Hydrologic processes are complex and when modeling them using a deterministic or stochastic approach one invariably introduces errors because of simplifications and assumptions made. However, not all assumptions and simplifications in the approach chosen produce the amount of errors; in fact the impact of deviations from the truth on a final output set of variables varies greatly. In addition, not every catchment behaves alike adding another layer of complexity to the modeling effort. Hence, every approach exhibits a degree of uncertainty in their results. While this uncertainty can be examined systematically in this technical note we focus on the development of a repository for modeling uncertainty data. We store information about the model used (lumped, semi distributed, fully distributed), the objective function (Nash Sutcliff, Root Mean Square Error, …) used to calculate the fitness of an approach, a Pareto best parameter combination, and also some statistical values that arrive from a specific approach and its ensemble such as median, max and min values. We describe the development of a database to store this data and also an online based submission system (based on the DRUPAL environment) that can be used to submit, explore, and retrieve uncertainty data. Finally, we use a sample data set from the 392 Model Parameter Estimation Experiment (MOPEX) catchments as an initial submission to our system which we use to show some of the features of our Uncertainty DB that will be accessible through http://uncert.net.
Etienne, Elius and Piasecki, Michael, "Development Of A Repository For Hydrologic Model Uncertainty Data" (2014). CUNY Academic Works.