Evaluation of Radar Quantitative Precipitation Estimates (QPEs) as an Input of Hydrological Models for Hydrometeorological Applications

Abstract

Weather radar provides real-time, spatially distributed precipitation estimates, whereas traditional gauge data are restricted in space. The use of radar quantitative precipitation estimates (QPEs) as an input of hydrological models for hydrometeorological applications has increased with the development of weather radar worldwide. New dual-polarization technology and algorithms are showing improvements to radar QPEs. This study evaluates radar QPEs from C-band radar at King City, Canada (WKR), and NEXRAD S-band radar at Buffalo, New York (KBUF), to verify the reliability and accuracy for operational use in the Humber River (semiurban) and Don River (urban) watersheds in the Greater Toronto Area (GTA), Canada. Twenty rainfall events that occurred from 2011 to 2017 were determined from hourly gauge measurements and compared with nine radar QPEs. Rain rates were estimated with different algorithms using three dual-polarized reflectivity values: horizontal reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP. The correlation coefficient, bias, detection, and root-mean-square error were calculated and averaged over all events for each gauge station to show the spatial distribution and in a similar pattern to represent the variation by the event. The quality of the results in terms of accuracy and reliability indicates that the radar QPEs from KBUF S-band and WKR C-band multiparameter rain rate estimators can be effectively used as precipitation forcing of hydrological models for hydrometeorological applications. The high spatiotemporal resolution, long-term data archive, and good percent detection of radar QPEs can facilitate hydrometeorological applications by providing a continuous time series for hydrological models.

The Use of Weather Radar Data: Possibilities, Challenges and Advanced Applications

“…Recent progress and changes in weather radar hydrologic applications make its use a crucial tool for water resource management. The main topics of growth concerning weather radar applied to hydrology related to: (i) radar QPE [42][43][44][45][46], (ii) multi-radar and multi-sensor precipitation analysis [47][48][49], (iii) hydrologic modelling [50][51][52], (iv) urban hydrologic and hydraulic applications [48,[53][54][55][56], (v) precipitation frequency analysis [57,58], (vi) hydrometeorological process studies [59,60], (vii) precipitation nowcasting, forecasting [61], (viii) hydrometeorological applications [62].…”

Use of Radar Quantitative Precipitation Estimates (QPEs) for Improved Hydrological Model Calibration and Flood Forecasting

“…It is assumed that TRCA rain gauges characterize the precipitation distribution over the entire watershed. This assumption is valid due to the relatively small size of the watershed and relatively high rain gauge density of one gauge per ;75 km 2 (Wijayarathne et al 2020b). Subhourly (5-15 min) streamflow data from 2013 to 2018 recorded by the Water Survey of Canada (compiled at https://wateroffice.ec.gc.ca/search/historical_ e.html) were collected from a long-term flow gauge named ''Islington'' (identifier: 02HC033) (Fig.…”

“…In Canada, research in weather radar began after the Second World War in 1943 under the project Stormy Weather (Sills and Joe 2019;Douglas 1990). Weather radars were subsequently used for various hydrological studies in the Canadian context (Wijayarathne et al 2020a;Hassan et al 2019;Sills and Joe 2019;Huang et al 2010;Hudak et al 2008Hudak et al , 2002Brown et al 2007;Chen and Farrar 2007;Germann and Zawadzki 2004;Germann and Zawadzki 2002;Bellon and Zawadzki 1994;Bellon andAustin 1984, 1978;Bellon et al 1980;Barge et al 1979). The main applications of weather radar in Canada include determining the type of precipitation, precipitation features, and structure, operational forecasting such as weather forecasts and snow depth predictions, operational weather warnings, and as a tool to validate atmospheric models (Sills and Joe 2019).…”

“…A significant improvement in radar QPEs was observed after the introduction of dual-polarization technology and prototype algorithms in Canada (Boodoo et al 2015;Hall et al 2015;Chandrasekar et al 2013;Bringi et al 2011;Sugier et al 2006;Ryzhkov et al 2005), with dual-polarized approaches producing more accurate radar QPEs than is possible with single-polarized radar. In addition to dual-polarization, a significant improvement to radar QPEs is possible via adjustment of values to match rain gauge observations (radar-gauge merging) (Wijayarathne et al 2020b;Ochoa-Rodriguez et al 2019;Falck et al 2018;Wang et al 2015;Goudenhoofdt and Delobbe 2009;Vieux and Bedient 2004). Radar-gauge merging combines the advantages of both gauge and radar QPEs while minimizing their weaknesses to produce accurate and reliable radar QPEs (McKee and Binns 2016).…”

Hydrological Analysis of Extreme Rain Events in a Medium-Sized Basin

“…Paixao et al [7] suggested the simultaneous use of remotely sensed radar observations and tipping bucket rain gauges recording, to better identify areas with homogeneous severe precipitation. The effectiveness of radar quantitative precipitation estimates (QPEs) for the assessment of reliable rainfall intensity to be used to hydrological software was also punctuated by Wijayarathne et al [8].…”