A new tool developed by Washington State University researchers could someday provide daily or weekly forecasts of water availability in the mountains similar to a weather forecast that agencies could use for important water management decisions.
“Snow-water equivalent is critical for decision making because it tells you how much water would be available from the melted snow, which would go through streamflow or watersheds,” said Krishu Thapa, first author on the work and a graduate student in WSU’s School of Electrical Engineering and Computer Science.
“We should be able to provide an exemplar to the rest of the nation,” Kalyanaraman said, “in terms of how to most effectively and responsibly embrace AI into a complex, decision-driven system like agriculture.”
“What this forecasting does is take that to the next level,” said Kirti Rajagopalan, assistant professor in the School of Biological Systems and a co-author on the paper. “Instead of just looking at years in the past, we can fine-tune our model into a smaller subset of future states that are relevant.”
Spatiotemporal SWE forecasting with confidence interval for location i over a horizon h, using k days of historical observations with f attributes. Each blue dot in the map is a SNOTEL location.
