Beck, M.B. 1985. Water quality management: A review of the development and application of mathematical models. Springer-Verlag, NY, NY “Different types of models are appropriate for solving different kinds of problems; there is no universal model for solving all manner of problems; comprehensiveness and complexity in a simulation are no longer equated with accuracy; and there is a healthy mood of critical questioning of the validity and credibility of water quality models.”
2003 CALSIM II Peer Review Report(p.23) “…(I)nterpretation of model results … (P)ractices in terms of presenting model results, discussion of the model, and examination of model performance in a historical context, …, contain(ing) … the kind of written discussion and interpretation of results that … demonstrate that the authors have thought about the results and drawn conclusions in a realistic and self-critical manner. … the perceived credibility of the work and makes the study … informative for readers (most of who surely do not have the modeling background of the authors).”
Some questions to think about: Why? What? How? Who, When, and Where?
Why are we doing this? Modeling is not about generating numbers. It is about providing useful information. How reliable is the information? How would the information affect decisions?
What are the goals? Provide confidence to users of model results Quantify the accuracy of modeling results Put everyone on the same page What are the expected improvements? When can one claim victory?
How to quantify uncertainties and potential modeling errors? Uncertainties in input data Assumptions and approximations Verify formulation and algorithm Validate model performance with field data
Who, When, Where? Resources, Documentation, Web postings
Some technical details: Identify problematic areas. Do not spend time on a question unless there is a reasonable uncertainty that an answer exists. Determine if implementation of alternate model formulations is warranted before proceeding to calibration Given the rather large uncertainties in Delta modeling, it would make the effort more efficient if the accuracy targeted (± 20%, say) is defined ahead of time. Explore sensitivity of model results to calibration parameters for a simple channel network before going into full Delta simulation. Measures of model performance Water and salt balance in the model domain Track sources of salt Importance of flow measurements – stage is only the beginning Comparison with other models (e.g. Kimmerer-Monismith equation, GQwest-model) would be of interest, but consistency with these other models need not be the goal – these other models are subject to uncertainties themselves. Documentation, documentation, documentation