The HydroFrame project combines cutting-edge environmental modeling approaches with modern software principals to build an end-to-end workflow for regional and continental scale scientific applications, by enabling modelers to extract static datasets from continental datasets and execute them using high performance computing hardware hosted at Princeton University. In prior work we have provided the capability for users to extract domain data for the ParFlow model at local scales and execute them using freely accessible cloud computing services (i.e. MyBinder.org). We extend this functionality to support larger study areas and timescales by leveraging Kepler for workflow management, Flask for web interface design, and Slurm for asynchronous job execution.