Year Established: 2019 Start Date: 2019-06-01 End Date: 2020-05-31
Total Federal Funds: $14,824 Total Non-Federal Funds: $34,089
Principal Investigators: Eric A. Sproles
Abstract: Mountain snowpack is an essential water resource for people, economies, and ecosystems in Montana, the western United States, and across the Earth. This resource functions as a natural water tower that collects, stores, and releases water to fill streams and recharge aquifers. Despite its importance, measurements of mountain snowpacks are sparse, and even when available they rely on hydro-meteorological monitoring sites that are location-specific. These point-based networks are not representative of rugged mountain landscapes, and are stationary locations in an unstationary climate. Satellite measurements capture variability across mountain topography and bridge sparse monitoring networks, providing near-real time data with global coverage. For example, NASAâ€™s Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily snow cover product (MOD10A1) at 500m resolution. These Earth observations provide a unique perspective from space offering novel insights that improve our understanding of complex landatmosphere interactions from pole to pole, fundamentally changing the way that the Earth is measured, mapped, and modeled. With broad spatial and temporal coverage, satellite products support new water resource metrics and novel insights into the spatial and temporal connections between mountain snowpack and downstream water resources that support basic and applied science. Additionally, Earth observations provide key input data for streamflow prediction models, and are especially valuable in data sparse watersheds. This project will provide water and natural resource stakeholders in Montana with a prototype streamflow forecast model that assimilates satellite measurements. This approach will build upon the success of SnowCloudHydro, a cloud-based stream forecast framework that uses spatially-integrated measurements of snow cover to forecast streamflow for watersheds in Chile developed by Sproles et al. . This Montana Water Center project will expand the initial SnowCloudHydro framework to include space-borne measurements of precipitation and soil moisture. The computing component of SnowCloudHydro is entirely web-based, utilizing the Google Earth Engine (GEE) platform for data analysis and geovisualization. The methods combine cloud-based data access, interactive web-based geospatial data visualization, and forecast tools through a web-browser. This innovative approach sets a new paradigm for delivering time-critical snow hydrology information to resource managers, decision-makers, and researchers. Specifically, this project will: Objective 1) Improve SnowCloudHydro using satellite measurements of snow cover, precipitation, and soil moisture for implementation in Montana watersheds. Objective 2) Test how the modelâ€™s skill is related to watershed size and characteristics (e.g. Where are the higher/lower levels of forecast skill?). Objective 3) Integrate the results of Objectives 1 & 2 to develop a functioning stream forecast model through a web-based portal for at least six watersheds in Montana. These deliverables will aid the efforts of water resource stakeholders and professionals across Montana and beyond. The goals and scope of this project directly support this solicitationâ€™s objectives by advancing hydrological knowledge and understanding, providing research and outcomes that are highly relevant to Montana water stakeholders and decision-makers, and by supporting graduate student research.