Rainfall estimation using moving cars as rain gauges (RainCars)

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Objective of the proposed research is the investigation of a completely new approach for rainfall estimation using motorcars as moving rain gauges with windscreen wipers as sensors to detect precipitation. This idea would easily be technically feasible if the cars are provided with GPS and a small memory chip for recording the coordinates, car speed and wiper frequency. This initial research will explore theoretically the benefits of such an approach. For that valid relationships between wiper speed and rainfall rate (W-R-relationship) are assumed and derived from laboratory and field experiments. Different traffic models are developed to generate motorcars on roads in a river basin. Radar data are used as reference truth rainfall fields. Rainfall from these fields is sampled from the conventional rain gauge and dynamic car networks. Areal rainfall is calculated from these networks for different scales using geostatistical interpolation methods and compared against truth radar data. The car sensors can be considered as a geosensor network. It allows to measure and process information locally in a decentralized way and thus has benefits with respect to scalability, which is crucial when large areas have to be covered with large amounts of measurement units.