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Abstract
<jats:p>The Snow-Informed Reservoir Operations (SIRO) project aims to reduce uncertainty in forecasting snowpack water storage, a primary inflow source for many of the 752 reservoirs across the US monitored by the US Army Corps of Engineers (USACE). To establish a baseline of current practices and operational needs, the SIRO team surveyed and interviewed USACE district and division personnel in fall 2025. The investigation revealed that operators primarily rely on traditional methods such as locally developed regressions, sparse in situ station data, and institutional knowledge, with limited use of snow models. Key challenges contributing to forecast uncertainty include unreliable model outputs that often lack uncertainty quantification, rigid water control plans, data accessibility, and difficulties in predicting extreme weather events (i.e., snow drought and rain-on-snow). Moving forward, these findings will guide the SIRO project’s targeted technical improvements, including snow data assimilation, and model intercomparison experiments to advance current modeling capabilities, while strengthening the collaboration between researchers and operators to produce more effective decision support tools.</jats:p>