The dangerous temptation of optimality in hydrological and water resources modelling

Hydrological and water systems modelling has long been driven by the search for better models. We do so by searching for models or at least parameter combinations that provide the best fit to given observations. We ourselves have contributed to this effort by developing new methods and by publishing diverse case studies. However, we repeatedly find that searching for and finding an optimal model is highly fraught in the presence of unclear signal-to-noise ratios in our observations, of incomplete models and of highly imbalanced databases. We present examples of our own work through which we have realized that achieving optimality was possible but futile unless we give equal consideration to issues of consistency, robustness and problem framing. We argue here that the strong focus on optimality continues to be a hindrance for advancing hydrologic science and for transferring research achievements into practice – probably more so than in other areas of the geosciences.