The agricultural community has a challenge of increasing food production by more than 70% to meet demand from the global population increase by the mid-21st century. Sustainable food production involves the sustained availability of resources, such as water and energy, to agriculture. The key challenges to sustainable food production are population increase, increasing demands for food, climate change, and climate variability, decreasing per capita land and water resources. To discuss more details on (a) the challenges for sustainable food production and (b) mitigation options available, a special issue on “Water Management for Sustainable Food Production” was assembled. The special issue focused on issues such as irrigation using brackish water, virtual water trade, allocation of water resources, consequences of excess precipitation on crop yields, strategies to increase water productivity, rainwater harvesting, irrigation water management, deficit irrigation, and fertilization, environmental and socio-economic impacts, and irrigation water quality. Articles covered several water-related issues across the U.S., Asia, Middle-East, Africa, and Pakistan for sustainable food production. The articles in the special issue highlight the substantial impacts on agricultural production, water availability, and water quality in the face of increasing demands for food and energy.

Quantifying the interactions of the food-energy-water (FEW) nexus is crucial to support new policies for the conjunctive management of the three resources. Currently, our understanding of FEW systems in metropolitan regions is limited. Here, we quantify and model FEW interactions in the metropolitan area of Phoenix, Arizona, using the Water Evaluation and Planning (WEAP) platform. In this region, the FEW nexus has changed over the last thirty years due to a dramatic population growth and a sharp decline of cultivated land. We first thoroughly test the ability of WEAP to simulate water allocation to the municipal, agricultural, industrial, power plant, and Indian sectors against historical (1985–2009) data. We then apply WEAP under possible future (2010–2069) scenarios of water and energy demand and supply, as well as food production. We find that, if the current decreasing trend of agricultural water demand continues in the future, groundwater use will diminish by ~23% and this would likely result in aquifer safe-yield and reduce the energy demand for water. If agricultural activities decrease at a lower rate or a multidecadal drought occurs, additional (from 7% to 33%) water from energy-intensive sources will be needed. This will compromise the ability to reach safe-yield and increase energy demand for water up to 15%. In contrast, increasing the fraction of energy produced by solar power plants will likely guarantee safe-yield and reduce energy demand of 2%. This last solution, based on an expanded renewable portfolio and current trends of municipal and agricultural water demand, is also projected to have the most sustainable impacts on the three resources. Our analytical approach to model FEW interconnectivities quantitatively supports stakeholder engagement and could be transferable to other metropolitan regions.

This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.

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.

Ecuador is facing several threats to its food and water security, with over a tenth of its population currently undernourished and living in poverty. As a response, its government is incorporating new patterns of land use and developing regional water infrastructure to cope with the related challenges. In this study, we assess to what point these efforts contribute to integrated water and food security in the country. We investigated the period 2004–2013 in the most productive agricultural region - the Guayas river basin district (GRBD) - and analysed the impacts of different scenarios of agricultural change on local water security. Our approach integrates MuSIASEM (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism) with the hydrological SWAT model. Freshwater allocation is evaluated within all the water cycle from its source (natural systems) to the final users (societal systems). Water security is assessed spatiotemporally in terms of water stress for the population living in poverty. Water productivity is obtained in relation to agricultural production and nutrition. The multi-scale analysis shows that whereas at river basin district level the median annual streamflow has a similar magnitude than rainfall stored in soil, these two parameters differ spatiotemporally at subbasin level. The study finds the greatest challenge in achieving water security is the south-east and central part of the GRBD, due to water scarcity and a larger population living in poverty. However, these areas are also simultaneously, where the greatest crop water productivity is found. We conclude that food production for both domestic consumption and market-oriented exports can be increased while meeting ecosystem water demands in all the GRBD regions except for the east. Our integration of methods provides a better approach to inform integrated land and water management and is relevant for academics, practitioners and policymakers alike.

Food security is inextricably linked with water and energy use in irrigated agriculture. This article develops an optimization model to evaluate the sustainability of water and energy use for food production, and the coordination among water, energy and carbon footprints. A case study of Heping Irrigation District, China, demonstrates the applicability of the model. We find that 87.47, 86.12, and 83.67 million m³ of irrigation water allocation are sustainable for high, normal, and low flow levels, respectively, considering economic, social and environmental benefits. The structure of surface water and groundwater allocation remains consistent for different subareas.

Climate change and variability will impact water availability and the food security of India. Trend analyses of historical data indicate an increase in temperature and changes in rainfall pattern in different parts of the country. The general circulation models (GCMs) also project increased warming and changes in precipitation patterns over India. This chapter presents examples of model applications in water management and crop yield simulation in India, focusing on climate change impact assessment. Simulation models have been successfully applied for rotational water allocation, deficit irrigation scheduling, etc. in different canal commands. Application of a universal soil loss equation in a distributed parametric modeling approach by partitioning watershed into erosion response units suggests that by treating only 14% of the watershed area, a 47% reduction in soil loss can be achieved. Simulation studies conducted using different hydrological models with different climate change projections and downscaling approaches showed varied hydrological responses of different river basins to the future climate change scenarios, depending on the hydrological model, climate change scenarios, and downscaling approaches used. Crop yield modeling showed decreases in irrigated and rainfed rice (Oryza sativa L.) yields under the future climate change scenarios, but the decrease is marginal for rainfed rice. Maize (Zea mays L.) yields in monsoon may be adversely affected by a rise in atmospheric temperature, but increased rain can partly offset those losses. Wheat (Triticum aestivum L.) yields are likely to be reduced by 6 to 23% and 15 to 25% during the 2050s and 2080s, respectively. A combined bottom-up participatory process and top-down integrated modeling tool could provide valuable information for locally relevant climate change adaptation planning.