[1] Hydrologic synthesis, I believe, is needed in at least three respects: across processes, where the challenge is how to represent complex interacting dynamic systems including feedbacks between system components; across places, where the challenge is how to synthesize the plethora of case studies around the world in the past decades; and across scales, where one is interested in the general characteristics of processes as a function of space and time scales for the same site or an ensemble of sites. Seeking explanations for patterns, puzzles, and paradoxes is the way toward synthesis, and this should be pursued through two approaches. The first is to engage in more complex model building, but model complexity may ultimately limit the practical applicability of these models. The alternative is to seek more parsimonious avenues to synthesis. One of them is classification and similarity concepts which, generally speaking, can be profitably used when the processes are not fully understood. This often is the case in hydrology. Among the key unresolved issues and research challenges in hydrology is separating the predictable and the unpredictable. Synthesis, I think, needs to focus on the patterns of predictability. There is also an important, alternative, role of models in water resources management using models as communication tools. The best model then is not the most accurate one but the one that serves best the purpose of reaching a consensus among the players.
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