Zusammenfassung: | |
Optimal spatial assessment of short-time step precipitation for hydrological modelling is still an important research question considering the poor observation networks for high time resolution data. The main objective of this paper is to present a new approach for rainfall observation. The idea is to consider motorcars as moving rain gauges with windscreen wipers as sensors to detect precipitation. This idea is easily technically feasible if the cars are provided with GPS and a small memory chip for recording the coordinates, car speed and wiper frequency. This study explores theoretically the benefits of such an approach. For that a valid relationship between wiper speed and rainfall rate considering uncertainty was assumed here. A simple traffic model is applied to generate motorcars on roads in a river basin. Radar data are used as reference rainfall fields. Rainfall from these fields is sampled with a conventional rain gauge network and with several dynamic networks consisting of moving motorcars, using different assumptions such as accuracy levels for measurements and sensor equipment rates for the car networks. Those observed point rainfall data from the different networks are then used to calculate areal rainfall for different scales. Ordinary kriging and indicator kriging are applied for interpolation of the point data with the latter considering uncertain rainfall observation by cars e.g. according to a discrete number of windscreen wiper operation classes. The results are compared with the values from the radar observations. The study is carried out for the 3300 km 2 Bode river basin located in the Harz Mountains in Northern Germany. The results show, that the idea is theoretically feasible and motivate practical experiments. Only a small portion of the cars needed to be equipped with sensors for sufficient areal rainfall estimation. Regarding the required sensitivity of the potential rain sensors in cars it could be shown, that often a few classes for rainfall observation are enough for satisfactory areal rainfall estimation. The findings of the study suggest also a revisiting of the rain gauge network optimisation problem.
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Lizenzbestimmungen: | CC BY 3.0 Unported - http://creativecommons.org/licenses/by/3.0/ |
Publikationstyp: | Article |
Publikationsstatus: | publishedVersion |
Erstveröffentlichung: | 2010 |
Schlagwörter (englisch): | Accuracy level, Different scale, Discrete numbers, Dynamic network, Germany, Harz mountains, High-time resolution, Hydrological modelling, Indicator kriging, Memory chips, Modelling studies, New approaches, Ordinary kriging, Point data, Radar data, Radar observations, Rain gauge networks, Rain gauges, Rainfall data, Rainfall estimations, Rainfall fields, Rainfall rates, Research questions, River basins, Spatial assessment, Time step, Traffic model, Estimation, Gages, Interpolation, Meteorological instruments, Optimization, Radar, Rain gages, Sensors, Watersheds, Rain, accuracy assessment, automobile, data set, GPS, interpolation, kriging, optimization, precipitation (climatology), radar, rainfall-runoff modeling, raingauge, river basin, sensor, spatial analysis, Germany, Harz Mountains |
Fachliche Zuordnung (DDC): | 550 | Geowissenschaften, 551 | Geologie, Hydrologie, Meteorologie |
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