Microwave links for rainfall estimation in an urban environment: Insights from an experimental setup in Luxembourg-City

Although the theoretical aspects of rainfall monitoring through microwave links are quite well established, only few practical applications have evaluated this technique in an operational setting. Microwave links are of particular interest in urban areas, where high frequency measurements are needed due to the fast hydrological response of the system, and link networks are usually already in-place. This study presents the first results of an on-going experiment in Luxembourg-City, which includes two dual-frequency links and several rain gauges at intermediate locations along the links. The experimental set-up allows comparing rain rate estimates based on the individual frequencies as well as estimates based on the difference between the two frequencies. We compared several models for expressing the relationship between attenuation and rain rate, including different baseline estimation methods such as the traditional constant-baseline model and a one-parameter model based on a first order low-pass filter. The models were evaluated using a Bayesian approach and subjected to posterior scrutiny based on several diagnostics. In contrast to previous research, our results indicated that estimates based on the attenuation difference appeared poorer than the estimates based on individual frequencies. The one-parameter baseline estimation method provided consistently better results than the traditional constant-baseline method, which justifies the increased model complexity. Uncertainty of model predictions was relatively large for low intensity rainfall, which highlights one of the limitations of this technique. Models were validated in different periods and on different links, in some cases demonstrating large bias. Model parameters were generally well-identifiable, though uncertainty in the rainfall predictions appeared under-estimated in some cases. © 2012 Elsevier B.V.Fabrizio Fenicia, Laurent Pfister, Dmitri Kavetski, Patrick Matgen, Jean-François Iffly, Lucien Hoffmann, Remko Uijlenhoe