Chatting with Nathan in Water Talks brings back many good modeling memories. Still learning modeling was hard for me despite all the great mentors I had throughout my career.
This is my weekend project for the next few months. I will post a series of posts to illustrate how I eventually get addicted to modeling. Surprisingly, using approaches I learned from graduate school doing scientific research many years ago. I’ll blog what worked well for me, and I hope that will make your modeling journey more enjoyable than mine.
The approach I am going to show is not typical, and used to be much harder to do. Thanks to the rapid advancements in big data and AI technology, a new generation of data analysis tools are bringing such tools to anyone who has an Internet connection and a desire to learn.
Let’s get started. For the first month, I’ll try to get the following done,
- week 1: get the software installed, run the model and see the results.
- week 2: sensitivity analysis
- week 3: dry weather analysis
- week 4: calibration statistics
In the following months, I’ll focus more on advanced topics of calibration and optimization.
Here are the projects:
SWMM with Python week 1 — Setup the environment
