Saugat Sapkota, a junior majoring in Electrical Engineering in the Bagley College of Engineering, has published a research article in Environmental Research Communications.

The paper, “Advancing wildfire prediction in Nepal using machine learning algorithms,” evaluates how machine‑learning models can improve the prediction and mapping of wildfire susceptibility across Nepal. 

The paper, “Advancing wildfire prediction in Nepal using machine learning algorithms,” examines how machine‑learning models can enhance the accuracy of wildfire‑susceptibility prediction and mapping across Nepal. Using a Random Forest model, the study produced a high‑resolution (1‑km) wildfire‑risk map that identified 11.1% of Nepal, spanning 12 districts and 48 municipalities, primarily in the southwestern region, as very high‑risk areas. By incorporating daily meteorological data, the research offers a framework that strengthens wildfire‑risk management and provides actionable insights for decision‑makers working to support resilience in fire‑prone regions.

Sapkota served as the lead systems designer and lead engineer for the project. He described the experience as “incredibly rewarding” and noted that his motivation came from the real‑world impact of developing "a practical tool that addresses a critical environmental hazard and supports broader climate‑management efforts in Nepal."

Advancing wildfire prediction in Nepal using machine learning algorithms