Water Diplomacy in Action: Contingent Approaches to Managing Complex Water Problems

by Shafiqul Islam (Editor), Kaveh Madani (Editor)

Overview

Complex water problems cannot be resolved by numbers or narratives. Contingent and negotiated approaches are necessary for actionable outcome. In the face of a constantly changing array of interconnected water issues that cross multiple boundaries, the challenge is how to translate solutions that emerge from science and technology into the context of real-world policy and politics. Water Diplomacy in Action addresses this task by synthesizing two emerging ideas––complexity science and negotiation theory––to understand and manage risks and opportunities for an uncertain water future. Rooted in the ideas of complexity science and mutual gains negotiation, this edited volume shows why traditional systems engineering approaches may not work for complex problems, what emerging tools and techniques are needed and how these are used to resolve complex water problems. 

Product Details

ISBN-13:	9781783084937
Publisher:	Anthem Press
Publication date:	01/02/2017
Series:	Science Diplomacy: Managing Food, Energy and Water Sustainably , #1
Pages:	344
Product dimensions:	6.00(w) x 8.90(h) x 1.10(d)

About the Author

Shafiqul Islam is a professor of civil and environmental engineering and professor of water diplomacy at the Fletcher School of Law and Diplomacy, Tufts University. He is the director of the Water Diplomacy Program and the 2016 recipient of the Prince Sultan Bin Abdulaziz International Water Prize for Creativity.

Kaveh Madani is a reader in systems analysis and policy at the Centre for Environmental Policy of the Imperial College London. He is one of the four recipients of the Arne Richter Award for Outstanding Young Scientists in 2016 for his fundamental contributions to integrating game-theory and decision-analysis into water management models.

Read an Excerpt

Water Diplomacy in Action

Contingent Approaches to Managing Complex Water Problems

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By Shafiqul Islam, Kaveh Madani

Wimbledon Publishing Company

Copyright © 2017 Shafiqul Islam and Kaveh Madani
All rights reserved.
ISBN: 978-1-78308-493-7

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CHAPTER 1

COMPLEXITY AND CONTINGENCY: UNDERSTANDING AND MANAGING COMPLEX WATER PROBLEMS

Shafiqul Islam

Abstract

While classical scientific methods seek generalizable and predictable solutions, these methods do not work for complex problems where solution spaces are neither well bounded nor predictable. A key challenge for many water problems — such as allocation between competing uses, providing access to water in urban slums or creating water-sharing arrangements between riparian countries — is that outcomes from interventions are not predictable due to the dynamic nature of interactions and interdependencies of complex water systems. An interdisciplinary understanding of different schools of thought from complexity science can provide a pragmatic way to diagnose sources of complexity, identify intervention points and develop equitable and sustainable solutions for complex water-management problems. Here we provide an overview of key concepts from complexity science and use a case example to illustrate how to operationalize complexity thinking to address a complex water allocation problem. This case example of water sharing between Israel and Jordan demonstrates how the creation of an actionable space with a commitment to collaborative adaptive management can produce a relatively sustainable water agreement. To manage complex water problems, we need to reframe traditional specify-design-implement to a try-select-adapt management approach. Instead of searching for optimal solutions to address complex problems we need to look for optimal space where certain solutions are actionable given the constraints the context imposes.

Introduction

This introductory chapter is intended to provide a broad overview of complexity science from multiple domains of knowledge (e.g., Anderson et al. 1988; Nicolis and Prigogine 1989; Lewin 1992; Kauffman 1993; Mainzer 1994; Bar-Yam 1997; Cilliers 1998; Maguire et al. 2006; Maguire 2011). A cursory look around this vast body of literature in complexity sciences shows incredible diversity in terms of ontological and epistemological assumptions, foundational concepts, levels of analysis, research methods and so on. Clearly, there are important differences among the approaches followed by disciplinary groups but, among these examples, the within-group differences are much smaller compared to the differences between groups. In this chapter we focus on broad ways of thinking about the different faces of complexity: numbers and narratives; models and meanings; objective and interpretive. Clearly, the boundary between these domains (e.g., numbers and narratives) is not as sharp as implied; in addition, the breadth and depth of scholarship within each domain suggest that a comprehensive synthesis may not be attainable. Our goal is not to provide a complete description of the multifaceted reality but to develop an interdisciplinary understanding of these two broad ways of thinking about complexity. We hope an interdisciplinary understanding of different schools of thought from complexity science can provide a pragmatic way to diagnose sources of complexity, identify intervention points and develop equitable and sustainable solutions for complex water-management problems. This chapter is organized in three sections: Understanding Complexity; Understanding Complexity of Water; and Managing Complexity of Water Resources.

Understanding Complexity

From Clock to Confusion: Origin of Complexity

We desire clocklike precision, clear certainty, deterministic prediction, and explicit knowledge to guide us in making objective choices and decisions about the future. Yet, the world that we live in is filled with confusing signals; uncertainty and randomness are everywhere, and many of our choices and decisions are guided by tacit knowledge and subjective interpretations where numbers and narratives often collide to reinforce perceptions and create meaning.

Is there one or multiple world(s) and worldview(s)? Is there a difference between world(s) and worldview(s)?

These are age-old philosophical questions without definitive answers; yet, they have practical implications in our everyday life. Do we live in one world or multiple worlds? Differences in thinking about and acting in these singular and multiple worlds with competing — and often conflicting — worldviews create complexity. These are not new problems; in fact, many of the important problems were (are), indeed, complex, and wise people knew (know) how to deal with them. For centuries, stories and metaphors have crystallized wisdom of complexity through cultures and continents using narratives — think about the story of blind men and the elephant from the Indian subcontinent, the fable of the eighteenth camel from the Middle East, or the parable of the tortoise and the hare from multiple continents. Difficulties arise when we try to translate the wisdom of complexity to prescriptive advice using tools and techniques we have developed to address simple and complicated problems.

Complexity arises because (a) the world is a system that can be put together in an infinite number of ways because its components are intricately connected and interdependent; (b) it is impossible to enumerate all the interactions and interdependencies of this system explicitly to ensure predictable outcomes; (c) such an enumeration demands our explicit as well as tacit interpretation of multiple worldviews to define the nature of system components and their interactions; and (d) our attempt to analyze this system objectively often fails because of our multiple worldviews. Casual pathways for such systems — known as complex systems — are intractable and open to a plurality of representation and interpretation. The solution space for these complex systems is neither bounded nor predictable. Yet, a common presumption is to seek certainty in our ability to plan and act in a way that will yield predictable outcomes. This notion of a predictable outcome may be theoretically achievable for well-defined scientific problems where causal connections are well understood. We can tell, for example, with absolute certainty where the sun will be when it is 7:37 a.m. in Boston one hundred years from today; yet, we cannot predict with any reasonable certainty how much will it rain at 7:37 a.m. in Boston a week from today. Neither can we predict — with reasonable certainty — the water use and availability in Boston one hundred years from now. Our classical scientific methods seek generalizable and predictable solutions while complexity arises because of interactions, interdependencies and feedback as well as a multiplicity of interpretations and representations of uncertainty. How, then, can one use traditional scientific methods to address complex water problems?

Classical scientific knowledge can be broadly grouped into two categories: "hard" sciences where generalizable mathematical formalism and numbers are used to express the laws of nature (think about the position of sun as a function of time and spatial location) with predictive certainty, while "soft" sciences explain events in terms of narratives. For example, completion of Activity A will result in Output B, leading to Outcome C and Impact D. This linear idea of cause and effect has profoundly affected our understanding of classical science for centuries. Classical (or reductionist) scientific methods tend to use a machine metaphor: a machine is built from distinct elements that can be reduced to its elemental parts without losing its machine-like character. Newton gave us three laws of motion that could be generalized from particle motion to galaxies. This broad generalization has been the foundation of the classical scientific method that we refer to here as the Newtonian Paradigm.

This Newtonian view of the world has influenced our education system, our culture, our institutions and our management practices so effectively that it has become the reality. This view of reality assumes that: (a) a system responds because something causes it to respond (cause and effect); (b) system components are linearly related, implying that responses are proportional to forces and causes are proportional to effects (linearity); (c) linear systems can be broken down into their components to analyze each component and its response separately, and all the separate responses can be added to get the response of the whole system (reductionism); (d) our world is orderly and it works like a machine with known and predictable laws (machine metaphor); and (e) the optimal way to manage this world is to organize institutions with hierarchical governance structure with clear prescriptions (command and control).

At the beginning of the twentieth century, the certainty of this Newtonian view of a mechanical world was questioned by quantum mechanics and the Heisenberg Uncertainty Principle. Einstein told us that time is relative, space is curved, matter and energy are interchangeable — and other new challenges to this Newtonian view of reality began to emerge. For example, leading biologists started questioning the idea that living organisms can be reduced to mechanical operations, and argued that even a single cell has more complexity than a typical car. Scientists in other disciplines started to explore issues of nonlinear dynamics and limits of predictability for well-structured mathematical systems. Lorenz's butterfly effect — how a butterfly flapping its wings in Beijing (a small difference at the beginning of an experiment) may create a thunderstorm in Boston (a massive difference at a later stage at a different location) — is perhaps one of the most vivid and influential metaphors to illustrate the effects of nonlinearity on predictable outcomes for well-structured and bounded systems. Clocklike precision and predictability of a mechanical Newtonian world was challenged by these discoveries in atmospheric sciences (Lorenz 1963), biology (von Bertalanffy 1968) and other disciplines. Linear and reductionist modes of thinking — in which the future world is seen as a straightforward extrapolation of the past — started losing credibility and relevance. A new domain of knowledge — known as complexity science — began to emerge to address this non-Newtonian world.

Complexity Science: Foundational Ideas and Concepts

Complexity science challenges not only the foundation of our knowledge but also the effectiveness of institutions built on that knowledge. Adopting a complexity perspective has significant ontological, epistemological and axiological implications to understand and manage water-resources systems. When relatively simple rules collectively give rise to very complex behavior — for example, when the micro-scale behavior of individuals generates an unpredictable macro-scale economy; and when three wetlands in the same region evolve differently because of small contextual differences in natural and societal processes (Narayanan and Venot 2009) — we need a different approach to understand and manage these systems. The key ideas of the complexity science perspective are summarized below from two different domains of knowledge:

• "We have learned that nature is not a well-designed puzzle with only one way to put it back together. In complex systems the components can fit in so many different ways that it would take billions of years for us to try them all" (Barabási 2003).

• "The option of optimal design is not available to mere mortals. The number of combinations of specific rules that are used to create action situations is far larger than any set that analysts could ever analyze even with space-age computer assistance" (Ostrom 2005).

The implications of these two assertions are profound. In short, we cannot prespecify the state space for complex systems — where variables, processes, actors and institutions are interconnected and interdependent with nonlinearity and feedback — and the possible solution space is theoretically infinite dimensional. That means we may not know the entire sample space with any degree of certainty. Of course, knowing the sample space does not tell us what will happen but allows us to theoretically determine what can happen. Since we cannot prestate which variables, processes, actors and institutions will become relevant for complex systems, we will not know what can happen. This appreciation for the unknowable nature of complex systems is critical to understand and manage complex water problems. We begin with a brief overview of key foundational ideas and concepts related to complexity science.

Complicated and Complex Systems

Everyone would agree that a car, with its thousands of electronic elements, is an extremely complicated system. The same can be said of the stock market. Both the car and the stock market are human constructions, but there is a significant difference between them. A complicated car was carefully designed and tested by a team of engineers who positioned every mechanical and electronic element in its place with precision, and it works in a reliable and predictable way. But no one designed the stock market, and no one claims to fully understand or control it, and yet it works — perhaps not as reliably and predictably as a car — without explicit control by anyone. While the effective operation of a car is highly dependent on the successful operation of every one of its core elements, the functioning of the stock market is much more robust in the face of perturbations and failures at the level of its elements and agents.

Looking around, one can see systems with similar characteristics from the water world: drought in California, water allocation in transboundary rivers such as the Nile, or water access in megacity slums. What is it that unites these systems and makes them different from a car? And what can we learn from these systems to help us develop more equitable and sustainable water management systems? More generally, can we understand the relationship of structure to function in nature for the benefit of science and society? These systems — stock markets, transboundary water management, urban water supply and treatment — have come to be known as complex systems , not to be confused with complicated systems such as a car. This distinction is important because although these systems arguably share similar characteristics, they are fundamentally different. A municipal water supply system — similar to a car — is complicated, while providing equitable and sustainable access of water to urban slums is complex.

Here, elements and agents are used interchangeably and consist of four broad groups: variables (e.g., quantity and quality of water) and processes (e.g., hydrologic, climatic, ecological) from the natural system, while actors (e.g., stakeholders) and institutions (e.g., markets, values, governance) are from the societal system. In complicated systems, relationships, interactions and feedback among elements are known and can be controlled. In complex systems, relationships, interactions and feedback are not precisely known; more importantly, interactions and feedback among agents usually change dynamically, and such changes cannot be reliably predicted or controlled.

Different Faces of Complexity Science

Over the last several decades, complexity science has received increased attention from several disciplines (e.g., Anderson et al. 1988; Nicolis and Prigogine 1989; Lewin 1992; Kauffman 1993; Mainzer 1994; Bar- Yam 1997; Cilliers 1998; Maguire et al. 2006; Maguire 2011). It is important, however, to recognize that what is usually referred to as complexity science actually is a collection of frameworks, theories, models, and tools from a number of disciplines, including systems engineering, chaos theory, cybernetics and complex adaptive systems. A cursory look at the growing body of literature in complexity science reveals incredible diversity in terms of ontological and epistemological assumptions, foundational concepts, levels of analysis, research methods and so on. Complexity science has its origin in many disciplines (Table 1.5.2 in Maguire et al. 2006 provides an excellent summary of different key concepts and their disciplinary origins); two increasingly overlapping threads of intellectual development may be broadly classified as European and North American approaches to complexity (Maguire et al. 2008); yet, understanding of emergent phenomena — a key attribute of a complex system — requires both schools of thought. Another broad grouping of literature is dominated by scholars from natural and social sciences (Furtado and Sakowski 2014; Hidalgo 2015 and references therein). Clearly, there are important differences among the approaches followed by disciplinary groups, but since the within-group differences are much smaller compared to the differences between groups, we will here focus on these two broad ways of thinking about the different faces of complexity — exploring both numbers and narratives; both models and meanings; both objective and interpretive — for two reasons. First, any discussion of the nature and origin of complexity that transcends the boundary between the social and natural sciences is rare. Second, the diverging sets of literature on complexity will be enriched by translating the disciplinary jargon of one body of literature into the language of the other to enrich mutual understanding of each other's goals and objectives. Admittedly, the boundary between these domains (e.g., numbers and narratives) is not as clearly delineated as implied; in addition, the breadth and depth of scholarship within each domain suggest that a comprehensive synthesis may not be attainable. Of course, the breadth of the effort resultant from these domains implies that discussion here is destined to be narrow — may even be viewed by some domain experts as somewhat generic — and incomplete. Our goal is not to provide a complete description of multifaceted reality, but to develop an interdisciplinary understanding of complexity to find a pragmatic way of diagnosing sources of complexity, identifying intervention points and developing equitable and sustainable solutions.

(Continues...)

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Excerpted from Water Diplomacy in Action by Shafiqul Islam, Kaveh Madani. Copyright © 2017 Shafiqul Islam and Kaveh Madani. Excerpted by permission of Wimbledon Publishing Company.
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Table of Contents

List of Figures; List of Tables; The Blind Men, the Elephant and the Well: A Parable for Complexity and Contingency - Maimuna Majumder; Preface; Part I. Roots and Causes of Complexiety and Contingency in Water Problems; Chapter One Complexity and Contingency: Understanding and Managing Complex Water Problems - Shafiqul Islam; Chapter Two Leveraging Diplomacy for Resolving Transboundary Water Problems - Benjamin Pohl and Ashok Swain; Part II. Tools, Techniques, Models and Analyses to Resolve Complex Water Problems; Chapter Three Ten Bankruptcy Methods for Resolving Natural Resource Allocation Conflicts - Mahboubeh Zarezadeh, Ali Mirchi, Laura Read and Kaveh Madani; Chapter Four Flexible Design of Water Infrastructure Systems - Melanie Wong Turlington, Richard de Neufville and Margaret Garcia; Chapter Five Extreme Value Analysis for Modeling Nonstationary Hydrologic - ChangeArpita Mondal and P. P. Mujumdar; Chapter Six The Water– Food Nexus and Virtual Water Trade - Joel A. Carr and Paolo D’Odorico; Chapter Seven A Hybrid Analytical Approach for Modeling the Dynamics of Interactions for Complex Water Problems - Yosif Ibrahim and Shafiqul Islam; Chapter Eight A Call for Capacity Development for Improved Water Diplomacy - Dena Marshall, Léna Salamé and Aaron T. Wolf; Chapter Nine Water Complexity and Physics- Guided Data Mining - Udit Bhatia, Devashish Kumar, Evan Kodra and Auroop R. Ganguly; Part III. Case Studies; Chapter Ten The Nature of Enabling Conditions of Transboundary Water Management: Learning from the Negotiation of the Indus and Jordan Basin Treaties - Enamul Choudhury; Chapter Eleven Mediation in the Israeli– Palestinian Water Conflict: A Practitioner’s View - Patrick Huntjens; Chapter Twelve Risk Distribution and the Adoption of Flexibility: Desalination Expansion in Qatar - Abdulla AlMisnad, Richard de Neufville and Margaret Garcia; Chapter Thirteen The Grand Ethiopian Renaissance Dam: Conflict and Water Diplomacy in the Nile Basin - Ronny Berndtsson, Kaveh Madani, Karin Aggestam and Dan- Erik Andersson; Chapter Fourteen Engaging Stakeholders for Water Diplomacy: Lessons for Integrated Water Resources Management - Bhadranie Thoradeniya and Basant Maheshwari; Chapter Fifteen Strategic Insights for California’s Delta Conflict - Mohammad R. Moazezi, Kaveh Madani and Keith W. Hipel; Notes on Contributors; Index.

What People are Saying About This

From the Publisher

“This volume amplifies the fact that water is an interdisciplinary resource and analyzes the complex array of interconnected water issues that cross multiple boundaries. It diagnoses water problems, identifies intervention points and proposes some sustainable solutions that blend science, law, policy and politics. It is a major contribution to the field of water diplomacy.”
—Salman M. A. Salman, former World Bank Adviser on Water Law and Editor-in-Chief, International Water Law

“Opening up avenues for nonviolent resolution of water-related disputes and conflicts, this book shows how diverse knowledge bases can be used for putting that very useful goal in real-world actions.”
—Jayanta Bandyopadhyay, Visiting Distinguished Fellow, Observer Research Foundation, India  

“Water Diplomacy in Action provides a comprehensive view on complex water problems, integrating qualitative and quantitative approaches and combining these with real-life case studies.”
—Erik Mostert, Assistant Professor, Department of Water Management, Delft University of Technology, The Netherlands 

“The book is an excellent contribution to the literature on how formal and informal institutions and engagement of stakeholders continue being the best ways to address the complexity of water resources.”
—Cecilia Tortajada, Senior Research Fellow, Institute of Water Policy, Lee Kuan Yew School of Public Policy, National University of Singapore