Upstream Tech awarded Phase 1 SBIR grant from Department of Energy

Upstream Tech has been selected to receive a Small Business Innovation Research (SBIR) Phase 1 award from the Department of Energy (DOE) to support improved hydropower decision-making with the further development of HydroForecast. The original announcement from the DOE’s Water Power Technologies Office is linked here.

Upstream Tech is a US-based public benefit corporation that uses satellite imagery and machine learning to create environmental decision-support technologies. Their HydroForecast service is a neural network-based approach to forecasting streamflow for hydropower operational decision-making. Hydropower operators rely on forecasts for planning and operational decision-making, but the inaccuracy of current forecasts has implications for revenue, risk, and regulatory requirements. Upstream Tech’s SBIR proposal, entitled “Hydropower Decision-Support with Machine Learning and Satellite Driven Forecasts,” leverages machine learning and satellite imagery innovations to improve the accuracy and reliability of hydrologic forecasts.

The Phase 1 project leverages machine learning and satellite imagery innovations to improve the accuracy and reliability of hydrologic forecasts. This work includes three main components:

1. Creating a spatially distributed machine learning model to better represent the varied weather and hydrologic processes within a basin;
2. Incorporating an ensemble of weather forecasts to more accurately convey the river forecast variability caused by the range of possible future weather patterns; and
3. Leveraging the latest research on explainable machine learning to enable users to understand what is driving changes in the forecast and how they make their predictions, via an easy-to-use web dashboard.