6
1 Introduction
further, let us consider only one of the three components that influences decisions,
i.e., computational capacities of individuals and institutions:
“Simon’s focus on computationally efficient methods that yield solutions that
are… “good enough”, in Simon’s terms, involves search procedures, stopping criteria,
and how information is integrated in the course of making a decision. Simon offers
several examples to motivate inquiry into computationally efficient methods. Here
is one. Applying the game-theoretic minimax algorithm to the game of chess calls
for evaluating more chess positions than the number of molecules in the universe
(Simon 1957). Yet if the game of chess is beyond the reach of exact computation, why
should we expect everyday problems to be any more tractable? Simon’s question is
to explain how human beings manage to solve complicated problems in an uncertain
world given their meager resources. Answering Simon’s question, as opposed to
applying Friedman’s method to fit a constrained optimization model to observed
behavior, is to demand a model with better predictive power concerning boundedly
rational judgment and decision making” (Wheeler 2018).
Let us very briefly consider two of the important points presented in the
above quote, namely, optimization and judgment, in relation to water management.
Regarding the former, Loucks and van Beek (2005) write: “Hence at best a mathematical model of a complex water resources system is only an approximate description
of the real system. The optimal solution of any model is optimal only with respect to
the particular model, not necessarily with respect to the real system. It is important
to realize this limited meaning of the word ‘optimal,’ a term commonly used by
water resources and other systems analysts, planners and engineers.” They go on to
state that “Even when combined with efficient techniques for selecting the values of
each decision variable, an enormous computational effort may still lead to a solution
that is still far from the best possible.” In this way, and according to Simon, there
should be a clear effort in abandoning the word ‘optimum’ that means “the best
possible” solution, and go toward employing good-enough or reasonable words and
approaches.
The second crucial point is judgement in decision-making. Regarding the Berlin
Rules on Water Resources, Dellapenna (2008) states that “in English, at least, the
word “judgment” carries a connotation that the result is not dictated in any immediate sense by the factual and other inputs that the judge relies upon in exercising
judgment.” For a water manager, this is the case because s/he has to consider all types
of inputs, sometimes non-quantitative or very hard to quantify, such as political and
other societal sensitivities. In Chap. 4 regarding sustainable performance of water
systems, we will expand two notions linked to judgment (a) Loucks (2002) defines
sustainability and affirms that its advancement depends on “Public value judgments”,
and consequently significant stakeholder involvement, (b) noise or chance variability
of judgments is crucial in advancing good-enough water management.
In this view, water policy makers act as satisficers (using Simon’s ideas) trying to
have good-enough outcomes rather than an optimal one. Loucks and van Beek (2005)
write that because of the high complexity involved in water resources management,
the idea may prove to be more sustainable if one uses the satisficing decision making.
The theory presented in this book makes judgments of water managers much bounded
1 Introduction
further, let us consider only one of the three components that influences decisions,
i.e., computational capacities of individuals and institutions:
“Simon’s focus on computationally efficient methods that yield solutions that
are… “good enough”, in Simon’s terms, involves search procedures, stopping criteria,
and how information is integrated in the course of making a decision. Simon offers
several examples to motivate inquiry into computationally efficient methods. Here
is one. Applying the game-theoretic minimax algorithm to the game of chess calls
for evaluating more chess positions than the number of molecules in the universe
(Simon 1957). Yet if the game of chess is beyond the reach of exact computation, why
should we expect everyday problems to be any more tractable? Simon’s question is
to explain how human beings manage to solve complicated problems in an uncertain
world given their meager resources. Answering Simon’s question, as opposed to
applying Friedman’s method to fit a constrained optimization model to observed
behavior, is to demand a model with better predictive power concerning boundedly
rational judgment and decision making” (Wheeler 2018).
Let us very briefly consider two of the important points presented in the
above quote, namely, optimization and judgment, in relation to water management.
Regarding the former, Loucks and van Beek (2005) write: “Hence at best a mathematical model of a complex water resources system is only an approximate description
of the real system. The optimal solution of any model is optimal only with respect to
the particular model, not necessarily with respect to the real system. It is important
to realize this limited meaning of the word ‘optimal,’ a term commonly used by
water resources and other systems analysts, planners and engineers.” They go on to
state that “Even when combined with efficient techniques for selecting the values of
each decision variable, an enormous computational effort may still lead to a solution
that is still far from the best possible.” In this way, and according to Simon, there
should be a clear effort in abandoning the word ‘optimum’ that means “the best
possible” solution, and go toward employing good-enough or reasonable words and
approaches.
The second crucial point is judgement in decision-making. Regarding the Berlin
Rules on Water Resources, Dellapenna (2008) states that “in English, at least, the
word “judgment” carries a connotation that the result is not dictated in any immediate sense by the factual and other inputs that the judge relies upon in exercising
judgment.” For a water manager, this is the case because s/he has to consider all types
of inputs, sometimes non-quantitative or very hard to quantify, such as political and
other societal sensitivities. In Chap. 4 regarding sustainable performance of water
systems, we will expand two notions linked to judgment (a) Loucks (2002) defines
sustainability and affirms that its advancement depends on “Public value judgments”,
and consequently significant stakeholder involvement, (b) noise or chance variability
of judgments is crucial in advancing good-enough water management.
In this view, water policy makers act as satisficers (using Simon’s ideas) trying to
have good-enough outcomes rather than an optimal one. Loucks and van Beek (2005)
write that because of the high complexity involved in water resources management,
the idea may prove to be more sustainable if one uses the satisficing decision making.
The theory presented in this book makes judgments of water managers much bounded