Having accurate and high-resolution information on the distribution and evolution of snow helps constrain forecasts (weeks-to-months timescale) of water availability

The Bureau of Reclamation awarded a $1,175,151.46 Cooperative Agreement on April 28, 2025 to Oregon State University (OSU) under the Snow Water Supply Forecasting program (CFDA 15.078). The project aims to improve water supply forecasts by fusing high-resolution LiDAR data with in-situ snow measurements to better model snowpack distribution and evolution. Key objectives include: (1) integrating LiDAR (high spatial resolution, low temporal) with snow telemetry and community science data (low spatial, high temporal) to enhance snowpack modeling, and (2) scaling up LiDAR overflights to larger areas to obtain high-accuracy model results. The project will leverage new airborne LiDAR data acquisitions in the Oregon Cascades. OSU is partnering with NV5 Geospatial, Inc. and the State of Alaska on sub-award efforts focused on fusing LiDAR and in-situ measurements to improve snowpack estimates.

This project contributes to the improvement of water supply forecasts by acquiring new datasets and by looking for new ways to blend and optimize datasets that will improve both the accuracy and resolution of our understanding of snow. This project will use several datasets to help improve snowpack models. In addition to leveraging existing datasets, new airborne light detection and ranging data will be acquired in the oregon cascades. The project has two main objectives: (1) fuse light detection and ranging (high spatial resolution, low temporal resolution) data with point data from snow telemetry and community science programs (low spatial resolution, high temporal resolution) to obtain better model results than using just one data source (2) scale a relatively small light detection and ranging over-flight to much larger areas and obtain high-accuracy model results. The project outcomes will maximize the benefits of costly flights to water supply forecasting.