Machine Learning model for reservoir storage forecasting

Reservoirs are an important surface water store. Changing rainfall patterns make reservoirs more significant​. Forecasting reservoir storage can help with decision making. This webinar introduces machine learning modeling as a new tool for seasonal reservoir storage forecasting to inform water managers and water users. It elaborates on ensemble tree models, the data requirements and the seasonal forecasting outputs.

Learning Objectives

• Understand the why we are interested in forecasting reservoir stores​
• Understand the basics of ensemble tree models​
• Explore the outputs of a ML reservoir forecasting model

Target Audience

• Water managers, water resource modellers

Keywords

machine learning, reservoir modeling, reservoir storage, forecasting

Related Resources

• Deliverable 3.1: Gap analysis of existing tools in the RBs

• Deliverable 3.2: Improved modelling frameworks for better understanding of water resources at the river basin scale

• Deliverable 3.4: Data-driven water resources models (available in Sept.2025)