Exploring synergistic benefits of Water-Food-Energy Nexus through multi-objective reservoir optimization schemes

Conducting water-energy-food nexus studies: what, why, and how

The increasing pressure on resources and the persistent failure to address global malnutrition are evident challenges. A significant contributing factor is the decline in the quality of production resources, particularly water. As a result, many countries and their experts have prioritized the need to balance resource consumption. To address the research gap regarding balanced and optimal resource use, various methodologies have been developed over time, culminating in nexus studies. This study aimed to investigate the what, why, and how of conducting water-energy-food nexus (WEFN) studies. The research employed a sequential mixed-methods approach, integrating content analysis with the Analytical Network Process (ANP). The findings reveal that the objectives of WEFN studies encompass a wide range of interests, which can be systematically categorized into seven principal domains: system sustainability assessment, integration of planning and decision-making processes related to resource consumption, optimization of resource use, management of resource consumption systems, development of theoretical frameworks for the nexus, evaluation of the impacts of resource consumption, and assessment of associated risks. Notably, the results indicate that system sustainability assessment is the most critical reason for conducting WEFN studies. Furthermore, the analysis of WEFN methodologies identified simulation as the most effective technique within the Analytical Hierarchy Process (AHP) framework. In the context of the ANP technique, statistical analysis and simulation emerged as the most important methods. This research advocates for using a diagram to facilitate the selection of the optimal method for conducting a WEFN study.

Integration of deep learning and improved multi-objective algorithm to optimize reservoir operation for balancing human and downstream ecological needs

Dam (reservoir)-induced alterations of flow and water temperature regimes can threaten downstream fish habitats and native aquatic ecosystems. Alleviating the negative environmental impacts of dam-reservoir and balancing the multiple purposes of reservoir operation have attracted wide attention. While previous studies have incorporated ecological flow requirements in reservoir operation strategies, a comprehensive analysis of trade-offs among hydropower benefits, ecological flow, and ecological water temperature demands is lacking. Hence, this study develops a multi-objective ecological scheduling model, considering total power generation, ecological flow guarantee index, and ecological water temperature guarantee index simultaneously. The model is based on an integrated multi-objective simulation-optimization (MOSO) framework which is applied to Three Gorges Reservoir. To that end, first, a hybrid long short-term memory and one-dimensional convolutional neural network (LSTM_1DCNN) model is utilized to simulate the dam discharge temperature. Then, an improved epsilon multi-objective ant colony optimization for continuous domain algorithm (ε-MOACOR) is proposed to investigate the trade-offs among the competing objectives. Results show that LSTM _1DCNN outperforms other competing models in predicting dam discharge temperature. The conflicts among economic and ecological objectives are often prominent. The proposed ε-MOACOR has potential in resolving such conflicts and has high efficiency in solving multi-objective benchmark tests as well as reservoir optimization problem. More realistic and pragmatic Pareto-optimal solutions for typical dry, normal and wet years can be generated by the MOSO framework. The ecological water temperature guarantee index objective, which should be considered in reservoir operation, can be improved as inflow discharge increases or the temporal distribution of dam discharge volume becomes more uneven.

Multi-objective winter wheat irrigation strategies optimization based on coupling AquaCrop-OSPy and NSGA-III: A case study in Yangling, China

The contradiction between crop water requirements and water supplies in Guanzhong Plain of Northwest China restricts the production of local winter wheat. The optimization of irrigation strategies considering multiple-objectives is of great significance to alleviate water crisis and sustainability of winter wheat production. This paper considered three typical hydrological years (dry year, normal year, and wet year), and a simulation optimization model coupling AquaCrop and NSGA-III was developed using Python language. The multi-objective optimization problem considered four objectives: (1) maximize crop yield (Y), (2) minimize irrigation water (IW), (3) maximize irrigation water productivity (IWP), and (4) maximize water use efficiency (WUE). The TOPSIS-Entropy method was then adopted for decision-making based on the Pareto fronts which were generated by multi-objective optimization, thus facilitating the optimization of the irrigation strategies. The results show that AquaCrop model could accurately simulate the growth process of winter wheat in the study area, the relative error is acceptable. The R² of canopy cover (CC) is 0.75 and 0.61, and above ground biomass production (B) is 0.94 and 0.93, respectively. In the Pareto fronts, the difference between the maximum and minimum yield of winter wheat is 9.48 %, reflecting the diversity of multi-objective optimization results. According to the analysis results of this paper, the performance of different irrigation scenarios in each typical year varies greatly. The performance of the optimization in dry years is significantly better than that in normal years and wet years. The optimization of irrigation strategies and comparison of different scenarios play a positive role in improving the local water use efficiency, the winter wheat yield, as well as the sustainable development level of water resources.

Water strategies and water-food Nexus: challenges and opportunities towards sustainable development in various regions of the World

The twenty-first century is witnessing an explosion in global population, environmental changes, agricultural land disintegration, hunger, and geopolitical instabilities. It is difficult to manage these conditions or standardize improvement systems without thinking of the three main elements or subsystems that are necessary for any meaningful development-namely water (W), energy (E), and food (F). These key elements form what is globally agreed upon as the "WEF Nexus." While considering them, one should think about the other key factors that influence WEF Nexus, including population's growth, impacts of environmental changes (including climate change), moderation and adaptation regimes to climate change and climate resilience, loss of biodiversity, and sustainable nature. Together, the WEF Nexus subsystems represent a framework to ensure environmental protection that should be seen as an ethical and socioeconomic obligation. Issues, such as protection of water resources, and strategies and management tools or mechanisms for the use of water assets and agricultural innovations under the obligations of sustainable use, are investigated in this paper. Attention is paid to the relationship between water and food (WF Nexus) or water for food security in various world regions, including the Gulf Cooperation Council (GCC) countries, Central Asia countries and the Caucasus, China, Africa, and Canada. This paper also presents analyses of a great number of up-to-date publications regarding the "Nexus" perspective and its applications and limitations. This paper suggests that the Nexus' approach, in its different concepts (WEF, WE, WF and EF), can promote sustainable development and improve the quality of life of communities, while preserving natural, human, and social capital, addressing sustainability challenges, and protecting natural resources and the environment for long-term use.

Where Will ‘Water-Energy-Food’ Research Go Next?—Visualisation Review and Prospect

Research on water, energy, and food (WEF) is gradually becoming a global research hotspot in response to threats caused by the overexploitation of resources. In this study, 13,202 documents were selected from the WoS database and CiteSpace to judge frontier development in WEF research. In this study, visualisation research was carried out in 1547 papers that are most relevant to WEF research. The results show that WEF research has gradually increased during the research period, especially since 2015. The Food and Agriculture Organisation of the United Nations, Hoff, and Bazilian have the greatest influence on the promotion of WEF research and there is significant cooperation between institutions and countries. The United States, China, and the United Kingdom were the main contributors. The WEF nexus has become the most important hotspot in WEF research. In this case, 823 papers focused on the WEF nexus were selected to demonstrate the research contents, frontiers and clusters, and methods of the WEF nexus. Applied researches on the WEF nexus, such as security issues and multi-objective optimisation are current frontiers. Some new topics such as the pandemic and geopolitics have not attracted enough attention relative to their potential importance. A comprehensive data platform for the inter-department of water, energy, and food subsystems should be constructed in the near future.

Water-energy-ecosystem nexus modeling using multi-objective, non-linear programming in a regulated river: Exploring tradeoffs among environmental flows, cascaded small hydropower, and inter-basin water diversion projects

Small hydropower (SHP) possesses significant economic, technical, and environmental advantages, and accounts for a large proportion of hydropower development in China. However, the concentrated, cascaded, and diversion-type development of SHP has resulted in long-distance dewatering of river sections, and inter-basin water transfers have led to severe exploitation of water resources and damage to river ecosystems. In this paper, the Datong River Basin, a secondary sub-basin of the Yellow River Basin in China, was selected as the illustrative case, which includes 22 hydropower projects (HPPs) and three inter-basin water diversion projects (WDPs). A nexus system model was established that used weighted multi-objective programming to consider three main objectives: the water resources utilization (local water withdrawal and inter-basin water transfer), energy production (by cascaded HPPs), and riverine environmental conservation. The Tennant method was used to estimate the environmental flows (e-flows) at the cross-sections immediately downstream of the dam/sluice gate and immediately downstream of the hydropower plant of diversion-type HPPs. The decreased percentage of regulated flow in comparison with runoff and the guaranteed rate of e-flow at the control cross-section were introduced to assess the degree of environmental impact to the river. Using a historical series of runoff data during 1956-2016 as the model input (i.e., implicit stochastic method), the Multi-start solver of nonlinear programming of LINGO software was used to conduct optimizations and analyses for multiple scenarios (with/without e-flow, with consideration of various levels of e-flow, and with/without water resources utilization). The sectoral linkages relating to the water-energy-ecosystem (WEE) nexus were quantitatively identified. The possible influences of different boundary conditions (i.e., initial/final reservoir storage, inter-basin water diversion capacity, and climate change) on the WEE nexus were further explored. The present study aims to provide an exemplar for the optimal operation and scientific management of a complicated water resources system in a regulated river with cascaded SHP and inter-basin WDPs.

Artificial Intelligence in the Water–Energy–Food Model: A Holistic Approach towards Sustainable Development Goals

This study aims to analyze the role of artificial intelligence (AI) in the Water–Energy–Food (WEF) nexus under the lens of institutional, stakeholder, and innovation theories. Specifically, this study focuses on AI as the technology adopted by companies to promote Sustainable Development Goals (SDGs). A structured literature review has been conducted on 94 articles published from 1990 to 2021 in ISI Web of Science, Scopus, and Google Scholar. This study develops an in-depth review of the literature on the main articles arguing about these issues. The findings highlight the increasing relevance of AI in the water, energy, and food industries individually considered, but the study of AI as a connector between water, energy, and food to achieve SDGs is still under investigation. Research on AI for WEF nexus management has adopted mostly a technical perspective, neglecting the relevance of management tools and the business model concept. Most of the articles did not adopt a specific theoretical lens, but scholars recognize the need to adopt a multi-stakeholder approach and the important role played by AI and other digital technologies to address the WEF nexus challenge. This study proposes an integrated approach for managing the nexus through AI technologies to meet sustainable and responsible business models. The gap between research and policy making could be filled by combining scientific data and policy needs with inclusive tools that are technically viable for sustainable resource utilization.

Impact of Economic Development Level and Agricultural Water Use on Agricultural Production Scale in China

The change of agricultural production scale is directly related to food security and the stable development of social economy. Particularly, the influence of economic development level and agricultural water use on agricultural production scale cannot be ignored. Therefore, this paper uses the fully modified ordinary least squares (FMOLS) and the Dumitrescu–Hurlin panel causality test models to discuss the effects of the level of economic development, agricultural water use, the level of urbanization, and the market price of agricultural products on the scale of agricultural production in China. The analysis results indicated that agricultural water use, the level of urbanization, and the market price of agricultural products promoted an increase of the scale of agricultural production at the total sample level; a 1% increase for these three variables will result in an increase of the scale of agricultural production of 0.634%, 0.377%, and 0.292%, respectively. The influence of economic development level on agricultural production scale accords with Kuznets curve. However, at the regional level, the influence of each variable on the eastern region is consistent with the trend of the total sample. In the central region, the impact of economic development on agricultural production scale shows a U-shaped curve, and the improvement of urbanization level inhibits the expansion of agricultural production scale. In the western region, all variables failed to pass the significance test. The results of the FMOLS model were validated by the fixed effects model. The results of causality tests showed that bidirectional causality existed between the scale of agricultural production and the level of economic development, the scale of agricultural production and agricultural water use, the level of economic development and the market price of agricultural products, and the level of urbanization and the market price of agricultural products. In different regions, there were differences in causality between variables. Therefore, based on the empirical results, we put forward some policy suggestions to maintain the scale of agricultural production.

Prospects for Rooftop Farming System Dynamics: An Action to Stimulate Water-Energy-Food Nexus Synergies toward Green Cities of Tomorrow

Rooftop farming is a practical solution of smart urban agriculture to furnish diverse socio-environmental benefits and short food supply chains, especially in densely populated cities. This study aims to raise urban food security with less use of public water and energy in food production, through utilizing green water and energy for sustainable management. A system dynamics (SD) model framed across the nexus of climate, water, energy and food (WEF) sectors is developed for a rooftop farm in Taipei City of Taiwan. The urban WEF Nexus is structured to address how local weather affects water and energy utilization to grow vegetables. The SD results showed that the annual yields of sweet potato leaves achieved 9.3 kg/m2, at the cost of 3.8 ton/m2 of harvested rainwater and 2.1 ton/m2 of tap water together with 2.1 kwh/m2 of solar photovoltaic power and 0.4 kwh/m2 of public electricity. This study not only demonstrates that green resources show great potential to make a significant reduction in consuming urban irrigation resources for rooftop farming, but contributes to urban planning through a sustainable in situ WEF Nexus mechanism at a city scale. The WEF Nexus can manifest the rooftop farming promotion as cogent development to facilitate urban sustainability.

Linking reservoir ecosystems research to the sustainable development goals

Reservoirs account for about 10% of the freshwater stored in lakes worldwide. These reservoirs are home to 'reservoir ecosystems', that is, the aquatic and non-aquatic interactive ecosystems associated with artificial lakes where water is stored, typically behind a dam, for human purposes. While reservoir ecosystems provide various ecosystem services for sustainable development, their significance in research and policy has not been well understood and not well defined in the 2030 United Nation's (UN) Agenda for Sustainable Development. To advance understanding of reservoir ecosystems and their impact on policy, here we provide an overview of research on reservoir ecosystems and link it to UN SDGs and their Targets. Based on 5280 articles published in the last three decades, we applied network visualization to construct a framework for research addressing reservoir ecosystems. The framework covers four major themes: (1) ecosystem structure and function, (2) environmental pollution and stress effects, (3) climate impacts and ecological feedbacks, and (4) ecosystem services and management. We have found that sustainable reservoir ecosystems synergistically support 121 Targets of UN SDGs (71% of all). Reservoir ecosystems have both negative and positive implications for 15 targets (9%) and negative trade-offs for only 3 targets (2%). Thirty SDG Targets (18%) are unrelated to sustainable reservoir ecosystems. The synergies and trade-offs exist in three fields, securing basic material needs (SDGs 2, 6, 7, 14 and 15), pursuing common human well-being (SDGs 1, 3, 4, 5, 8 and 10), and coordinating sustainable governance policies (SDGs 9, 11, 12, 13, 16 and 17). Exploring these linkages allows better integration of reservoir ecosystems into the UN SDGs framework and guides sustainable management of reservoir ecosystems for sustainable development.

Risk Assessment of Water Resources and Energy Security Based on the Cloud Model: A Case Study of China in 2020

With the rapid development of economy and society, China’s demand for water resources and energy is increasing, and the supply situation is becoming increasingly severe. The correlation and binding characteristics between the two have become increasingly prominent, which will become bottlenecks in sustainable economic and social development in the future. In this paper, the Liang–Kleeman method was used to screen the risk factors of water resources and energy security, and then four major risk factors were selected. Based on the cloud model, the water resource and energy security risk assessment models were constructed combined with the predicted values using GM (1,1) and Pearson III curve methods, and the water resource and energy security risks of 30 provinces (cities) in 2020 were quantitatively assessed. The risk assessment results showed that the risk level zoning of water resource shortage with different guarantee rates in most regions has undergone little change, but the spatial distribution was quite different, showing the characteristics of “low in the South and high in the North”. When the guarantee rate changed from P = 25% to P = 95%, the risk level of water shortage in Sichuan, Jiangxi, Hunan, Hainan, Jilin, Ningxia and Nei Monggol significantly increased, and the spatial distribution of energy security risk and water resource shortage risk was obviously inconsistent.

The Relationship between Coordination Degree of the Water–Energy–Food System and Regional Economic Development

The sustainable development of the water–energy–food (WEF) system has gained global attention as a result of limited land resources, inadequate energy supply and growing water stress. Coordination degree is an important indicator to measure the sustainable development of the WEF system. Improving the coordination degree contributes to the sustainable development of the WEF system and affects regional economic development. The extended Cobb–Douglas function is applied to examine the relationship between coordination degree of the WEF system and regional economic development in 31 provinces of China during the period of 2007–2018. By using the system generalized method of moments (GMM) estimation, empirical results indicate that in the regions with low coordination degree, improved coordination degree of the WEF system will hinder regional economic growth. In the regions with high coordination degree, it will promote regional economic growth. The results indicate that there is a lag period for the influence of improved coordination degree on regional economic growth. When making resources management policies, shortening the lag period is conducive to achieving sustainable development and promoting regional economic development. Governments of various regions should formulate different resource management policies based on the conditions of each region and the different relationships between coordination degree of the WEF system and regional economic development.

Multi-Criteria Decision-Making Methods to Address Water Allocation Problems: A Systematic Review

The water allocation problem is complex and requires a combination of regulations, policies, and mechanisms to support water management to minimize the risk of shortage among competing users. This paper compiles the application of multi-criteria decision-making (MCDM) related to water allocation. In this regard, this paper aims to identify and to discern the pattern, distribution of study regions, water problem classifications, and decision techniques application for a specific water allocation problem. We applied a systematic literature review study from 2000 to 2019 by using four literature databases (Web of Science, Scopus, Science Direct, and Google Scholar). From 109 papers, 49 publications have been identified and information extracted. This study reveals that in the past two decades the application of MCDM in the area of water allocation has increased particularly after 2014. Around 65% and 12% of study papers were conducted in Asia and Europe, respectively. Water shortage, water use management, and water quality were consecutively the most top-ranked discussed water problems. NSGA II (non-dominated sorting genetic algorithm), GA (genetic algorithm), and LP (linear programming) are the more often applied decision methods to solve water allocation problems. The key findings of this study provide guidelines for future research studies.

A Robust Neutrosophic Modeling and Optimization Approach for Integrated Energy-Food-Water Security Nexus Management under Uncertainty

Natural resources are a boon for human beings, and their conservation for future uses is indispensable. Most importantly, energy-food-water security (EFWS) nexus management is the utmost need of our time. An effective managerial policy for the current distribution and conservation to meet future demand is necessary and challenging. Thus, this paper investigates an interconnected and dynamic EFWS nexus optimization model by considering the socio-economic and environmental objectives with the optimal energy supply, electricity conversion, food production, water resources allocation, and CO2 emissions control in the multi-period time horizons. Due to real-life complexity, various parameters are taken as intuitionistic fuzzy numbers. A novel method called interactive neutrosophic programming approach (INPA) is suggested to solve the EFWS nexus model. To verify and validate the proposed EFWS model, a synthetic computational study is performed. The obtained solution results are compared with other optimization approaches, and the outcomes are also evaluated with significant practical implications. The study reveals that the food production processes require more water resources than electricity production, although recycled water has not been used for food production purposes. The use of a coal-fired plant is not a prominent electricity conversion source. However, natural gas power plants’ service is also optimally executed with a marginal rate of production. Finally, conclusions and future research are addressed. This current study emphasizes how the proposed EFWS nexus model would be reliable and beneficial in real-world applications and help policy-makers identify, modify, and implement the optimal EFWS nexus policy and strategies for the future conservation of these resources.

A Bibliometric Analysis of Food–Energy–Water Nexus: Progress and Prospects

Food, energy and water are important basic resources that affect the sustainable development of a region. The influence of food–energy–water (FEW) nexus on sustainable development has quickly become a frontier topic since the Sustainable Development Goals (SDGs) were put forward. However, the overall context and core issues of the FEW nexus contributions to SDGs are still unclear. Using co-citation analysis, this paper aims to map the knowledge domains of FEW nexus research, disentangles its evolutionary context, and analyzes the core issues in its research, especially the progress of using quantitative simulation models to study the FEW nexus. We found that (1) studies within the FEW nexus focused on these following topics: correlation mechanisms, influencing factors, resource footprints, and sustainability management policies; (2) frontier of FEW studies have evolved from silo-oriented perspective on single resource system to nexus-oriented perspective on multiple systems; (3) quantitative research on the FEW nexus was primarily based on spatiotemporal evolution analysis, input–output analysis and scenario analysis; (4) the resource relationship among different sectors was synergies and tradeoffs within a region. In general, current research still focuses on empirical data, mostly qualitative and semiquantitative analyses, and there is a lack of research that can systematically reflect the temporal and spatial contribution of the FEW nexus to multiple SDGs. We believe that future research should focus more on how FEW nexus can provide mechanistic tools for achieving sustainable development.

Sustainability Considerations in Water–Energy–Food Nexus Research in Irrigated Agriculture

Irrigated agriculture is essential to satisfying the globally increasing demand for food and bio-based products. Yet, in water scarce regions, water-use for irrigation aggravates the competition for the use of water for other purposes, such as energy production, drinking water and sanitation. Solutions for sustainable food production through irrigated agriculture require a systemic approach to assess benefits and trade-offs across sectors. Here, the water–energy–food (WEF) nexus has become an important concept in natural resource management. It has been conceptualized to analyze linkages and trade-offs between the three sectors, across temporal and spatial scales. However, the concept has so far mainly been conceptual, with little empirical evidence or proof of concept in real world cases. The objective of this paper was to take stock of the rapidly advancing literature on the WEF nexus in irrigated agriculture, and to analyze how the concept was actually implemented in research studies, and how the nexus between water, food and energy was actually dealt with. The study period ranges from 2011 to 2019, and includes 194 articles. Results showed that the WEF nexus is indeed very relevant in irrigated agriculture, and the respective literature makes up one third of all WEF nexus papers. Modeling and empirical research have caught up with conceptual synthesis studies during the last four years, thereby indicating that the WEF nexus concept is indeed increasingly operationalized. However, most studies addressed the WEF nexus from a perspective of either socioeconomic, technological or environmental categories, and they place one of the dimensions of water, food or energy into the foreground. To address sustainable development, there is a need to fully integrate across research disciplines and thematic dimensions. Such studies are only starting to emerge. These findings are an important evidence-base for future WEF nexus research on irrigated agriculture, in support of sustainable solutions for water scarce regions, especially in settings undergoing transformations.

Advances in Hydrologic Forecasts and Water Resources Management

The impacts of climate change on water resources management as well as the increasing severe natural disasters over the last decades have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resources management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modelling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has the great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modelling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; and (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue can not only advance water sciences but can also support policy makers toward more sustainable and effective water resources management.

Managing the water-energy-food nexus in China by adjusting critical final demands and supply chains: An input-output analysis

The rapid population growth in China has increased the demand for limited water, energy and food resources. Because the resource supply is constrained by future uncertainties such as climate change, it is necessary to examine the connections among water, energy and food resources from the perspective of the relevant final demands. Based on an input-output model and structural path analysis, this study aims to explore the hidden connections among water, energy and food resources by identifying important final demands and examine how these resources are embodied in upstream production and downstream consumption processes along the supply chain. The water-energy-food nexus approach in this research identifies where and how these resources intersect in economic sectors. By simultaneously considering the water, energy and food footprints, synergistic effects can be maximized among these resource systems. The results reveal that urban household consumption and fixed capital formation have large impacts on water-energy-food resources. Besides, agriculture, construction and service sectors have the largest water-energy-food footprints. For each resource, we rank the top-20 supply chain paths from the final demands to the upstream production sectors, and six critical supply chain paths are identified as important contributors to the consumption of all these resources. Compared with independent approach to manage water, energy and food resources, the nexus approach identifies the critical linkages of the water, energy and food systems and helps to formulate integrated policies to effectively manage these resources across sectors and actors. Synergistic strategies for conserving water, energy, and food resources can be achieved through avoiding unnecessary waste in end uses and improving resource use efficiency along critical supply chains. This research can help consumers, industries and the government make responsible consumption and production decisions to conserve water, energy and food resources.

Explore the relationship between fish community and environmental factors by machine learning techniques

In the face of multiple habitat alterations originating from both natural and anthropogenic factors, the fast-changing environments pose significant challenges for maintaining ecosystem integrity. Machine learning is a powerful tool for modeling complex non-linear systems through exploratory data analysis. This study aims at exploring a machine learning-based approach to relate environmental factors with fish community for achieving sustainable riverine ecosystem management. A large number of datasets upon a wide variety of eco-environmental variables including river flow, water quality, and species composition were collected at various monitoring stations along the Xindian River of Taiwan during 2005 and 2012. Then the complicated relationship and scientific essences of these heterogonous datasets are extracted using machine learning techniques to have a more holistic consideration in searching a guiding reference useful for maintaining river-ecosystem integrity. We evaluate and select critical environmental variables by the analysis of variance (ANOVA) and the Gamma test (GT), and then we apply the adaptive network-based fuzzy inference system (ANFIS) for an estimation of fish bio-diversity using the Shannon Index (SI). The results show that the correlation between model estimation and the biodiversity index is higher than 0.75. The GT results demonstrate that biochemical oxygen demand (BOD), water temperature, total phosphorus (TP), and nitrate-nitrogen (NO₃-N) are important variables for biodiversity modeling. The ANFIS results further indicate lower BOD, higher TP, and larger habitat (flow regimes) would generally provide a more suitable environment for the survival of fish species. The proposed methodology not only possesses a robust estimation capacity but also can explore the impacts of environmental variables on fish biodiversity. This study also demonstrates that machine learning is a promising avenue toward sustainable environmental management in river-ecosystem integrity.

Transnational resource generativity: Efficiency analysis and target setting of water, energy, land, and food nexus for OECD countries

Depletion of natural resources needs quantification and efficiency analysis of the use of resources to improve sustainability. This paper evaluates the efficiency of Organization for Economic Co-Operation and Development (OECD) countries in terms of Water-Energy-Land-Food (WELF-Nexus) to ensure sustainability and environmental viability for both present and future generations. An input-output index system is built at a transnational level. Composite and intrinsic indicators are introduced to incorporate the interconnections and tradeoffs between sectors of the nexus and outcomes of the nexus. The nonparametric benchmarking order-α model, resulting from Data Envelopment Analysis (DEA) is used to estimate WELF-Nexus efficiency of each country, and to alleviate the intricacies of using composite and intrinsic indicators. To ensure resource generativity, an output target setting model that accommodates predefined input is proposed. Results show variation in performance among OECD members, with an annual average efficiency score of 68%, 69% and 78% in 2007, 2012, and 2016. Sensitivity analysis was performed to measure the effect of drought on WELF efficiency, a decrease of about 13% on average WELF efficiency was observed. Outputs improvement was recommended for each country: Lithuania (14%), Mexico (10%) and 11% for Hungary, Latvia, and Turkey due to their high inefficiency. The study provides a robust framework for policy making and shows that a win-win strategy for the nexus must be implemented to achieve WELF-Nexus efficiency, given the trade-offs within its sectors. Furthermore, it highlights that innovative-driven policies will enhance WELF-Nexus efficiency and sustainability.

A Literature Review to Propose a Systematic Procedure to Develop “Nexus Thinking” Considering the Water–Energy–Food Nexus

There is a growing interest in the literature on the theme of the water–energy–food nexus, as there is growing recognition that sectors that share natural resources have interdependent and interconnected systems. Despite the widespread popularity of nexus thinking, it still lacks standardized procedures and methodologies to assist in its development. Therefore, this paper proposes, from a literature review, a systematic procedure to assist in the development of management models based on nexus thinking. To this end, 304 papers were analyzed using the following criteria: nexus concept, type of approach, geographic scale, elements in the nexus system, application context, and types of assessment methods and tools. The results of the review served as the basis for determining the procedure, which consisted of four steps: (a) understanding nexus thinking, (b) identification of composing variables, (c) evaluation (diagnosis and prognosis), and (d) decision-making. In addition to the standardization of these steps, the main information used to compose the procedure was organized and synthesized with a mind map.

Multi-Objective Optimal Operation of the Inter-Basin Water Transfer Project Considering the Unknown Shapes of Pareto Fronts

Studies have shown that the performance of multi-objective evolutionary algorithms depends to a large extent on the shape of the Pareto fronts of the problem. Although, most existing algorithms have poor applicability in dealing with this problem, especially in the multi-objective optimization operation of reservoirs with unknown Pareto fronts. Therefore, this paper introduces an evolutionary algorithm with strong versatility and robustness named the Multi-Objective Evolutionary Algorithm with Reference Point Adaptation (AR-MOEA). In this paper, we take two water conservancy hubs (Huangjinxia and Sanhekou) of the Hanjiang to Wei River Water Diversion Project as example, and build a multi-objective operation model including water supply, ecology, and power generation. We use the AR-MOEA, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and the Indicator-Based Evolutionary Algorithm (IBEA) to search the optimal solutions, respectively. We analyze the performance of four algorithms and the operation rules in continuous dry years. The results indicate that (1) the AR-MOEA can overcome the difficulty of the shape and distribution of the unknown Pareto fronts in the multi-objective model. (2) AR-MOEA can improve the convergence and uniformity of the Pareto solution. (3) If we make full use of the regulation ability of the Sanhekou reservoir in the dry season, the water supply for coping with possible continuous dry years can be guaranteed. The study results contribute to the identification of the relationship among objectives, and is valued for water resources management of the Hanjiang to Wei River Water Diversion Project.

Evaluation of GloFAS-Seasonal Forecasts for Cascade Reservoir Impoundment Operation in the Upper Yangtze River

Standard impoundment operation rules (SIOR) are pre-defined guidelines for refilling reservoirs before the end of the wet season. The advancement and availability of the seasonal flow forecasts provide the opportunity for reservoir operators to use flexible and early impoundment operation rules (EIOR). These flexible impoundment rules can significantly improve water conservation, particularly during dry years. In this study, we investigate the potential application of seasonal streamflow forecasts for employing EIOR in the upper Yangtze River basin. We first define thresholds to determine the streamflow condition in September, which is an important period for decision-making in the basin, and then select the most suitable impoundment operation rules accordingly. The thresholds are used in a simulation–optimization model to evaluate different scenarios for EIOR and SIOR by multiple objectives. We measure the skill of the GloFAS-Seasonal forecast, an operational global seasonal river flow forecasting system, to predict streamflow condition according to the selected thresholds. The results show that: (1) the 20th and 30th percentiles of the historical September flow are suitable thresholds for evaluating the possibility of employing EIOR; (2) compared to climatological forecasts, GloFAS-Seasonal forecasts are skillful for predicting the streamflow condition according to the selected 20th and 30th percentile thresholds; and (3) during dry years, EIOR could improve the fullness storage rate by 5.63% and the annual average hydropower generation by 4.02%, without increasing the risk of flooding. GloFAS-Seasonal forecasts and early reservoir impoundment have the potential to enhance hydropower generation and water utilization.

Multi-Objective Joint Optimal Operation of Reservoir System and Analysis of Objectives Competition Mechanism: A Case Study in the Upper Reach of the Yangtze River

The multi-objective optimal operation and the joint scheduling of giant-scale reservoir systems are of great significance for water resource management; the interactions and mechanisms between the objectives are the key points. Taking the reservoir system composed of 30 reservoirs in the upper reaches of the Yangtze River as the research object, this paper constructs a multi-objective optimal operation model integrating four objectives of power generation, ecology, water supply, and shipping under the constraints of flood control to analyze the inside interaction mechanisms among the objectives. The results are as follows. (1) Compared with single power generation optimization, multi-objective optimization improves the benefits of the system. The total power generation is reduced by only 4.09% at most, but the water supply, ecology, and shipping targets are increased by 98.52%, 35.09%, and 100% at most under different inflow conditions, respectively. (2) The competition between power generation and the other targets is the most obvious; the relationship between water supply and ecology depends on the magnitude of flow required by the control section for both targets, and the restriction effect of the shipping target is limited. (3) Joint operation has greatly increased the overall benefits. Compared with the separate operation of each basin, the benefits of power generation, water supply, ecology, and shipping increased by 5.50%, 45.99%, 98.49%, and 100.00% respectively in the equilibrium scheme. This study provides a widely used method to analyze the multi-objective relationship mechanism, and can be used to guide the actual scheduling rules.

Synergies within the Water-Energy-Food Nexus to Support the Integrated Urban Resources Governance

Rapid urbanization poses great challenges to water-energy-food nexus (WEF-Nexus) system, calling for integrative resources governance to improve the synergies between subsystems that constitute the Nexus. This paper explores the synergies within the WEF-Nexus in Shenzhen city while using the synergetic model. We first identify the order parameters and their causal paths in three subsystems and set several eigenvectors under each parameter. Secondly, a synergetic model is developed to calculate the synergy degree among parameters, and the synergetic networks are then further constructed. Centrality analysis on the synergetic networks reveals that the centralities of food subsystem perform the highest level while the water subsystem at the lowest level. Finally, we put forward some policy implications for cross-sectoral resources governance by embedding the synergy degree into causal paths. The results show that the synergies of the Nexus system in Shenzhen can be maximized by stabilizing water supply, coordinating the energy imports and exports, and reducing the crops sown areas.

Mathematical modeling suggests high potential for the deployment of floating photovoltaic on fish ponds

Rising energy needs and pressure to reduce greenhouse gas emissions have led to a significant increase in solar power projects worldwide. Recently, the development of floating photovoltaic (FPV) systems offers promising opportunities for land scarce areas. We present a dynamic model that simulates the main biochemical processes in a milkfish (Chanos chanos) pond subject to FPV cover. We validated the model against experimental data collected from ponds with and without cover during two production seasons (winter and summer) and used it to perform a Monte-Carlo analysis of the ecological effects of different extents of cover. Our results show that the installation of FPV on fish ponds may have a moderate negative impact on fish production, due to a reduction in dissolved oxygen levels. However, losses in fish production are more than compensated by gains in terms of energy (capacity of around 1.13 MW/ha). We estimated that, with approximately 40,000 ha of aquaculture ponds in Taiwan, the deployment of FPV on fish ponds in Taiwan could accommodate an installed capacity more twice as high as the government's objective of 20 GW solar power by 2025. We argue that the rules and regulations pertaining to the integration of FPV on fish ponds should be updated to allow realizing the full potential of this new green technology.

Revealing the water-energy-food nexus in the Upper Yellow River Basin through multi-objective optimization for reservoir system

Since the 21st century, the natural runoff from the headwater region of the Yellow River has generally been decreasing, resulting in a particularly prominent contradiction in utilization of water resources. In this study, key components were identified from the perspective of water-energy-food (WEF) nexus, and a WEF nexus model was established for the Upper Yellow River Basin (UYRB), taking into consideration the benefits of water supply to the middle and lower reaches of Yellow River, food growth in major food-producing areas in the UYRB and hydropower utilization of the UYR reservoir system. The Multi-start Solver of LINGO and the ε constraint method were used to carry out multi-objective optimization, revealing the trade-off between the WEF benefits. 1) The model computed the Pareto non-inferior set of solutions for the electricity generated by the UYR reservoir system and the degree to which the water demands of the main intake areas (Ningxia and Inner Mongolia irrigated areas, and Toudaoguai section) are satisfied, quantifying the improvement room for the overall benefits brought about by the jointly optimal operation of the WEF sectors. 2) The historical operation of Longyangxia Reservoir, a multi-year storage reservoir, was evaluated, the results of which show that the realization of the WEF benefits is determined by the proper operation of Longyangxia Reservoir. To guarantee the overall benefits in the long term, Longyangxia Reservoir should maintain a high water level. 3) The trade-offs between the WEF benefits under different boundary conditions were discussed, including various initial/final fore-bay water levels of Longyangxia Reservoir and inflows of various total water amounts from the headwater region of the UYRB. The research reveals the WEF nexus in the UYRB under different scenarios, and moreover, the formulated multi-objective optimization model is a good example that can be extended to other similar WEF nexus systems worldwide.

Coupling and Coordination Degrees of the Core Water⁻Energy⁻Food Nexus in China

Achieving sustainable development in the water–energy–food (WEF) nexus is gaining global attention. The coupling and coordination degrees are a way to measure sustainable development levels of a complex system. This study assessed the coupling and coordination degrees of the core WEF nexus and identified key factors that affect sustainable development. First, an index system for assessing coupling and coordination degrees of the core WEF nexus was built. Second, the development levels of three subsystems as well as the coupling and coordination degrees of the core WEF nexus in China were calculated. The results showed that from 2007 to 2016, the mean value of the coupling degree was 0.746 (range (0.01, 1)), which was a high level. This proved that the three resources were interdependent. Hence, it was necessary to study their relationship. However, the mean value of the coordination degree was 0.395 (range (0, 1)), which was a low level. This showed that the coordination development of the core WEF nexus in China was low. It is necessary to take some measures to improve the situation. According to the key factors that affect the development levels of water, energy, and food subsystems, the authors put forward some suggestions to improve the coordination development of the WEF system in China.

A Food-Energy-Water Nexus approach for land use optimization

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.

Optimum socio-environmental flows approach for reservoir operation strategy using many-objectives evolutionary optimization algorithm

Water resource system complexity, high-dimension modelling difficulty and computational efficiency challenges often limit decision makers' strategies to combine environmental flow objectives (e.g. water quality, ecosystem) with social flow objectives (e.g. hydropower, water supply and agriculture). Hence, a novel Optimum Social-Environmental Flows (OSEF) with Auto-Adaptive Constraints (AAC) approach introduced as a river basin management decision support tool. The OSEF-AAC approach integrates Socio-Environmental (SE) objectives with convergence booster support to soften any computational challenges. Nine SE objectives and 396 decision variables modelled for Iraq's Diyala river basin. The approach's effectiveness evaluated using two non-environmental models and two inflows' scenarios. The advantage of OSEF-AAC approved, and other decision support alternatives highlighted that could enhance river basin SE sectors' revenues, as river basin economic benefits will improve as well. However, advanced land use and water exploitation policy would need adoption to secure the basin's SE sectors.