With continuing growth of urban populations worldwide, high-resolution hydrologic forecasting is an increasingly important hydroinformatics service for large urban areas. In the Dallas-Fort Worth (DFW) area, the Collaborative Adapting Sensing of Atmosphere (CASA) WX program has been providing real-time hydrologic products, such as rainfall and streamflow, at 1 min–500 m resolution using the NWS Research Hydrologic Distributed Model forced by the Quantitative Precipitation Estimate from a network of X-band weather radars. There is an increasing demand, however, for even higher-spatial resolution hydrologic products. In this paper, we assess the ability of the current streamflow product to capture the hydrologic response of urban catchments in the DFW area, the utility of ultrasonic distance sensors for real-time sensing of water level in urban streams, and the feasibility of higher-resolution operation using parallel processing and cloud computing. We show that the CASA WX streamflow product skillfully captures the stage and streamflow response from rainfall for the majority of the nine catchments studied, but that timing errors significantly deteriorate the quality of streamflow prediction for certain basins. Comparative evaluation of different computing models shows that a reduction in runtime of up to 34% is possible with parallel processing at 1 min–250 m resolution.

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