Week 10 Blog Post: Signing Off with Gratitude and Snow

As my senior project comes to a close, I’m filled with a sense of accomplishment and gratitude. What started with camera site comparisons and questions about snow depth has evolved into a fully functioning predictive model that simulates seasonal snowpack behavior.

Over the past few months, I’ve collected data from burned and unburned regions, explored how elevation and fire severity affect snow retention, and visualized these insights through carefully crafted graphs. I then turned those insights into a model that predicts snow depth across a full water year—culminating in the final graph below, which reflects realistic accumulation and melt trends from November to July.

What makes this meaningful is not just the code or the charts—it’s the bigger picture. This project wasn’t just about data science or environmental trends; it was about using technology to better understand our planet and potentially support water and energy management systems in the future.

Thank you for following along on this journey. It’s been a pleasure sharing my progress, frustrations, and breakthroughs with you. I’ve learned so much—not just about snowmelt or Python—but about what it means to take an idea and follow it through to something real.

Until next time,

Shashwath Senthil

BIF ’25