Radar-Rainfall Technology Integration into Hydrologic and Hydraulic Modeling Projects
This chapter describes the background and methodology for integrating gauge and radar rainfall measurements into hydraulic and hydrologic modeling projects. Considering the importance of rainfall in modeling physical systems such as watersheds or sewer systems, attention to the accuracy, precision, spatial resolution, and processing protocol is essential for successful project completion. Using rain gauge network to adjust radar rainfall requires assessment of the rain gauge network and historical data that can help ensure accurate and reliable data. Radar is growing in acceptance in the management, monitoring, and design of sewer system improvements. Important aspects of how radar measures rainfall include understanding how measured reflectivity is converted to rainfall rates and then adjusted using rain gauges. Limitations and advantages of incorporating this data source depends on quality control and assurance procedures applied by project personnel and by the operators of the radar.
The NEXRAD (WSR-88D) radar deployed in the U.S. is a nationwide system that can be used in urban drainage system applications with appropriate post- and real-time processing. Services are available that provide both real-time products useful in sewer system management and real-time control. Retrospective studies are possible for re-constructing events using radar data from multiple or single radar installations, and for which flow monitored data was collected. Comparison of hydrographs produced using rain gauges versus radar reveals that radar is capable of producing accurate hydrographs. Calibrating hydraulic models to account for infiltration and inflow induced by rainfall is accurate when using rainfall that is spatially and temporally representative of rainfall over the specific catchment.
Results are presented showing that peak flow, depth, volume agreement, and hydrograph shape are better matched than with the closest gauge. Overall performance during calibration using radar rainfall for 29 events revealed that the median agreement between monitored and modeled flow depths is 12.4%. Using representative rainfall for model calibration helps avoid parameter distortion beyond physically realistic or typical values. This improves reliability and confidence in the model that translates translates to better decision making and accurate definition of infrastructure improvement projects. Guidelines and recommendations are provided to ensure proper integration of radar rainfall.
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