Dani Jones

Dani Jones

they/them

Marine Data Scientist

GLERL BIL-SA Project: Improving Water Level Forecasting

Overview

The GLERL BIL-SA Project is an ongoing collaboration aimed at improving water level forecasting tools used by the U.S. Army Corps of Engineers (USACE) and Environment and Climate Change Canada (ECCC). This project focuses on advancing the precision of predictions for the Great Lakes’ water levels, which is essential for flood management, infrastructure protection, and environmental sustainability in the region.

Key Objectives:

  • Enhance predictive models for water level forecasting
  • Support decision-making related to flood management and infrastructure protection
  • Integrate climate change data into predictive tools for long-term planning
  • Apply advanced machine learning and AI techniques to improve model accuracy

My Role:

As part of the team, I lead the integration of machine learning approaches to refine existing forecasting models and help build tools for more accurate and timely water level predictions.

Impact:

This project aims to deliver practical solutions that directly inform policy and operational decisions, helping to safeguard communities, ecosystems, and infrastructure in the Great Lakes basin.

  • [Link to any relevant paper or publication, if applicable]

Future Directions:

As we continue refining the forecasting models, we will incorporate more detailed climate data and explore new methodologies for improving long-term predictive capabilities.