Suchergebnisse

Abstract. Although channel discharge represents one of the primary controls of bedload transport rates in mountain streams, it is rarely measured in small, steep catchments. Thus, it is often impossible to use it as a predictor of hazardous bedload events. In this study, the characteristics of rainfall events leading to bedload transport were investigated in five small Alpine catchments located in different geographical and morphological regions of Switzerland, Italy and France. Using rainfall data at high temporal resolution, a total of 370 rainfall events were identified that led to abundant sediment transport in the different catchments, and corresponding threshold lines were defined using a power law in intensity–duration space. Even though considerable differences in the distribution of the rainfall data were identified between catchments located in various regions, the determined threshold lines show rather similar characteristics. Such threshold lines indicate critical conditions for bedload transport initiation, but rainfall events that do not cause transport activity (so called no-bedload events) can still plot above them. With 0.67 overall in the Erlenbach (Swiss Prealps) and 0.90 for long-duration, low-intensity rainfall, the false alarm rate is considerable. However, for short-duration, high-intensity events, it is substantially smaller (0.33) and comparable to values determined in previous studies on the triggering of Alpine debris flows. Our results support the applicability of a traditional, generalized threshold for prediction or warning purposes during high-intensity rainfall. Such (often convective) rainfall events are unfortunately (i) difficult to measure, even by dense rain gauge networks, and (ii) difficult to accurately predict, both due to their small spatial and temporal scales. Still, for the protection of human life (e.g. along transportation infrastructure such as roads and railway) automated alerts based on power law threshold lines may be useful.

Abstract. Rainfall intensity–duration (ID) thresholds are commonly
used to assess flash flood potential downstream of burned watersheds.
High-intensity and/or long-duration rainfall is required to generate flash
floods as landscapes recover from fire, but there is little guidance on how
thresholds change as a function of time since fire. Here, we force a
hydrological model with radar-derived precipitation to estimate ID thresholds
for post-fire flash floods in a 41.5 km2 watershed in southern
California, USA. Prior work in this study area constrains temporal changes
in hydrological model parameters, allowing us to estimate temporal changes in
ID thresholds. The results indicate that ID thresholds increase by more than a
factor of 2 from post-fire year 1 to post-fire year 5. Thresholds based on
averaging rainfall intensity over durations of 15–60 min perform better
than those that average rainfall intensity over shorter time intervals.
Moreover, thresholds based on the 75th percentile of radar-derived
rainfall intensity over the watershed perform better than thresholds based
on the 25th or 50th percentile of rainfall intensity. Results
demonstrate how hydrological models can be used to estimate changes in ID
thresholds following disturbance and provide guidance on the rainfall
metrics that are best suited for predicting post-fire flash floods.

Abstract
As a significant detriment to physical and mental health, millions of motor vehicle crashes occur in the United States each year, with approximately 23% of these crashes linked to adverse weather conditions. This study builds upon a strong knowledge base to provide a deeper understanding of how rainfall intensity influences relative crash risk. Gridded precipitation and temperature data were aggregated to the county level and analyzed alongside motor vehicle crash data for all 146 counties in the Carolinas (North Carolina and South Carolina) for the period 2003–19. A matched-pair analysis routine linked unique time steps of rainfall (daily, 6-h, and hourly) to corresponding dry periods to evaluate relative crash risk across each state. Risk estimates were calculated on the basis of precipitation thresholds (light, moderate, heavy, and very heavy). Results indicate a statistically significant increase in crash risk during periods of rainfall in the Carolinas. As a baseline, the relative risk of experiencing a crash increases by 11.6% during days with accumulating rainfall and as much as 81.0% during heavy rainfall events over a 6-h period. In general, estimates of risk increase relative to the intensity of the rainfall event and the temporal delineation of the matched-pair routine. However, these relationships have unique spatiotemporal patterns indicating that, although hourly risk estimates may be beneficial for urban counties, daily relative risk estimates may be the only way to accurately capture risk in rural areas.

Significance Statement
Each year, more than 1 000 000 motor vehicle crashes in the United States are linked to adverse weather conditions in police reports, with rainfall events being among the largest contributors to increased crash risk. In this study, crash frequencies are evaluated to better understand how the intensity of rainfall events (light vs heavy) influences the risk of experiencing a collision on roadways in North Carolina and South Carolina. The results of statistical analyses revealed that risk increases significantly during rainfall events in both states and that the risk of experiencing a crash is highest during the heaviest rainfall events. However, even during light precipitation events, the risk of experiencing a crash is significantly higher than when driving during dry conditions. These results are helpful to transportation stakeholders and emergency responders in the hope of reducing crash risk in our changing climate.

Abstract. In several countries, the rising occurrence of sinkholes has led to severe
social and economic damage. Based on the mechanism of sinkhole development,
researchers have investigated the correlation between rainfall intensity and
sinkholes caused by damaged sewer pipes. In this study, the effect of
rainfall intensity on the formation of eroded zones, as well as the
occurrence of sinkholes caused by soil erosion due to groundwater
infiltration through pipe defects, has been analyzed through model tests.
The ground materials in Seoul were represented by weathered granite soil,
which is generally used for backfill sewer pipes, and groundwater levels
corresponding to three different rainfall intensity conditions were
considered. The ground level changes and ground displacements were measured
continuously, and the particle image velocimetry (PIV) algorithm was applied
to measure the displacement at each position of the model ground. The
results indicate that impeding the excessive rise in groundwater levels by
securing sufficient sewage treatment facilities can effectively prevent the
development of sinkholes caused by pipe defects.

A lava flood disaster is a volcanic hazard that often occurs when heavy rains are happening at the top of a volcano. This flood carries volcanic material from upstream to downstream of the river, affecting populous areas located quite far from the volcano peak. Therefore, an advanced early warning system of cold lava floods is inarguably vital. This paper aims to present a reliable, remote, Early Warning System (EWS) specifically designed for lava flood detection, along with its disaster communication system. The proposed system consists of two main subsystems: lava flood detection and disaster communication systems. It utilizes a modified automatic rain gauge; a novel configured vibration sensor; Fuzzy Tree Decision algorithm; ESP microcontrollers that support IoT, and disaster communication tools (WhatsApp, SMS, radio communication). According to the experiment results, the prototype of rainfall detection using the tipping bucket rain gauge sensor can measure heavy and moderate rainfall intensities with 81.5% accuracy. Meanwhile, the prototype of earthquake vibration detection using a geophone sensor can remove noise from car vibrations with a Kalman filter and measure vibrations in high and medium intensity with an accuracy of 89.5%. Measurements from sensors are sent to the webserver. The disaster mitigation team uses data from the webserver to evacuate residents using the disaster communication method. The proposed system was successfully implemented in Mount Merapi, Indonesia, coordinated with the local Disaster Deduction Risk (DDR) forum. Doi: 10.28991/esj-2021-SP1-011 Full Text: PDF

Abstract. The relationship between the multi-spectral cloud field characterization from the Advanced Very High Resolution Radiometer (AVHRR) and the rainfall intensities from the Advanced Microwave Sounding Unit-module B (AMSU-B) data were studied for a convective storm event, which occurred during the first 15 days of June 2007 over the Mediterranean. The cloud products exploited in this analysis, cloud mask, type, optical thickness, and effective radius, are obtained from the NOAA-NESDIS operational processing system Clouds from the AVHRR-Extended algorithm (CLAVR-x), whereas the rain intensity values are retrieved from the AMSU-B brightness temperatures via a fast algorithm, using opaque frequencies (centred at 183 GHz) to correct for the presence of water vapour affecting the retrieval results. The algorithm is conceived to discriminate between convective and stratiform rain using a suitable set of thresholds; the retrieval is subsequently carried out separately for the two types. A test for the discrimination of precipitating from non-precipitating areas was based on the comparison between the precipitation information and the retrieved cloud parameters. The test produced a cloud optical thickness threshold value, beyond which the precipitation initiates, and an effective radius range for the identification of the precipitating clouds. The results stemming from the application of the test to the June 2007 case study are very encouraging, although still preliminary and restricted to the analyzed Mediterranean storms. In particular, the test shows high potential for delineating non-precipitating areas (more than 90% of successful cases for every considered cloud type) and to identify precipitating ice clouds related to convective rain (confirmed by 82% of hits). On the other hand, the relative inability to address the stratiform cloud systems is proved by the fact that the majority of the missed cases, for each cloud types, is characterized by light rain intensities (≤3 mm h−1).

Abstract. A total of more than 140 000 kg of small-magnitude rockfall deposits was measured in eight rockfall collectors of altogether 940 m2 in size between 1999–2003 below a 400–600 m high rock face in the Reintal, German Alps. Measurements were conducted with a temporal resolution up to single days to attribute rockfall intensity to observed triggering events. Precipitation was assessed by a rain gauge and high-resolution precipitation radar. Intense rainstorms triggered previously unreported rockfall intensities of up to 300 000 g/(m2h) that we term "secondary rockfall event." In comparison to dry periods without frost (10−2g/(m2h)), rockfall deposition increased by 2–218 times during wet freeze-thaw cycles and by 56-thousand to 40-million times during secondary rockfall events. We obtained three nonlinear logistic growth models that relate rockfall intensity [g/(m2h)] to rainfall intensity [mm/h]. The models account for different rock wall intermediate storage volumes, triggering thresholds and storage depletion. They apply to all rockfall collector positions with correlations from R2=0.89 to 0.99. Thus, the timing of more than 90% of the encountered rockfall is explained by the triggering factor rainfall intensity. A combination of rockfall response models with radar-supported storm cell forecast could be used to anticipate hazardous rockfall events, and help to reduce the exposure of individuals and mobile structures (e.g. cable cars) to the hazard. According to meteorological recordings, the frequency of these intense rockfall events is likely to increase in response to global warming.