Science, Democracy, and Water Policy (original) (raw)
Policy in question: from problem solving to problematology
2005
Abstract Since the postpositivist critique of the policy sciences, policy theory has come into question. More particularly, the 'problem orientation'upon which Lasswell defined the policy sciences has come into question because policy making does not conform to his problem solving logic.
Science Informed Water Management Policies
2021
Clearly policy makers should consider the impacts of any decisions they might make before making them. Science can provide estimates of various economic, ecologic, environmental, and even social impacts of alternative policies, impacts that determine how effective any particular policy will be. These impact estimates can be used to compare and evaluate alternative policies in the search for identifying the best one to implement. Among all scientists providing inputs to policy making processes are analysts who develop and apply models that provide these estimated impacts and, possibly, their probabilities of occurrence. But just producing them is not a guarantee that they will be considered by policy makers. This paper discusses ways scientists, including systems analysts, can effectively contribute to and inform those involved in making water management decisions. Brief descriptions of a variety of past and on-going water management policy making processes illustrate both some succe...
Science Informed Policies for Managing Water
Hydrology, 2021
Water resource management policies impact how water supplies are protected, collected, stored, treated, distributed, and allocated among multiple users and purposes. Water resource policies influence the decisions made regarding the siting, design, and operation of infrastructure needed to achieve the underlying goals of these policies. Water management policies vary by region depending on particular hydrologic, economic, environmental, and social conditions, but in all cases they will have multiple impacts affecting these conditions. Science can provide estimates of various economic, ecologic, environmental, and even social impacts of alternative policies, impacts that determine how effective any particular policy may be. These impact estimates can be used to compare and evaluate alternative policies in the search for identifying the best ones to implement. Among all scientists providing inputs to policy making processes are analysts who develop and apply models that provide these ...
Policymakers and Practitioners
2015
Science has always helped to build decisions not actually make the decisions (Cortner 2000). This paper addresses how decisions on environmental flows should not just be determined directly from sci-entific data but requires active learning and communication between stakeholders from the inception of an assessment to the implementa-tion. Informed decision making requires that the decision maker un-derstands what the outputs of an environmental flows assessment are and how they can be used to aid in deciding future water allocations. This type of approach to environmental flows assessment is a multi-step process that provides a bridge between the science and policy realms. Cooperative communication coupled with action learning can ensure that the knowledge imparted by scientists to inform deci-sion makers will also be informed by the needs of the decision mak-ers themselves.
1999
Think by decomposing the problem 3 Choose by evaluating options comprehensively 4 Choose after considering alternative scenarios 5 Anticipate by foreshadowing people's reactions 6 Anticipate by managing uncertainty 10.2 NOW WHAT? Whereas most books claim to be cooperative efforts, the writing of this one proved to be a rather solitary adventure. Nevertheless, I am deeply grateful to those who provided encouragement during its darker moments. I would particularly like to thank Jim Smith for being such an enthusiastic promoter of the Strategizer software, and the writers of the other three packages featured in this book for their unstinting encouragement and advice-John Dickey, John Friend and Thomas Saaty. I must once again express my gratitude to my long-time and loyal supporters, Peter Hall and Mike Batty, for their unwavering confidence in my work. I would also like to thank my managing editor at Alexandrine Press, Ann Rudkin, for her initial enthusiasm, continued patience and enduring good humour. The University of Melbourne generously provided me with facilities, computers and study leave during the first half of 1998, when I (almost) completed this book. I would also like to thank colleagues within its Department of Geography and Environmental Studies, particularly its leaders, Neal Enright and Brian Findlayson, for tolerating my working within such a deviant area as policymaking software. RW Traditional approaches Looking firstly at the analytical tradition, note that countless research organizations have been set up around the world to 'get to the bottom of things'. Their rationale is that if we had perfect knowledge, policymaking would be redundant-it would simply be obvious what needs to be done. The well known lateral thinker Edward de Bono (quoted in Kelly, 1994) put it thus: If you had complete and totally reliable information on everything, then you would not need to do any thinking. Such an attitude has spawned the existence of many 'think tanks', institutes and higher education establishments. Within such organizations lurks a deep and pervasive desire to arrive at policy through the route of complete and comprehensive understanding. They are imbued with some sort of collective ethic that if understanding is good enough, better policymaking will inevitably follow. They use methods like 'simulation', 'inferential statistics', 'optimization' and 'modelling' to try to understand environmental mechanisms. Presumably, this will dispel the fog of complexity-induced confusion that pervades postindustrial civilization and so point the way to better policymaking. By contrast, and looking (secondly) at the design tradition, some of its supporters actually reject analysis out of hand. Indeed, some designers the author knows really believe that numbers and computers will stifle their creativity. And it is creativity, nothing more and nothing less, which is the path to exemplary policymaking. Such an approach, which involves 'master' policymakers designing their way out of contemporary problems, resembles a medieval guild system of apprenticeships. Emphasis is on personal attributes like 'synthesizing skill', 'education', 'sensitivity', 'intuition', 'originality', 'intellect' and 'an ability to empathize with people's multifaceted needs, wants and spiritual requirements'. Such traits are then all focused on improving the world through aesthetics and through the achievement of harmony. Hence we have two dominant approaches to policymaking-the analytical tradition and the design tradition. The question immediately arises: why only two? Cannot other approaches be taken? This is an especially pertinent question when one realizes that both the analytical and the design tradition fall well short of constituting good policymaking. To see why, we look at each tradition in turn. Turning firstly to analysis, note that policymaking actually means to decide what to do in the future (Boritz, 1983). Yet analysis, whether in the form of modelling, forecasting, optimization or whatever, is only peripherally about deciding what to do in the future. Analysis is preparation for policymakingdecision support. Indeed, analysis might actually inhibit good policymaking by over-complicating issues. If too much is known about a situation, the policymaker can become confused to the point of suffering 'analysis paralysis'. That is, analytical experts can sometimes know so much about the difficulties associated with all of the alternative policies that they will be unable to recommend any of them. The result will be a loss of decisiveness and missed opportunity, a little like that suffered by the centipede in the following poem (anon.): The centipede was doing well, Until the fox in fun, said, Pray, which leg goes after which? xiv xvi boost to their policymaking skill, such study becomes anything but boring. It becomes exhilarating and exciting because of its obvious potential. Still, and this is a second drawback of our approach, many can never be convinced that policymaking methods are exciting. In a sense they are correct. Most of us are more interested in driving a car than attending courses about what goes on under the bonnet-the technical part. Some mechanically minded people might well be interested in motors, but most of us prefer to drive around with the wind in our hair. Similarly, many performers are more interested in popular music than in classical music training and many computer users prefer to stumble along rather than take lessons in programming. It is similar with policymaking-its excitement comes from the gossip, the intrigue and richness that surrounds real case studies rather than from dedicated scrutiny of improved methods. But consider the advantages of being disciplined. If we know about mechanics we can sometimes make a car do some incredible things. Classically trained musicians are equipped to become better popular music performers than untrained musicians, and computer programmers can make computers do so many more things than can most lay users. Similarly, technically trained policymakers will have more chance of performing well than people whose sole qualification is that they are interested in gossip and intrigue. Indeed, it could be argued that in any field, unless one goes back to basics and looks at source methods, one will forever be hemmed in by a ceiling that caps one's potential for improvement. By contrast, the classically trained will have no such limitations. For example, those who are trained in Latin and ancient Greek will be better equipped to speak eloquently, those who are trained in classical gymnastics will be better equipped to become circus performers, and those who are trained in a swimming pool will probably develop a better style for open-water racing. It is just that the classical training seems so tedious. But it need not be, provided one progresses to the stage of becoming enormously excited by its potential benefits. Yet if we look within many educational institutions that specialize in policymaking, current thinking is against this. That is, a third drawback of our approach is its lack of academic fashionability. Scores of scholars have written much about the futility of studying planning methods, and such opinions have partly stemmed from the mistakes that were made by planners during the over-mechanization of their methods during the 1960s and 1970s (Wyatt, 1996a). Consequently, there is now an increasingly popular sentiment in some circles that policymaking is a warm, human, mysterious, organic and ambiguous activity for which the assistance of cold, inhuman, logical, silicon-based and precise computers is grossly inappropriate. Enlisting such philistine technology is like cooking a pizza without the cheese. Stripping away policymaking's essential richness, flavour and human interest is very misguided and, above all, dull and boring. After all, students and professionals are usually much more interested in discussing hypotheses than in performing technical manipulations. Instead of dealing in abstractions they prefer to study phenomena that have social immediacy. Yet such objections to our approach are in some ways rather facile. Things still need to get done, like policymaking, and simply rejecting an approach to it because it is 'mere technology', or because humanism is more important, can sometimes mean that things are done less well than they otherwise could have been. Besides, who is to say that the end result of technological advance cannot be profoundly humanitarian? Consider the look in the eyes of a deaf child who hears for the first time using a bionic ear-an intensely technical piece of apparatus. Such a look is likely to give the technologist as deep a humanitarian feeling as will ever be experienced by the anti-technology, social science-based 'doubting Thomases'.