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Presentation
Rapidly Develop, Deploy and Scale a Snow Model in the Cloud, Providing Valuable Real Time Information for More Efficient Water Management in California
AGU Fall Meeting (2019)
  • Scott Havens, USDA-ARS
  • Danny G. Marks, USDA-ARS
  • Ernesto Trujillo, USDA-ARS
  • Andrew R. Hedrick, USDA-ARS
  • Micah Johnson, USDA-ARS
  • Mark Robertson, USDA-ARS
  • Frederick B. Pierson, USDA-ARS
Abstract
The USDA Agricultural Research Service is involved in a technology transfer project to enhance water supply management in the Western US through the application of a snow modeling system. Cloud services are readily attainable by our stakeholders and the modeling system has been designed from the ground up to utilize the computational abilities of the cloud. The last few years of development have been focused on a proof of concept modeling system (Automated Water Supply Model - AWSM) on a private cloud in order to evaluate the modeling system performance. During snowmelt season of 2019, ARS utilized SCINet on AWS to successfully provide modeled snow data to decision makers in real time. A publicly available GIS server allowed users to browse real time model results for a 14,000 km2 region of the high Sierra Nevada in California. Detailed snow model summary reports were hosted on AWS to provide web access to the stakeholders. Because of the modeling efforts and data distribution of the past year, water managers in California were able to modify their operational decisions to more efficiently manage snowmelt runoff, saving water for summer agricultural use valued in the 10’s of millions of dollars.
Disciplines
Publication Date
December 10, 2019
Location
San Francisco, CA
Citation Information
Scott Havens, Danny G. Marks, Ernesto Trujillo, Andrew R. Hedrick, et al.. "Rapidly Develop, Deploy and Scale a Snow Model in the Cloud, Providing Valuable Real Time Information for More Efficient Water Management in California" AGU Fall Meeting (2019)
Available at: http://works.bepress.com/ernesto-trujillo/34/