Chapter 5
Use of Radar Rainfall Data in Hydrologic Modeling
Publication: Radar Rainfall Data Estimation and Use (MOP 139)
Abstract
This chapter discusses radar rainfall data formats for use in hydrologic models. Radar rainfall estimation offers potential to provide accurate rainfall surfaces because radar can cover entire watersheds completely, provide high spatial resolution, and provide high temporal resolution. Hydrologic models are grouped into two categories: lumped or gridded. A lumped hydrologic model combines all hydrologic processes within a single watershed or sub-watershed into a single element. A gridded model considers hydrologic processes within a rectilinear grid cell. The National Weather Service Weather Service Radar Doppler 88D radars were first installed in the early to mid-1990s. However, the growing national database of radar rainfall estimates represents the first opportunity for hydrologists to conduct in-depth studies of rainfall events’ geometric properties.
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References
Curtis, D. C., J. Humphrey, and D. W. Bare. 2011. “Radar-based depth area reduction factors for Colorado.” Presented at the American Geophysical Union Fall Meeting, San Francisco, CA, December 5-9.
Durrans, S. R., L. T. Julian, and M. Yekta. 2002. “Estimation of depth-area relationships using radar-rainfall data.” J. Hydrol. Eng. 7(5).
Gill, T. D. 2005. “Transformation of point rainfall to areal rainfall by estimating areal reduction factors, using radar data, for Texas.” Master’s thesis, Civil Engineering, Texas A&M Univ. Accessed August 2018. http://hdl.handle.net/1969.1/2420.
Harader, E., V. Borrell-Estupina, S. Ricci, M. Coustau, O. Thual, A. Piacentini, et al. 2012. “Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France.” Hydrol. Earth Sys. Sci. 16: 4247-4264.
Hoblit, B., S. Zelinka, C. Castello, and D. Curtis. 2004. “Spatial analysis of storms using GIS.” Proc., 24th Ann. ESRI Int. User Conf., ESRI, Redlands, CA.
Kim, J., and C. Yoo. 2014. “Use of a dual Kalman filter for real-time correction of mean field bias.” J. Hydrol. 519: Part D, 2785-2796.
Vieux, B. E., P. B. Bedient, and E. Mazroi. 2005. “Real-time urban runoff simulation using radar rainfall and physics-based distributed modeling for site-specific forecasts.” Proc., 10th Int. Conf. on Urban Drainage, Copenhagen, Denmark, August 21-26.
Zhu, D., D. Z. Peng, and I. D. Cluckie. 2013. “Statistical analysis of error propagation from radar rainfall to hydrological models.” Hydrol. Earth Sys. Sci. 17, 1445-1453.
Information & Authors
Information
Published In
Radar Rainfall Data Estimation and Use (MOP 139)
Pages: 59 - 62
Editors: Chandra S. Pathak, Ph.D., P.E., D.WRE, and Ramesh S. V. Teegavarapu, P.E.
ISBN (Print): 978-0-7844-1511-5
ISBN (Online): 978-0-7844-8176-9
Copyright
© 2018 American Society of Civil Engineers.
History
Published in print: Dec 2, 2018
Published online: Dec 4, 2018
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