Articles | Volume 20, issue 9
Hydrol. Earth Syst. Sci., 20, 3907–3922, 2016
Hydrol. Earth Syst. Sci., 20, 3907–3922, 2016

Research article 26 Sep 2016

Research article | 26 Sep 2016

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

Ehsan Rabiei1, Uwe Haberlandt2, Monika Sester2, Daniel Fitzner2, and Markus Wallner3 Ehsan Rabiei et al.
  • 1Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering, Leibniz University of Hanover, 30167 Hanover, Germany
  • 2Institute of Cartography and Geoinformatics, Leibniz University of Hanover, Hanover, Germany
  • 3Federal Institute for Geosciences and Natural Resources, Groundwater Resources – Quality and Dynamics, 30655 Hanover, Germany

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.

Short summary
The value of using moving cars for rainfall measurement purposes (RCs) was investigated with laboratory experiments by Rabiei et al. (2013). They analyzed the Hydreon and Xanonex optical sensors against different rainfall intensities. A continuous investigation of using RCs with the derived uncertainties from laboratory experiments for areal rainfall estimation as well as implementing the data in a hydrological model are addressed in this study.