (WEF nexus) concept is a novel approach to manage limited resources. Since 2011, a number of studies were conducted to develop computer simulation models quantifying the interlinkage among water, energy, and food sectors. Advancing a nationwide WEF nexus simulation model (WEFSiM) previously developed by the authors, this study proposes an optimization module (WEFSiM-opt) to assist stakeholders in making informed decisions concerning sustainable resource management. Both single- and multi-objective optimization modules were developed to maximize the user reliability index (URI) for water, energy, and food sectors by optimizing the priority index and water allocation decisions. In this study, the developed models were implemented in Korea to determine optimal resource allocation and management decisions under a plausible drought scenario. This study suggests that the optimization approach can advance WEF nexus simulation and provide better solutions for managing limited resources. It is anticipated that the proposed WEFSiM-opt can be utilized as a decision support tool for designing resource management plans.

Approaching water, energy, and food, as interconnected system of systems, as an alternative to traditional silo-based resources planning and management approaches continues to fall short of expectations of its research-backed benefits. The lack of nexus applications in policy and decision making can be related to numerous factors, with the main barrier being the complex nature of “nexus” systems combined with the disarray of tools attempting to model its interconnections. The paper aims to provide a method for comparing the perceived complexity of nexus tools identified by international organizations as well as primary literature sources. Eight separate criteria are introduced and discussed as measures of a tool “complexity index” and used to score the relative simplicity, or complexity, of a given tool. The result of this process is used to identify trends within existing nexus-assessment tools while guiding potential users towards appropriate tool(s) best-suited for their case study needs and objectives. The main objectives of this paper are to: 1) categorize nexus assessment tools according to a criteria-set which allows for suitable tool selection; 2) identify a method for rapid evaluation of the trade-offs for choosing different tools (simple-complex spectrum). The results of the comparative analysis of the selected nexus assessment tools concur with literature citing a growing gap between nexus research and applications in actual policy and decision-making settings. Furthermore, results suggest that tools receiving higher complexity scores, while being able to capture details to specific resource interactions, are unable to cover a larger number of interactions and system components simultaneously, as compared to lower complexity score tools. Lastly, the outcome of the analysis point towards the need for integrating more preliminary assessment capabilities, i.e. diagnostics, guidelines, and capacity building, into existing tools that improve the communication and translation of model outputs into policy and decision-making. © 2018 Elsevier B.V.

The missing link between cross-sectoral resource management and full-scale adoption of the water-energy-food (WEF) nexus has been the lack of analytical tools that provide evidence for policy and decision-making. This study defined WEF nexus sustainability indicators, from where an analytical model was developed to manage WEF resources in an integrated manner using the Analytic Hierarchy Process (AHP). The model established quantitative relationships among WEF sectors, simplifying the intricate interlinkages among resources, using South Africa as a case study. A spider graph was used to illustrate sector performance as related to others, whose management is viewed either as sustainable or unsustainable. The model was then applied to assess progress towards the Sustainable Development Goals in South Africa. The estimated integrated indices of 0.155 and 0.203 for 2015 and 2018, respectively, classify South Africa’s management of resources as marginally sustainable. The model is a decision support tool that highlights priority areas for intervention.

The missing link between cross-sectoral resource management and full-scale adoption of the water-energy-food (WEF) nexus has been the lack of analytical tools that provide evidence for policy and decision-making. This study defined WEF nexus sustainability indicators, from where an analytical model was developed to manage WEF resources in an integrated manner using the Analytic Hierarchy Process (AHP). The model established quantitative relationships among WEF sectors, simplifying the intricate interlinkages among resources, using South Africa as a case study. A spider graph was used to illustrate sector performance as related to others, whose management is viewed either as sustainable or unsustainable. The model was then applied to assess progress towards the Sustainable Development Goals in South Africa. The estimated integrated indices of 0.155 and 0.203 for 2015 and 2018, respectively, classify South Africa’s management of resources as marginally sustainable. The model is a decision support tool that highlights priority areas for intervention.

Food, energy, and water (FEW) are interconnected pillars that underpin the security of people’s livelihoods. In this paper, we propose a decision-support model to better understand and aid management of regional FEW nexus systems under uncertainty. We apply the model to a case study focusing on fluctuations in water supply, which significantly affect production in the agriculture and energy sectors in Shanxi Province, China. We use a two-stage, stochastic, chance-constrained programming approach to the proposed spatially detailed cost-minimizing FEW nexus model under demand and natural resource (land and water) constraints. This approach translates the target reliability level (i.e., the probability that the devised solution can satisfy all constraints) into a penalty that has to be paid in the case of their non-fulfillment. On this basis, robust decisions (i.e., production options suitable for a broad variation in certainty of water supply) are derived. Using this approach, we estimate the penalties required to achieve given levels of reliability by incentivizing the deployment of water-saving technologies. For example, our model predicts that water storage would become cost-effective if the penalty for exceeding the available water supply were 2.5 times higher than the current price for industrial water; this would enable at least 40% reliability compared to 18% if the penalty were at the current water price level. Taking advantage of the differences in water intensity of crops in different sites, our model optimizes the reservoir location, which allows water withdrawal by agriculture to be reduced by 1.23%. We also evaluate the benefits of incorporating uncertainty and missed opportunity due to a lack of perfect information. In the case study, we show that the benefits of including uncertainty in the form of the two-stage stochastic programming approach appear to be quite significant, reaching 4% of the total solution costs. Water-importing costs, taxes, and subsidies are instruments that translate into the penalty in this model; the modeling approach presented here can thus be used to inform cost-effective and robust management of the FEW nexus in Shanxi Province, China, and other water-scarce regions around the world.

Food contact materials can release low levels of multiple chemicals (migrants) into foods and beverages, to which individuals can be exposed through food consumption. This paper investigates the potential for non-carcinogenic effects from exposure to multiple migrants using the Cefic Mixtures Ad hoc Team (MIAT) decision tree. The purpose of the assessment is to demonstrate how the decision tree can be applied to concurrent exposures to multiple migrants using either hazard or structural data on the specific components, i.e. based on the acceptable daily intake (ADI) or the threshold of toxicological concern. The tree was used to assess risks from co-exposure to migrants reported in a study on non-intentionally added substances (NIAS) eluting from food contact-grade plastic and two studies of water bottles: one on organic compounds and the other on ionic forms of various elements. The MIAT decision tree assigns co-exposures to different risk management groups (I, II, IIIA and IIIB) based on the hazard index, and the maximum cumulative ratio (MCR). The predicted co-exposures for all examples fell into Group II (low toxicological concern) and had MCR values of 1.3 and 2.4 (indicating that one or two components drove the majority of the mixture’s toxicity). MCR values from the study of inorganic ions (126 mixtures) ranged from 1.1 to 3.8 for glass and from 1.1 to 5.0 for plastic containers. The MCR values indicated that a single compound drove toxicity in 58% of the mixtures. MCR values also declined with increases in the hazard index for the screening assessments of exposure (suggesting fewer substances contributed as risk potential increased). Overall, it can be concluded that the data on co-exposure to migrants evaluated in these case studies are of low toxicological concern and the safety assessment approach described in this paper was shown to be a helpful screening tool.