SWMM with Python Week 2: Sensitivity Analysis
I am not very gifted in math, and I don’t always get what to expect from the model simply by looking at the equations. The good news is that I found I can learn directly from the model, and after doing that for a while I realized it is called sensitivity analysis.
In this example, I am running 27 model runs to learn how the Green Ampt hydrology works in SWMM5. In that process, I’ll share with you the techniques of automating the tedious tasks of changing parameters, running the model and compiling the results together using python tools.
And more importantly, I would like to share with you how I understand complicated systems through experiments. It is like doing research in graduate school, I had to start somewhere, do some experiments, then learn something. After that I form a hypothesis, then design more experiments to test it. With python, the cycles can be much shorter.
You can find the data and notebook on github.