Parts II through IV of this book emphasize three separate aspects of landscape ecology (landscape structure, landscape function, and landscape change in structure and function) and their corresponding management paradigms (multi-scale management, cross-boundary management, and adaptive management). While separate aspects of landscape research and management paradigms are important, an integrated approach to study and manage landscape integrity is urgently needed. By landscape integrity, we mean overall measures of landscape health status. Although landscape integrity is a relatively unexplored subject, we believe that it can be measured by indicators, such as productivity and diversity of native species. As landscape integrity may result from the interactions between landscape structure and function, and it may vary with the dynamics of landscape structure and function, the management of landscape integrity requires an integrated approach incorporating multi-scale, cross-boundary, and adaptive management. It is essential that different types of management are balanced for different objectives and coordinated by integrating both spatial and temporal dimensions of landscapes. Integrated management considers landscape structure, function, and change simultaneously, and accounts for multiple resources at the same time. Because a landscape consists of multiple resources (e.g., forest, wildlife, land, water), considering only single resources will likely change the balance among various resources and thus result in imbalance or loss of landscape integrity. Furthermore, many resources depend on each other. For example, many wildlife species (e.g., birds) help trees in pollen transfer and seed dispersal. On the other hand, many trees provide wildlife species with food and shelter. The four chapters in Part V address various important issues related to landscape integrity and integrated management.

Introduction

Natural resource managers are increasingly charged with meeting multiple, often conflicting goals in landscapes undergoing significant change due to shifts in land use. Conversion from native to anthropogenic habitats typically fragments the landscape, reducing the size and increasing the isolation of the resulting patches, with profound ecological impacts (see Whitcomb et al., 1981; Harris, 1984; Wilcove et al., 1986; Robinson et al., 1995). These impacts occur both within and adjacent to the area under active management, creating new and extensive edges between habitat types. Boundaries established between management areas, for example, between timber harvest units or between reserves and adjacent agricultural fields, inevitably lead to differences in the quality of habitats on either side of the boundary, and a habitat edge results. Although edges are common components of undisturbed landscapes, the amount of edge proliferates rapidly as landscapes are fragmented (Fig. 8.1).

The creation of edges has important ecological implications at the individual, population, and ecosystem levels. Early ecologists and wildlife managers noted that community organization and species abundances are often markedly different near habitat edges (Leopold, 1933; Lay, 1938). Resource managers and conservation biologists have long attempted to translate these observations into managementactions,oftenbyattemptingtomaximizeorminimizetheamountof edge in some manner (e.g., Giles, 1971; Forman et al., 1976). Despite this long history of consideration and recent advances in understanding the consequences of habitat fragmentation, the development of tools for predicting these impacts has progressed slowly. In this chapter, we offer an historical perspective on attempts to address the influence of habitat edges on wildlife and ecological processes, and we describe a spatial modeling approach that can help managers quantify these effects and incorporate species-specific data into a predictive framework for comparing the likely impacts of alternative managements cenarios.

This final section provides syntheses and perspectives regarding the interrelationships between landscape ecology and natural resource management. Although many chapters in previous sections have offered different degrees of syntheses and have touched upon various aspects of future directions, Turner et al. elevate the syntheses to an even higher level, while Odum and Forman provide foresight regarding the future of landscape ecology and natural resource management.

Turner et al. (Chapter 18) synthesize the viewpoints and findings about the spatial interrelationships among landscape elements at multiple scales and discuss the challenges in the shift toward research and management of integrated ecosystems. They then identify the causes and types of gaps between landscape ecology and natural resource management, including differences in goals, incongruities of scale, tools and methods, training and experiences of landscape ecologists and resource managers, infrastructure and data, and institutional culture. To truly integrate landscape ecology into natural resource management and use management practices as opportunities for landscape ecological research, the authors offer practical suggestions for bridging each of these gaps.

Landscape ecology traditionally has focused on scales from patches to landscapes, but Odum (Chapter 19) argues that region is a more appropriate scale for addressing many land-use and environmental problems. His argument is supported by the fact that many ecological processes occur across landscape boundaries, as demonstrated by examples in many other chapters of this book, especially those in Part III (“Landscape function and cross-boundary management”). Further, he suggests that it is necessary to have closer cooperation between academic and non-academic institutions, as well as integration between social and natural sciences at large scales.

Introduction

Grasslands occupy large fractions of every continent except Antarctica (Knapp et al., 1998). In the United States, the Great Plains are generally divided into three regions: short-grass steppe in the west, mixed-grass in the center, and tallgrass prairie to the east (Reichman, 1987). The tallgrass prairie once stretched from central Canada to the Texas Gulf Coast and from eastern Kansas into Indiana. While large tracts of short- and mixed-grass grasslands still exist throughout the western Great Plains, it is estimated that 95.9% of the tallgrass prairie has been lost to agriculture. Illinois, Indiana, Iowa, North Dakota, and Wisconsin have lost 99.9% of their original tallgrass prairie (Samson and Knopf, 1994). The only extensive tract of tallgrass prairie that remains is the Flint Hills region of eastern Kansas, on the western, drier edge of the tallgrass prairie (Knapp et al., 1998) (Fig. 16.1).

Today, the tallgrass prairie is highly fragmented. Outside of the Flint Hills region, most prairies are remnants, often found in old cemeteries or railroad rights-of-way (Betz and Lamp, 1988). These prairies are often smaller than a hectare and usually isolated by tens of kilometers from the nearest remnant. The regional landscape of the tallgrass prairie region today is dominated by row-crop agriculture.

Grasslands provide multiple challenges to natural resource managers. Grasslands are often a complex mosaic of private, state, and federal land ownership. Land cover can consist of native or introduced (brome and fescue) species, small forests or woodlots, and agricultural crops. Land use can consist of grazing by livestock, row-cropping, and more recently residential development.

Introduction

Landscape change is one of the foremost themes underlying landscape ecology research. This theme ranges from a focus on the causes of landscape change to the effect of landscape change on ecosystems and organisms. The end result of such diverse research has been the creation of a large body of knowledge and significant advance in the scientific understanding of landscapes. However, while knowledge has advanced, scientists and resource managers have only begun to integrate the findings into natural resource management. One strategy in natural resource management that offers a strong potential for integration with landscape change is adaptive management.

Adaptive management differs from traditional resource management (Halbert, 1993) by treating management actions as experiments with testable hypotheses (Holling, 1978; Walters, 1986; Lee, 1993; Gunderson, 1999). The intent of adaptive management is to maximize the information gained and thereby reduce uncertainty about the system, especially for those areas suspected to be critical to proper system function. Moreover, adaptive management emphasizes applying new knowledge to help refine and possibly alter future actions (Holling, 1978; Walters, 1986; Lee, 1993; Gunderson, 1999). This approach can be applied to landscapes by dividing the landscapes into experimental units that meet management goals while providing information about how landscape change affects management actions.

The objectives of this chapter are two-fold: (1) to describe various patterns and causes of landscape change, and summarize its effects on wildlife; and (2) to discuss using landscape change information in adaptive management of wildlife resources. To highlight these objectives in a real world situation we will present a case study of two watersheds in Michigan's Lower Peninsula that have contrasting landscape structures and patterns of landscape change.

ABSTRACT

This chapter describes recent developments in the methods used to cope with uncertainty in water systems in Australia. The very high historical variability of Australian rainfall and runoff means that climate change simply may amplify a preexisting problem. Variability of flows to urban, irrigation, and environmental uses is considered, as well as issues of infrastructure robustness in the face of an increasing probability of large rainfall events. In general, the thrust has been to develop practices for flow allocation and demand management that are based on relative water availability, stochastically interpreted, rather than on absolute quantities. Operating rules are being adopted that allow decentralized decision making to take place within the constraints imposed by variability. This allows individual agents to express their risk preferences, and where possible to exercise their own decisions about risk and reliability. There is a growing need for expressions of social risk preference to be built explicitly into the trade-offs that are implicit in system design and operation.

VARIABILITY IN AUSTRALIA'S CLIMATE AND HYDROLOGY

The hydrologic environments of Australia and of Southern Africa are fundamentally different from those of the Northern Hemisphere. Even within the same climatic zones, annual flow variability of these Southern Hemisphere continents is two to four times that of northwest Europe and North America (see Table 7.1). For Australia, part of the difference is that the continent lies at the western end of the El Niño/Southern Oscillation (ENSO) system (Ropelewski and Halpert 1987) and is affected by rain depressions resulting from tropical cyclones.

ABSTRACT

One of the main characteristics of the sustainability concept is in the long-term evaluation of the possible set of outputs from any decision. Due to the fact that water resources projects have an extremely long physical lifetime and quite broad and diverse impacts, ranging from social, to environmental and economic outputs, the impact evaluation procedure is subjected to a substantial degree of uncertainty. Another approach is seen in the identification of actions that are as far as possible reversible to be able to cope with unexpected and disadvantageous outputs. It is the objective of this chapter to analyze the usefulness of measures such as reversibility to characterize sustainability. Two examples are investigated from which one is based on utilities that are time dependent, while in the other example a physically based approach is emphasized. Both examples refer to water and environmental management.

INTRODUCTION

Water management structures are designed for a long life time. Several reservoirs in the Middle East have been continuously operated for centuries and irrigation schemes date back over millennia (Garbrecht 1985; Garbrecht and Vogel 1991; Hartung and Kuros 1991; Glick 1970; Schnitter 1994; Petts, Möller, and Roux 1989). Similarly, navigation channels in Europe are being utilized since the medieval age, first for shipping purposes and now for recreation and tourism. On the other hand, many examples are known where reservoir capacity has been quickly decreased due to sedimentation processes, and large irrigation schemes are referenced which quickly lead to salinization of soils to such an extent that the irrigated area had to be abandoned (Goldsmith and Hildyard 1984).

ABSTRACT

A genetic algorithm model was developed to derive the best water allocation distribution within a multiple-reservoir water supply system. Three different objective functions were used to test the applicability of the model on a real-world seven-reservoir system. The appraisal of obtained solutions was carried out through the respective system's performance evaluation using a number of performance indicators. Due to the difference in the objective functions, the use of performance indicators proved crucial in the comparison of the solutions proposed by the three models. In addition, in all of the three cases the resulting release distributions produced in repeated runs of the same model showed substantial variability. The variability, however, was not reflected in the respective objective function achievement, indicating that there might be a number of potential solutions to the problem. In this respect, the comparison of the related performance indicator estimates was found to be a valuable means to provide a better insight into the essential difference between different solutions.

INTRODUCTION

Genetic algorithms (GA) fall into a group of search strategies that are based on the Darwinian concept of biological evolution. They apply the principles of natural genetics and selection to solve optimization problems related to artificial systems (Holland 1975). By using the objective function as a fitness measure, GAs emulate the Darwinian concept of “survival of the fittest” on a population of artificial beings to search the solution space of the optimization problem. The artificial “creatures” that the search is based on represent a specific coding of potential solutions to the problem.

ABSTRACT

A fuzzy compromise approach is applied to two water resources systems planning examples, for the purpose of allowing various sources of uncertainty and facilitating a flexible form of group decision support. The examples compare the ELECTRE method, and Compromise Programming, with the fuzzy approach. The fuzzy compromise approach allows a family of possible conditions to be reviewed, and supports group decisions through fuzzy sets designed to reflect collective opinions and conflicting judgments. Evaluating alternatives to produce rank orderings are accomplished with two ranking measures for fuzzy sets. The ranking measures are also shown to indicate the impact of different levels of decision-maker risk aversion. Two distinct ranking measures are used – a centroid measure and a fuzzy comparison measure based on a fuzzy goal.

INTRODUCTION

Multicriteria decision analysis (MCDA) has been moving from optimization methods to more interactive decision support tools. Some areas of interest have been identified by Dyer et al. (1992) as:

Uncertainty is a source of complexity in decision making that can be found in many forms. Typical ones include uncertainty in model assumptions and uncertainty in data or parameter values. There may also be uncertainty in the interpretation of results. While some uncertainties can be modeled as stochastic variables in a Monte Carlo simulation, for example, other forms of uncertainty may simply be vague or imprecise.

Traditional techniques for evaluating discrete alternatives such as ELECTRE (Benayoun, Roy, and Sussmann 1966), AHP (Saaty 1980), Compromise Programming (Zeleny 1973, 1982), and others normally do not consider uncertainties involved in procuring criteria values.

ABSTRACT

Flood damage in France and Europe in recent years has shown that there is still a long way to cope with this problem. It seems that the conceptualization of the risk by dividing it between a socioeconomical dimension (vulnerability) and a hydrologicalhydraulic dimension (hazard) is a promising means of investigation. Moreover, recent hydrological synthetic models, called flow-duration-frequency models, allow one to propose quantification of these two parameters of risk, that is, vulnerability and hazard. Estimating its spatial characteristics is very useful in the process of objective negotiation where land use managers take into account flood risk and socially acceptable risk. Representative maps, such as those proposed by the “inondabilité” model, can be forwarded to decision makers in order to help them use hydrological and hydraulic results in a more efficient way. These new concepts and methods should improve risk mitigation and lead to better acceptability of the risk level in the potentially flooded area.

INTRODUCTION

Extreme floods have been particularly numerous in France in the recent past. They caused severe economic and human damage. Among disastrous recent floods were those of Vaison la Romaine (1992), Corsica (1993) and Camargue area (1994), north and west of France (1994 and 1995), Var (1994), and so on. These events showed that flood risk management, and especially land use management in flood plains, is not sufficient to cope with the problem.

A risk policy should be based on three different aspects, as shown in Figure 6.1: these are prevention in the phase of land use management, flood forecasting and crisis management, and individual risk culture to improve citizen reactions to flood risk (Gilard and Givone 1993).

ABSTRACT

There are nearly 40,000 large dams in the world, increasing around 250 a year. More reservoirs need to be built, in developing countries, for anticipated population growth, upgrading standard of living, urbanization, flood control, hydroelectric energy, and so on. In developed countries, however, instead of reservoir construction, more emphasis will be placed on demand management and efficient use and reuse of water to meet higher environmental quality needs. Climate change would increase the importance of reservoirs but societal adaptation measures should precede the physical counteractions. The average sedimentation rate to fill reservoirs in the world may not be very high, but the rate is much higher in East and Southeast Asia where many reservoirs would suffer from sedimentation problems in the latter part of the twenty-first century. Reservoirs are the most important component for risk and uncertainty management of water resources systems. But for a reliable and robust water resources system, an integrated management and the administrative structure that makes it possible are most important. The integrated management is also the key strategy for sustainable reservoirs and water resources management.

INTRODUCTION

Reservoirs are indispensable to utilize running water for sustaining life and civilized activities. They must have been built ever since the beginning of human history and clearly since the emergence of irrigated agriculture. The oldest ruin of a dam may be the Sad el-Kafara Dam, 30km south of Cairo, Egypt (length 104m, height 11m and storage capacity 0.57 · 106m3), that was built around 2800 B.C. for water supply, and believed to be destroyed by the first hit of a flood (Biswas 1970).

ABSTRACT

A stochastic precipitation-runoff modeling approach is used to estimate water yield from a particular forested watershed in North Central Arizona. The procedure uses selected theoretical probability distribution functions and a random number generator to describe and simulate various precipitation characteristics, such as storm depth, duration, and time between storm events. The spatial characteristics of precipitation events are described in terms of their orographic and areal distribution patterns while temporal distributions are expressed in terms of daily events in the watershed. The generated precipitation events are used as input into a precipitation-runoff model to estimate water yield from a particular forested watershed. The method uses geographic information systems (GIS) to subdivide the study watershed into cells assumed to be homogenous with respect to watershed characteristics, such as elevation, aspect, slope, overstory density, and soil type. The total water yield is the accumulated surface runoff generated at the watershed outlet. The outcome is the development of an improved model for estimating water yield which takes into consideration uncertainty, as well as temporal and spatial watershed characteristics. This method is useful not only for providing water resources managers with a good estimate of the amount of water yield, but also for determining the reliability or failure of a source to meet desired downstream water demands.

INTRODUCTION

This chapter is concerned with the development of an appropriate precipitation-runoff model for estimating water yield from a semi-arid forested watershed. This involves combining a stochastic precipitation model and a deterministic runoff model. The first one is selected to capture the inherently uncertain characteristics of precipitation, while the latter is chosen to simplify an otherwise complex surface runoff estimation method.

ABSTRACT

Changing hydroclimatological conditions lead to changes in hydrological risk. Recent hydrological extremes such as floodings along the Rhine, Mississipi, or Oder Rivers can to a large extent be explained by the occurrence of unusual hydroclimatological extremes. Whether these extremes are part of natural variability, indicate possible climatic fluctuations, or are signals of an anthropogenically induced climate change is the first question to be answered. For this purpose, time series of different hydrological variables (atmospheric circulation patterns, rainfall, and runoff) are investigated. As hydrological risk is related to extremes, the series are investigated from that viewpoint, and not only from that of their mean behavior. Different statistical methods including nonparametric methods and bootstrap are applied to selected series to test the hypothesis of stationarity. Whenever this hypothesis is rejected, assumptions about the future have to be made. This can either be a scenario based on present trends, an assumption of stationarity at the present level, or a scenario based on a general circulation model (GCM). In the GCM case, due to the coarse resolution, a downscaling method is also needed. The next step is to assess the probabilities of extremes under these changes. It is demonstrated that areal precipitation extremes should be evaluated using not only precipitation amount but also duration and persistence of events. An example of extreme areal precipitation demonstrates this part of the methodology. On the basis of scenarios based either on present conditions or assumed trends, one may obtain a direct assessment of the flood risk. In contrast, GCM-based scenarios do not yield runoff values, thus a hydrological model has to be used to transform downscaled hydroclimatological series into runoff.

ABSTRACT

The U.S. National Weather Service has supported the development of an integrated probabilistic hydrometeorological forecasting system. The system produces probabilistic quantitative precipitation forecasts that are used to produce probabilistic river stage forecasts; these in turn are input to optimal decision procedures for issuing flood warnings, operating waterways and barges, or controlling storage reservoirs. The system is designed based on Bayesian principles of probabilistic forecasting and rational decision making. This chapter outlines the system concept.

INTRODUCTION

Systems approach to hydrometeorological forecasting

That forecasts should be stated in probabilistic rather than categorical terms has been argued from operational (Cooke 1906) and decision-theoretic (Murphy 1991) perspectives for almost a century. Yet most operational systems produce deterministic forecasts and most research in physical and statistical sciences has been devoted to finding the “best” estimates rather than probability distributions of predictands. Undoubtedly, the leap from a deterministic frame of thought to one that not only admits our limited knowledge and information, but also quantifies uncertainty about future states of the environment, requires a vast and coordinated effort at two levels: engineering – to design probabilistic forecasting systems, and organizational – to alter the institutional mindset and modus operandi.

The U.S. National Weather Service (NWS) has embarked on making such a quantum change (Zevin 1994; Krzysztofowicz 1998). The goal is to increase the value of service to users by developing and implementing an integrated probabilistic hydrometeorological forecasting system.

ABSTRACT

Measuring the relative sustainability of water resources systems is much needed though very difficult. Being able to quantify sustainability makes it possible to evaluate and compare development alternatives, plans, and policies in order to choose the preferred solutions. It also makes it possible to include sustainability as one of multiple objectives in system design and operation. Commonly used multiple risk criteria – measures of reliability, resilience, and vulnerability – are combined into an aggregate index quantifying relative system sustainability. The procedure is illustrated in an example of regional development alternatives.

INTRODUCTION

Ever since the concept of sustainability, as expressed in the Brundtland Commission's report Our Common Future (WCED 1987), was introduced, professionals from many disciplines have been trying to define and measure it. This has turned out to be more difficult than expected. Nevertheless, this chapter attempts to do so, that is, to define sustainability in a manner that can help us better address some of the many issues and challenges that accompany the Commission's concept of sustainability. At the same time this definition should allow us to measure or quantify, at least relatively, the extent to which sustainability is being, or may be, achieved. We need such measures if we are to evaluate our development alternatives and monitor our water resources systems, and indeed our economy, our environment, and our social systems to see if they are becoming increasingly sustainable.

ABSTRACT

Uncertainty in flood forecasts is dominated by errors in the measurements and forecasts of rainfall used as input. Error magnitudes are influenced by raingauge network density (possibly used in combination with weather radar), by rainfall intensity, and by the method of rainfall forecasting employed. An empirical approach to quantifying uncertainty associated with rainfall measurements and forecasts is taken, supported by data from two dense raingauge networks, together with weather radars, in southern Britain. The impact of uncertainty in rainfall on flood forecasts is examined through a comprehensive case study within the Thames basin in the vicinity of London. This study also allows the relative effect of model and catchment on flood forecast uncertainty to be better appreciated. Reliability of flood forecasts is considered in the context of the complexity of region-wide flood forecasting systems and the need to ensure that forecasts are made under all situations, including the possible loss of significant telemetry data. The River Flow Forecasting System's Information Control Algorithm is outlined as a solution to providing reliable forecasts, coping with both complexity and data loss. Risk is considered here in the context of when to issue a flood warning given an uncertain flood forecast. The use of both informal and more formal methods of ensemble forecasting is introduced as a means of quantifying the likelihood of flooding implied by a flood forecast.

INTRODUCTION

Flood forecasting systems function in real-time to transform telemetered field measurements (principally relating to river level and rainfall) and external forecasts (especially of weather) to forecasts of river level and flow, possibly along with settings associated with river control structures and reservoirs.

ABSTRACT

A three-phase system framework is identified to assess uncertainty in the risk analysis of water resources systems under climate change. The uncertainty arises among others from the hydrometeorological inputs, such as precipitation and temperature, that are used for predicting extreme events (floods and droughts) under climate change. These inputs play an important role in the three system phases, namely planning, design, and operation. In this study, the hydrometeorological inputs under climate change are obtained by using downscaling models that use information from a general circulation model (GCM) output. The uncertainty is assessed by a new technique using a fuzzy approach. The methodology is illustrated by an example of uncertainty assessment in the risk analysis of a water resources system under climate change in a semi-arid region.

THREE-PHASE SYSTEM FRAMEWORK

A water resources system, such as a reservoir built for flood control or for water supply during severe droughts, may be described in three phases, namely planning, design, and operation. Planning phase of a water resources system must take into account multiple users, multiple purposes, and generally multiple criteria and/or objectives. Furthermore, in the planning phase, the emphasis also needs to be given to the system sustainability. A sustainable system should not only meet the present demands but should also consider future generations' demands. The notion of sustainability which is often described by non-numerical, qualitative, and philosophical means, may be found in more detail, for example, in Haimes (1992), Gleick et al. (1995), Plate (1993), and WCED (1987).