Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

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Rabiei, E.; Haberlandt, U.; Sester, M.; Fitzner, D.; Wallner, M.: Areal rainfall estimation using moving cars - computer experiments including hydrological modeling. In: Hydrology and Earth System Sciences Discussions (2016), S. 1-38. DOI:

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Sum total of downloads: 161

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have been emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rainfall amounts. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e. RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance, but also for use in hydrological modeling. The results show that the RCs considering measurement errors derived from laboratory experiments provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Even assuming higher uncertainties for RCs as obtained from the laboratory up to a certain level is observed practical.
License of this version: CC BY 3.0
Document Type: article
Publishing status: publishedVersion
Issue Date: 2016
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 135 83.85%
2 image of flag of United States United States 12 7.45%
3 image of flag of India India 3 1.86%
4 image of flag of Czech Republic Czech Republic 2 1.24%
5 image of flag of Russian Federation Russian Federation 1 0.62%
6 image of flag of Philippines Philippines 1 0.62%
7 image of flag of Mexico Mexico 1 0.62%
8 image of flag of Japan Japan 1 0.62%
9 image of flag of Indonesia Indonesia 1 0.62%
10 image of flag of Argentina Argentina 1 0.62%
    other countries 3 1.86%

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