| 20 May 2025
Torrential rainfall in Valencia (Spain) recorded by personal weather stations preceding and during the 29 October 2024 floods
Abstract. On 29 October 2024, torrential rainfall locally exceeding 300 mm within less than 24 h, caused devastating floods in the province of Valencia in Spain. In this study we quantify and describe the spatial and temporal structure of the rainfall event on this day using rainfall observations from approximately 225 personal weather stations (PWSs), low-cost commercial devices primarily operated by citizens. The network density of PWSs is ~7 times higher compared to the dedicated rain gauge network operated by the Spanish Meteorological Agency (AEMET) in the province of Valencia, allowing a more detailed analysis of the spatial and temporal rainfall dynamics. In addition, PWS observations are available in near real-time to the public with a temporal resolution of 5 min, whereas the data from AEMET are not available in real time for the public and at a lower publicly available temporal resolution (1 h). Daily rainfall sums recorded by the PWSs showed a high correlation (r = 0.94) and low bias (underestimation of 4 %) compared to rainfall reported by AEMET. In the upstream parts of the Magro catchment (1661 km2), a first burst of extreme rainfall, reaching up to 180 mm of rainfall in a few hours, started in the morning, leading to the generation of a first flood wave in the upstream parts of the catchment. While the resulting flood wave was propagating downstream through the channel network, a second rainfall peak occurred, which moved downstream along with the flood wave. This spatial and temporal coincidence has likely exacerbated the devastating power of this event. Based on the PWS data, it could have been anticipated that the extreme rainfall already occurring early in the morning would likely result in flooding in the Magro catchment. Areal rainfall maps based on interpolating PWS data indicated catchment average rainfall exceeding 150 mm d-1 across an area of more than 2500 km2. However, the total accumulated rainfall remains uncertain due to interrupted measurements likely caused by power outage and inherent uncertainty associated with interpolating point measurements. For the Rambla de Poyo catchment, the resulting average discharge was around 900 m3 s-1. The estimated return period of the catchment-average rainfall and resulting discharge from this event exhibits large uncertainties, with on average exceeding 10,000 years and 900 years, respectively. This study shows the potential of PWSs for real-time rainfall monitoring and potentially flood early warning systems, by complementing dedicated rain gauge networks in order to reduce the uncertainty from areal rainfall estimates and to localize potential flooding more accurately.
Competing interests: One of the authors (MH) is member of the editorial board of HESS.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Overall, a well written paper that makes a clear case for the value of high spatial resolution rain fall measurements from personal weather stations. The authors have made well justified decisions in their data analysis.
Major comment:
The spatial sequence of rainfall during the flooding event is not clearly shown with the existing Figures. It is hard for the reader to relate the time series shown in Fig 5 and Fig 6a to the big picture of how the event unfolded. Suggest add a multi-panel plot that shows the sequence of maps of average rainfall in each catchment for shorter time intervals than the storm total ones shown in Figure 6b-d. Perhaps 3 or 4 hour time intervals and use the PWS and AEMET combined data. If use 4 hours as time interval, it would be 4 subplots maps, hours 4-7, hours 8-11, hours 12-15, hours 16-19 would cover nearly all of the period of interest. Discussion of this new figure would complement discussion of the warning timeline in Section 5.5.
Minor comments:
Suggest change title to: “Torrential rainfall in Valencia, Spain recorded by personal weather stations preceding and during the 24 October 2024 floods” (i.e. remove parentheses)
Overuse and misuse of conjunctions like “However” and “Nevertheless”. For example, line 181: ”However, the timing of the peaks and the rainfall depth varied within this region.” Better would be “The timing of the peaks and the rainfall depth varied within this region.” since authors are not contradicting previous sentence.
Line 42: Suggest add a sentence as part of this paragraph. Especially in mountainous areas, radar beams can be blocked over areas of interest.
Caption for Table 1: For clarity please change “Mean discharge and peak discharge for gauge ID1, ID2, ID3…” to “Mean discharge and mean yearly peak discharge for gauges ID1, ID2, ID3…”
Line 140, if this is the correct interpretation, suggest change “the nugget is assumed to be negligible” to “the nugget is assumed to be zero”
Line 215, please cite reference for Hortonian overland flow
Line 324-328, for clarity suggest revise “However, selecting smaller catchment areas would increase the uncertainty in the interpolated rainfall estimates based on point measurements, particularly for areas with no or only a few rain gauges. Rainfall estimates from weather radars can mitigate these gaps. Additionally, these delinations do not necessarily match the upstream areas of streamflow gauges. Nevertheless, given the unavailability of of high temporal resolution discharge time series, this is not a limitation for this study.”
To “Selecting smaller catchment areas would increase the uncertainty in the interpolated rainfall estimates based on point measurements, particularly for areas with no or only a few rain gauges. Additionally, smaller catchment areas would not necessarily match the upstream areas of streamflow gauges.” [not clear how the Nevertheless sentence relates to the rest of the paragraph so suggest taking it out].
Line 337. As a reader I got confused by this paragraph:
“The Poyo catchment, is characterized by an ephemeral stream, as it primarily depends on rainfall (Camarasa-Belmonte, 2016). This streamflow-gauge is not included in the EStreams database employed in this study. However, the mean and maximum specific peak flow for 37 flash flood events in this catchment, occurring between 1989 and 2007, were 16 and 246 mmd−1, respectively (Camarasa-Belmonte, 2016). Compared to this average peak flow, the recorded discharge on the 29th and 30th with147 and 433 mm d−1 is approximately 9 and 27 times higher, respectively. The average discharge on the 30th with 433 mm d−1 is significantly higher (1.75 times) compared to the maximum peak flow in this period. However, due to the short duration of the historical record used in Camarasa-Belmonte (2016) (18-years), no definitive conclusions can be drawn regarding the rarityof this event.”
Some points of confusion:
“This streamflow-gauge is not included in the EStreams database employed in this study.” Since streamflow-gauge is included in Table 1 as ID4, I think you mean in terms of computing mean and mean yearly peak.
It is not clear what numbers are being referred to and where it is coming from for the “average discharge” and “maximum peak flow in this period”.
Suggest revise to read:
“The Poyo catchment, is characterized by an ephemeral stream, as it primarily depends on rainfall (Camarasa-Belmonte, 2016). For 37 flash flood events in this catchment occurring between 1989 and 2007, the mean was 16 mm d−1 and maximum specific peak flow was 246 mm d−1 (Camarasa-Belmonte, 2016). The daily recorded discharges from the Poyo catchment on the October 29th and 30th of 147 and 433 mm d−1 are approximately 9 and 27 times higher, respectively (Table 1). Due to the short duration of the historical record used in Camarasa-Belmonte (2016) (18-years), no definitive conclusions can be drawn regarding the rarity of this event.”