Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period

Destro, Elisa; Marra, Francesco; Nikolopoulos, Efthymios I.; Zoccatelli, Davide; Creutin, Jean‐Dominique; Borga, Marco

doi:10.1016/j.geomorph.2016.11.019

Cited by 45 publications

(35 citation statements)

References 44 publications

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“…Synthetic rain gauge networks were produced using the procedure proposed by Nikolopoulos et al (2015a) and Destro et al (2017). The location of the rain gauges was randomly generated to obtain densities of 1/A, with A set to 10, 20, 50, and 100 km 2 .…”

Section: Comparison Between Thresholds Derived From Spatially Aggregamentioning

confidence: 99%

“…They are primarily triggered by heavy rainfall hitting headwater catchments and, in many areas, their frequency is expected to increase in response to the intensification of the hydrological cycle caused by global warming (Westra et al, 2014;Gariano and Guzzetti, 2016;Dietrich and Krautblatter, 2017). Forecasting their occurrence is fundamental to save lives and property and relies on early warning systems .…”

Section: Introductionmentioning

confidence: 99%

“…This data set is a representative sample (∼ 20 %) of the debris flows that occurred in the study region in the period 2000-2014 (Nikolopoulos et al, 2015b). See Destro et al (2017) for additional information on the debris flow database and on the storm events.…”

Section: Introductionmentioning

confidence: 99%

“…Following the results reported by Destro et al (2017), we related the distribution of the estimation error to the severity of the triggering rainfall. The return period of the triggering rainfall (T ) was computed from depth-durationfrequency curves derived for the region using the method of the L-moments, and a kriging interpolation procedure in a regional generalized extreme values framework .…”

Section: Introductionmentioning

confidence: 99%

“…Conversely, mild events (T ≤ 2 years) show a substantially different pattern, with aggregated estimates overestimated even for 20 km grid sizes. In fact, as shown by Destro et al (2017), debris flows triggered by short-return-period rainfall are often located close, but not corresponding, to the local rain depth peaks, so that the spatial aggregation is expected to include larger rain depths. The IQR is as high as 0.93 for 12 km grid size, and decreases to 0.8 for 20 km grid size.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds

Marra

Destro

Nikolopoulos

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. The systematic underestimation observed in debris flow early warning thresholds has been associated with the use of sparse rain gauge networks to represent highly non-stationary rainfall fields. Remote sensing products permit concurrent estimates of debris-flow-triggering rainfall for areas poorly covered by rain gauges, but the impact of using coarse spatial resolutions to represent such rainfall fields is still to be assessed. This study uses fine-resolution radar data for ∼ 100 debris flows in the eastern Italian Alps to (i) quantify the effect of spatial aggregation (1-20 km grid size) on the estimation of debris-flow-triggering rainfall and on the identification of early warning thresholds and (ii) compare thresholds derived from aggregated estimates and rain gauge networks of different densities. The impact of spatial aggregation is influenced by the spatial organization of rainfall and by its dependence on the severity of the triggering rainfall. Thresholds from aggregated estimates show 8-21 % variation in the parameters whereas 10-25 % systematic variation results from the use of rain gauge networks, even for densities as high as 1/10 km −2 .

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Section: Comparison Between Thresholds Derived From Spatially Aggregamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds

Marra

Destro

Nikolopoulos

et al. 2017

Hydrol. Earth Syst. Sci.

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Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

Leonarduzzi

Molnár

McArdell

2017

Water Resources Research

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A high‐resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972–2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity‐duration ID curves and validated their performance. The best predictive performance was obtained by the intensity‐duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country‐wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high‐quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack‐knife and cross‐validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

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Runoff‐generated debris flows: Observation of initiation conditions and erosion–deposition dynamics along the channel at Cancia (eastern Italian Alps)

Simoni

Bernard

Berti

et al. 2020

Earth Surf Processes Landf

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In the Dolomitic region, abundant coarse hillslope sediment is commonly found at the toe of rocky cliffs. Ephemeral channels originate where lower permeability bedrock surfaces concentrate surface runoff. Debris flows initiate along such channels following intense rainfall and determine the progressive erosion and deepening of the channels. Sediment recharge mechanisms include rock fall, dry ravel processes and channel-bank failures. Here we document debris flow activity that took place in an active debris flow basin during the year 2015. The Cancia basin is located on the southwestern slope of Mount Antelao (3264ma.s.l.) in the dolomitic region of the eastern Italian Alps. The 2.5km 2 basin is incised in dolomitic limestone rocks. The data consist of repeated topographic surveys, distributed rainfall measurements, time-lapse (2s) videos of two events and pore pressure measurements in the channel bed. During July and August 2015, two debris flow events occurred, following similarly intense rainstorms. We compared rainfall data to existing rainfall triggering thresholds and simulated the hydrological response of the headwater catchment with a distributed model in order to estimate the total and peak water discharge. Our data clearly illustrate how debris entrainment along the channel is the main contributor to the overall mobilized volume and that erosion is dominant when the channel slope exceeds 16°. Further downstream, sediment accumulation and depletion occurred alternately for the two successive events, indicating that sediment availability along the channel also influences the flow behaviour along the prevailing-transport reach. The comparison between monitoring data, topographical analysis and hydrological simulation allows the estimation of the average solid concentration of the two events and suggests that debris availability has a significant influence on the debris flow volume.

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Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period

Cited by 45 publications

References 44 publications

Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds

Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

Runoff‐generated debris flows: Observation of initiation conditions and erosion–deposition dynamics along the channel at Cancia (eastern Italian Alps)

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