Areal rainfall estimation using moving cars – computer experimentsincluding hydrological modeling
Areal rainfall estimation using moving cars – computer experimentsincluding hydrological modeling
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DOI：
10.5194/hess-20-3907-2016
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发表时间：
2015-12
影响因子：
6.3
通讯作者：
E. Rabiei;U. Haberlandt;Monika Sester;D. Fitzner;M. Wallner
中科院分区：
文献类型：
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作者：
E. Rabiei;U. Haberlandt;Monika Sester;D. Fitzner;M. Wallner
摘要。多项研究已讨论了水文分析对高时空分辨率降水数据的需求。尽管雨量计能提供有价值的信息，但一个非常密集的雨量计网络成本高昂。因此，一些新的思路应运而生，以帮助估算具有更高时空分辨率的区域降雨量。拉比伊等人（2013年）观察到，被称为“雨车”（RCs）的行驶车辆有可能成为测量降雨率的新数据来源。该研究中使用的光学传感器是为操作挡风玻璃雨刮器而设计的，在降雨测量方面显示出有前景的结果。它们的测量精度已在实验室实验中得到量化。明确考虑这些误差，本研究的主要目的是探究使用“雨车”估算区域降雨量的益处。为此，进行了计算机实验，其中雷达降雨量被视为参考，而其他数据来源，即“雨车”和雨量计的数据则从雷达数据中提取。将“雨车”与雨量计及参考数据对区域降雨量估算的质量进行比较，有助于探究“雨车”的益处。这种额外数据来源的价值不仅在区域降雨量估算性能方面得到评估，还在水文建模中得到评估。考虑到从实验室实验得出的测量误差，结果表明，“雨车”为区域降雨量估算以及水文建模提供了有用的额外信息。此外，通过对“雨车”测试更大的不确定性，发现它们在一定程度上对区域降雨量估算和流量模拟是有用的。
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.