The Art and Science of Hydrologic Modeling¶
A project-based course in hydrologic modeling using SUMMA¶
This site consists of a series of modules that are meant as the basis for a graduate course in hydrologic modeling. In general, we expect that an instructor will take these modules and tailor them to a specific course. For those who already have a strong background in hydrology and hydrologic modeling, self-study may be an option, but that is not the primary focus.
The course modules specifically deal with the development, implementation, and evaluation of numerical models that simulate the flow of water and energy at and near the land surface. Clearly, the selection of topics and their treatment is heavily colored by how we think this should be accomplished. There is a rich literature on alternative views of model development, some of which we will refer to in the module Model Philosophy. Much of our own modeling philosophy is captured in the Structure for Unifying Multiple Modeling Alternatives or SUMMA, which is introduced in the module An Introduction to SUMMA. SUMMA will also be used for most if not all of the exercises in this course.
Part of the art in model development and application is deciding on what processes and model constructs are essential in capturing the relevant hydrologic processes. Part of the science is making sure that this is implemented correctly and in evaluating and analyzing model results. Our aim with this series of modules is to guide graduate students in both.
This is not a course in basic concepts of hydrology or on the description of hydrologic processes. There are many textbooks that cover a wide variety of topics in this area. Instead, the goal is to convey an understanding of how to represent existing process understanding in numerical models, how to devise meaningful model experiments and how to evaluate these experiments in a systematic manner.
The modules rely heavily on suggested readings of journal papers and scientific reports. We rely on the individual instructors to take this material and augment and substitute each module’s reading list to tailor it to their own purpose. Note that we cannot help you in getting access to literature on the reading lists. That is between you and your librarian.
The order of the modules will be left to the individual instructors, although the order provided below makes most sense to us. This means that later modules may assume knowledge presented in earlier modules. Where necessary, we will provide links to the earlier material. That said, we strongly suggest that the first five modules be covered in order. These modules provide a general foundation as well as an introduction to SUMMA, which is instrumental in the exercises that are part of each module. We expect that much of the learning is likely to happen as part of these exercises.
Finally, we invite anyone to help us expand and enhance this series of modules. Detailed instructions on how to contribute can be found here.
- 1. Course Introduction
- 2. An Introduction to SUMMA
- 3. Model Philosophy
- 4. Model Construction and Numerics
- 5. Model Evaluation
- 6. Model Forcing Data
- 7. Process Representations and Parameterizations
- 8. Spatial Heterogeneity and Connectivity
- 9. Model Parameters
- 10. Model Uncertainty
- 11. Capstone Project
- 12. References