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

机译:使用移动汽车进行地域降雨估算-包括水文模型在内的计算机实验

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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 Rain-Cars (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.
机译:在一些研究中已经讨论了对高时空分辨率降水数据进行水文分析的需求。尽管雨量计可以提供有价值的信息,但是非常密集的雨量计网络成本很高。结果,出现了一些新的想法来帮助估算具有更高时空分辨率的区域降雨。 Rabiei等。 (2013年)观察到,称为雨车(RC)的行驶中的汽车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雨刷而设计的,并显示出用于降雨测量的有希望的结果。在实验室实验中已经量化了它们的测量精度。明确考虑这些误差,本研究的主要目的是研究使用RC估算面积降雨的好处。为此,进行了计算机实验,其中雷达雨水被视为参考,其他数据来源,即。例如,RC和雨量计是从雷达数据中提取的。将RC的区域降雨估算质量与雨量计和参考数据进行比较有助于研究RC的优势。这种额外的数据源的价值不仅可以用于区域降雨估算性能评估,还可以用于水文建模。考虑到来自实验室实验的测量误差,结果表明,RCs为面积降雨估计以及水文模型提供了有用的附加信息。此外,通过测试RC的较大不确定性,他们发现在一定程度上可用于区域降雨估算和流量模拟。

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