Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment

Pastorek, Jaroslav; Fencl, Martin; Bareš, Vojtěch

doi:10.1016/j.jhydrol.2022.129051

Cited by 7 publications

(7 citation statements)

References 47 publications

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“…Zheng et al [191] focus particularly on the capability of CML data to provide good area rainfall data in urban areas. Recent studies in general confirm that with careful processing, CML data can provide distributed rainfall data that can be applied with confidence to studies of urban hydrology and flooding problems (Liu et al [192], Pastorek et al [183]).…”

Section: Microwave Attenuation (Cellular Phone Links Satellite Links ...mentioning

confidence: 93%

“…The great advantage offered by radar-based methods, however, is their ability to provide area-wide data with high temporal resolution, such that the progression of storm cells across the landscape can be monitored. Quantitative rainfall measurements are still problematic and affected by many influences other than rainfall itself, including ground clutter (Krajewski et al [182]); performance in heavy rainfall remains relatively poor (Pastorek et al [183]).…”

Section: Radar-based Approachesmentioning

confidence: 99%

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Recording Rainfall Intensity: Has an Optimum Method Been Found?

Dunkerley

2023

Water

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Many design principles for rain gauges that have the capacity to record rainfall intensity have been proposed or developed. These are here grouped into 15 categories, and the abilities and limitations of each are discussed. No standard or optimum method has emerged, despite more than 80 years of effort in the last two centuries, together with prior work from the 17th C onwards. Indeed, new methods continue to be explored for both point-based and area-wide collections of intensity data. Examples include the use of signal attenuation by rain along the tower-to-tower links of cellular phone networks, monitoring the speed of vehicle windscreen wipers, and exploiting the sound or vision from security and traffic-monitoring cameras. Many of these approaches have the potential to provide vastly more observation sites than conventional meteorological stations equipped with rain gauges. Some of these contemporary approaches seek to harness the potential of crowdsourced or citizen-science data. It is hoped that the present overview of methods will provide a guide for those wishing to collect or analyses rainfall intensity data for application in areas such as soil erosion processes, ecohydrology, agrochemical washoff, or urban flash flooding. Because rainfall intensity is one of the key aspects of the hydrologic cycle likely to respond as climate change and variability proceed, the choice of appropriate data collection methods has additional contemporary importance for the monitoring of regional and global precipitation changes.

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Section: Microwave Attenuation (Cellular Phone Links Satellite Links ...mentioning

confidence: 93%

Section: Radar-based Approachesmentioning

confidence: 99%

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Dunkerley

2023

Water

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“…Follow this principle, each CMLs in a communication network can be considered as a rainfall sensor. Such rainfall information can be used not only for the 2‐D rain field reconstruction (Goldshtein et al., 2009, Messer et al., 2022; Zheng et al., 2022), but also for radar adjustment (Cummings et al., 2009), rainfall nowcasting (Imhoff et al., 2020), and hydrological models (Cazzaniga et al., 2022; Pastorek et al., 2023; Smiatek et al., 2017; Stransky et al., 2018), etc.…”

Section: Introductionmentioning

confidence: 99%

“…rainfall nowcasting (Imhoff et al, 2020), and hydrological models (Cazzaniga et al, 2022;Pastorek et al, 2023;Smiatek et al, 2017;Stransky et al, 2018), etc.…”

mentioning

confidence: 99%

A Statistical Approach to Retrieve Rainfall Intensity by Attenuation Measurements From Commercial Microwave Links

Zheng,

Messer,

Qin

et al. 2023

Earth's Future

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Commercial microwave link (CML) has become one of the most widely used opportunistic sensors for rainfall monitoring. The high density and coverage of CMLs enable us to monitor near‐ground rainfall in high spatial resolution. The empirical power‐law (PL) model proposed in 1978 is the leading approach in relating CML attenuation with rain rate. However, while giving good rain rate estimates for CMLs longer than 1 km, in short CMLs, large errors are observed when the PL approach is applied. In this paper, we studied a statistical approach to convert CML attenuation measurement to rainfall intensity. The proposed approach calculates the exceedance probability, p, of rain‐induced attenuation and derives the corresponding rainfall intensity based on the rain rate cumulative distribution curve. Data from two cities in two countries were used to validate the approach. The results of the proposed approach were compared with that of the PL model. Results show that the models derived using our approach outperform PL for short CMLs, while showing similar performance for long ones. Since in the next generation mobile networks short CMLs will become more and more dominant, our work provides a way to derive retrieval models for the future generation CML networks.

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“…van het Schip et al (2017) showed the complimentary potential of CML and satellite data by determining wet and dry periods using the satellite data, while Hoedjes et al (2014) proposed to use this for a conceptual flash flood early warning system in Kenya. Fencl et al (2013) and Pastorek et al (2023) used CMLs as input data for an urban drainage model and demonstrated the benefits of the relatively high spatial resolution on these models. Also, Imhoff et al (2020) showed that nowcasting rainfall events could be performed using CML networks, with good results when compared to weather radar precipitation estimates and nowcasts.…”

Section: Introductionmentioning

confidence: 99%

Measuring rainfall using microwave links: the influence of temporal sampling

van der Valk,

Coenders-Gerrits,

Hut

et al. 2023

Preprint

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Abstract. Terrestrial microwave links are increasingly being used to estimate path-averaged precipitation by determining the attenuation caused by rainfall along the link path, mostly with commercial microwave links from cellular telecommunication networks. However, the temporal resolution of and method to derive these rainfall estimates is often determined by the temporal sampling strategy that is employed by the mobile network operators. Currently, the links are most often sampled at a temporal resolution of 15 minutes with a recording of the minimum and maximum values, while more recently also a form of instantaneous sampling with possible intervals up to 1 s has been set up. For rainfall research purposes, often high temporal resolutions in combination with averaged values are preferred. However, it is uncertain how these various temporal sampling strategies affect the estimated rainfall intensity. Here we aim to understand how temporal sampling strategies affect the measured rainfall intensities using microwave links. To do so, we use data from three collocated microwave links, two 38 GHz and one 26 GHz, sampled at 20 Hz and covering a 2.2 km path over the city of Wageningen, the Netherlands. We aggregate the microwave link power levels to multiple time intervals (1 s to 60 min) and use a mean, instantaneous, and minimum and maximum value to characterize the signal. Based on the aggregated data, we compute rainfall intensities and compare these with 20 Hz rainfall estimates, such that we isolate errors and uncertainties caused by the sampling strategies from instrumental effects, such as different biases between instruments and representativeness errors. In general, our results show that for all sampling strategies an increase in sampling time interval reduces the performance of the rainfall estimates, which especially holds for the instantaneous sampling strategy. Even the mean sampling strategy, which generally performs best of all strategies, is sensitive to this reduction in temporal resolution and could lead to significant underestimations. In this, the non-linear relation between attenuation and rainfall intensity seems to play an important role. The min-max sampling strategy is mostly prone to minor underestimations or large overestimations of the path-averaged rainfall intensities. Moreover, our results, including a comparison with theoretical events, show that the attenuation due to wet antennas not only affects the comparison between the rainfall estimates obtained with a microwave link and another reference instrument, but also has a significant influence on the rainfall retrieval algorithm. Overall, this study demonstrates the effect a selected sampling strategy can have on rainfall intensity estimates using (commercial) microwave links.

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Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment

Cited by 7 publications

References 47 publications

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Recording Rainfall Intensity: Has an Optimum Method Been Found?

A Statistical Approach to Retrieve Rainfall Intensity by Attenuation Measurements From Commercial Microwave Links

Measuring rainfall using microwave links: the influence of temporal sampling

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