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Evaluation of radar-rain gauge merging methods for urban hydrological applications: Relative performance and impact of gauge density

Abstract:

Rainfall estimates of very high accuracy and resolution are required for urban hydrological applications, given the high impermeability, small size and fast response which characterise urban catchments. Traditionally, urban drainage modelling applications have relied mainly upon rain gauge data as input, given that these sensors provide relatively accurate point rainfall estimates near the ground. However, they cannot capture the spatial variability of rainfall, which has a significant impact on the urban hydrological system and thus on the modelling of urban runoff. With the advent of weather radars, radar quantitative precipitation estimates (QPEs) with higher temporal and spatial resolution have become increasingly available and have started to be used operationally for urban storm-water modelling. Nonetheless, the insufficient accuracy of radar QPEs, arising from the indirect measurement of rainfall-often significantly high above ground-, has proven problematic and has hindered its widespread practical use (Schellart et al., 2012). In order to improve the accuracy of radar rainfall estimates while preserving their spatial description of rainfall fields, it is possible to dynamically adjust them based on rain gauge measurements. Gauge-based adjustment of radar QPEs, also referred to as radar-rain gauge combination or merging, has been an active topic of research over the last few decades and has proven effective to improve the accuracy of radar QPEs, thus improving their applicability for hydrological applications. However, most gauge-based adjustment methods have been tested and applied at large spatial and temporal scales-of the order of thousands of square kilometres and at temporal resolutions 1 h - (e.g. (Goudenhoofdt & Delobbe, 2009)), and their suitability for small-scale urban hydrology is seldom explored.