scholarly journals The use of rain gauge measurements and radar data for the model‐based prediction of runoff‐generated debris‐flow occurrence in early warning systems

2021 ◽  
Author(s):  
Martino Bernard ◽  
Carlo Gregoretti
Keyword(s):  
Debris Flow ◽  
Early Warning ◽  
Early Warning Systems ◽  
Radar Data ◽  
Rain Gauge ◽  
Warning Systems ◽  
Model Based

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

2017 ◽  
Author(s):  
Francesco Marra ◽  
Elisa Destro ◽  
Efthymios I. Nikolopoulos ◽  
Davide Zoccatelli ◽  
Jean Dominique Creutin ◽  
...  
Keyword(s):  
Debris Flow ◽  
Early Warning ◽  
Debris Flows ◽  
Spatial Organization ◽  
Radar Data ◽  
Rain Gauge ◽  
Spatial Aggregation ◽  
Scale Parameters ◽  
The Impact ◽  
Triggering Rainfall

Abstract. The systematic underestimation observed in debris flows early warning thresholds has been associated to 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 up to 8 % and 21 % variations in the shape and scale parameters respectively. Thresholds from synthetic rain gauge networks show > 10 % variation in the shape and > 25 % systematic underestimation in the scale parameter, even for densities as high as 1/10 km−2.

scholarly journals Brief Communication: A new testing field for debris flow warning systems and algorithms

2015 ◽  
Vol 3 (3) ◽  
pp. 1717-1729
Author(s):  
M. Arattano ◽  
V. Coviello ◽  
M. Cavalli ◽  
F. Comiti ◽  
P. Macconi ◽  
...  
Keyword(s):  
Debris Flow ◽  
Early Warning ◽  
Hazard Mitigation ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Italian Alps ◽  
Research Activity ◽  
Essential Step ◽  
Testing Field

Abstract. Early warning systems (EWSs) are among the measures adopted for the mitigation of debris flow hazards. EWSs often employ algorithms that require careful and long testing to grant their effectiveness. A permanent installation has been so equipped in the Gadria basin (Eastern Italian Alps) for the systematic test of event-EWSs. The installation is conceived to produce didactic videos and host informative visits. The populace involvement and education is in fact an essential step in any hazard mitigation activity and it should envisaged in planning any research activity. The occurrence of a debris flow in the Gadria creek, in the summer of 2014, allowed a first test of the installation and the recording of an informative video on EWSs.

Model-based Development of Self-organizing Earthquake Early Warning Systems

2009 ◽  
Vol 18 (3-4) ◽  
pp. 9-20 ◽  
Author(s):  
Joachim Fischer ◽  
Frank Kühnlenz ◽  
Klaus Ahrens ◽  
Ingmar Eveslage
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
Earthquake Early Warning ◽  
Warning Systems ◽  
Model Based ◽  
Earthquake Early Warning Systems ◽  
Self Organizing

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

2017 ◽  
Vol 21 (9) ◽  
pp. 4525-4532 ◽  
Author(s):  
Francesco Marra ◽  
Elisa Destro ◽  
Efthymios I. Nikolopoulos ◽  
Davide Zoccatelli ◽  
Jean Dominique Creutin ◽  
...  
Keyword(s):  
Debris Flow ◽  
Early Warning ◽  
Spatial Organization ◽  
Radar Data ◽  
Rain Gauge ◽  
Spatial Aggregation ◽  
Rain Gauges ◽  
Fine Resolution ◽  
The Impact ◽  
Triggering Rainfall

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.

scholarly journals Numerical Modeling of Infrasound Energy Radiation by Debris Flow Events

2021 ◽  
Author(s):  
M. Coco ◽  
E. Marchetti ◽  
O. Morandi
Keyword(s):  
Numerical Modeling ◽  
Debris Flow ◽  
Early Warning ◽  
Debris Flows ◽  
Flow Characteristics ◽  
Early Warning Systems ◽  
Numerical Results ◽  
Warning Systems ◽  
Simulation Code ◽  
Energy Radiation

AbstractDebris flows constitute a severe natural hazard in Alpine regions. Studies are performed to understand the event predictability and to identify early warning systems and procedures. These are based both on sensors deployed along the channels or on the amplitude of seismic and infrasound waves radiated by the flow and recorded far away. Despite being very promising, infrasound cannot be used to infer the source characteristics due to the lack of a physical model of the infrasound energy radiated by debris flows. Here the simulation of water flow along a simple channel is presented, experiencing the fall from a dam, performed within the open source simulation code OpenFOAM. The pressure perturbation within the atmosphere produced by the flow is extracted and the infrasound signature of the events as a function of the flow characteristics is defined. Numerical results suggest that infrasound is radiated immediately downstream of the dam with amplitude and period that scale with dam height and water level. Modeled infrasound waveform is interpreted as being produced mostly by waves at the water free surface developing downstream of the dam. Despite the effect of sediments is not considered in this first study and will be implemented in future investigations, numerical results obtained with this simple model are in general agreement with experimental results obtained from array analysis of infrasound data recorded at Illgraben, Switzerland. Results highlight how numerical modeling can provide critical information to define a source mechanism of infrasound energy radiation by debris-flow, that is required also to improve early warning systems.

scholarly journals Application and verification of a multivariate real-time early warning method for rainfall-induced landslides: implication for evolution of landslide-generated debris flows

Landslides ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. 2409-2419
Author(s):  
Zongji Yang ◽  
Liyong Wang ◽  
Jianping Qiao ◽  
Taro Uchimura ◽  
Lin Wang
Keyword(s):  
Debris Flow ◽  
Real Time ◽  
Early Warning ◽  
Early Warning Systems ◽  
Mechanical Analysis ◽  
Warning Systems ◽  
Physical Mechanisms ◽  
New Strategy

Abstract Rainfall-induced landslides are a frequent and often catastrophic geological disaster, and the development of accurate early warning systems for such events is a primary challenge in the field of risk reduction. Understanding of the physical mechanisms of rainfall-induced landslides is key for early warning and prediction. In this study, a real-time multivariate early warning method based on hydro-mechanical analysis and a long-term sequence of real-time monitoring data was proposed and verified by applying the method to predict successive debris flow events that occurred in 2017 and 2018 in Yindongzi Gully, which is in Wenchuan earthquake region, China. Specifically, long-term sequence slope stability analysis of the in situ datasets for the landslide deposit as a benchmark was conducted, and a multivariate indicator early warning method that included the rainfall intensity-probability (I-P), saturation (Si), and inclination (Ir) was then proposed. The measurements and analysis in the two early warning scenarios not only verified the reliability and practicality of the multivariate early warning method but also revealed the evolution processes and mechanism of the landslide-generated debris flow in response to rainfall. Thus, these findings provide a new strategy and guideline for accurately producing early warnings of rainfall-induced landslides.

scholarly journals Satellite rainfall products outperform ground observations for landslide prediction in India

2021 ◽  
Vol 25 (6) ◽  
pp. 3267-3279
Author(s):  
Maria Teresa Brunetti ◽  
Massimo Melillo ◽  
Stefano Luigi Gariano ◽  
Luca Ciabatta ◽  
Luca Brocca ◽  
...  
Keyword(s):  
Early Warning ◽  
Daily Rainfall ◽  
Early Warning Systems ◽  
Rain Gauge ◽  
Warning Systems ◽  
Landslide Prediction ◽  
Landslide Occurrence ◽  
Monitoring Process ◽  
Satellite Rainfall ◽  
The Impact

Abstract. Landslides are among the most dangerous natural hazards, particularly in developing countries, where ground observations for operative early warning systems are lacking. In these areas, remote sensing can represent an important detection and monitoring process to predict landslide occurrence in space and time, particularly satellite rainfall products that have improved in terms of accuracy and resolution in recent times. Surprisingly, only a few studies have investigated the capability and effectiveness of these products in landslide prediction in reducing the impact of this hazard on the population. We have performed a comparative study of ground- and satellite-based rainfall products for landslide prediction in India by using empirical rainfall thresholds derived from the analysis of historical landslide events. Specifically, we have tested Global Precipitation Measurement (GPM) and SM2RAIN-ASCAT satellite rainfall products, and their merging, at daily and hourly temporal resolution, and Indian Meteorological Department (IMD) daily rain gauge observations. A catalogue of 197 rainfall-induced landslides that occurred throughout India in the 13-year period between April 2007 and October 2019 has been used. Results indicate that satellite rainfall products outperform ground observations thanks to their better spatial (0.1∘ vs. 0.25∘) and temporal (hourly vs. daily) resolutions. The better performance is obtained through the merged GPM and SM2RAIN-ASCAT products, even though improvements in reproducing the daily rainfall (e.g. overestimation of the number of rainy days) are likely needed. These findings open a new avenue for using such satellite products in landslide early warning systems, particularly in poorly gauged areas.

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