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At least 397 records · Page 22Linked to original sources

Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico

Hurricane Maria induced about 70 000 landslides throughout Puerto Rico, USA, including thousands each in three municipalities situated in Puerto Rico's rugged Cordillera Central range. By combining a nonlinear soil-depth model, presumed wettest-case pore pressures, and quasi-three-dimensional (3D) slope-stability analysis, we developed a landslide susceptibility map that has very good performance and continuous susceptibility zones having smooth, buffered boundaries. Our landslide susceptibility map enables assessment of potential ground-failure locations and their use as landslide sources in a companion assessment of inundation and debris-flow runout. The quasi-3D factor of safety, F 3 , showed strong inverse correlation to landslide density (high density at low F 3 ). Area under the curve (AUC) of true positive rate (TPR) versus false positive rate (FPR) indicated success of F 3 in identifying head-scarp points (AUC = 0.84) and source-area polygons (0.85 ≤ AUC ≤ 0.88). The susceptibility zones enclose specific percentages of observed landslides. Thus, zone boundaries use successive F 3 levels for increasing TPR of landslide head-scarp points, with zones bounded by F 3 at TPR = 0.75, very high; F 3 at TPR = 0.90, high; and the remainder moderate to low. The very high susceptibility zone, with 118 landslides km −2 , covered 23 % of the three municipalities. The high zone (51 landslides km −2 ) covered another 10 %.

Puerto Rice↗

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗

Rapid simulation of wave runup on morphologically diverse, reef-lined coasts with the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process model

Low-lying, tropical, coral-reef-lined coastlines are becoming increasingly vulnerable to wave-driven flooding due to population growth, coral reef degradation, and sea-level rise. Early-warning systems (EWSs) are needed to enable coastal authorities to issue timely alerts and coordinate preparedness and evacuation measures for their coastal communities. At longer timescales, risk management and adaptation planning require robust assessments of future flooding hazard considering uncertainties. However, due to diversity in reef morphologies and complex reef hydrodynamics compared to sandy shorelines, there have been no robust analytical solutions for wave runup to allow for the development of large-scale coastal wave-driven flooding EWSs and risk assessment frameworks for reef-lined coasts. To address the need for fast, robust predictions of runup that account for the natural variability in coral reef morphologies, we constructed the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process modeling system. We developed this meta-process model using a training dataset of hydrodynamics and wave runup computed by the XBeach Non-Hydrostatic process-based hydrodynamic model for 440 combinations of water level, wave height, and wave period with 195 representative reef profiles that encompass the natural diversity in real-world fringing coral reef systems. Through this innovation, BEWARE-2 can be applied in a larger range of coastal settings than meta-models that rely on a parametric description of the coral reef geometry. In the validation stage, the BEWARE-2 modeling system produced runup results that had a relative root mean square error of 13% and relative bias of 5% relative to runup simulated by XBeach Non-Hydrostatic for a large range of oceanographic forcing conditions and for diverse reef morphologies (root mean square error and bias 0.63 and 0.26 m, respectively, relative to mean simulated wave runup of 4.85 m). Incorporating parametric modifications in the modeling system to account for variations in reef roughness and beach slope allows for systematic errors (relative bias) in BEWARE-2 predictions to be reduced by a factor of 1.5–6.5 for relatively coarse or smooth reefs and mild or steep beach slopes. This prediction provided by the BEWARE-2 modeling system is faster by 4–5 orders of magnitude than the full, process-based hydrodynamic model and could therefore be integrated into large-scale EWSs for tropical, reef-lined coasts and used for large-scale flood risk assessments.

Natural Hazards and Earth System Sciences↗

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗

Topographic controls on landslide mobility: Modeling hurricane-induced landslide runout and debris-flow inundation in Puerto Rico

In 2017, Hurricane Maria triggered more than 70 000 landslides in Puerto Rico. After initiation, these predominantly shallow landslides were mobilized to varying extents – some landslides only traveled partway downslope, whereas others reached drainage channels and were mobilized into long-traveled debris flows that could severely impact roads and infrastructure. Thus, forecasting potential landslide runout and inundation zones is critical for estimating landslide and debris-flow hazards. Here we conduct an in-depth topographic analysis of landslide-affected areas from nine study areas and apply a linked modeling technique to estimate locations susceptible to varying degrees of landslide runout in the Lares, Utuado, and Naranjito municipalities. We find that the longest runout lengths are observed on high-relief escarpments, although highly mobile long-runout debris flows also occurred in lower-relief dissected uplands. These topographic differences indicate that landslides that are initiated under similar conditions and possess equal potential to be mobilized as debris flows may not travel the same distances or affect the same areal extent. Our modeling approach allows the local topography to automatically control the implementation of two runout methods: (1) H/L runout zones are assigned directly downslope of landslide source zones, and (2) debris-flow inundation zones are estimated in the presence of a channel network. Debris-flow volumes are calculated as a function of area-integrated growth factors, estimated as a function of the upstream areas susceptible to shallow landslides. Applying our empirical modeling scheme over an area of 560 km 2 , our results highlight the efficacy of our methods for the assessment of the potential for landslide runout and debris-flow inundation over diverse terrains with varied susceptibility.

Puerto Rico↗

Social sensing a volcanic eruption: Application to Kīlauea, 2018

Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology, conducted primarily by volcano monitoring and emergency management organisations, but it is complicated by scarce knowledge of how communities respond in times of crisis. Social sensing is a rapidly developing practice that can be adapted for volcanology. Here we use social sensing of Twitter (currently known as X) posts to track changes in social action and reaction throughout the 2018 eruption of Kīlauea on the island of Hawai`i. The volume of relevant posts very rapidly increases in early May, coincident with the beginning of the eruption; automated sentiment analysis shows a simultaneous shift towards more negative emotions being expressed in post text. Substantial negative trends in sentiment are evident in reaction to high-impact events, including the destruction of a popular residential area and injuries sustained by tourists viewing the eruption. Topics of local Twitter conversation reveal societal actions, including the sharing of hazard warnings, mitigation actions, and aid announcements. Temporal trends in societal actions reflect patterns in volcanic activity (e.g. the peak and waning of eruptive activity), civil protection actions (e.g. risk mitigation actions and the communication of official warnings), and socioeconomic pressures (e.g. the destruction of homes). Local tweets detailing eruption damage and disruption display a similar temporal trend to independent estimates of the number of buildings in contact with lava. We show how hazard and risk information is discussed and reacted to on Twitter, which helps inform our understanding of community response actions and aids situational awareness, and outline how our approach could be adapted for use in real time.

Hawaii↗

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems

Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.

Alaska↗

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗

Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA

Large magnitude snow avalanches (destructive size ≥ D3) impact settlements, transportation corridors, and public safety worldwide. In Colorado, United States, avalanches have killed more people than any other natural hazard since 1950. In March 2019, a large magnitude avalanche cycle occurred throughout the entire mountainous portion of Colorado resulting in more than 1000 reported avalanches during a two-week period. Nearly 200 of these avalanches were size D4 or larger with at least three D5 avalanches. However, placing this 2019 large magnitude avalanche cycle in historic context requires data prior to the instrumental record. Here, we paired tree disturbance data from dendrochronology (1698 to 2020) with meteorological data from the modeled and instrumental record (1901 to 2020) to understand the frequency and climate drivers of large magnitude snow avalanche cycles. The extensive number of downed trees from the 2019 avalanche cycle allowed us to collect 1,188 cross-sections and cores from 1023 individual trees within 24 avalanche paths across the state. From these samples we identified 4135 avalanche-related growth disturbances. We employed a strategic nested sampling design to spatially aggregate avalanche frequency from individual avalanche paths, to counties, to three major sub-regions (i.e., north, central, and south), and across the entire region (i.e., state of Colorado). Over a period spanning more than three centuries (1698 to 2020), we identified 76 avalanche years within 24 individual avalanche paths. Large magnitude avalanche event frequency varied across paths and sub-regions with several notable region-wide avalanche cycles. Both tree-ring and historical written records highlighted 1899 as a year with widespread and large magnitude avalanche activity similar to the March 2019 avalanche cycle. Since the early-20th century (1900 to 2020) regional avalanche probability declined significantly in parallel with decreasing snowpack throughout Colorado. Similarly, dominant avalanche regimes shifted from large magnitude regional cycles driven by above average snowfall years over most of the record, to regional avalanche cycles occurring more commonly in average to low snow years since 1988. In recent decades, a lack of December precipitation and above average March precipitation characterized years with regional large magnitude avalanche activity. Even with declining snow water equivalent, truly extreme regional large magnitude avalanche cycles remain possible – as demonstrated by the 2019 cycle. This underscores that rare but high-impact events are not eliminated by long-term trends. Understanding the changing snow and weather drivers and subsequent behavior of large magnitude avalanche cycles across multiple spatial scales may improve avalanche forecasting and the products and mitigations strategies developed by structural engineers to mitigate avalanche danger. This can decrease the avalanche risk to the public and improve infrastructure design in avalanche terrain.

Colorado↗

The damability function: A probabilistic approach to regional landslide dam susceptibility analysis applied to the Oregon Coast Range, USA

Landslides can dam rivers and require rapid response to mitigate catastrophic outburst floods. Here, we present a workflow to map landslide dam formation susceptibility at a regional scale. We define a probabilistic function that combines river valley width and landslide volume to efficiently determine the likelihood of a landslide dam or “damability”. We combine damability values with landslide susceptibility to estimate landslide dam susceptibility. The valley width measurements are automated using a new elevation threshold-based algorithm. Landslide volume is represented as a statistical distribution from mapped landslides. We validate and apply our approach to the Oregon Coast Range, USA and find that 36 % of river stretches exceed a dam potential threshold; these are in river headwaters and steeper terrain, which in this case correlate with more resistant lithologies. We also estimate volumes of the potential dammed lakes and find that most rivers with high dam susceptibility are less likely to impound large lakes because they have low drainage areas. However, widespread susceptibility, and the potential impacts from exceptionally large landslides, suggest that this hazard should be considered in the Pacific Northwest. The damability function workflow can ingest new data and be applied more broadly to assess future landslide dam hazards.

Oregon↗

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗

Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut

Compound flood events, the co-occurrence of multiple flood drivers, can result in flood hazard potential exceeding that of any single driver alone. To evaluate compound flooding in a semi-urbanized coastal area, historical records dating back to 1970 are used to study the co-occurrences of high precipitation, storm surge, and shallow groundwater conditions along the coastlines of New York and Connecticut. Joint return periods for coincident precipitation-surge events were computed using statistical dependence models and compared to the assumption of independence as a ratio, referred to here as a return period adjustment. Results indicate distinct seasonality where compound events in the area disproportionately occur in the cold season between October and April. Return period adjustments range from a factor of 1 to almost 9, demonstrating the range in precipitation-storm surge dependence across the study area. Across all 24 station triad locations, groundwater levels were elevated during times of precipitation- surge co-occurrence, reflecting the tendency for coastal storms and shallow groundwater conditions to co-occur seasonally. The result is a pseudo-trivariate compound flood hazard score and corresponding hazard map that integrates dependence between daily precipitation-surge events and overall monthly groundwater levels (as a precondition) into a relative compound hazard score. The location with the highest compound flood hazard score is on the south shore of Long Island, as well as locations across coastal Connecticut where groundwater levels compound the co-occurrence of heavy precipitation and storm surge.

Connecticut, New York↗

Rockfall hazard and risk assessment in the Yosemite Valley, California, USA

Rock slides and rock falls are the most frequent types of slope movements in Yosemite National Park, California. In historical time (1857-2002) 392 rock falls and rock slides have been documented in the valley, and some of them have been mapped in detail. We present the results of an attempt to assess rock fall hazards in the Yosemite Valley. Spatial and temporal aspects of rock falls hazard are considered. A detailed inventory of slope movements covering the 145-year period from 1857 to 2002 is used to determine the frequency-volume statistics of rock falls and to estimate the annual frequency of rock falls, providing the temporal component of rock fall hazard. The extent of the areas potentially subject to rock fall hazards in the Yosemite Valley were obtained using STONE, a physically-based rock fall simulation computer program. The software computes 3-dimensional rock fall trajectories starting from a digital elevation model (DEM), the location of rock fall release points, and maps of the dynamic rolling friction coefficient and of the coefficients of normal and tangential energy restitution. For each DEM cell the software calculates the number of rock falls passing through the cell, the maximum rock fall velocity and the maximum flying height. For the Yosemite Valley, a DEM with a ground resolution of 10 ?? 10 m was prepared using topographic contour lines from the U.S. Geological Survey 1:24 000-scale maps. Rock fall release points were identified as DEM cells having a slope steeper than 60??, an assumption based on the location of historical rock falls. Maps of the normal and tangential energy restitution coefficients and of the rolling friction coefficient were produced from a surficial geologic map. The availability of historical rock falls mapped in detail allowed us to check the computer program performance and to calibrate the model parameters. Visual and statistical comparison of the model results with the mapped rock falls confirmed the accuracy of the model. The model results are compared with a previous map of rockfall talus and with a geomorphic assessment of rock fall hazard based on potential energy referred to as a shadow angle approach, recently completed for the Yosemite Valley. The model results are then used to identify the roads and trails more subject to rock fall hazard. Of the 166.5 km of roads and trails in the Yosemite Valley 31.2% were found to be potentially subject to rock fall hazard, of which 14% are subject to very high hazard. ?? European Geosciences Union 2003.

Natural Hazards and Earth System Sciences↗

Undersea landslides: Extent and significance in the Pacific Ocean, an update

Submarine landslides are known to occur disproportionately in a limited number of environments including fjords, deltas, canyons, volcanic islands and the open continental slope. An evaluation of the progress that has been made in understanding Pacific Ocean submarine landslides over the last 15 years shows that mapping technologies have improved greatly, allowing a better interpretation of landslide features. Some features previously identified as landslides are being reinterpreted by some as sediment waves. Previously underappreciated environments for landslides such as deep-sea trenches are being recognized and lava deltas are being found to be landslide prone. Landslides are also being recognized much more commonly as a potential source of tsunamis. Landslides that have produced tsunamis in the past are being mapped and in some cases modeled. The flow characteristics of turbidity currents produced by landslides in canyon heads have recently been monitored and the source of these failures has been identified using repeated multibeam mapping. Finally, some landslide deposits are being dated as part of assessing risk to coastal cities from landslide-tsunamis. European Geosciences Union ?? 2005 Author(s). This work is licensed under a Creative Commons License.

Natural Hazards and Earth System Sciences↗

A magnetotelluric study of the sensitivity of an area to seismoelectric signals

During recent years, efforts at better understanding the physical properties of precursory ultra-low frequency pre-seismic electric signals (SES) have been intensified. Experiments show that SES cannot be observed at all points of the Earth's surface but only at certain so-called sensitive sites. Moreover, a sensitive site is capable of collecting SES from only a restricted number of seismic areas (selectivity effect). Tberefore the installation of a permanent station appropriate for SES collection should necessarily be preceded by a pilot study over a broad area and for a long duration. In short, a number of temporary stations are installed and, after the occurrence of several significant earthquakes (EQs) from a given seismic area, the most appropriate (if any) of these temporary stations, in the sense that they happen to collect SES, can be selected as permanent. Such a long experiment constitutes a serious disadvantage in identifying a site as SES sensitive. However, the SES sensitivity of a site should be related to the geoelectric structure of the area that hosts the site as well as the regional geoelectric structure between the station and the seismic focal area. Thus, knowledge of the local and regional geoelectric structure can dramatically reduce the time involved in identifying SES sites. hi this paper the magnetotelluric method is used to investigate the conductivity structure of an area where a permanent SES station is in operation. Although general conclusions cannot be drawn, the area surrounding an SES site near Ioannina, Greece is characterized by: (1) major faults in the vicinity; (2) highly resistive structure flanked by abrupt conductivity contrasts associated with large-scale geologic contacts, and (3) local inhomogeneities in conductivity structure. The above results are consistent with the fact that electric field amplitudes from remotely-generated signals should be appreciably stronger at such sites when compared to neighboring sites. European Geosciences Union ?? 2005 Author(s). This work is licensed under a Creative Commons License.

Natural Hazards and Earth System Sciences↗

Calibration of numerical models for small debris flows in Yosemite Valley, California, USA

This study compares documented debris flow runout distances with numerical simulations in the Yosemite Valley of California, USA, where about 15% of historical events of slope instability can be classified as debris flows and debris slides (Wieczorek and Snyder, 2004). To model debris flows in the Yosemite Valley, we selected six streams with evidence of historical debris flows; three of the debris flow deposits have single channels, and the other three split their pattern in the fan area into two or more channels. From field observations all of the debris flows involved coarse material, with only very small clay content. We applied the one dimensional DAN (Dynamic ANalysis) model (Hungr, 1995) and the two-dimensional FLO2D model (O'Brien et al., 1993) to predict and compare the runout distance and the velocity of the debris flows observed in the study area. As a first step, we calibrated the parameters for the two softwares through the back analysis of three debris- flows channels using a trial-and-error procedure starting with values suggested in the literature. In the second step we applied the selected values to the other channels, in order to evaluate their predictive capabilities. After parameter calibration using three debris flows we obtained results similar to field observations We also obtained a good agreement between the two models for velocities. Both models are strongly influenced by topography: we used the 30 m cell size DTM available for the study area, that is probably not accurate enough for a highly detailed analysis, but it can be sufficient for a first screening. European Geosciences Union ?? 2005 Author(s). This work is licensed under a Creative Commons License.

Natural Hazards and Earth System Sciences↗

Drainage effects on the transient, near-surface hydrologic response of a steep hillslope to rainfall: Implications for slope stability, Edmonds, Washington, USA

Shallow landslides on steep (>25??) hillsides along Puget Sound have resulted in occasional loss of life and costly damage to property during intense or prolonged rainfall. As part of a larger project to assess landslide hazards in the Seattle area, the U.S. Geological Survey instrumented two coastal bluff sites in 2001 to observe the subsurface hydrologic response to rainfall. The instrumentation at one of these sites, near Edmonds, Washington, consists of two rain gauges, two water-content probes that measure volumetric water content at eight depths between 0.2 and 2.0 m, and two tensiometer nests that measure soil-water suction at six depths ranging from 0.2 to 1.5m. Measurements from these instruments are used to test one- and two-dimensional numerical models of infiltration and groundwater flow. Capillary-rise tests, performed in the laboratory on soil sample from the Edmonds site, are used to define the soil hydraulic properties for the wetting process. The field observations of water content and suction show an apparent effect of porosity variation with depth on the hydraulic response to rainfall. Using a range of physical properties consistent with our laboratory and field measurements, we perform sensitivity analyses to investigate the effects of variation in physical and hydraulic properties of the soil on rainfall infiltration, pore-pressure response, and, hence, slope stability. For a two-layer-system in which the hydraulic conductivity of the upper layer is at least 10 times greater than the conductivity of the lower layer, and the infiltration rate is greater than the conductivity of the lower layer, a perched water table forms above the layer boundary potentially destabilizing the upper layer of soil. Two-dimensional modeling results indicate that the addition of a simple trench drain to the same two-layer slope has differing effects on the hydraulic response depending on the initial pressure head conditions. For slope-parallel flow conditions, pressure head is significantly reduced near the drain; however, for transient, vertical infiltration in a partially saturated soil, conditions consistent with those observed during monitoring at the Edmonds site, the drain decreases the thickness of a perched water table by a small amount.

Natural Hazards and Earth System Sciences↗

Submarine landslides in the Santa Barbara Channel as potential tsunami sources

Recent investigations using the Monterey Bay Aquarium Research Institutes (MBARI) Remotely Operated Vehicles (ROVs) "Ventana" and "Tiburon" and interpretation of MBARI's EM 300 30 kHz multibeam bathymetric data show that the northern flank of the Santa Barbara Basin has experienced massive slope failures. Of particular concern is the large (130 km2) Goleta landslide complex located off Coal Oil Point near the town of Goleta, that measures 14.6-km long extending from a depth of 90 m to nearly 574 m deep and is 10.5 km wide. We estimate that approximately 1.75 km3 has been displaced by this slide during the Holocene. This feature is a complex compound submarine landslide that contains both surfical slump blocks and mud flows in three distinct segments. Each segment is composed of a distinct head scarp, down-dropped head block and a slide debris lobe. The debris lobes exhibit hummocky topography in the central areas that appear to result from compression during down slope movement. The toes of the western and eastern lobes are well defined in the multibeam image, whereas the toe of the central lobe is less distinct. Continuous seismic reflection profiles show that many buried slide debris lobes exist and comparison of the deformed reflectors with ODP Drill Site 149, Hole 893 suggest that at least 200 000 years of failure have occurred in the area (Fisher et al., 2005a). Based on our interpretation of the multibeam bathymetry and seismic reflection profiles we modeled the potential tsunami that may have been produced from one of the three surfical lobes of the Goleta slide. This model shows that a 10 m high wave could have run ashore along the cliffs of the Goleta shoreline. Several other smaller (2 km2 and 4 km2) slides are located on the northern flank of the Santa Barbara Basin, both to the west and east of Goleta slide and on the Concepcion fan along the western flank of the basin. One slide, named the Gaviota slide, is 3.8 km2, 2.6 km long and 1.7 km wide. A distinct narrow scar extends from near the eastern head wall of this slide for over 2 km eastward toward the Goleta slide and may represent either an incipient failure or a remnant of a previous failure. Push cores collected within the main head scar of this slide consisted of hydrogen sulfide bearing mud, possibly suggesting active fluid seepage and a vibra-core penetrated ???50 cm of recent sediment overlying colluvium or landslide debris confirming the age of ???300 years as proposed by Lee et al. (2004). However, no seeps or indications of recent movement were observed during our ROV investigation within this narrow head scar indicating that seafloor in the scar is draped with mud. ?? 2006 Author(s). This work is licensed under a Creative Commons License.

Natural Hazards and Earth System Sciences↗