Technical abstract: salient proposes to develop technology for accurate subseasonal to seasonal (S2S) water availability forecasts so that communities may manage water resources in preparation for…

Technical abstract: salient proposes to develop technology for accurate subseasonal to seasonal (S2S) water availability forecasts so that communities may manage water resources in preparation for hazardous events like floods and droughts. Hydrological models face challenges related to data inputs, as climate change has been presenting weather patterns atypical from historical data. Without quality data inputs, the accuracy of the output from hydrological models suffers. To overcome these challenges, salient proposes to use improved S2S forecasts as the weather input to variable infiltration capacity (VIC) hydrological forecasts, thus providing improved water availability forecasts on the S2S timeframe. Salients base S2S forecast technology uses machine learning and various oceanic, atmospheric, and land-based variables to make improved predictions of weather up to a year in advance. In phase i, salient developed a predictive hydrologic model for soil moisture and river flow by combining its weather forecasts with the VIC hydrologic model for the central valley of california. Phase II will address challenges related to 1) downscaling salients forecasts for utilization as an input to the VIC model for improved soil moisture predictions, and 2) improving scalability to make the deployment and execution of VIC hydrological models for the continental united states feasible. Summary of anticipated results: successful completion of the proposed work will create a more efficient, scalable, and accurate version of the phase i model and improve S2S forecast variables so that distributed hydrological models can more accurately forecast at the 252-week horizon for a variety of commercial applications. Many markets depend on water availability to thrive, including agriculture, energy, supply chain and logistics, disaster risk management, and the carbon market. At local scales, decision-makers depend on models like VIC to make strategic decisions based on hydrological responses to resource use. At present, the current VIC model does not account for human impacts from climate change, which directly affect water availability. Salients S2S weather insights (currently available) and water insights (in development via this funding) help enterprise customers optimize performance, mitigate risk, improve resiliency, and plan initiatives up to a year in advance. Combining salients current technology with VIC will result in more useful hydrological models and water availability forecasts.