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Urban green space has increased significantly in many cities in China as a result of rapid urbanization. Despite various environmental and societal benefits of urban green space, its irrigation water use has become an important yet under-researched issue in urban water management. Using a newly developed green space evapotranspiration and soil water budgeting model coded in Python, this research estimated the irrigation water requirement of urban green space for 286 cities at the prefecture level and above in China, with daily meteorological data in 1986–2011, the distribution and areas of urban green space from the 30 m resolution “Essential Urban Land-Use Categories in China” database, and green space types from the 10 m resolution “10 m resolution global land cover” database. The estimated annual average irrigation water requirement of urban green space for these 286 cities was 8.7 billion m3, accounting for over 20% of residential water consumption in the cities where data on residential water use were available. We also investigated the spatiotemporal variation of urban green space irrigation water requirement and the factors that influence such variations. To the best of our knowledge, this study develops the first set of results of urban green space irrigation for all major cities in China, thus providing useful insights for green space irrigation and urban water man-agement in the context of rapid urbanization and sustainable water management.

The Mekong River is the largest transboundary river in Southeast Asia and the main source of water supply for agricultural irrigation in the Lower Mekong River Basin (LMRB), supporting socioeconomic development and the livelihoods of millions of people. Irrigation accounts for more than 70% of water use in the LMRB, and issues of water use and allocation in the basin attract much attention, especially in dry years. However, there is a lack of systematic and up-to-date estimation of irrigation water requirements (IWR) in the LMRB, for historical and climate change conditions, which are essential for water resources planning and management in the basin. We use gridded meteorological and crop land use data to estimate monthly IWR at 5-arc minute resolution in the five LMRB countries, namely Myanmar, Laos, Thailand, Cambodia and Vietnam, using meteorological observations of 1991-2020 and climate projections for 2031-2060 and 2061-2090 by five global climate models under two climate scenarios, SSP126 and SSP585. Crop water productivity and water footprint are also estimated along with IWR. Under historical climate, the total IWR in the LMRB is estimated to be 20.44 billion m3, with Vietnam having the largest share of 9.18 billion m3, followed by Thailand with 7.54 billion m3. IWR concentrates in the dry season of November-April, accounting for 78.4% of annual IWR. Rice is the main water-consuming crop, accounting for 86.7% of total IWR. Relative to historical climate condition, SSP126 generally leads to slightly decreased IWR, whereas SSP585 leads to a large increase in IWR. Crop water productivity of rice is unevenly distributed in the basin, being higher in Vietnam and Laos and lower in Cambodia and Thailand. Green water footprint of rice is about 3.7 times higher than that of blue water footprint, indicating most of rice water consumption is from precipitation. Under SSP126, there is little change in water footprint, however under SSP585 blue water footprint increases significantly, in 2061-2090. This study provides update-to-date and high-resolution IWR estimates which can support water use and allocation dialogue, policy-making and management in the basin.

Urban residential water uses entail energy consumption and associated carbon emissions. Reducing residential water uses thus can simultaneously save water and energy and help reduce carbon emissions. However, residential water uses are strongly affected by the choices of household appliances and fixtures, and water use behaviors. In this study, we first conducted a household water use survey in Shanghai, the largest city in China, to understand residential water use behaviors in different seasons. A two-stage stochastic optimization model is developed to optimize water and energy conservation decisions so as to minimize the expected total cost of water and water-related energy uses and maximize carbon emission reduction. Data collected through questionnaire surveys are used to parameterize the optimization model. Water and energy conservation choices are categorized into long- and short-term decisions. The results show that in Shanghai residential water uses has a strong impact on urban carbon emission reduction. Typical temperature range in different seasons strongly affects the effectiveness of short-term conservation actions. The results support a subsidy policy for water-saving appliances that can incentivize citizens in water-saving. Model results are useful for exploring the water-energy-carbon nexus of urban households considering seasonal factors

Agriculture is essential for economic growth in the Lower Mekong River basin (LMB), which plays a key role in ensuing water and food security of the riparian regions and provides livelihoods for tens of millions of people. Agricultural irrigation, hydropower development, increasing water demand from other sectors, and ecosystem protection necessitate taking a holistic approach when analyzing irrigation in the LMB. This paper examines the existing problems and opportunities of irrigation in the LMB from the angle of water-food-energy (WFE) nexus. We selected journal articles from the Web of Science database and imported them into CiteSpace, a bibliometric analysis software for visual exploration of scientific literature. The visualized results summarize the significance of authors and their affiliations in the selected body of literature, and the country-wise distribution. Four key research themes of LMB irrigation were identified based on the bibliometric analysis, for conducting an in-depth review. First, we investigated the factors that influence agricultural water management which directly affects irrigation water demand and supply as well as crop productivity. This part of the literature focused on water and land management and applications of various models to assess impacts on crop yields of irrigation management. Second, from the literature we analyzed the identified impacts of human flow alternations on downstream water uses, ecosystem health, and land subsidence due to groundwater overdraft. Nevertheless, upstream water management can mitigate downstream flood damages and augment dry-season water supply. Third, the spatiotemporal mismatch between water demand and supply pose a serious challenge for transboundary river basin management. Moreover, inappropriate water utilization, mismanagement and poor governance appear to be the more fundamental causes of the LMB water problems, thus calling for sound agricultural water policies within a riparian country and effective water management cooperation strategies across the riparian countries. Fourth, despite of the relatively few publications on the Mekong’s WFE nexus so far, this particular topic is gaining growing attention in the Mekong basin research community. Moreover, it offers a valuable holistic perspective for analyzing irrigation in the LMB, by considering its connections with the food and energy sectors in one way or another, compared against many existing studies that view irrigation as solely an agricultural water management problem.

Water shortage and soil salinization are main limiting factors in agricultural production in arid and semi-arid regions worldwide. Located in western Inner Mongolia of China, the Hetao Irrigation District (HID) is the largest gravity-fed irrigation district in Asia and one of the top three largest irrigation districts in China. Irrigation water overuse and high level of soil salinity are the main challenges that curb agricultural productivity, adversely affect farmers’ revenues, and threaten long-term sustainability of irrigated farming in the HID. Nevertheless, irrigation water allocation, salt leaching and accumulation, crop productivity and farming decisions are intrinsically connected and thus necessitate taking a holistic approach to investigate into the interactions among all those factors and devising appropriate technological, management and policy interventions. Towards this goal, an integrated hydro-agro--economic optimization model was developed to optimize water allocation among sub-irrigation districts, across stable and cash crops, and in the four irrigation events of a year that are unique for the HID. The model optimizes net revenue of the HID considering water and salt balance, the response of crops to salinity and water stress, land availability, and existing irrigation management practices that have been proved effective. The Positive Mathematical Programming (PMP) approach is used to calibrate the model such that it can reproduce base year observations of crop acreage, water uses and production costs and benefits, making the model suitable for evaluating alternative management and policy scenarios. Sensitivity analysis were conducted for initial groundwater table, initial soil salinity level and leaching coefficient, and the results were moderately sensitive to initial soil salinity and marginally sensitive to groundwater table and leaching coefficient values. Scenario analyses were conducted to analyze the effects of irrigation water supply, winter irrigation (non-growing period) water application, irrigation efficiency and crop commodity market prices. We found that water supply reduction increases land fallow and reduces net revenue. Winter irrigation can store soil moisture to increase summer crop planting areas and increase salt-leaching to lower crop salinity stress. However, irrigation water use efficiency improvement can cause unintended negative consequences, such as exacerbated soil salinization. Higher crop commodity market price increases planting areas and water allocation of the crop but reduce areas and water uses of other crops, leading to a “crowding-out” effects. These results and modeling exercises provide a holistic perspective and useful insights for future water, land and salinity management, irrigation infrastructure investment, and market risk management in the HID.

Highlights • Increased agricultural investments alone will not achieve SDG2 in Africa; complementary non-ag investments will be needed. • Climate change could lead to 16 million more people at risk of hunger compared to a scenario without climate change. • Investment in agriculture can more than compensate for the negative effects of climate change. • Enhanced agricultural R&D can reduce the prevalence of hunger by 55 million people in Africa. • Multi-model ensemble used to more holistically assess cost and benefits of increased agricultural investments in Africa., We use IFPRI’s IMPACT framework of linked biophysical and structural economic models to examine developments in global agricultural production systems, climate change, and food security. Building on related work on how increased investment in agricultural research, resource management, and infrastructure can address the challenges of meeting future food demand, we explore the costs and implications of these investments for reducing hunger in Africa by 2030. This analysis is coupled with a new investment estimation model, based on the perpetual inventory methodology (PIM), which allows for a better assessment of the costs of achieving projected agricultural improvements. We find that climate change will continue to slow projected reductions in hunger in the coming decades—increasing the number of people at risk of hunger in 2030 by 16 million in Africa compared to a scenario without climate change. Investments to increase agricultural productivity can offset the adverse impacts of climate change and help reduce the share of people at risk of hunger in 2030 to five percent or less in Northern, Western, and Southern Africa, but the share is projected to remain at ten percent or more in Eastern and Central Africa. Investments in Africa to achieve these results are estimated to cost about 15 billion USD per year between 2015 and 2030, as part of a larger package of investments costing around 52 billion USD in developing countries.

The pandemic of the coronavirus disease 2019 (COVID-19) has become a global public health crisis. The symptoms of COVID-19 range from mild to severe, but the physiological changes associated with COVID-19 are barely understood. In this study, we performed targeted metabolomic and lipidomic analyses of plasma from a cohort of patients with COVID-19 who had experienced different symptoms. We found that metabolite and lipid alterations exhibit apparent correlation with the course of disease in these patients, indicating that the development of COVID-19 affected their whole-body metabolism. In particular, malic acid of the TCA cycle and carbamoyl phosphate of the urea cycle result in altered energy metabolism and hepatic dysfunction, respectively. It should be noted that carbamoyl phosphate is profoundly down-regulated in patients who died compared with patients with mild symptoms. And, more importantly, guanosine monophosphate (GMP), which is mediated not only by GMP synthase but also by CD39 and CD73, is significantly changed between healthy subjects and patients with COVID-19, as well as between the mild and fatal cases. In addition, dyslipidemia was observed in patients with COVID-19. Overall, the disturbed metabolic patterns have been found to align with the progress and severity of COVID-19. This work provides valuable knowledge about plasma biomarkers associated with COVID-19 and potential therapeutic targets, as well as an important resource for further studies of the pathogenesis of COVID-19.

Advances in probabilistic seasonal flow forecasts sparked renewed interests to improve water management, through explicit incorporation of forecasts and forecast uncertainties into decision-making. Here, we develop a three-stage stochastic programming model to optimize integrated agricultural and urban water management decisions by directly considering probabilistic seasonal flow forecasts. The model represents urban water users which make short-term and long-term water conservation choices to maximize supply reliability and minimize conservation costs; it also represents irrigators which optimize land and water allocations to annual and perennial crops to maximize farm revenue, besides water transfers between agricultural and urban uses. Long-term urban conservation measures, areas of perennial crops, and capital investments in onfarm irrigation are considered in the first stage; annual crop areas, which depend on forecasted flows, are considered in the second stage; and reductions of irrigated annual and perennial crop areas due to water scarcity, conjunctive use operations, and water transfers informed by realized hydrologic year types are considered in the third stage. The temporal hierarchy of these decisions intends to approximate actual decision-making process by simultaneously considering long- and short-term decisions, forecasts, and forecasting skills. This paper provides a framework for quantifying the value of probabilistic forecasting information and forecasting skills, for managing complex regional water systems, including agricultural and urban water uses, water transfers, and conjunctive use of surface water and groundwater.

The Yangtze River Delta (YRD) is a major economic engine of China. Despite its bountiful natural resources, high population density, urbanization and rapid economic growth have led to increasingly high demand for water, energy and food, thus raising the region’s level of exposure to the risks of water, energy, or food insecurity. To analyze the current situation and identify challenges to resource sustainability, we build an input-output (IO) model for the YRD and link it to existing sector models of water, energy and food. The IO model explicitly represents interdependencies of the sectors including but not limited to water, energy and food, whereas the process-driven sector models provide additional details of spatiotemporal dynamics within each sector. A set of metrics were also designed to quantify the level of sustainability of the water, energy and food sectors in the YRD.

This article develops an economic model to analyze how the risk of water shortages affects farmers’ land irrigation decision and how the priority‐based water sharing arrangement redistributes such a risk among farms with different water rights priorities. The analysis brings together an array of comprehensive data files on irrigation rights, water supplies, and agricultural land use from eastern Idaho. Results indicate that a more left‐skewed distribution of streamflow significantly discourages land irrigation among farmers except the most senior rights holders. The priority‐based water sharing arrangement redistributes the macroscale risk of water shortages and thus exposes farmers of different water rights priorities to heterogeneous levels of risk: senior water rights holders are affected the least and such a risk is instead passed mostly on to junior water rights holders. The role of water rights in risk redistribution is more significant when the probability distribution of water shortage risk is asymmetric rather than symmetric. The historical development pattern of water rights influences how the priority of water rights takes effect on land irrigation decision.

The water-food-energy-GHG nexus under climate change has been gaining increasing attention from both the research and policy communities, especially over the past several years. However, most existing nexus studies are qualitative and explorative in nature. So far, very few studies provide integrated analysis of this nexus across all the four sectors. The purpose of this paper is to examine this nexus by assessing the effects of climate change on agricultural production through the change in water availability, evaluating the adjustment responses and resulting energy consumption and GHG emission, with the Northeast China as a case study. Based on our simulation results, by 2030, climate change is projected to increase water supply and demand gap for irrigation in Northeast China. Due to the increase in water scarcity, irrigated areas will decrease, and the cropping pattern will be adjusted by increasing maize sown areas and decreasing rice sown areas. As a result, the total output of crops and profits will clearly be reduced. Finally, energy consumption and GHG emission from irrigation will be reduced. This study suggests that climate change impact assessment fully consider the nexus among water, food, energy and GHG; however, more studies need to be conducted in the future.

A two-parameter annual water balance model was developed for reconstructing annual terrestrial water storage change (ΔTWS) and groundwater storage change (ΔGWS). The model was integrated with the Gravity Recovery and Climate Experiment (GRACE) data and applied to the Punjab province in Pakistan for reconstructing ΔTWS and ΔGWS during 1980–2015 based on multiple input data sources. Model parameters were estimated through minimizing the root-mean-square error between the Budyko-modeled and GRACE-derived ΔTWS during 2003–2015. The correlation of ensemble means between Budyko-modeled and GRACE-derived ΔTWS is 0.68 with p-value

The Water-Food-Energy nexus study identifies developmental challenges and trade-offs present along the transboundary river basins. Intensive reservoir development for hydropower production impacts existing actors in the Lancang-Mekong River Basin. Concerns from these stakeholders highlight three major trade-offs that occur between hydropower and irrigation (HP-AG), hydropower and fisheries (HP-F), and irrigation and fisheries (AG-F). Dam construction has an impact not only on power production but also on ecosystems and ultimately the livelihood of people. In this study, we quantify the effects of reservoir operation on hydropower generation, irrigated crop production and fisheries yield in the Tonle Sap lake through a novel hydro-economic model at the whole basin scale. Our main finding is that trade-offs can be turned into synergetic opportunities. First, the dam operation can increase water availability for irrigation without severely harming hydropower production, raising irrigated crop revenue by 49% and reducing crop losses during droughts by 30%. Second, eco-friendly management increases fisheries yield by up to 75%, but decreases both irrigated crop production (-48%) and power production (-17%). Reservoirs can, therefore, benefit the whole basin by releasing more water in months with high irrigation demand (April and December) and by minimizing the adverse effects of flow fluctuations on the livelihood of farmers and fishers living downstream. Our results also reveal the overlooked trade-off between irrigated agriculture and fisheries. Cross-sectoral and transboundary partnerships should strengthen stakeholder participation in decision-making. Local solutions such as enhanced reservoir operation can respond to the broader global issue of natural resource trade-offs and sharing. Our alternative narrative enhances the dialogue about fair and efficient water use among Mekong riparian countries.

Following the debate on whether drought has become more severe under climate change, this paper assesses drought frequency in northern and eastern India using two datasets of Palmer Drought Severity Index (PDSI) (generated by Dai, 2013 and Sheffield et al., 2012 ). The univariate return period for three drought characteristics (duration, severity and peak intensity) is examined regarding whether drought has occurred with longer duration, higher severity and/or larger peak intensity. The spatial variation of those changes is analyzed through eight areas in the study region. The temporal and spatial comparisons based on the univariate return period show different change patterns of duration, severity and peak intensity in different areas. Generally, in the areas which plant wheat more than rice (areas 1 and 2), drought has been alleviated in duration and intensity after 1955; while in the areas which plant more rice than wheat (areas 3–8), drought have been aggravated in duration, severity and intensity (except for area 8, a coastal area). This spatial change pattern may imply potential crop pattern change, for example, switching from rice to wheat in areas 3–7. Furthermore, the bivariate return period for pairs of drought characteristics based on the copulas and considering correlation between the drought characteristics is examined to understand how bivariate return periods change over time and space. Finally, it is also found that one data set (Sheffield et al.) results in more severe, longer and more intense drought in most of the areas, especially for the drought events with long-return-periods than the other (Dai).

The resolution adopted by the General Assembly of the United Nations on 25 September 2015 is symptomatic of the water-energy-food (WEF) nexus. It postulates goals and related targets for 2030 that include (1) End hunger, achieve food security and improved nutrition, and promote sustainable agriculture (SDG2); (2) Ensure availability and sustainable management of water and sanitation for all (SDG6); and (3) Ensure access to affordable, reliable, sustainable, and modern energy for all (SDG7). There will be tradeoffs between achieving these goals particularly in the wake of changing consumption patterns and rising demands from a growing population expected to reach more than nine billion by 2050. This paper uses global economic analysis tools to assess the impacts of long-term changes in fossil fuel prices, for example, as a result of a carbon tax under the UNFCCC or in response to new, large findings of fossil energy sources, on water and food outcomes. We find that a fossil fuel tax would not adversely affect food security and could be a boon to global food security if it reduces adverse climate change impacts.

Sudan is a country with a predominantly rainfed agriculture which is a major contributor to GDP, foreign exchange earnings, and livelihoods. However, with current and projected environmental changes on the horizon there is an urgent need to measure and analyze the impact of these changes. This study analyzes the economy-wide impacts of climate change and consults national policy plans, strategies, and environmental assessments to identify interventions for mitigating the effects. We feed climate forcing data, projected water demand, and macro-socioeconomic trends into a modeling suite, which includes models for global hydrology, river basin management, water stress, and crop growth. This modeling suite provides us with annual crop yields and global food prices under various climate change scenarios until 2050. The effects from climate change are assessed by using a single country dynamic CGE model for the Sudan. Additionally, we introduce yield variability into the CGE model based on stochastic shocks of crop yields until 2050. The results reveal that extreme negative variability could cost the Sudan cumulatively US$ 105.5 billion in GDP between 2018 and 2050 compared to a baseline scenario without climate change.

This paper describes the IMPACT Global Hydrological Model (IGHM), a component of the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) integrated modeling system. IMPACT has been developed in the early 1990s to identify and analyze long-term challenges and opportunities for food, agriculture, and natural resources at global and regional scales and builds on a series of previous food demand and supply projections models developed at the International Food Policy Research Institute since the early 1980s. The IGHM has been developed to assess water availability and variability as drivers of water use and irrigated crop production in IMPACT. It adopts a saturation runoff generation scheme and uses a linear groundwater reservoir to simulate base flow in 0.5º latitude by 0.5º longitude grid cells over the global land surface excluding Antarctica. The IGHM has four cell-specific calibration parameters, which are determined through maximizing the Kling–Gupta efficiency (KGE) with a genetic algorithm at the grid cell level, using gridded natural runoff series generated by the WaterGAP Global Hydrological Model (WGHM). During the calibration and validation periods, globally, the majority of grid cells attain KGE values greater than 0.50. As a meta-model of the more computationally expensive WGHM, IGHM transfers the climate-hydrology dynamics provided by WGHM into the integrated IMPACT model at a lower computational cost and enables coupling hydrology and other related processes considered in IMPACT which are important for analyzing long-term water and food security under a range of environmental and socioeconomic changes.

In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and Gross Domestic Product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose; the Southern African Development Community, the Southern African Power Pool, and trade of agricultural products amounting to significant transfers of embedded water.

Published in Agron. J. 107:1533–1538 (2015) doi:10.2134/agronj14.0256 Available freely online through the author-supported open access option. Copyright © 2015 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. aBstract

Efficient reallocation and conjunctive operation of existing water supplies is gaining importance as demands grow, competitions among users intensify, and new supplies become more costly. This paper analyzes the roles and benefits of conjunctive use of surface water and groundwater and market-based water transfers in an integrated regional water system where agricultural and urban water users coordinate supply and demand management based on supply reliability and economic values of water. Agricultural users optimize land and water use for annual and perennial crops to maximize farm income, while urban users choose short-term and long-term water conservation actions to maintain reliability and minimize costs. The temporal order of these decisions is represented in a two-stage optimization that maximizes the net expected benefits of crop production, urban conservation and water management including conjunctive use and water transfers. Long-term decisions are in the first stage and short-term decisions are in a second stage based on probabilities of water availability events. Analytical and numerical analyses are made. Results show that conjunctive use and water transfers can substantially stabilize farmer's income and reduce system costs by reducing expensive urban water conservation or construction. Water transfers can equalize marginal values of water across users, while conjunctive use minimizes water marginal value differences in time. Model results are useful for exploring the integration of different water demands and supplies through water transfers, conjunctive use, and conservation, providing valuable insights for improving system management.

Total crop production is a function of the harvested area and the yield. Many studies have investigated opportunities to increase production by closing the yield gap and by expanding cropland area. However, the potential to increase the harvested area by increasing the cropping frequency on existing cropland has remained largely unexplored. Our study suggests that the attainable harvested area gap (HAG) in China ranges from 13.5 to 36.3 million ha, depending on the selected water allocation scenario, relative to the current harvested area of 160.0 million ha. Spatially, South China and the Lower Yangtze region have the largest potential to increase harvested area, as these regions allow triple-cropping, have sufficient water available, and have a good irrigation infrastructure. The results imply that management factors are equally important for exploring the potential against the resource endowment: water allocation has a large impact on both the size and the spatial pattern of the attainable HAG. This indicates the necessity of further examining the spatial-temporal dynamics of HAG at national and regional scales, and its potential contribution to food security and sustainable agricultural development.

Water plays a major role in the climate system and in mediating impacts of climate variability and change on all sectors of the economy. The incorporation of water resources modeling into integrated assessment models (IAMs) to study climate–hydrology processes, related water impacts and adaptation options is thus an area of interest, yet it poses a number of methodological challenges. In particular, models of economic activity, climate, water availability and use, and adaptation are developed at differing temporal and spatial scales and with different goals. This makes their integration highly complex and computationally demanding. In this review we highlight a set of modeling challenges in water resource systems, describe the state of the art of approaches to integrating water resources modeling with IAMs and economic modeling, and identify constraints and opportunities moving forward in the development of water resources modeling within the IAM frameworks.

There is increasing interest in the water–food nexus, especially the restrictive effect of water on food production in hot spots where irrigation stress is growing. However, little is known about the larger-scale implications of future irrigation shortfalls for global trade and economic welfare, as well as of the potential buffering impacts of international trade on the local impacts of irrigation shortage. In this paper, we utilize a recently developed model, GTAP-BIO-W, to study the economic effects of changes in irrigation outlook for 126 river basins, globally by 2030. Projected irrigation availability is obtained from the IMPACT-WATER model, and imposed upon the present-day economy. Irrigation availability in 2030 is expected to drop by 30–60% in several key rivers basins, including: Hai He, Indus, Luni, and the Eastern Mediterranean basin, leading to significant output declines in China, South Asia, and the Middle East. We find that the regional production impacts of future irrigation water shortages are quite heterogeneous, depending on the size of the shortfall, the irrigation intensity of crop production, the possibility of expanding rainfed areas, as well as the crop mix. These changes in regional output significantly alter the geography of international trade. To compensate for the loss of productivity caused by the irrigation constraint, an estimated 7.6 million hectares of cropland expansion is needed to meet the demand for food. In spite of the remarkable reduction of irrigation in some basins, the resulting welfare impact is relatively modest as a result of the buffering capacity of global markets. The global welfare loss amounts to $3.7 billion (2001 prices) and results from a combination of the reduction in irrigation availability as well as the interplay with agricultural support policies.

The International Food Policy Research Institute’s International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) supports analysis of long-term challenges and opportunities for food, agriculture, and natural resources at global and regional scales. IMPACT is continually being updated and improved to better inform the choices that decisionmakers face today. This document describes the latest version of the model. IMPACT version 3 expands the geographic and commodity scope of the model in response to desires expressed by researchers and policymakers to address more complex questions involving climate change, food security, and economic development into the future. IMPACT 3 is an integrated modeling system that links information from climate models (Earth System Models), crop simulation models (for example, Decision Support System for Agrotechnology Transfer), and water models linked to a core global, partial equilibrium, multimarket model focused on the agriculture sector. This model system supports longer-term scenario analysis through the integration of these multidisciplinary modules to provide researchers and policymakers with a flexible tool to assess and compare the potential effects of changes in biophysical systems, socioeconomic trends, technologies, and policies.

This study summarizes the concept of the food-energy-water security nexus (FEW nexus). The aim is to create awareness about the importance of the nexus and to enable stakeholders to consider interconnections between the sectors in their work. The FEW nexus is discussed in the context of Africa south of the Sahara (SSA)—using Malawi and Mozambique as case studies. Even though analyzing food, energy, and water security issues simultaneously is critical given the interconnections, summarizing interventions with the FEW nexus approach in Malawi and Mozambique, we found that there are only a limited number of interventions in place. Additionally, this study reviews macro- and microeconomic models that are able to analyze the FEW nexus. On the macrolevel, especially general equilibrium models are discussed, because they show trade-offs and synergies of nexus interventions at all economic levels. These models can help guide policymakers’ understanding of nexus effects ex ante and convince them to think beyond their respective political departments. On the microlevel, the impact of nexus interventions can be assessed with qualitative and quantitative approaches. There are specific challenges for nexus interventions when it comes to aggregation and planning of the targeting. A secondary data analysis of nexus interventions shows that existing data is not sufficient to conduct research specifically related to the FEW nexus. The results of this study will help research programs to reflect the key questions required to enhance adoption of FEW technologies and inform policymakers as they formulate policies that will exploit the strong synergies of food security, energy, and water investments.