Rain-triggered lahars following the 2010 eruption of Merapi volcano, Indonesia: A major risk

Bélizal, Édouard de; Lavigne, Franck; Hadmoko, Danang Sri; Degeai, Jean‐Philippe; Dipayana, Gilang Aria; Mutaqin, Bachtiar Wahyu; Marfai, Muh Aris; Coquet, Marie; Mauff, Baptiste Le; Robin, Anne-Kyria; Vidal, Céline; Cholik, Noer; Aisyah, Nurnaning

doi:10.1016/j.jvolgeores.2013.01.010

Cited by 107 publications

(52 citation statements)

References 28 publications

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“…Thus, the parameterization of Multihaz is preliminary and the performance of the model is not tested against real data. However, at certain volcanoes (e.g., Mount Merapi, Indonesia; Lavigne et al, 2000a;De Bélizal et al, 2013), large datasets of lahar observations may be used to either calibrate the Multihaz parameters or test the performance of the network (Figure 11). That is, using combinations of node states that have been observed (e.g., RI=high, RD=medium, IV=medium), it is possible (i) to refine/update, through Bayesian inference, the probability values (i.e., parameters) in Multihaz; or (ii) to calculate the likelihood of observing the aforementioned combinations, given our paramerization of Multihaz (e.g., Murphy, 2001;Koller and Friedman, 2009).…”

Section: Use Of Bbns To Model Rain-triggered Laharsmentioning

confidence: 99%

A Framework for Probabilistic Multi-Hazard Assessment of Rain-Triggered Lahars Using Bayesian Belief Networks

et al. 2017

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Volcanic water-sediment flows, commonly known as lahars, can often pose a higher threat to population and infrastructure than primary volcanic hazardous processes such as tephra fallout and Pyroclastic Density Currents (PDCs). Lahars are volcaniclastic flows of water, volcanic debris and entrained sediments that can travel long distances from their source, causing severe damage by impact and burial. Lahars are frequently triggered by intense or prolonged rainfall occurring after explosive eruptions, and their occurrence depends on numerous factors including the spatio-temporal rainfall characteristics, the spatial distribution and hydraulic properties of the tephra deposit, and the pre-and post-eruption topography. Modeling (and forecasting) such a complex system requires the quantification of aleatory variability in the lahar triggering and propagation. To fulfill this goal, we develop a novel framework for probabilistic hazard assessment of lahars within a multi-hazard environment, based on coupling a versatile probabilistic model for lahar triggering (a Bayesian Belief Network: Multihaz) with a dynamic physical model for lahar propagation (LaharFlow). Multihaz allows us to estimate the probability of lahars of different volumes occurring by merging varied information about regional rainfall, scientific knowledge on lahar triggering mechanisms and, crucially, probabilistic assessment of available pyroclastic material from tephra fallout and PDCs. LaharFlow propagates the aleatory variability modeled by Multihaz into hazard footprints of lahars. We apply our framework to Somma-Vesuvius (Italy) because: (1) the volcano is strongly lahar-prone based on its previous activity, (2) there are many possible source areas for lahars, and (3) there is high density of population nearby. Our results indicate that the size of the eruption preceding the lahar occurrence and the spatial distribution of tephra accumulation have a paramount role in the lahar initiation and potential impact. For instance, lahars with initiation volume ≥10 5 m 3 along the volcano flanks are almost 60% probable to occur after large-sized eruptions (∼VEI ≥ 5) but 40% after medium-sized eruptions (∼VEI4). Some simulated lahars can propagate for 15 km or reach combined flow depths of 2 m and speeds of 5-10 m/s, even over flat terrain. Probabilistic multi-hazard frameworks like the one presented here can be invaluable for volcanic hazard assessment worldwide.

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Section: Use Of Bbns To Model Rain-triggered Laharsmentioning

confidence: 99%

A Framework for Probabilistic Multi-Hazard Assessment of Rain-Triggered Lahars Using Bayesian Belief Networks

et al. 2017

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“…A similar event was observed in 2005, when tropical storm Stan triggered landslides and debris flows from the Tolimán Volcano (Guatemala), causing more than 400 fatalities in the Panabaj community (Sheridan et al, 2007). Other examples can be found at the Pinatubo (Philippines), Merapi and Semeru (Indonesia), Soufriére Hills (Montserrat) and Tungurahua (Ecuador) volcanoes, where tropical storms and heavy rainfall seasons have triggered high-frequency lahar events (Umbal and Rodolfo, 1996;Lavigne et al, 2000;Lavigne and Thouret, 2002;Barclay et al, 2007;Dumaisnil et al, 2010;de Bélizal et al, 2013;Jones et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Hydrological control of large hurricane-induced lahars: evidence from rainfall-runoff modeling, seismic and video monitoring

Capra

Coviello

Borselli

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. The Volcán de Colima, one of the most active volcanoes in Mexico, is commonly affected by tropical rains related to hurricanes that form over the Pacific Ocean. In 2011 hurricanes Jova, Manuel and Patricia, respectively, triggered tropical storms that deposited up to 400 mm of rain in 36 h, with maximum intensities of 50 mm h −1 . The effects were devastating, with the formation of multiple lahars along La Lumbre and Montegrande ravines, which are the most active channels in sediment delivery on the southsouthwest flank of the volcano. Deep erosion along the river channels and several marginal landslides were observed, and the arrival of block-rich flow fronts resulted in damages to bridges and paved roads in the distal reaches of the ravines. The temporal sequence of these flow events is reconstructed and analyzed using monitoring data (including video images, seismic records and rainfall data) with respect to the rainfall characteristics and the hydrologic response of the watersheds based on rainfall-runoff numerical simulation. For the studied events, lahars occurred 5-6 h after the onset of rainfall, lasted several hours and were characterized by several pulses with block-rich fronts and a maximum flow discharge of 900 m 3 s −1 . Rainfall-runoff simulations were performer using the SCS-curve number and the Green-Ampt infiltration models, providing a similar result in the detection of simulated maximum watershed peaks discharge. Results show different behavior for the arrival times of the first lahar pulses that correlate with the simulated catchment's peak discharge for La Lumbre ravine and with the peaks in rainfall intensity for Montegrande ravine. This different behavior is related to the area and shape of the two watersheds. Nevertheless, in all analyzed cases, the largest lahar pulse always corresponds with the last one and correlates with the simulated maximum peak discharge of these catchments. Data presented here show that flow pulses within a lahar are not randomly distributed in time, and they can be correlated with rainfall peak intensity and/or watershed discharge, depending on the watershed area and shape. This outcome has important implications for hazard assessment during extreme hydro-meteorological events, as it could help in providing real-time alerts. A theoretical rainfall distribution curve was designed for Volcán de Colima based on the rainfall and time distribution of hurricanes Manuel and Patricia. This can be used to run simulations using weather forecasts prior to the actual event, in order to estimate the arrival time of main lahar pulses, usually characterized by block-rich fronts, which are responsible for most of the damage to infrastructure and loss of goods and lives.

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“…The Indonesian term "lahar" is used for a mixture of debris and water, other than stream flow, that flows on volcano slopes at relatively high speed [41]. Rain-triggered lahars devastated several villages on the west and south flank of Merapi in 2011 and 2012 [42][43].…”

Section: Introductionmentioning

confidence: 99%

The adaptive governance of natural disaster systems: Insights from the 2010 mount Merapi eruption in Indonesia

Bakkour

Enjolras

Thouret

et al. 2015

International Journal of Disaster Risk Reduction

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Rain-triggered lahars following the 2010 eruption of Merapi volcano, Indonesia: A major risk

Cited by 107 publications

References 28 publications

A Framework for Probabilistic Multi-Hazard Assessment of Rain-Triggered Lahars Using Bayesian Belief Networks

A Framework for Probabilistic Multi-Hazard Assessment of Rain-Triggered Lahars Using Bayesian Belief Networks

Hydrological control of large hurricane-induced lahars: evidence from rainfall-runoff modeling, seismic and video monitoring

The adaptive governance of natural disaster systems: Insights from the 2010 mount Merapi eruption in Indonesia

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