The importance of adequate correction for the wet antenna effect when predicting urban rainfall-runoff using microwave link data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F20%3A00345276" target="_blank" >RIV/68407700:21110/20:00345276 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The importance of adequate correction for the wet antenna effect when predicting urban rainfall-runoff using microwave link data

Popis výsledku v původním jazyce

Commercial microwave links (CMLs) are point-to-point radio connections densely covering urban areas around the world. They can provide quantitative precipitation estimates (QPEs) as they operate at frequencies where radio signal is attenuated by rainfall droplets. The attenuation data can be retrieved from CMLs at sub-minute temporal resolutions and in near real time, suggesting that CML QPEs could be very perspective for urban rainfall-runoff prediction. However, if the attenuation due to raindrops is not adequately separated from other attenuation sources, such as the wet antenna attenuation (WAA), the resulting QPEs can contain considerable systematic errors. Although the wet antenna effect has been lately extensively investigated, implications of various WAA estimation methods on rainfall-runoff prediction in urban environments remain unclear. In this study, we show that the WAA estimation model choice crucially affects simulated rainfall-runoff. In a small (1.3 km2) urban catchment in Prague, Czech Republic, we collected for three years data from 16 real-world CMLs, three traditional rain gauges and a flow meter at the catchment outlet. We correct QPEs derived from the CMLs for WAA using i) a simple approach modelling WAA as a constant and ii) the model of Valtr et al. (2019) explicitly relating WAA to rainfall intensity. First, the WAA model parameters are calibrated using the rain gauge data. Next, using a different event set, CML QPEs are derived without additional rainfall information. The QPEs in the 1-min resolution are then propagated through a SWMM rainfall-runoff model. The modelling performance is quantified by comparing the predicted and observed runoffs.

Název v anglickém jazyce

The importance of adequate correction for the wet antenna effect when predicting urban rainfall-runoff using microwave link data

Popis výsledku anglicky

Commercial microwave links (CMLs) are point-to-point radio connections densely covering urban areas around the world. They can provide quantitative precipitation estimates (QPEs) as they operate at frequencies where radio signal is attenuated by rainfall droplets. The attenuation data can be retrieved from CMLs at sub-minute temporal resolutions and in near real time, suggesting that CML QPEs could be very perspective for urban rainfall-runoff prediction. However, if the attenuation due to raindrops is not adequately separated from other attenuation sources, such as the wet antenna attenuation (WAA), the resulting QPEs can contain considerable systematic errors. Although the wet antenna effect has been lately extensively investigated, implications of various WAA estimation methods on rainfall-runoff prediction in urban environments remain unclear. In this study, we show that the WAA estimation model choice crucially affects simulated rainfall-runoff. In a small (1.3 km2) urban catchment in Prague, Czech Republic, we collected for three years data from 16 real-world CMLs, three traditional rain gauges and a flow meter at the catchment outlet. We correct QPEs derived from the CMLs for WAA using i) a simple approach modelling WAA as a constant and ii) the model of Valtr et al. (2019) explicitly relating WAA to rainfall intensity. First, the WAA model parameters are calibrated using the rain gauge data. Next, using a different event set, CML QPEs are derived without additional rainfall information. The QPEs in the 1-min resolution are then propagated through a SWMM rainfall-runoff model. The modelling performance is quantified by comparing the predicted and observed runoffs.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10501 - Hydrology

Projekt

<a href="/cs/project/GC20-14151J" target="_blank" >GC20-14151J: Plošné srážkové odhady kombinující pozorování z mikrovlnných spojů a statistickou asimilaci dat (SpraiLINK)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů