Rainfall intensity–duration thresholds for bedload transport initiation in small Alpine watersheds

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.

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Point-Based Rainfall Intensity Information System in Mt. Merapi Area by X-Band Radar

Journal of Disaster Research ◽

10.20965/jdr.2019.p0080 ◽

2019 ◽

Vol 14 (1) ◽

pp. 80-89 ◽

Cited By ~ 1

Author(s):

Santosa Sandy Putra ◽

Banata Wachid Ridwan ◽

Kazuki Yamanoi ◽

Makoto Shimomura ◽

Sulistiyani ◽

...

Keyword(s):

Satellite Data ◽

Early Warning Systems ◽

Radar Data ◽

Rain Gauge ◽

Data Grid ◽

Rainfall Data ◽

Rainfall Events ◽

Rain Gauge Data ◽

X Band ◽

Gauge Data

An X-band radar was installed in 2014 at Merapi Museum, Yogyakarta, Indonesia, to monitor pyroclastic and rainfall events around Mt. Merapi. This research aims to perform a reliability analysis of the point extracted rainfall data from the aforementioned newly installed radar to improve the performance of the warning system in the future. The radar data was compared with the monitored rain gauge data from Balai Sabo and the IMERG satellite data from NASA and JAXA (The Integrated Multi-satellitE Retrievals for GPM), which had not been done before. All of the rainfall data was compared on an hourly interval. The comparisons were conducted based on 11 locations that correspond to the ground rainfall measurement stations. The locations of the rain gauges are spread around Mt. Merapi area. The point rainfall information was extracted from the radar data grid and the satellite data grid, which were compared with the rain gauge data. The data were then calibrated and adjusted up to the optimum state. Based on January 2017–March 2018 data, it was obtained that the optimum state has a NSF value of 0.41 and R2value of 0.56. As a result, it was determined that the radar can capture around 79% of the hourly rainfall occurrence around Mt. Merapi area during the chosen calibration period, in comparison with the rain gauge data. The radar was also able to capture nearby 40–50% of the heavy rainfall events that pose risks of lahar. In contrast, the radar data performance in detecting drizzling and light rain types were quite precise (55% of cases), although the satellite data could detect slightly better (60% of cases). These results indicate that the radar sensitivity in detecting the extreme rainfall events must receive higher priority in future developments, especially for applications to the existing Mt. Merapi lahar early warning systems.

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Recent changes in rainfall characteristics and their influence on thresholds for debris flow triggering in the Dolomitic area of Cortina d'Ampezzo, north-eastern Italian Alps

Natural Hazards and Earth System Science ◽

10.5194/nhess-10-571-2010 ◽

2010 ◽

Vol 10 (3) ◽

pp. 571-580 ◽

Cited By ~ 27

Author(s):

M. Floris ◽

A. D'Alpaos ◽

C. Squarzoni ◽

R. Genevois ◽

M. Marani

Keyword(s):

Debris Flow ◽

Short Duration ◽

High Intensity ◽

Debris Flows ◽

Meteorological Data ◽

Rain Gauge ◽

Annual Rainfall ◽

Interarrival Time ◽

Italian Alps ◽

Rainfall Events

Abstract. In this paper, we examine variations in climate characteristics near the area of Cortina d'Ampezzo (Dolomites, Eastern Italian Alps), with particular reference to the possible implications for debris-flow occurrence. The study area is prone to debris-flow release in response to summer high-intensity short-duration rainfalls and, therefore, it is of the utmost importance to investigate the potential increase in debris-flow triggering rainfall events. The critical rainfall threshold is agreed to be a crucial triggering factor for debris-flows. Data from a monitoring system, placed in a catchment near Cortina (Acquabona), show that debris-flows were triggered by rainfalls with peak rainfall intensities ranging from 4.9 to 17.4 mm/10 min. The analyses of meteorological data, collected from 1921 to 1994 at several stations in the study area, show a negative trend of annual rainfall, a considerable variation in the monthly rainfall distribution, and an increase in the temperature range, possibly related to global climate changes. Moreover, high-intensity and short-duration rainfall events, derived from data collected from 1990 and 2008, show an increase in exceptional rainfall events. The results obtained in a peak-over-threshold framework, applied to the rainfall data measured at the Faloria rain gauge station from 1990 to 2008, clearly show that the interarrival time of over-threshold events computed for different threshold values decreased in the last decade. This suggests that local climatic changes might produce an increase in the frequency of rainfall events, potentially triggering debris flows in the study area.

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Comparison of annual maximum rainfall events of modern rain gauge data (1961–2010) and Chukwooki data (1777–1910) in Seoul, Korea

Journal of Water and Climate Change ◽

10.2166/wcc.2017.110 ◽

2017 ◽

Vol 9 (1) ◽

pp. 58-73 ◽

Cited By ~ 2

Author(s):

Chulsang Yoo ◽

Minkyu Park ◽

Hyeon Jun Kim ◽

Changhyun Jun

Keyword(s):

Rain Gauge ◽

Rainfall Event ◽

Rainfall Data ◽

Time Interval ◽

Annual Maximum ◽

Bivariate Exponential Distribution ◽

Maximum Rainfall ◽

Rainfall Events ◽

Event Series ◽

Annual Maximum Rainfall

Abstract In this study, the annual maximum rainfall event series were constructed and compared for both the modern flip-bucket type rainfall data, collected since 1961 (the modern data), and the old Chukwooki rainfall data, collected from 1777 to 1910 (the Chukwooki data). First, independent rainfall events were derived, by applying the same rainfall threshold of 2 mm and data collection time interval of 2 hours, to both the Chukwooki and the modern data. Annual maximum rainfall event series were then constructed, by applying Freund's bivariate exponential distribution annually. Finally, bivariate frequency analysis was done for the annual maximum rainfall event series constructed, by applying the bivariate logistic model to evaluate and quantify their characteristics. The results are in summary: (1) characteristics of the Chukwooki rainfall events and modern rainfall events are very similar to each other; (2) the annual maximum rainfall events of modern data are slightly larger than those of the Chukwooki data. The total rainfall depth per rainfall event for any given return period is thus estimated to be a little higher for the modern data than that of the Chukwooki data. However, based on the findings in this study, it could not be concluded that the rainfall characteristics have significantly changed during the last 200 years.

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Seasonal Variation of the Diurnal Cycle of Rainfall in Southern Contiguous China

Journal of Climate ◽

10.1175/2008jcli2188.1 ◽

2008 ◽

Vol 21 (22) ◽

pp. 6036-6043 ◽

Cited By ~ 68

Author(s):

Jian Li ◽

Rucong Yu ◽

Tianjun Zhou

Keyword(s):

Seasonal Variation ◽

Diurnal Cycle ◽

Radiative Forcing ◽

Early Morning ◽

Rain Gauge ◽

Rainfall Events ◽

Late Afternoon ◽

Long Duration ◽

China Region ◽

Afternoon Peak

Abstract Hourly station rain gauge data are employed to study the seasonal variation of the diurnal cycle of rainfall in southern contiguous China. The results show a robust seasonal variation of the rainfall diurnal cycle, which is dependent both on region and duration. Difference in the diurnal cycle of rainfall is found in the following two neighboring regions: southwestern China (region A) and southeastern contiguous China (region B). The diurnal cycle of annual mean precipitation in region A tends to reach the maximum in either midnight or early morning, while precipitation in region B has a late-afternoon peak. In contrast with the weak seasonal variation of the diurnal phases of precipitation in region A, the rainfall peak in region B shifts sharply from late afternoon in warm seasons to early morning in cold seasons. Rainfall events in south China are classified into short- (1–3 h) and long-duration (more than 6 h) events. Short-duration precipitation in both regions reaches the maximum in late afternoon in warm seasons and peaks in either midnight or early morning in cold seasons, but the late-afternoon peak in region B exists during February–October, while that in region A only exists during May–September. More distinct differences between regions A and B are found in the long-duration rainfall events. The long-duration events in region A show dominant midnight or early morning peaks in all seasons. But in region B, the late-afternoon peak exists during July–September. Possible reasons for the difference in the diurnal cycle of rainfall between the two regions are discussed. The different cloud radiative forcing over regions A and B might contribute to this difference.

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Point process models of rainfall: developments for fine-scale structure

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2007.1889 ◽

2007 ◽

Vol 463 (2086) ◽

pp. 2569-2587 ◽

Cited By ~ 62

Author(s):

Paul Cowpertwait ◽

Valerie Isham ◽

Christian Onof

Keyword(s):

Poisson Process ◽

Time Scales ◽

Rain Gauge ◽

Historical Record ◽

Rainfall Data ◽

Process Models ◽

Third Order ◽

Time Intervals ◽

Historical Series ◽

Derived Properties

A conceptual stochastic model of rainfall is proposed in which storm origins occur in a Poisson process, where each storm has a random lifetime during which rain cell origins occur in a secondary Poisson process. In addition, each cell has a random lifetime during which instantaneous random depths (or ‘pulses’) of rain occur in a further Poisson process. A key motivation behind the model formulation is to account for the variability in rainfall data over small (e.g. 5 min) and larger time intervals. Time-series properties are derived to enable the model to be fitted to aggregated rain gauge data. These properties include moments up to third order, the probability that an interval is dry, and the autocovariance function. To allow for distinct storm types (e.g. convective and stratiform), several processes may be superposed. Using the derived properties, a model consisting of two storm types is fitted to 60 years of 5 min rainfall data taken from a site near Wellington, New Zealand, using sample estimates taken at 5 min, 1 hour, 6 hours and daily levels of aggregation. The model is found to fit moments of the depth distribution up to third order very well at these time scales. Using the fitted model, 5 min series are simulated, and annual maxima are extracted and compared with equivalent values taken from the historical record. A good fit in the extremes is found at both 1 and 24 hour levels of aggregation, although at the 5 min level there is some underestimation of the historical values. Proportions of time intervals with depths below various low thresholds are extracted from the simulated and historical series and compared. A tendency for underestimation of the historical values is evident at some time scales, with a close fit being obtained as the threshold is increased.

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Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach

Hydrology and Earth System Sciences ◽

10.5194/hess-18-4913-2014 ◽

2014 ◽

Vol 18 (12) ◽

pp. 4913-4931 ◽

Cited By ~ 56

Author(s):

D. J. Peres ◽

A. Cancelliere

Keyword(s):

Monte Carlo ◽

Slope Stability ◽

Power Law ◽

Rainfall Intensity ◽

Antecedent Rainfall ◽

Rainfall Events ◽

Physically Based ◽

Power Law Equation ◽

Triggering Rainfall ◽

Landslide Triggering

Abstract. Assessment of landslide-triggering rainfall thresholds is useful for early warning in prone areas. In this paper, it is shown how stochastic rainfall models and hydrological and slope stability physically based models can be advantageously combined in a Monte Carlo simulation framework to generate virtually unlimited-length synthetic rainfall and related slope stability factor of safety data, exploiting the information contained in observed rainfall records and field-measurements of soil hydraulic and geotechnical parameters. The synthetic data set, dichotomized in triggering and non-triggering rainfall events, is analyzed by receiver operating characteristics (ROC) analysis to derive stochastic-input physically based thresholds that optimize the trade-off between correct and wrong predictions. Moreover, the specific modeling framework implemented in this work, based on hourly analysis, enables one to analyze the uncertainty related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall). A specific focus is dedicated to the widely used power-law rainfall intensity–duration (I–D) thresholds. Results indicate that variability of intensity during rainfall events influences significantly rainfall intensity and duration associated with landslide triggering. Remarkably, when a time-variable rainfall-rate event is considered, the simulated triggering points may be separated with a very good approximation from the non-triggering ones by a I–D power-law equation, while a representation of rainfall as constant–intensity hyetographs globally leads to non-conservative results. This indicates that the I–D power-law equation is adequate to represent the triggering part due to transient infiltration produced by rainfall events of variable intensity and thus gives a physically based justification for this widely used threshold form, which provides results that are valid when landslide occurrence is mostly due to that part. These conditions are more likely to occur in hillslopes of low specific upslope contributing area, relatively high hydraulic conductivity and high critical wetness ratio. Otherwise, rainfall time history occurring before single rainfall events influences landslide triggering, determining whether a threshold based only on rainfall intensity and duration may be sufficient or it needs to be improved by the introduction of antecedent rainfall variables. Further analyses show that predictability of landslides decreases with soil depth, critical wetness ratio and the increase of vertical basal drainage (leakage) that occurs in the presence of a fractured bedrock.

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Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013)

Remote Sensing ◽

10.3390/rs10121879 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1879 ◽

Cited By ~ 7

Author(s):

Véronique Michot ◽

Daniel Vila ◽

Damien Arvor ◽

Thomas Corpetti ◽

Josyane Ronchail ◽

...

Keyword(s):

Amazon Basin ◽

Daily Rainfall ◽

Rain Gauge ◽

Rainfall Data ◽

Annual Rainfall ◽

Spatial Coverage ◽

Rainfall Regimes ◽

Trmm 3B42 ◽

Good Agreement

Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

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Extreme Rainfall in the Mediterranean: What Can We Learn from Observations?

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-083.1 ◽

2013 ◽

Vol 14 (3) ◽

pp. 906-922 ◽

Cited By ~ 79

Author(s):

N. Rebora ◽

L. Molini ◽

E. Casella ◽

A. Comellas ◽

E. Fiori ◽

...

Keyword(s):

Extreme Rainfall ◽

Flash Floods ◽

Rain Gauge ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Life Threatening ◽

The Mediterranean ◽

Moderate Resolution Imaging Spectroradiometer ◽

Ground Effects

Abstract Flash floods induced by extreme rainfall events represent one of the most life-threatening phenomena in the Mediterranean. While their catastrophic ground effects are well documented by postevent surveys, the extreme rainfall events that generate them are still difficult to observe properly. Being able to collect observations of such events will help scientists to better understand and model these phenomena. The recent flash floods that hit the Liguria region (Italy) between the end of October and beginning of November 2011 give us the opportunity to use the measurements available from a large number of sensors, both ground based and spaceborne, to characterize these events. In this paper, the authors analyze the role of the key ingredients (e.g., unstable air masses, moist low-level jets, steep orography, and a slow-evolving synoptic pattern) for severe rainfall processes over complex orography. For the two Ligurian events, this role has been analyzed through the available observations (e.g., Meteosat Second Generation, Moderate Resolution Imaging Spectroradiometer, the Italian Radar Network mosaic, and the Italian rain gauge network observations). The authors then address the possible role of sea–atmosphere interactions and propose a characterization of these events in terms of their predictability.

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Stochastorm: A stochastic rainfall simulator for convective storms

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0017.1 ◽

2020 ◽

Author(s):

Catherine Wilcox ◽

Claire Aly ◽

Théo Vischel ◽

Gérémy Panthou ◽

Juliette Blanchet ◽

...

Keyword(s):

Impact Analysis ◽

Extreme Values ◽

Rain Gauge ◽

Convective Precipitation ◽

Precipitation Event ◽

Storm Event ◽

Spatial And Temporal Scales ◽

Convective Storms ◽

Distribution Parameters ◽

Temporal Disaggregation

AbstractStochastic rainfall generators aim to reproduce the main statistical features of rainfall at small spatial and temporal scales. The simulated synthetic rainfall series are recognized as suitable for use with impact analysis in water, agricultural, and ecological management. Convection-driven precipitation, dominant in certain regions of the world such as the intertropical belt regions, presents properties that require specific consideration when modeling: (i) strong rainfall intermittency, (ii) high variability of intensities within storms, (iii) strong spatiotemporal correlation of intensities, and (iv) marked seasonality of storm properties. In this article, improvements for an existing statistico-dynamic rainfall generator that models convective storms are presented. Notable novelties include (i) the ability to model precipitation event timing, (ii) an improved temporal disaggregation scheme representing the rainfall distribution at sub-event scales, and (iii) using covariates to reflect seasonal changes in precipitation occurrence and marginal distribution parameters. Extreme values are explicitly considered in the distribution of storm event intensities. The simulator is calibrated and validated using 28 years of five-minute precipitation data from the 30 rain gauge AMMA-CATCH network in the Sahelian region of southwest Niger. Both large propagative systems and smaller local convective precipitation are generated. Results show that simulator improvements coherently represent the local climatology. The simulator can generate scenarios for impact studies with accurate representation of convective precipitation characteristics.

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