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Using NASA Earth Observations to Monitor Snow Cover Extent for Water Resource Management on the Navajo Nation
  • Suzanne Goldstein,
  • Amber Jean McCullum,
  • Carlee McClellan
Suzanne Goldstein
San Francisco State University

Corresponding Author:[email protected]

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Amber Jean McCullum
Bay Area Environmental Research Institute, NASA Ames Research Center
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Carlee McClellan
Navajo Nation Dept. of Water Resources
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The southwestern U.S. has been experiencing prolonged drought conditions contributing to declines in snowpack and surface water supply. On the Navajo Nation (NN), the largest U.S. federally recognized sovereign tribal nation in land area, snowpack is an essential reservoir for surface water storage and aquifer recharge, but has not been extensively monitored. Within the NN, only two high elevation regions, Chuska Mountains and Defiance Plateau, have in-situ snow monitoring at eight sites (consisting of two SNOTEL stations and eight snow courses). With climate change contributing to long-term temperature increases, patterns of snowfall and snowmelt are changing and NN leaders are recognizing the need for more detailed and reliable monitoring systems. This study explored how NASA Earth Observations can be used to provide more frequent, high-resolution tracking of snow cover extent on the NN, and how those data can offer actionable insights for local water managers. The Normalized Difference Snow Index (NDSI), as derived from NASA MODIS products, was used to create daily cloud/gap-free images of Snow Covered Area (SCA) during the winter months (November – April) from 2002 to 2018. Aggregated weekly and monthly means were then constructed to study spatial and temporal anomalies in SCA. These data were compared with the available ground-based measurements of snow water equivalent (SWE). Results indicate that SCA anomalies can serve as a proxy for monitoring snowpack variability across all high-elevation areas of the NN. SCA anomalies also suggest that the NN snowpack is exhibiting increased variability during peak winter months, along with declines in the spring months, consistent with broader regional climate trends. This study aids in the establishment of remotely sensed snow monitoring on the NN. Further analyses would be improved through the use of additional snow products, such as the MODIS Snow Covered-Area and Grain size retrieval algorithm (MODSCAG) to estimate fractional snow cover and snow grain size, and NASA’s Airborne Snow Observatory (ASO) to estimate snow albedo and SWE.