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SNOTEL,the Soil Climate Analysis Network,and water supply forecasting at the Natural Resources Conservation Service: Past,present, and future
Authors:Sean W Fleming  Lucas Zukiewicz  Michael L Strobel  Heather Hofman  Angus G Goodbody
Institution:1. National Water and Climate Center, Natural Resources Conservation Service, U.S. Department of Agriculture, Portland, Oregon, USA;2. National Water and Climate Center, Natural Resources Conservation Service, U.S. Department of Agriculture, Portland, Oregon, USA

Contribution: Conceptualization, Writing - original draft, Writing - review & editing;3. National Water and Climate Center, Natural Resources Conservation Service, U.S. Department of Agriculture, Portland, Oregon, USA

Contribution: Conceptualization, Visualization, Writing - original draft, Writing - review & editing

Abstract:The Snow Survey and Water Supply Forecasting (SSWSF) Program and the Soil Climate Analysis Network (SCAN) of the United States Department of Agriculture's Natural Resources Conservation Service (NRCS) generate key observational and predictive information for water managers. Examples include mountain climate and snow monitoring through manual snow surveys and the SNOw TELemetry (SNOTEL) and SNOtel LITE networks, in situ soil moisture data acquisition through the SCAN and SNOTEL networks, and water supply forecasting using river runoff prediction models. The SSWSF Program has advanced continuously over the decades and is a major source of valuable water management information across the western United States, and the SCAN network supports agricultural and other water users nationwide. Product users and their management goals are diverse, and use-cases range from guiding crop selection to seasonal flood risk assessment, drought monitoring and prediction, avalanche and fire prediction, hydropower optimization, tracking climate variability and change, environmental management, satisfying international treaty and domestic legal requirements, and more. Priorities going forward are to continue innovating to enhance the accuracy and completeness of the observational and model-generated data products these programs deliver, including expanded synergies with the remote sensing community and uptake of artificial intelligence while maintaining long-term operational reliability and consistency at scale.
Keywords:water resources  snow  climate  mountain weather  forecasting  remote sensing  modeling
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