In 1992 the National Institute of Public Health and the Environment (RIVM) launched the interdisciplinary research programme ‘Global Dynamics and Sustainable Development’. The main objective of this research has been to investigate the concept of sustainable development from a global perspective. A key project within the programme was the development of a global model called TARGETS (Tool to Assess Regional and Global Environmental and health Targets for Sustainability). TARGETS belongs to a class of integrated assessment models which build on a tradition started in the early 1970s with the World3 model used in the Report to the Club of Rome. Despite better information and greater insights into the global system, a model like TARGETS only represents a simplified description of the world, and therefore still has many limitations and deficiencies. However, TARGETS distinguishes itself from previous integrated assessment models in that it deals explicitly with prevailing uncertainties in the form of perspective-based model routes.

It has been our intention for the TARGETS model to be used to assess the interlinkages between social, economic and biophysical processes on a global scale. One of our motivations has been the fact that the increasing rate and complexity of global change processes forces us to go beyond disciplinary boundaries and carry out integrative research, using integrated assessment models. We see the TARGETS model as a tool for experimenting with new concepts and techniques, not as some kind of ‘truth machine’ that generates predictions. More particularly, we have aimed at to produce fresh insights – not ready-made answers – on issues of global change processes in the context of the Rio Declaration on Sustainable Development and Agenda 21.

The National Institute of Public Health and the Environment (RIVM) is a centre of expertise that provides support to the Dutch government in the development of its National Environmental Policy. The relationship between economic activity in the past and projections for the future, as well as the implications for health and the environment, are quantified by means of simulation models in scenario-based studies. These models deal with a wide range of issues, ranging from local air and soil pollution to climate change. Integration of the models, which are defined ‘bottom-up’, enables ‘integrated assessment’ of alternative future environmental policies. Integrated assessment, however, cannot be based on a ‘bottom-up’ approach alone. As early as the 1980s, RIVM developed the IMAGE model which takes a ‘top-down’ approach, to describe climate change. This model, and the IMAGE 2.0 version, that was developed subsequently, have made a substantial contribution to the assessment rounds of the Intergovernmental Panel on Climate Change (IPCC). It was felt, however, that issues related to sustainable development, as discussed during the 1992 Rio Conference, should be more integrated. As a first step, RIVM cooperated with Dennis and Donella Meadows of the University of New Hampshire on a re-evaluation of their book Limits to Growth, which was presented to the Club of Rome in 1971. The results of this cooperation were published in 1992 in the book Beyond the Limits.

In this chapter we use the TERRA submodel to explore whether malnutrition and food insecurity can be eliminated while safeguarding the productive potential and broader environmental functions of agricultural resources for future generations. This is done within the context of the three cultural perspectives. The food problem is explained not so much as a problem of production but as one of availability and distribution. The submodel simulations are, however, largely confined to aggregate food demand and supply. Costs and environmental trade-offs are assessed in both utopian and dystopian worlds to determine under what conditions the planet will be able to feed its future population. We explore perspective-based scenarios for population and GWP, the surface area available for cropping, the use of irrigation, fertilisers and other inputs, wood production, reforestation, and the effects of changes in atmospheric CO2 and temperature.

Introduction

Currently, sufficient food is produced to feed the world population, yet at the same time more than 1,000 million people cannot afford or do not have the possibility to buy enoughfood to live healthy and productive lives. More than 500 million are chronically undernourished (FAO, 1993a). Malnutrition and food insecurity are not so much related to food production but rather to the unequal distribution of available food (IFPRI, 1995). This is caused by socio-economic factors such as poverty, the political situation, deficient infrastructure and (food) trade.

Any exploration of future developments inevitably involves a considerable degree of uncertainty and integrated assessment modelling is no exception. One of the major uncertainties has to do with the direction of policy-making. In order to accommodate a wide variety of world views and management styles, this chapter introduces the concept of multiple model routes. These are alternative ways of looking at model relationships, taking into account the bias and preferences of a number of stereo-typical perspectives. These perspectives, which each represent a different attitude to nature and society, are typified as hierarchist, egalitarian, individualist and fatalist. Matching a consistent management style with the first three (active) perspectives permits an analysis of ‘utopias’, while the opposite case – when world view and management style are out of step – reveals the risk of a number of possible ‘dystopias’.

Introduction

The future is inherently uncertain and thus unpredictable. Nevertheless, people in general, and decision-makers in particular, are interested in exploring future developments in order to make plans. One of the roles of science is to assist decisionmakers by sketching images of the future of the planet and of humankind. Scientists are facing an increase in both the magnitude and the degree of complexity. The issues currently associated with global change differ from other scientific problems in several respects (Funtowicz and Ravetz, 1993):

• they are global in scale and long term in their impact;

• the available data is lamentably inadequate; and

• the phenomena, being novel, complex and variable, are themselves not well understood.

This chapter introduces the integrated water assessment tool AQUA. This model has been developed to assist policy analysts assessing complex global water problems. A number of major long-term water policy issues are reviewed and AQUA is calibrated and validated against values in the literature. The model has been further validated at the regional level in studies that focus on the Zambezi and Ganges-Brahmaputra river basins.

Introduction

Managing water resources has become an independent field of expertise and a separate domain of public policy. Nowadays, however, many problems of water scarcity and pollution interact with socio-economic development and environmental change to such an extent that a single discipline or sector approach can no longer provide satisfactory solutions. Water flows are purposely being regulated via reservoirs, dikes, canals, and irrigation and drainage schemes. However, runoff is unintentionally being affected by changes in land cover and soil degradation in many parts of the world; future water availability may be affected by climate change; and water pollution is often part of a disturbance of total element cycles. In developing countries, limited availability of clean, fresh water is a major cause of many diseases. The world's food supply increasingly depends on irrigated agriculture and thus again on the availability of fresh water. There is a growing recognition that studies should focus on the interlinkages and feedback mechanisms between water and (other) environmental and human systems (Young et al., 1994).

This chapter discusses an integrated water assessment tool, the AQUA submodel, that has been designed to analyse complex water problems which cannot be understood without adopting a comprehensive approach towards environmental change and socio-economic development.

In this chapter we present simulation experiments and outcomes of the energy submodel TIME. First, the major controversies and uncertainties are discussed. Next, the cultural perspectives are introduced with reference to world energy, after which we clarify the way in which these are linked to assumptions and model routes. Some results of sensitivity and uncertainty analyses are also given. We discuss a few energy dystopias which could emerge if, for a given population-economy scenario, the world view and the management style within the energy system are discordant. Some conclusions are presented about the plausibility of and risks related to the utopian energy futures. The impacts of the emissions from fossil fuel combustion on water, land, and element cycles are discussed in the next three chapters.

Introduction

In 1886 Jevons warned in his book ‘The coal question’ about the rapid depletion of British coal fields threatening the British Empire. Numerous appraisals of coal, oil and gas availability have been made since then, many of them for strategic reasons. Environmental issues and the two oil crises in the 1970s have intensified the debate on fossil fuel use. Later on, it has been broadened by incorporating demand side management and renewable supply options and by including macro-economic aspects. Controversies and uncertainties about the future development of the world energy system abound.

This is the first of five chapters which focus on submodels within TARGETS. The framework of the Population and Health submodel includes socio-economic and environmental pressures, simulations of fertility, disease-specific mortality and morbidity, and their impact on population size, structure and health levels. The response subsystem comprises policies in the field of fertility and health. Whereas there are a number of separate models of fertility and population, the innovative aspect of the approach adopted here is that it is highly integrative, incorporating both population and health dynamics.

Introduction

During the past century, most populations of the world have experienced an increase in their levels of social welfare and economic development. These changes have shown a concomitant increase in the average life expectancy at birth and a decrease, although slower, in fertility levels (UNFPA, 1996; World Bank, 1993). The result has been an increase in world population size and a demand for resources unprecedented in history (UN, 1992; WCED, 1987). Reduction of health risks and the increased access to health services have resulted in a world-wide average life expectancy of more than 65 years during the past decades (WHO, 1996). Even though fertility rates are dropping, for some countries even rapidly, the world population is still growing at 1.5% per year. Presently, world population size in the year 2050 is estimated to be determined for about 50% merely by the present size of the fertile female population.

This chapter provides an introduction to the theme of the book by explaining the importance of the three central concepts global change, sustainable development and integrated assessment. The book focuses on five areas: population and human health, energy, water, land and food, and global biogeochemical cycles. The idea of using multiple definitions of sustainable development in an integrated approach to global change is put forward. The construction and use of the TARGETS integrated assessment model (Tool to Assess Regional and Global Environmental and health Targets for Sustainability) is justified in terms of providing a platform for communication within the scientific community that can inform policy debates about likely trends over the next 100 years or so.

Introduction

With the approach of a new millennium, global change and sustainable development are evolving as key concepts for assessing the future of the planet and of humankind. Over the last few decades, we have become used to the idea that our activities may have serious and irreversible impacts on the environment. Human-induced changes are recognised as having the potential to significantly modify the structure and functioning of the Earth system as a whole. Furthermore, activities at one place on Earth can affect the lives of people around the globe and even jeopardise those of future generations. The use of land, water, minerals and other natural resources by humans has increased more than tenfold during the past two centuries.

When tackling a subject as complex as global change and sustainable development, it is essential to be able to ‘frame the issues’. This was one of the main reasons for developing the TARGETS model, an integrated model of the global system, consisting of metamodels of important subsystems. In this chapter we introduce TARGETS. Building on the previous chapters, we elaborate on the possibilities and limitations of integrated assessment models. Some of the key issues discussed are aggregation, model calibration and validation, and dealing with uncertainty.

Introduction

One of the main tools used in integrated assessment of global change issues is the Integrated Assessment (IA) model. This chapter introduces such an integrated model, TARGETS, which builds upon the systems approach and related concepts introduced in Chapter 2. Previous integrated modelling attempts either focused on specific aspects of global change, for instance the climate system (IPCC, 1995), or consisted merely of conceptual descriptions (Shaw et al., 1992). We have tried to go one step further, linking a series of cause-effect chains of global change. Although we realise the shortcomings in our current version of the TARGETS model, we felt there was a need to present our model to a wide audience. We first give some advantages and limitations of IA models. Next, we discuss issues of aggregation, calibration, validation and uncertainty. We proceed with a brief description of the five TARGETS submodels which coincides with the PSIR concept and the vertical integration as introduced in Chapter 2. A more detailed description of these submodels is given in Chapters 4 to 8.

The most widely used social, economic and environmental indicators are scale, sector or subject-specific. Indicators for sustainable development, however, need to address the linkages between different aspects of global change and this requires a systemic approach. One way of systematically structuring the interlinkages between indicators is by using integrated assessment models. In this chapter we discuss indicators from a modeller's point of view, including their use for communicating model results. A hierarchical framework is introduced for models in general and TARGETS in particular.

Introduction

Indicators are pieces of information designed to communicate complex messages in a simplified, (quasi-)quantitative manner so that progress in the field of decision-making can be measured. Social and economic indicators have been used for decades at both the national and international level. More recently, environmental indicators have been developed, which are not yet as widely adopted as socio-economic indicators. The most widely used social, economic and environmental indicators are scale, sector or subject-specific. Indicators for sustainable development, however, need to address the interlinkages between the social, economic and environmental aspects of sustainable development. Because there are so many different linkages at different levels, this requires a systemic approach. One way of systematically structuring the interlinkages between indicators is by using models, in particular integrated assessment models.

Chapter 40 of Agenda 21 (UNCED, 1992) calls for the development of indicators for sustainable development, at multiple levels. Indicators for sustainable development are needed in order to provide decision-makers with information on sustainable development that is simpler and more readily understood than raw or even analysed data (Billharz and Molda, 1995).

Global change is an extremely complex phenomenon, encompassing a wide variety of issues. An adequate approach to such a broad subject demands careful consideration of a host of interactions between people and the environment and a clear understanding of driving forces, be the demographic, social, economic or technological. If we wish to tackle such a complex issue, we need to establish some basic guiding concepts. This chapter proposes an integrated systems approach to a number of key aspects of global change: population, health, energy, land, water and element cycles. We define what we mean by ‘system’ and ‘model’ and introduce a conceptual framework for analysing global change. As a mechanism to structure this conceptual framework we use the Pressure-State-Impact-Response (PSIR) approach. We look at two different kinds of integration (vertical and horizontal) and discuss different levels of complexity. Finally, we explain the importance of communicating the results of integrated systems analysis and suggest the value of using different communication methods such as indicators and visualisation.

Introduction

Most systematic studies of global change have so far focused on subsystems in isolation. However, it is well known that when parts are combined into more complex structures, the resulting system may exhibit quite different properties and behaviour (Gregory, 1981). As mentioned in Chapter 1, there is a growing interest in an integrated approach to global change (for an overview see Parson (1996) and Rotmans et al. (1996)).

This chapter synthesises the insights gained from the model experiments made in the previous five chapters. The hierarchist utopia examined in Chapter 11 is only one possible future. We now explore the consequences of two other utopian futures: the egalitarian and the individualist. A selection of conditional forecasts from integrated simulation experiments with population, food, water and energy supplies, land use, global temperature and sea-level rise are presented. One way of looking at the model outcomes is by focusing on the various transitions which characterise the development of the human-environment system. Extending the time horizon of the model simulations into the 22nd century yields additional insights into the relation between the human and the environmental system.

Introduction

The main goal of the TARGETS 1.0 model is to place possible developments within the subsystems of the world in an integrated perspective. In Chapters 12 to 16, simulation results of experiments with the TARGETS 1.0 submodels are discussed in isolation, while in Chapter 11 the results of an integrated simulation experiment for the hierarchist utopia are presented. In this chapter, we pursue this analysis further and include the other two perspectives. In this way we elaborate on the various controversies which have been raised in the preceding chapters: can a large population be maintained at an adequate health level and will there be enough energy, water and food without overburdening the natural environment? We start with the integrated utopias which are based on assumptions about world view and management style taken from a single perspective for all submodels (see Table 11.1).

INTRODUCTION

Heterogeneity of porous media has been a troublesome topic from the very beginning of groundwater hydrology as a quantitative science. Darcy (1856) recognized the necessity to quantify flow through porous media using a macroscopic, rather than a microscopic, viewpoint; he defined a flux based on an average linear flow path through a representative volume of porous media. Meinzer (1932) called heterogeneity the ‘most formidable difficulty’ in quantifying aquifer parameters. Shortly after this, Theis (1935) offered a solution to the heterogeneity problem by developing a way of calculating effective aquifer parameters. He demonstrated that by measuring the drawdown of water levels in response to pumping, it is possible to use an analytical solution to calculate effective aquifer parameters for average transmission and storage characteristics. Theis' method in essence replaces the heterogeneous aquifer with an equivalent homogeneous porous medium.

Theis' technique for dealing with heterogeneity allowed groundwater hydrologists to ignore geological heterogeneity for approximately 40 years. Then, Freeze (1975) called attention to the effect of uncertainty in hydraulic conductivity on the head distribution computed using groundwater models. About the same time, researchers were beginning to attempt to use the advection–dispersion equation to describe the transport of contaminant plumes in groundwater (Bredehoeft & Pinder, 1973; Pinder, 1973), and they were confronted with the problem of quantifying the dispersion coefficient. Slichter (1905) had earlier recognized that the spreading he observed in tracer experiments could not be due solely to the effects of molecular diffusion.

This book contains the refereed and edited proceedings of the Second IHP/IAHS George Kovacs Colloquium on Subsurface Flow and Transport: The Stochastic Approach, held in Paris, France, during January 26–30, 1995. The Colloquium was convened by Professors Gedeon Dagan and Shlomo P. Neuman under the auspices of UNESCO's Division of Water Sciences as part of its International Hydrological Programme (IHP), and the International Association of Hydrological Sciences (IAHS).

The book is devoted to issues of fluid flow and solute transport in complex geologic environments under uncertainty. The resolution of such issues is important for the rational management of water resources, the preservation of subsurface quality, the optimization of irrigation and drainage efficiency, the safe and economic extraction of subsurface mineral and energy resources, and the subsurface storage of energy and wastes. Over the last two decades, it has become common to describe the spatial variability of geologic medium flow and transport properties using methods of statistical continuum theory (or geostatistics). According to the geostatistical philosophy, these properties constitute spatially correlated random fields. As medium properties are random, the equations that govern subsurface flow and transport are stochastic. This book takes stock of mathematical and computational solutions obtained for stochastic subsurface flow and transport equations, and their application to experimental field data over the last two decades. The book also attempts to identify corresponding future research needs.

The book contains invited articles on selected topics by 15 leading experts in the emerging field of stochastic subsurface hydrology. All 15 authors have made seminal contributions to this field during its early formative years.

INTRODUCTION

Application of the stochastic paradigm to the problems of contaminant transport in porous media has been a major center of research activity over the last few years. This surge of activity reflects the growing recognition of this concept as a viable problem solving tool, as well as the increase in the efforts to solve environmental problems.

It is not the goal of this chapter to take stock of all that has been achieved in recent years. The alternative pursued here is to identify and analyze some central areas of activity within the discipline with a view toward recording problems that were resolved or became better understood, as well as others that still await resolution.

INTRODUCTION

The aim of aquifer simulation is to predict how hydraulic heads and solute concentrations respond to system stresses such as pumping and recharge. In many cases, simulation alone does not provide the results necessary to manage groundwater resources. What is needed is a design tool to find the best arrangement of pumping and recharge in order to control the heads and concentrations over space and time. One might want the managed head declines to be limited to some target value, or to ensure that solute concentrations never exceed water quality standards at supply wells. These controls must be maintained while achieving some objective, such as minimizing cost or risk. The recognition that simulation is not an end in itself has led to the development of aquifer management models.

During the past 30 years, the field of aquifer management modeling has developed as a distinct discipline. It has provided a framework which replaces trial and error simulations. Modern aquifer management models combine simulation tools with optimization techniques. The optimization techniques were developed in fields such as operations research and applied physics, and were adapted to unite with aquifer simulation models. This combination of formal optimization and aquifer simulation provides a framework that forces the engineer or hydrologist to formulate carefully the groundwater management problem. The problem must contain a series of constraints on heads, drawdowns, pumping rates, hydraulic gradients, groundwater velocities, and solute concentrations. In addition, an objective, usually involving costs, cost surrogates, or risk, must be stated. The power underlying this union of highly computational technologies was unleashed when computers became fast and cheap.