Figure 5 - uploaded by Lorenzo Rosa
Content may be subject to copyright.
Global land area and its uses. Land area estimates are from Sachs (2015); the livestock contribution estimates are from Foley et al. (2011); the urban extent is a range from Potere and Schneider (2007) with <1% of land area in built-up urban areas.
Source publication
Water availability is a major factor constraining humanity's ability to meet the future food and energy needs of a growing and increasingly affluent human population. Water plays an important role in the production of energy, including renewable energy sources and the extraction of unconventional fossil fuels that are expected to become important p...
Contexts in source publication
Context 1
... a result, the global food system has become one of the most extensive ways by which humanity has modified the environment ( Ramankutty et al., 2008). Croplands and rangelands now cover approximately 38% of Figure 5). More than one half of the accessible runoff is withdrawn for human use (Richter, 2014), and nearly all of the anthropogenic consumptive water use (i.e., water loss to the atmosphere) is for agriculture . ...
Context 2
... other major share of water for energy is allocated to energy resource extraction (see previous sections). The water footprint of power generation is calculated in terms of consumptive use (i.e., evaporation losses), similar to the calculation for agricultural products (Figure 15). 6.1.7.1. ...
Context 3
... a result, the global food system has become one of the most extensive ways by which humanity has mod- ified the environment ( Ramankutty et al., 2008). Croplands and rangelands now cover approximately 38% of Figure 5). More than one half of the accessible runoff is with- drawn for human use (Richter, 2014), and nearly all of the anthropogenic consumptive water use (i.e., water loss to the atmosphere) is for agriculture . ...
Context 4
... other major share of water for energy is allocated to energy resource extraction (see previous sections). The water footprint of power generation is calculated in terms of consumptive use (i.e., evaporation losses), similar to the calculation for agricultural products (Figure 15). 6.1.7.1. ...
Similar publications
This chapter puts emphasis on the water security and aims to clarify the role of hydropower in the energy security of Armenia. Armenia can be considered one of the water-rich countries in the region, considering its significant water resources and the high amount of precipitation that feeds these resources. The universal water stress index categori...
Citations
... A changing lifestyle may require more meat, which results in greater land and water use for feed grain growth [73]. Urbanization leads to decreased arable land and limited agricultural water resources, thereby threatening food security [18]. Overall, these core elements and natural, economic, and social factors and their non-liner interrelationships render the WLFC nexus more complex. ...
To overcome the multiple challenges of water scarcity, agricultural land conversion, food security, and carbon emissions, an optimal collaborative management scheme for food production is urgently needed, especially in high food-production and food-consumption countries such as China. The water–land–food–carbon (WLFC) nexus provides a new perspective, but its interactions are complex, dynamic, and spatially heterogeneous; the coupling mechanism is not fully understood; and the driving forces and regulation strategies remain uncertain. Therefore, in this study, the WLFC nexus centered on low-carbon and high-quality agricultural development was systematically reviewed. The main contributions are as follows: (1) A framework of the regional agricultural WLFC nexus was proposed based on bibliographic analysis. (2) The main internal and external factors influencing the WLFC nexus in agriculture were identified by reevaluating meta-analysis review studies. The results showed that changes in the amount and type of irrigation water, the amount and planting activities of agricultural land, and climate change (temperature, precipitation, and CO2 concentration) affected food (rice, wheat, and maize) yields and carbon emissions to varying degrees. Moreover, population, technological innovation, trade, and polices were important external factors impacting food production and carbon emissions. (3) The common methods and tools for assessing, simulating, and optimizing the WLFC nexus in agriculture were summarized from the perspectives of its status, physical links, and embodied links. Integrated indices, complex system thinking, and process-based and data-driven methods were applied in the studies of the WLFC nexus. (4) Strategies and programs for collaborative WLFC management in agriculture within 10 global river basins were compiled. These findings could help us better understand the WLFC nexus in agriculture and identify the optimal cooperative management scheme, thereby realizing low-carbon and high-quality agricultural development.
... To overcome these challenges in the modelling of agri-food systems, Environmentally Extended Multi-Regional Input-Output (EE-MRIO) models are often employed [41][42][43], providing a thorough description of material flows in global supply chains, but introducing additional uncertainties due to known limitations of completeness and aggregation [44]. Parallel to this approach, a less data-intensive methodology was proposed by Kastner et al [31] and has been widely adopted to trace cultivation-related environmental impacts along food value chains [42,[45][46][47][48][49]. The assumption behind the algorithm is that a country's consumption originates in proportional shares from its own production and its imports. ...
Food loss and waste (FLW) is an issue of great public concern, due to its major impact on food security and on the social, economic and environmental resources involved in food production, trade and consumption. In this work, we put the lens on water resources, as those lost in the different stages of FLW represent about a quarter of the total freshwater resources used in food crop production. To this end, we propose the NETFLOW model (Network-based Evaluation Tool for Food LOss and Waste) as an innovative tool capable of reconstructing, for each commodity, the complex global multi-layered network linking FLW at each stage of the value chain with the corresponding wasted water resources. Food re-exports, nested supply chains, telecoupling of food markets, and different levels of food transformation are taken into account. Focusing on the emblematic case of wheat and its derived food commodities (e.g. flour, bread, pasta), we show the complexity and extent of the FLW-linked water network. For example, in 2016, more than 100 countries used their water resources (almost 3 km³) to produce wheat which was ultimately lost or wasted along the food consumption value chain in Italy, with almost half of this amount being directly attributable to the bread value chain. On the supply side, we show that about 18.3 km³ of water resources in the U.S. were lost through wheat-related FLW in 144 countries, about 40% for flour, 27% for raw wheat (mainly used for feed), and 24% for bread. The NETFLOW model proves useful in unravelling the complex links between (i) product-specific global trade networks, (ii) primary and derived products, (iii) country- and stage-dependent FLW, and (iv) country- and product-specific virtual water content.
... Water is critical for sustaining life and is central to nearly every human endeavor, including food and energy production [1]. Future water availability across regions is important to characterize yet deeply uncertain, given the complex nature of the global hydrologic cycle and the dependence of water supplies and demands on highly uncertain climate and socioeconomic conditions [2][3][4]. ...
... There are three major challenges associated with developing a global stochastic watershed model: (1) when applying a global stochastic model, we must account for spatial correlation across different water basins; (2) GHMs are computationally heavy, so our stochastic approach needs to be computationally efficient and not require many GHM simulations to generate ensemble members; and (3) there is no dataset of observed streamflow or runoff with a long enough historical record and sufficient spatial coverage to train the stochastic model. In this section, we describe how our stochastic watershed model addresses these three challenges. ...
There is significant uncertainty in how global water supply will evolve in the future, due to uncertain climate, socioeconomic, and land use change drivers and variability of hydrologic processes. It is critical to characterize the potential impacts of uncertainty in future water supply given its importance for food and energy production. In this work, we introduce a framework that integrates stochastic hydrology and human-environmental systems to characterize uncertainty in future water supply and its multisector impacts. We develop a global stochastic watershed model and demonstrate that this model can generate a large ensemble of realizations of basin-scale runoff with global coverage that preserves the mean, variance, and spatial correlation of a historical benchmark. We couple this model with a well-known human-environmental systems model to explore the impacts of runoff variability on the water and agricultural sectors across spatial scales. We find that the impacts of future hydrologic variability vary across sectors and regions. Impacts are felt most strongly in the water and agricultural sectors for basins that are expected to have unsustainable water use in the future, such as the Indus River basin. For this basin, we find that the variability in future irrigation water withdrawals and irrigated cropland increase over time due to uncertainty in renewable water supply. We also use the Indus basin to show how our stochastic ensemble can be leveraged to explore the global multisector consequences of local extreme runoff conditions. This work introduces a novel technique to explore the propagation of future hydrologic variability across human and natural systems and spatial scales.
... Similarly, the electricity consumption of cities also relies on electricity supplied from distant power plants distributed by the electricity grid (Siddik et al., 2020). Water is a critical input to both food and energy production (e.g., the Food-Energy-Water (FEW) nexus) (D'Odorico et al., 2018;Vora et al., 2017), which means that cities are linked to the distant watersheds-the physical organizing unit of hydrology and water resources-that support the production of FEW goods (Marston et al., 2015). In the United States, water supplies are projected to become more variable and scarcer under future climate and demand patterns (Brown et al., 2019). ...
Civil infrastructure underpins urban receipts of food, energy, and water (FEW) produced in distant watersheds. In this study, we map flows of FEW goods from watersheds of the contiguous United States to major population centers and highlight the critical infrastructure that supports FEW flows. To do this, we draw upon detailed records of agriculture, electricity, and public water supply production and couple them with commodity flow and infrastructure information. We also compare the flows of virtual water embedded in food and energy commodity flows with physical water flows in inter‐basin water transfer projects around the country. We found that the virtual blue water transfers through crops and electricity to major US cities was 53 billion and 8 billion m³ in 2017, respectively, while physical interbasin water transfers for crops, electricity, and public supply water averaged 20.8 billion m³. Highways are the primary infrastructure used to import virtual water associated with food and fuel into cities, although waterways and railways are most utilized for long‐distance transport. All of the 204 watersheds in the contiguous US support the food, energy, and/or water supplies of major US cities, with dependencies stretching far beyond each city's borders. Still, most cities source the majority of their FEW and embedded water resources from nearby watersheds. Infrastructure such as water supply dams and inland ports serve as important buffers for both local and supply‐chain sourced water stress. These findings can inform efforts to reduce water resources and infrastructure risks in domestic supply chains.
... The study of proper water management is considered crucial due to environmental, social, and economic challenges such as climate change, globalization, population growth, wasting water, and dietary habits changes [1][2][3][4], which put pressure on water resources [5]. Additionally, drought [6], water pollution [7,8], and poor water resource management [9] threaten the agricultural sector's sustainability. Certainly, it has been widely recognized for some time now that the natural resources (soil and water) employed in agricultural practices are no longer viewed as abundant and infinite reserves [10]. ...
Focusing on sustainability, the new Common Agricultural Policy (2023–2027) sets ambitious goals for water management, as reducing irrigation water use is a vital issue. Cooperation among farmers, relevant authorities, and researchers plays a significant role in achieving these objectives. Therefore, this study applies a multicriteria mathematical programming model to optimize land use, considering water use, profit, labor, and cost. The model was applied to three farmer groups located in Greece and proved to be valuable in the implementation of irrigation water use. Using the same methodology, two additional cases of farmer groups that utilize drylands are presented in complementary ways to investigate how the new CAP affects non-irrigated land uses. Regarding the irrigated case, reducing water usage involves decreasing the land dedicated to crops characterized by high water demand, such as rice, corn, vetch, and clover. This adjustment stems from the necessity to replace irrigated land with non-irrigated land because climate change demands low water consumption for crops and underscores the importance of the new policy framework to promote sustainable agriculture. As for the non-irrigated case, achieving optimal farm planning entails reducing the cultivated areas of vetch, grassland, and sunflower. This result is driven by the need to increase crops receiving primary subsidies, highlighting the necessity for non-irrigated farms to enhance their profitability through the benefits provided by the Common Agricultural Policy. Lastly, it is important to note that this study significantly contributes to guiding decision-makers in achieving alternative agricultural land uses and farm plans while also aiding in the comprehension of the new cross-compliance rules.
... GHG emissions and water consumption are generally major determinants of the environmental costs of food crop production, affecting all SDGs (Crippa et al., 2021;D'Odorico et al., 2018;Dalin et al., 2015;Liu et al., 2018). Based on the food sufficiency rate, we used carbon and water footprints to measure the environmental costs of feeding the Chinese population (Hoekstra and Wiedmann, 2014;Yang et al., 2020). ...
We assessed agricultural practices in China to identify workable solutions for sustainably feeding the Chinese population. We calculated the environmental costs of producing domestic rice, wheat, corn, soybeans, and imported soybeans. The environmental costs were enormous, and the food self-sufficiency and sufficiency (im-ported soybean included) rates were below 100 %. Subsequently, we assessed differences in environmental costs and crop yields between two main farming entities (small-holding and state-owned), effects of farm size, and uncertainties in soybean trade (China-US trade war and infrastructure improvement in Brazil). We presented scenario-based solutions that can reduce the carbon footprint, water footprint, and economic costs and increase both the food self-sufficiency and sufficiency rates above 100 %. Adopting the best-performing practices from both farming entities had the largest improvement effect. The individual solutions can improve China's United Nations Sustainable Development Goals ranking. Combined, they can act synergistically to navigate food crop production within a safe operating space.
... As the production and consumption chain of WEF are all intricately related, the WEF Nexus (WEFN) representing these relations was conceptualized at the Bonn 2011 Nexus Conference (D'Odorico et al., 2018;Mahlknecht et al., 2020). This interrelationship is reflected in both micro and macro aspects. ...
Water–energy–food (WEF) risks and security are widely concerned, but there are few quantitative studies on WEF security assessment, especially lacking of researches at the urban scale. This paper puts forward a measurement framework for assessing urban WEF security from social and economic perspectives, including dimensions of availability, accessibility, affordability, safety, and stability, and applies it to the WEF security assessment in the Yangtze River Delta urban agglomeration (YRDUA) by using an extended Multi-attribute Border Approximation Area Comparison (MABAC) method based on cloud model-CRITIC method and game theory. Based on the evaluation, social network analysis is used to study relations between cities in urban WEF security and determines key cities in the network. Results show that urban WEF security in most cities are positive; five dimensions of the WEF security level in each city show unbalanced characteristics; the level of energy security varies greatly among cities, followed by water and food security; urban WEF security from an economic perspective in most cities are positive, while it from a social perspective in almost half cities are positive; the spatial relation network of urban WEF security in YRUDA presents a core–edge structure; key cities in the region include Suzhou, Wuxi, and Changzhou. The evaluation framework and models help comprehensively evaluate urban WEF security at social and economic levels and put forward suggestions to enhance urban WEF security and promote horizontal cooperation among cities.
... Key commodities such as cattle, corn, dairy products, and soybeans contribute substantially to income generation. Environmental justice and equity considerations highlight the disproportionate impact of climate change on marginalized communities, exacerbating food insecurity among certain households and indigenous populations (D'Odorico et al., 2018). ...
Food is among the basic necessities of human life, and over the last decade global food supplies are facing severe challenge in form of growing population, increasing disease infestation, resource constraint, and climate change. At the same time global food demands are expected to increase by around 35–56% by the middle of the century. All this forecasts a dark image for global food security in coming decades. Plant pathogens are responsible for significant losses in major crops including wheat, rice, maize, soybean, and potato (up to 41% losses). In addition to this, the challenge of climate change is making things even worse as fluctuation in climatic patterns result in breeding and invasion of unorthodox pathogens and insects (collectively termed as pests) which can lead to major reduction in crop yields. Early detection and forecasting of these evolving pathogens is essential for disease management and to avoid severe infestations. Recent advances in artificial intelligence (AI) technology have the potential to deal with many of these challenges; massive weather forecasting and imagery dataset can be collected worldwide and analyzed using deep-AI models. This will ultimately provide real-time information regarding changing spatial-temporal dynamics of pests and alert policymakers, producers, and businesses to develop integrated strategy for mitigation of evolving pest infestation.
... The world is facing a daunting challenge characterized by increasing scarcity of food, water, and energy resources [1][2][3][4][5][6]. This scarcity is expected to be exacerbated by the impacts of climate change [7] and the needs of growing and more wealthy populations [8,9]. ...
... However, hydropower faces challenges due to diminishing natural water storage [12], increasing hydro-climatic variability [13] and concerns about its overall environmental sustainability [14][15][16][17]. Similarly, irrigated agriculture is the largest consumer of water worldwide [18], and anticipates further increases in water demand [4,19]. Irrigation faces similar challenges as hydropower from reduced natural water storage [20][21][22][23][24][25] and amplified climate variability [7,26], prompting concerns about its long-term viability [27]. ...
... Hydropower can provide electric energy with a relatively low carbon footprint, while irrigation will support food security without further increasing the global footprint of agriculture. Both hydropower and irrigation rely on grey infrastructure in several ways, but notably to provide water storage [4,27,76]. This joint reliance on water storage, often provided by the same grey infrastructure in the form of multi-purpose reservoirs, has created conflicts between these sectors in the past [101]. ...
Hydropower and irrigation are essential for achieving human development objectives and for climate mitigation and adaptation. These sectors depend on the same grey infrastructure, such as dammed reservoirs, which has created negative socio-ecological externalities and sectoral conflicts in the past. Yet, future needs for infrastructure in both sectors and their interdependencies remain unclear. We address this gap by applying data-fusion and machine-learning approaches and provide a comprehensive global overview and a new dataset that elucidates the role of existing dams and reservoirs for hydropower and irrigation. We then review projected demands for irrigation storage and hydropower by 2050 and analyze how projected growth aligns with the identified potential for irrigation and hydropower dams. Globally, projections point to an increased demand for hydropower in the order of 400 GW by 2050, which amounts to around 60 %–64 % of the identified potential and around +35 % compared to today. For irrigation, fully leveraging sustainable water resources would require 460 km3/yr of stored water, or around +70 % compared to today. Projected demands for hydropower and irrigation are larger than what future grey infrastructure could provide in many regions, especially in Europe, South Asia, and Africa. In such conditions, both sectors will be increasingly in competition for infrastructure. Our findings also highlight the need to study alternative solutions, such as other forms of renewable energy and nature-based solutions for water storage, to meet societal demands while avoiding negative externalities associated with grey water infrastructure.
... For life on land (SDG 15), potential enabling relationships include the repurposing of natural land, such as establishing wind and solar farms on degraded land 12 , whereas potential inhibiting relationships include the degradation of land quality when biomass contributes to soil erosion and degradation through the use of energy crops and the collection of crop residuals 13 . Regarding clean water and sanitation (SDG 6), potential enabling relationships include improved water-use efficiency 14,15 and potential inhibiting relationships relate to the reduced availability of drinking water, such as the contamination of underground aquifers from geothermal exploration, the tainting of potable surface water as a result of the leakage of biomass feedstock, and the allocation of significant water resources for hydropower infrastucture 16,17 . ...
Given the key role renewable energy plays in averting the impending climate crisis, assessments of the sustainability of renewable energy systems (RESs) are often heavily skewed towards their environmental benefits, such as reductions in carbon emissions. However, RES projects also have the potential to actively harm progress towards other aspects of sustainability, particularly when hidden within the energy generation process. Given the growing understanding of the ’dark side‘ of renewables, we must ask the question: Is renewable energy sustainable? To gain a better understanding of this issue, we analyzed the degree of alignment of seven aspects of the renewable energy production process with the Sustainable Development Goals (SDGs) and their targets for six renewable energy types categorizing the relationships as either enablers or inhibitors. This information makes it possible for decision- and policy- makers to move beyond carbon tunnel vision to consider the wider impacts of RESs on sustainable development.
