Year Established: 2019 Start Date: 2019-05-31 End Date: 2020-05-30
Total Federal Funds: $15,000 Total Non-Federal Funds: $30,000
Principal Investigators: Russell J. Qualls
Abstract: Water affects a huge portion of the Idaho economy. Water security, the ability to provide water in the quantity and quality desirable to sustain human health, and livelihood and maintain environmental quality, is essential. Improved hydrologic prediction can help reduce uncertainty, which threatens water security. In snowmelt runoff modeling, the actual location of the snow/land interface is important to snowmelt physics since exposed land adjacent to snow can heat the air and generate turbulent advection which provides much of the snowmelt energy. The current generation of energy balance snowmelt models do not use remotely sensed snow covered area as a model input because cloud obstruction of the data is too prevalent to meet model needs. Instead, snowpack location is a simulated model output thereby inducing uncertainty with respect to this important snowmelt physics process. Additionally, where they have been implemented, algorithms which include heat advection between the land/snow interface, incorporate tunable parameters with the algorithm. Together, these degrade the modelâ€™s ability to adapt to conditions different from its normal operating range. We have developed a new tool that uses Principal Component Analysis which can rapidly synthesize the recurrent snowmelt pattern across a watershed from multiple years of satellite images. The tool enables us to produce cloud-free snow covered area images in near-real time, as well as for retrospective and climate scenario hydrologic simulation. We propose to develop automated procedures to produce cloud-free snow covered image for agency stakeholders for whom the snow pattern itself is important, such as the Natural Resources Conservation Service operating the Snow Telemetry (SNOTEL) network and the US Army Corp of Engineers for reservoir operations. We also plan to partner with runoff modeling stakeholders to incorporate cloud-free remotely sensed snow covered area images produced by our melt pattern model into their snowmelt runoff models. These stakeholders include both research model developers and stakeholder model users. We expect to improve model accuracy and enhance water security in Idaho through these stakeholder partnerships.