scholarly journals Rainfall threshold calculation for debris flow early warning in areas with scarcity of data

2018 ◽  
Vol 18 (5) ◽  
pp. 1395-1409 ◽  
Author(s):  
Hua-Li Pan ◽  
Yuan-Jun Jiang ◽  
Jun Wang ◽  
Guo-Qiang Ou

Abstract. Debris flows are natural disasters that frequently occur in mountainous areas, usually accompanied by serious loss of lives and properties. One of the most commonly used approaches to mitigate the risk associated with debris flows is the implementation of early warning systems based on well-calibrated rainfall thresholds. However, many mountainous areas have little data regarding rainfall and hazards, especially in debris-flow-forming regions. Therefore, the traditional statistical analysis method that determines the empirical relationship between rainstorms and debris flow events cannot be effectively used to calculate reliable rainfall thresholds in these areas. After the severe Wenchuan earthquake, there were plenty of deposits deposited in the gullies, which resulted in several debris flow events. The triggering rainfall threshold has decreased obviously. To get a reliable and accurate rainfall threshold and improve the accuracy of debris flow early warning, this paper developed a quantitative method, which is suitable for debris flow triggering mechanisms in meizoseismal areas, to identify rainfall threshold for debris flow early warning in areas with a scarcity of data based on the initiation mechanism of hydraulic-driven debris flow. First, we studied the characteristics of the study area, including meteorology, hydrology, topography and physical characteristics of the loose solid materials. Then, the rainfall threshold was calculated by the initiation mechanism of the hydraulic debris flow. The comparison with other models and with alternate configurations demonstrates that the proposed rainfall threshold curve is a function of the antecedent precipitation index (API) and 1 h rainfall. To test the proposed method, we selected the Guojuanyan gully, a typical debris flow valley that during the 2008–2013 period experienced several debris flow events, located in the meizoseismal areas of the Wenchuan earthquake, as a case study. The comparison with other threshold models and configurations shows that the selected approach is the most promising starting point for further studies on debris flow early warning systems in areas with a scarcity of data.

2017 ◽  
Author(s):  
Hua-li Pan ◽  
Yuan-jun Jiang ◽  
Jun Wang ◽  
Guo-qiang Ou

Abstract. Debris flows are one of the natural disasters that frequently occur in mountain areas, usually accompanied by serious loss of lives and properties. One of the most used approaches to mitigate the risk associated to debris flows is the implementation of early warning systems based on well calibrated rainfall thresholds. However, many mountainous areas have little data regarding rainfall and hazards, especially in debris flow forming regions. Therefore, the traditional statistical analysis method that determines the empirical relationship between rainfall and debris flow events cannot be effectively used to calculate reliable rainfall thre-shold in these areas. To solve this problem, this paper developed a quantitative method to identify rainfall threshold for debris flow early warning in data-poor areas based on the initiation mechanism of hydraulic-driven debris flow. First, we studied the characteristics of the study area, including meteorology, hydrology, topography and physical characteristics of the loose solid materials. Then, the rainfall threshold was calculated by the initiation me-chanism of the hydraulic debris flow. The results show that the proposed rainfall threshold curve is a function of the antecedent precipitation index and 1-h rainfall. The function is a line with a negative slope. To test the proposed method, we selected the Guojuanyan gully, a typical debris flow valley that during the 2008–2013 period experienced several debris flow events and that is located in the meizoseismal areas of Wenchuan earthquake, as a case study. We compared the calculated threshold with observation data, showing that the accuracy of the method is satisfying and thus can be used for debris flow early warning in areas with scaricty of data.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1195 ◽  
Author(s):  
Minu Treesa Abraham ◽  
Neelima Satyam ◽  
Sai Kushal ◽  
Ascanio Rosi ◽  
Biswajeet Pradhan ◽  
...  

Rainfall-induced landslides are among the most devastating natural disasters in hilly terrains and the reduction of the related risk has become paramount for public authorities. Between the several possible approaches, one of the most used is the development of early warning systems, so as the population can be rapidly warned, and the loss related to landslide can be reduced. Early warning systems which can forecast such disasters must hence be developed for zones which are susceptible to landslides, and have to be based on reliable scientific bases such as the SIGMA (sistema integrato gestione monitoraggio allerta—integrated system for management, monitoring and alerting) model, which is used in the regional landslide warning system developed for Emilia Romagna in Italy. The model uses statistical distribution of cumulative rainfall values as input and rainfall thresholds are defined as multiples of standard deviation. In this paper, the SIGMA model has been applied to the Kalimpong town in the Darjeeling Himalayas, which is among the regions most affected by landslides. The objectives of the study is twofold: (i) the definition of local rainfall thresholds for landslide occurrences in the Kalimpong region; (ii) testing the applicability of the SIGMA model in a physical setting completely different from one of the areas where it was first conceived and developed. To achieve these purposes, a calibration dataset of daily rainfall and landslides from 2010 to 2015 has been used; the results have then been validated using 2016 and 2017 data, which represent an independent dataset from the calibration one. The validation showed that the model correctly predicted all the reported landslide events in the region. Statistically, the SIGMA model for Kalimpong town is found to have 92% efficiency with a likelihood ratio of 11.28. This performance was deemed satisfactory, thus SIGMA can be integrated with rainfall forecasting and can be used to develop a landslide early warning system.


Author(s):  
M. Coco ◽  
E. Marchetti ◽  
O. Morandi

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.


2016 ◽  
Vol 11 (4) ◽  
pp. 720-731 ◽  
Author(s):  
Xin Yao ◽  
◽  
Lingjing Li ◽  

For 5 years (2009–2013) after the 2008 Ms8.0 Wenchuan earthquake, rainfall led to the transformation of unconsolidated co-seismic deposits into extensive and severe debris flows, causing significant loss of life and property. For debris flows in the earthquake-disturbed area, a few common concerns exist. What is their spatial-temporal distribution? What are the controlling factors? How much is the rainfall threshold for debris flows? What areas are more susceptible? Where suffered the most severe losses of life and property? Using debris flow characteristics, this study analyzes the relationships between seismic geological factors, geomorphologic factors, extreme rainfall, and debris flows in the 5 years following the earthquake, and draws the following conclusions. (1) There are regional differences in the rainfall threshold for generation of debris flows, and the annual maximum 72-hour accumulated rainfall for triggering a debris flow decreases from pre-seismic periods (135–325 mm) to post-seismic periods (75–160 mm) by 44.4–50.8% in study area. (2) Areas with high debris flow susceptibility and hazard are primarily controlled by seismic geological conditions. (3) The long-term risk of debris flows will fall to moderate, and the affected area will shrink to that around the seismogenic fault. The results of this study will help with meteorological early warning systems, deployment of disaster prevention and control projects, and reconstruction site selection in the post-seismic Longmen Mountain area.


2015 ◽  
Vol 15 (3) ◽  
pp. 587-602 ◽  
Author(s):  
M. Berenguer ◽  
D. Sempere-Torres ◽  
M. Hürlimann

Abstract. This work presents a technique for debris-flow (DF) forecasting able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class warning ("low", "moderate" or "high") in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the eastern Pyrenees (Spain) from May to October 2010. The warning level stayed "low" during the entire period in 20% of the subbasins, while in the most susceptible subbasins the warning level was at least "moderate" for up to 10 days. Quantitative evaluation of the warning level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the three events observed in the catchment (one debris flow and two hyperconcentrated flow events) and produced no false alarm.


2020 ◽  
Author(s):  
Rosa M Palau ◽  
Marc Berenguer ◽  
Marcel Hürlimann ◽  
Daniel Sempere-Torres ◽  
Catherine Berger ◽  
...  

<p>Risk mitigation for rainfall-triggered shallow slides and debris flows at regional scale is challenging. Early warning systems are a helpful tool to depict the location and time of future landslide events so that emergency managers can act in advance. Recently, some of the regions that are recurrently affected by rainfall triggered landslides have developed operational landslide early warning systems (LEWS). However, there are still many territories where this phenomenon also represents an important hazard and lack this kind of risk mitigation strategy.</p><p>The main objective of this work is to study the feasibility to apply a regional scale LEWS, which was originally designed to work over Catalonia (Spain), to run in other regions. To do so we have set up the LEWS to Canton of Bern (Switzerland).</p><p>The LEWS combines susceptibility maps to determine landslide prone areas and in real time high-resolution radar rainfall observations and forecasts. The output is a qualitative warning level map with a resolution of 30 m.</p><p>Susceptibility maps have been derived using a simple fuzzy logic methodology that combines the terrain slope angle, and land use and land cover (LULC) information. The required input parameters have been obtained from regional, pan-European and global datasets.</p><p>Rainfall inputs have been retrieved from both regional weather radar networks, and the OPERA pan-European radar composite. A set of global rainfall intensity-duration data has been used to asses if a rainfall event has the potential of triggering a landslide event.</p><p>The LEWS has been run in the region of Catalonia and Canton of Bern for specific rainfall events that triggered important landslides. Finally, the LEWS performance in Catalonia has been assessed.</p><p>Results in Catalonia show that the LEWS performance strongly depends on the quality of both the susceptibility maps and rainfall data. However, in both regions the LEWS is generally able to issue warnings for most of the analysed landslide events.</p>


2020 ◽  
Author(s):  
Velio Coviello ◽  
Matteo Berti ◽  
Lorenzo Marchi ◽  
Francesco Comiti ◽  
Giulia Marchetti ◽  
...  

<p>The complete understanding of the mechanisms controlling debris-flow initiation is still an open challenge in landslide research. Most debris-flow models assume that motion suddenly begins when a large force imbalance is imposed by slope instabilities or the substrate saturation that causes the collapse of the channel sediment cover. In the real world, the initiation of debris flows usually results from the perturbation of the static force balance that retains sediment masses in steep channels. These perturbations are primarily generated by the increasing runoff and by the progressive erosion of the deposits. Therefore, great part of regional early warning systems for debris flows are based on critical rainfall thresholds. However, these systems are affected by large spatial-temporal uncertainties due to the inadequate number and distribution of rain gauges. In addition, rainfall analysis alone does not explain the dynamics of sediment fluxes at the catchment scale: short-term variations in the sediment sources strongly influence the triggering of debris flows, even in catchments characterized by unlimited sediment supply.</p><p>In this work, we present multi-parametric observations of debris flows at the headwaters of the Gadria catchment (eastern Italian Alps). In 2018, we installed a monitoring network composed of geophones, three soil moisture probes, one tensiometer and two rain-triggered videocameras in a 30-m wide steep channel located at about 2200 m a.s.l. Most sensors lie on the lateral ridges of this channel, except for the tensiometer and the soil moisture probes that are installed in the channel bed at different depths. This network recorded four flow events in two years, two of which occurred at night. Specifically, the debris flows that occurred on 21 July 2018 and 26 July 2019 produced remarkable geomorphic changes in the monitored channel, with up to 1-m deep erosion. For all events, we measured peak values of soil water content that are far from saturation (<0.25 at -20 cm, <0.15 at -40 cm, <0.1 at -60 cm). We derived the time of occurrence and the duration of these events from the analysis of the seismic signals. Combining these pieces of information with data gathered at the monitoring station located about 2 km downstream, we could determine the flow kinematics along the main channel.</p><p>These results, although still preliminary, show the relevance of a multi-parametric detection of debris-flow initiation processes and may have valuable implications for risk management. Alarm systems for debris flows are becoming more and more attractive due the continuous development of compact and low-cost distributed sensor networks. The main challenge for operational alarm systems is the short lead-time, which is few tens of seconds for closing a transportation route or tens of minutes for evacuating settlements. Lead-time would significantly increase installing a detection system in the upper part of a catchment, where the debris flow initiates. The combination of hydro-meteorological monitoring in the source areas and seismic detection of channelized flows may be a reliable approach for developing an integrated early warning - alarm system.</p>


Several works have been conducted all across the globe determining rainfall thresholds in context of intensity-duration thresholds. Such results provide results in terms of occurrence or non-occurrence of landslides. This paper determines probabilities for various rainfall parameters causing landslides using a Bayesian approach along Phuentsholing Thimphu Highway in Chukha Dzongkhag of Bhutan. For Bhutan Himalayas, probabilistic rainfall thresholds for landslide initiation has not yet been attempted. The probabilities determined can be used for early warning systems considering it is a major trade route with India


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