Weather Radar Adjustment Using Runoff from Urban Surfaces
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 5
Abstract
Weather radar data used for urban drainage applications are traditionally adjusted to point ground references, e.g., rain gauges. However, the available rain gauge density for the adjustment is often low, which may lead to significant representativeness errors. Yet, in many urban catchments, rainfall is often measured indirectly through runoff sensors. This paper presents a method for weather radar adjustment on the basis of runoff observations ( adjustment) as an alternative to the traditional adjustment on the basis of rain gauges. Data from a new monitoring station in Aalborg, Denmark, were used to evaluate the flow-based weather radar adjustment method against the traditional rain-gauge adjustment. The evaluation was performed by comparing radar-modeled runoff to observed runoff. The methodology was both tested on an events basis and multiple events combined. The results indicate that this adjustment method performs similarly to adjustment on the basis of well-placed rain gauges. This opens up the possibility of using flow measurements as an alternative to or in combination with rain gauges.
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Acknowledgments
The authors would like to acknowledge the Danish Meteorological Institute (DMI) for providing the weather radar data for this study. Furthermore, the authors would like to acknowledge Søren Enggaard A/S, C.W. Obel Ejendomme Aalborg, and COWI A/S Aalborg for their involvement in the realization of the measurement station used to obtain the data at the ground level for this study. The work presented in this paper is a part of the Storm and Water Informatics (SWI) project founded by The Danish Council for Strategic Research.
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Journal of Hydrologic Engineering
Volume 22 • Issue 5 • May 2017
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jan 16, 2015
Accepted: Jul 28, 2015
Published online: Dec 11, 2015
Discussion open until: May 11, 2016
Published in print: May 1, 2017
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