Agriculture accounts for 70% of global water withdrawal. (FAO)
Roughly 75% of all industrial water withdrawals are used for energy production. (UNESCO, 2014)
The food production and supply chain accounts for about 30% of total global energy consumption. (UNESCO, 2012)
90% of global power generation is water-intensive. (UNESCO, 2014)
Global water demand (in terms of water withdrawals) is projected to increase by 55% by 2050, mainly because of growing demands from manufacturing (400% increase). More than 40% of the global population is projected to be living in areas of severe water stress by 2050. (UNESCO, 2014)
Power plant cooling is responsible for 43% of total freshwater withdrawals in Europe (more than 50% in several countries), nearly 50% in the United States of America, and more than 10% of the national water cap in China. (UNESCO, 2014)
By 2035, water withdrawals for energy production could increase by 20% and consumption by 85%, driven via a shift towards higher efficiency power plants with more advanced cooling systems (that reduce water withdrawals but increase consumption) and increased production of biofuel. (UNESCO, 2014)
There is clear evidence that groundwater supplies are diminishing, with an estimated 20% of the world’s aquifers being over-exploited, some critically so. Deterioration of wetlands worldwide is reducing the capacity of ecosystems to purify water. (UNESCO, 2014)
It typically takes 3,000 – 5,000 litres of water to produce 1 kg of rice, 2,000 litres for 1kg of soya, 900 litres for 1kg of wheat and 500 litres for 1kg of potatoes. (WWF).
While almost 800 million people are currently hungry, by 2050 global food production would need to increase by 50% to feed the more than 9 billion people projected who live on our planet (FAO/IFAD/UNICEF/WFP/WHO, 2017).
From Background paper for the Bonn 2011 Nexus Conference: THE WATER, ENERGY AND FOOD SECURITY NEXUS
From How Shell, Chevron and Coke tackle the energy-water-food nexus
We know how important food, water and energy are to our daily lives, but what happens when we fail to value them as critical, interconnected resources for our economy?
In the summer of 2012, the U.S. was affected by one of the worst droughts in recent decades. Eighty percent of U.S. farms and ranches were affected, crop losses exceeded $20 billion and unforeseen ripple effects followed.
With corn crops withering from the lack of rainfall, prices for food and livestock feed supplies rose, as did ethanol, predominantly sourced from corn. Numerous power plants had to scale back operations or even shut down because the water temperatures of many rivers, lakes and estuaries had increased to the point where they could not be used for cooling. Household, municipal and farm wells in the Midwest had to be extended deeper into rapidly depleting aquifers to make up for the lack of rainfall, draining groundwater supplies and demanding more electricity to run the pumps. It is estimated that consumers will feel these ripple effects for years to come — over the next year alone, this impact could result in personal costs up to $50 billion.
Now more than ever, our infrastructure is built on an interlinked system for the production and use of energy, water and food. Water is needed for almost all forms of energy production and power generation, energy is required to treat and transport water, and both water and energy are needed to produce food.
This interconnection, or energy-water-food nexus, underscores the global challenges that we face as a society. The growing global population, increased wealth and urbanization will continue to stress energy, water and food supplies. Climate change and unsustainable development practices will exacerbate them. In preparing for a population that could top 10 billion by 2050, according to U.N. estimates, in the next 15 to 20 years alone we will need 30 percent more water, 45 percent more energy and 50 percent more food.
Consvation International’s Business & Sustainability Council (PDF) examined the corporate risk and opportunities related to the energy-water-food nexus. The nexus is still new in the minds of many corporations, but CI sees several examples of companies broadening their strategies to build synergistic solutions.
Shell shines the spotlight on the pressures from the energy-water-food stress nexus in its 2013 report, “The New Lens Scenario.” The company is using scenario planning to test and collaborate on the design of synergistic solutions to tackle these interlinked resource constraints. In British Columbia, Shell collaborated with the city of Dawson Creek to build a reclaimed water facility that virtually eliminated its need to draw on local freshwater sources for the operation of a natural gas venture. It also worked with the World Business Council for Sustainable Development and the University of Utrecht to develop a new methodology that could more accurately estimate the amount of water needed to generate energy from different sources — oil, gas, coal, nuclear and biofuels — using different technologies and in different locations.
In Kern County, about 100 miles from Los Angeles and home to Chevron’s largest California oil field, Chevron partnered with the Cawelo Water District to provide much needed water to local farmers for agricultural use. Water is a significant byproduct from steam flooding, a technology employed to extract thick, viscous oil out of the ground. For every barrel of oil, 10 barrels of water are produced, about 700,000 gallons per day. Chevron reclaims about one-third to generate new steam, and provides most of the remaining treated water to the Cawelo Water District to distribute to 160 farmers to irrigate 45,000 acres of crops, such as almonds, grapes, pistachios and citrus. This innovative solution is critical to creating a more sustainable local water supply and helping Kern County growers keep agriculture thriving in the region.
Since 2005, The Coca-Cola Company has set an ambitious water security commitment for its beverages and operations. In order to meet its goal, it implemented a series of technical and natural solutions in nearly 400 community water projects in more than 90 countries. These community water partnerships include rainwater harvesting, drip irrigation, agricultural water efficiency improvements and protecting watersheds. The company has taken an even broader perspective, enhancing the ability of watersheds to absorb threats associated with the uncertainties around climate change, and increased demands for water, energy and food from a burgeoning population.
Ensuring energy, water and food security on a global level requires equal consideration of the interdependency among all three systems and the underlying natural capital that supports them.
CI believes that addressing the stress nexus requires collaboration among government, business and civil society. Public-private partnerships offer an innovative way to leverage expertise and financing in order to pilot practical, scalable and collaborative solutions. The Sustainable Landscape Partnership being piloted in Indonesia with support from CI, USAID and the Walton Family Foundation looks to understand integrated approaches to build local economies while reducing deforestation and ensuring food and water security.
Lack of data specific to the nexus is currently a limiting factor in building solutions. Improved frameworks to price natural resources such as water will be critical — one reason CI is engaged with WAVES and the TEEB for Business Coalition. CI is also piloting a game-changing monitoring system called Vital Signs in Africa to provide near real-time ecological and social data and diagnostic tools to guide agricultural development decisions and monitor their outcomes. As we continue to pilot models that demonstrate resiliency of landscapes, open platforms for information sharing will generate innovations and efficiencies.
Combined together, this integrated approach will be critical to fully understanding where critical nexus interactions lie, where they are most susceptible and how we can meaningfully make better decisions, for this generation and the next.
On Anticipation: Going Beyond Forecasts and Scenarios
From Anticipation.Info of Mihai Nadin
A Second Cartesian Revolution
For about 400 years, humankind, or at least the western world, has let itself be guided by the foundation set by Descartes and Newton. The cause-and-effect, deterministic model of the machine became so powerful that every thing and every being came to be considered a machine. As a description of the material world and as an expression of the laws governing its functioning, deterministic-based physics and Cartesian reductionism (of the whole to its parts) proved to be extremely powerful instruments in the overall progress of humankind. But neither Descartes nor Newton, nor most of their followers, could have envisioned the spectacular development of science in its current depth and breadth.
The physicist Erwin Schrödinger concluded that organisms are subject to “a new physics,” which he did not produce, but rather viewed as necessary. This new physics might well be the domain of anticipation. Indeed, from within physics itself—that is, quantum mechanics—a possible understanding of some aspects of anticipation can be derived.
The realization that the world is the unity of reaction and anticipation is not new. What is new is the awareness of the limits of our understanding a dynamics of change that transcends the deterministic view. The urgent need for such an understanding is probably best expressed in the spectacular development of the life sciences.
The perspective of the world that anticipation opens justifies the descriptor “a second Cartesian Revolution.” Instead of explaining complexity away, we will have to integrate it into our existence as the informational substratum of rich forms through which anticipatory processes take place.
From Anticipation.Info of Mihai Nadin
Anticipation: Why is it a subject of research?
Anticipation occurs in all spheres of life. It complements the physics of reaction with the pro-active quality of the living. Nature evolves in a continuous anticipatory fashion targeted at survival. The dynamics of stem cells demonstrate this mechanism. Through entailment from a basic stem cell an infinite variety of biological expression becomes possible.
Sometimes we humans are aware of anticipation, as when we plan. Often, we are not aware of it, as when processesembedded in our body and mind take place before we realize their finality. In tennis, for example, the return of a professional serve can be successful only through anticipatory mechanisms. A conscious reaction takes too long to process. Anticipation is the engine driving the stock market. Creativity in art and design are fired by anticipation.
“The end is where we start from,” T. S. Eliot once wrote. Before the archer draws his bow, his mind has already hit the target. Motivation mechanisms in learning, the arts, and all types of research are dominated by the underlying principle that a future state—the result—controls present action, aimed at success. The entire subject of prevention entails anticipatory mechanisms.
From Anticipation.Info of Mihai Nadin
Research into anticipation revealed various aspects that suggested a number of definitions.
Robert Rosen, Mihai Nadin, Daniel Dennett and others who approached particular aspects of anticipation contributed to some of these definitions. Mihai Nadin (cf. Anticipation – A Spooky Computation) attempted an overview of the various angles from which anticipation can be approached if the focus is on computation. This overview is continued and expanded in the integrated publication (book+dvd+website) to which this website belongs. The following 12 definitions, or descriptions, of anticipation should be understood as working hypotheses. It is hoped and expected that the knowledge community of those interested in anticipation will eventually refine these definitions and suggest new ones in order to facilitate a better understanding of what anticipation is and its importance for the survival of living systems.
An anticipatory system is a system whose current state is determined by a future state. “The cause lies in the future,”. (cf. Robert Rosen, Heinz von Foerster)
Anticipation is the generation of a multitude of dynamic models of human actions and the resolution of their conflict. (cf. Mihai Nadin)
An anticipatory system is a system containing a predictive model of itself and/or of its environment that allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant. (cf. Robert Rosen)
Anticipation is a process of co-relation among factors pertaining to the present, past and future of a system. (cf. Mihai Nadin)
Anticipation is an expression of the connectedness of the world, in particular of quantum non-locality. (cf. Mihai Nadin)
Anticipation is the expression of natural entailment. (cf. Robert Rosen)
Anticipation is a mechanism of synchronization and integration. (cf. Mihai Nadin)
Anticipation is an attractor within dynamic systems. (cf. Mihai Nadin)
Anticipation is a recursive process described through the functioning of a mechanism whose past, present, and future states allow it to evolve from an initial to a final state that is implicitly embedded in the mechanism. (cf. Mihai Nadin)
Anticipation is a realization within the domain of possibilities. (cf. Mihai Nadin)
Anticipatory mechanisms can be reinforced through feedback. Feedforward and inverse kinetics are part of the integrated mechanism of anticipation. (cf. Daniel Dennett, Daniel Wolpert, Nadin)
Anticipation is a power law-based long-range interaction. (cf. Mihai Nadin)
From An Introduction to the Ontology of Anticipation
Recent years have witnessed the growth of significant interest in theories and methodologies which seek to foresee the future development of relevant situations. Studies of the future fall under many different denominations, and they employ a huge variety of techniques, ranging from forecasting to simulation, from planning to trend extrapolation, from future studies and scenarios to anticipatory systems. Widely different conceptualisations and formalisations have been proposed as well.1 This remarkable variety may be partly simplified by making explicit the main underlying assumptions of at least some of them. Two of these assumptions are that (1) the future is at least partly governed by the past, and (2) the future can be better confronted by opening our minds and learning to consider different viewpoints. According to (1) the future is part of a structured story whose past and present are at least partially known. The claim is defended that the forces that have shaped past and present situations will still be valid while the situation under consideration unfolds. The core thesis is that the future is embedded in the past; it is the projection of the past through the present. Time series analysis, trend extrapolation, and forecasting pertain to this family. Any of the mentioned methodologies may be further supplemented by computer-based simulations. On the other hand, instead of directly addressing the problem of searching for the seeds of the future in the past, (2) considers the different problem of preparing for the unforeseeable novelties awaiting us in the future. Learning about widely different outcomes is now the issue: one must be ready to consider and address possibly unfamiliar or alien scenarios. The main outcome of this exercise is an increased capacity to distinguish among possible, probable, and preferred future scenarios. These activities come under the heading of future studies, while scenario construction is the best known methodology adopted by practitioners. For now on I shall refer to (1) and (2) as respectively the forecasting and the scenario viewpoints. Forecasts and scenarios are not contradictory one to the other. They may and usually do coexist, since they address the future from two different standpoints. Furthermore, experience shows that both are useful. This paper introduces a third, different viewpoint, here termed the viewpoint of anticipatory systems, which can be profitably synthesized with forecasts and scenarios; i.e. it is not contradictory with the claims of either the forecasting or scenario viewpoint. Recent years have witnessed the growth of significant interest in anticipation.2 Anticipatory theories have been proposed in fields as different as physics, biology, physiology, neurobiology, psychology, sociology, economy, political science, computer science and philosophy. Unfortunately, no systematic comparison among the different viewpoints has so far been developed. It is therefore fair to claim that currently no general theory of anticipation is available. Generally speaking, anticipation concerns the capacity exhibited by some systems to tune their behaviour according to a model of the future evolution of the environment in which they are embedded. Generally speaking, the thesis is defended that “An anticipatory system is a system containing a predictive model of itself and/or its enviroment, which allows it to change state at an instant in accord with the model‟s predictions pertaining to a later instant” (Rosen [19: 341]). The main difference between forecasting and scenarios on the one hand, and anticipation on the 1 See, among many others, Adam , Bell , Cornish , Godet , Lindgren and Bandhold , Retzbach , Slaughter , Woodgate and Pethrick . 2 Starting from the seminal Rosen . See also , . 2 other, is that the latter is a property of the system, intrinsic to its functioning, while the former are cognitive strategies that a system A develops in order to understand the future of some other system B (of which A may or may not be a component element).
John J Kineman
Daniel M Dubois
Key Sources of Research:
Systems and models with anticipation in physics and its applications
Art of Long View: Future, Uncertainty and Scenario Planning
Long term Thinking
Causal Layered Analysis
Kees Van Der Heijden
P J H Schoemaker
Arie De Gues
Thomas J Chermack
From How plausibility-based scenario practices are grappling with complexity to appreciate and address 21st century challenges
The tighter interconnections of natural, social and economic systems lead to increased uncertainty and greater complexity. The growing list of today’s significant concerns, whether focused on fixing the financial crisis or progressing socio-ecological sustainability highlights the urgency to look forward and manage large scale, system transformations  and challenges the conventional western economic wisdom of continuous, linear or exponential growth. Failure to engage with irreducible uncertainty is more widely appreciated and attempts to tame uncertainty can make matters worse .
Scenarios were introduced over 50 years ago as a means to overcome the limits of linear, reductionist and deterministic thinking that underpinned the then dominant practices of forecast-based planning. Scenario builders reject the notion of wholly predictable futures and instead seek to construct alternative futures which explore not only the paths to each, but do so in a way that emphasizes the need to attend to disruptive change as normal. Scenarios work is conducted in different sectors – public, private, civil and academia – and for a wide range of purposes, such as learning , strategy , or conflict avoidance .
Scenario practices have evolved from a “hypothetical sequencing of events constructed with the purpose of focusing attention on causal structures and decision points”  to attendance to the dynamic interactions that create disruptive and turbulent change as organizations co-evolve with their wider contexts . At the same time, continuous innovation and diversity of scenario practices result in methodological confusions and misunderstandings . To avoid contributing to further confusion we first define and then justify our interest in one particular tradition of practice.
Bradfield et al.  highlight three different scenario ‘schools’. In this paper we focus on what those authors refer to as Intuitive Logics, with its emphasis on plausible alternative futures, in contrast with the normative French School and the probabilistic USA School. Our choice to focus on the intuitive logics school is justified by evidence of its growing dominance in non-probabilistic scenario work .
Schoemaker  describes how plausibility-based scenarios are useful approaches in situations characterized by increasing uncertainty and complexity. He notes the effectiveness of scenarios as a psychological basis for addressing biases due to cognitive limits and overcoming ‘group think’ resulting from consensus building processes in social organizations.
In the intuitive logics tradition, the future is a fiction. Scenarios are ‘open stories’  and stories and storytelling are deployed as a means to engage intuition, expose deeply held assumptions and forge new and shared interpretative frames. The assumption is that the emerging future cannot be forecasted but can be imagined and “lived in” and offers a different perspective to learning about the present than history alone provides. In effect, plausibility-based scenarios offer reframing devices rather than forecasting tools [17,18]. Scenarios are not populated with facts but with perceptions, assumptions and expectations.
Quality of a good scenario is not determined by its predictive accuracy but by its impact which can be evaluated in different ways — cognitive shift, enhancing judgment, leading to more and better strategic options and/or motivating change .
Despite the extensive and continued use of intuitive logics scenarios in the public and private sectors, the diversity of methods can lead to a wholesale dismissal of these practices by empiricist traditions of inquiry and evidence-based decision making cultures [20,21]. At the same time organizations, such as Shell, which have sustained the practice of plausibility-based, intuitive logics scenarios for over 50 years, appreciate the added value in terms of enabling decision makers to engage with uncertainty, enabling systemic insights and contributing to the adaptive capacity of the firm .
In contrast with the objectivist and positivist ontologies of probabilistic scenario practices, constructivism, nominalism and post-normal science are the mainstays of the plausibility-based, intuitive logics tradition [10,12,48,49]. As Burrell and Morgan  noted, a realist sees the nature of reality as ‘out there’, hard and concrete, while the nominalist sees the social world as the result of individual cognition and made up of names, labels and concepts. Wilkinson and Eidinow  note the objectivist– constructivist dichotomy between probable and plausible scenario traditions. Scenarios are pragmatic rather than positivistic: events and behaviors are explained from the perspective of the individuals involved and thus reflect equally valid understandings from multiple points in a system. A central challenge is thus to navigate plurality  (Table 1).
For many complexity practitioners, the science of multi- level interconnected systems is extending the boundary of uncertainty where quantitative analysis is applicable. Agent- based modeling is one of the new techniques being used to undertake quantitative assessment of the probability of the collapse of system resilience , enabling a statistical forecast of the transition between various regimes of the system. Such approach proved relevant in addressing in- stabilities in financial markets and the role of contagion of norms as proposed by Axelrod , or Gintis  in the reframing obesity as an epidemic  rather than induced by the marketing of dubious foods.
Paul Cilliers  reflects on the ontology of complexity as follows: “The argument from complexity thus wants to move beyond the objective/subjective dichotomy”. He goes on to say that complexity science is in some ways an extension of the traditional scientific approach, but the ontological issues are shifted to the problem of boundaries. Since complex systems are open systems that interact with other systems, the choice of boundary is arbitrary. He quotes the notion of ‘operational closure’ as a useful approach, rooted in pragmatism. The uncertainty on the state of the system in the future is therefore objectively bound by formal mathematical modeling, but at the same time subjectively framed through the (explicit or implicit) choices concerning critical systems heuristics e.g. definition of the system boundaries.