Speaker
Description
The use of opportunistic sensing (OS) devices for rainfall monitoring, such as commercial microwave links (CMLs), has attracted the attention of urban hydrologists and drainage engineers in the recent decade. However, the devices are neither originally designed for rainfall monitoring nor properly maintained or installed. Therefore, they can be affected by various factors other than rainfall, such as environmental conditions and technical issues and thus appropriate quality control (QC) is essential. By implementing QC, potential errors and uncertainties in the data can be identified and corrected, and the accuracy and precision of the estimated rainfall fields can be improved.
Previous studies suggested QC algorithms for single links (SL) removing artefacts from the time series of their signal levels leading to improved rain rate estimates and more accurate reconstructed rainfall maps. In this study, we propose a QC method relying on neighbouring links (NL) and compare it with SL algorithm at city scale with high density of CMLs and short correlation lengths. We also investigate the synergy of simultaneously utilizing both QC methods for short time steps of 5 minutes.
A dataset of CML measurement was obtained from the T-Mobile network in Prague, Czech Republic. The selected period is between July 2014 and September 2014. The CML network has 173 links. Two datasets were used as the reference. The first reference dataset was generated by interpolating the measurements from 23 local RGs using the inverse distance weighting. The second dataset consisted of C-band radar data that was adjusted using the measurements from these 23 RGs.
The overall results show clear improvements of performance metrics when combining both QC algorithms. For validation period RMSE decreased from 2.38 to 1.57 mm/h and Pearson correlation increased from 0.45 to 0.74. The results demonstrate that NL method can be effectively applied for CML-derived rainfall estimates, resulting in larger data availability compared to SL method. NL performs better than SL when the CML density is high, and the superiority diminishes as the CML density decreases. Simultaneously applying both types of QC methods can further reduce errors in the results, but there may be a trade-off with data availability. The results also indicate that performing simple QC operations on the CML measurement before applying NL can retain more data while achieving favourable results. The findings of this study provide guidance for improving the accuracy of retrieval and rain field reconstruction results.
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