Details
| Original language | English |
|---|---|
| Pages (from-to) | 3907-3922 |
| Number of pages | 16 |
| Journal | Hydrology and Earth System Sciences |
| Volume | 20 |
| Issue number | 9 |
| Publication status | Published - 26 Sept 2016 |
Abstract
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 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 rain rate. 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. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.
ASJC Scopus subject areas
- Environmental Science(all)
- Water Science and Technology
- Earth and Planetary Sciences(all)
- Earth and Planetary Sciences (miscellaneous)
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In: Hydrology and Earth System Sciences, Vol. 20, No. 9, 26.09.2016, p. 3907-3922.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Areal rainfall estimation using moving cars – computer experiments including hydrological modeling
AU - Rabiei, Ehsan
AU - Haberlandt, Uwe
AU - Sester, Monika
AU - Fitzner, Daniel
AU - Wallner, Markus
N1 - Funding information: The study was funded by the German Research Foundation (DFG, 3504/5-2). The authors thank the German Weather Service (DWD) for the meteorological data. Moreover, the authors wish to thank Anne Fangmann and Sarah Louise Collins for their comments on an earlier draft of the paper. The authors are very thankful to the associated editor, G. Pegram and one anonymous referee for their critical remarks on the manuscript to improve the paper.
PY - 2016/9/26
Y1 - 2016/9/26
N2 - 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 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 rain rate. 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. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.
AB - 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 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 rain rate. 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. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.
UR - http://www.scopus.com/inward/record.url?scp=84989350563&partnerID=8YFLogxK
U2 - 10.5194/hess-20-3907-2016
DO - 10.5194/hess-20-3907-2016
M3 - Article
AN - SCOPUS:84989350563
VL - 20
SP - 3907
EP - 3922
JO - Hydrology and Earth System Sciences
JF - Hydrology and Earth System Sciences
SN - 1027-5606
IS - 9
ER -