Precipitation Estimates from Microwave Links for Urban Hydrology: Improving the Accuracy Using Wet-Antenna Calibration

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F21%3A00357497" target="_blank" >RIV/68407700:21110/21:00357497 - 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

Precipitation Estimates from Microwave Links for Urban Hydrology: Improving the Accuracy Using Wet-Antenna Calibration

Popis výsledku v původním jazyce

Commercial microwave links (CMLs) can be used as unintentional rainfall sensors and provide path-integrated quantitative precipitation estimates (QPEs). However, the bias common in CML QPEs, which can be often attributed to imprecise correction for wet antenna attenuation (WAA), compromises the application of CML QPEs for many hydrological tasks. To achieve optimal performance, WAA models should be calibrated using independent local rainfall data with high spatiotemporal resolution. Such data are, however, often not available. We explore the possibility to reduce the bias in CML QPEs by calibrating a WAA model using data which could be better available to urban hydrology professionals. We show that, when simulating discharges in a small (1.3 km2) urban catchment, using the WAA model calibrated to discharge observations or to 60-min data from a single rain gauge in the distance of 7 km, the rainfall-runoff model performance is considerably improved compared to uncalibrated CML QPEs.

Název v anglickém jazyce

Precipitation Estimates from Microwave Links for Urban Hydrology: Improving the Accuracy Using Wet-Antenna Calibration

Popis výsledku anglicky

Commercial microwave links (CMLs) can be used as unintentional rainfall sensors and provide path-integrated quantitative precipitation estimates (QPEs). However, the bias common in CML QPEs, which can be often attributed to imprecise correction for wet antenna attenuation (WAA), compromises the application of CML QPEs for many hydrological tasks. To achieve optimal performance, WAA models should be calibrated using independent local rainfall data with high spatiotemporal resolution. Such data are, however, often not available. We explore the possibility to reduce the bias in CML QPEs by calibrating a WAA model using data which could be better available to urban hydrology professionals. We show that, when simulating discharges in a small (1.3 km2) urban catchment, using the WAA model calibrated to discharge observations or to 60-min data from a single rain gauge in the distance of 7 km, the rainfall-runoff model performance is considerably improved compared to uncalibrated CML QPEs.

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

2021

Kód důvěrnosti údajů

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