We leverage 4 years of hourly onsite WUE data from 1000+ locations to build scalable forecasting models for any location in the US. Instead of training expensive, location-specific models, we leverage the power of cluster-specific models by experimenting across techniques in time series clustering to group cities with similar patterns. By creating representative series for each cluster and applying SARIMA models, we enable efficient, accurate forecasting. This multilevel approach is cost-effective and adaptable for future scalability.