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Sean F. Gallen

Publications and source records attributed to Sean F. Gallen.

4 recordsLinked to original sources

Cascading land surface hazards as a nexus in the Earth system

Earth’s surface is sculpted by numerous processes that move sediment, ranging from gradual and benign to abrupt and catastrophic. Although infrequent, high-magnitude sediment mobilization events can be hazardous to people and infrastructure, leaving topographic imprints on the landscape and remarkable narratives in the historical record. Hazardous events such as fires, storms, and earthquakes accelerate erosion and sediment transport, increasing landscape sensitivity to subsequent perturbations, thus forming a cascading hazard. Although the redistribution of sediment across Earth’s landscape can result in higher risks to vulnerable populations, cascading processes are commonly unaccounted for in hazard assessments. Cascading hazards can occur almost immediately after triggering events, such as coseismic landslides, or over months, years, or even decades after an initial perturbation, such as debris flows after wildfires or flooding in channels alluviated by volcanic debris. Sediment cascades span Earth’s surface, from mountaintops to river valleys, where erosion, deposition, and aggradation can lead to a myriad of hazardous processes, including decreased river conveyance capacity, which increases the likelihood of downstream flooding. An improved understanding of the magnitude, frequency, and persistence of cascading hazards is critical given the rapid changes in the frequency and severity of storms, fires, sea-level change, and cryospheric melting, as well as the expansion of high-population-density urban footprints in regions susceptible to solid Earth hazards. Understanding the full consequences and underlying physics of Earth’s cascading land surface hazards can help minimize future human and economic losses.

California↗

The size, distribution, and mobility of landslides caused by the 2015 Mw7.8 Gorkha earthquake, Nepal

Coseismic landslides pose immediate and prolonged hazards to mountainous communities, and provide a rare opportunity to study the effect of large earthquakes on erosion and sediment budgets. By mapping landslides using high-resolution satellite imagery, we find that the 25 April 2015 M w 7.8 Gorkha earthquake and aftershock sequence produced at least 25,000 landslides throughout the steep Himalayan Mountains in central Nepal. Despite early reports claiming lower than expected landslide activity, our results show that the total number, area, and volume of landslides associated with the Gorkha event are consistent with expectations, when compared to prior landslide-triggering earthquakes around the world. The extent of landsliding mimics the extent of fault rupture along the east-west trace of the Main Himalayan Thrust and increases eastward following the progression of rupture. In this event, maximum modeled Peak Ground Acceleration (PGA) and the steepest topographic slopes of the High Himalaya are not spatially coincident, so it is not surprising that landslide density correlates neither with PGA nor steepest slopes on their own. Instead, we find that the highest landslide density is located at the confluence of steep slopes, high mean annual precipitation, and proximity to the deepest part of the fault rupture from which 0.5–2 Hz seismic energy originated. We suggest that landslide density was determined by a combination of earthquake source characteristics, slope distributions, and the influence of precipitation on rock strength via weathering and changes in vegetation cover. Determining the relative contribution of each factor will require further modeling and better constrained seismic parameters, both of which are likely to be developed in the coming few years as post-event studies evolve. Landslide mobility, in terms of the ratio of runout distance to fall height, is comparable to small volume landslides in other settings, and landslide volume-runout scaling is consistent with compilations of data on larger slope failures. In general, the size ratios of landslide source area to full landslide area are smaller than global averages, and hillslope length seems to largely control runout distance, which we propose reflects a topographic control on landslide mobility in this setting. We find that landslide size dictates runout distance and that more than half of the landslide debris was deposited in direct connection with stream channels. Connectivity, which is defined as the spatial proximity of landslides to fluvial channels, is greatest for larger landslides in the high-relief part of the High Himalaya. Although these failures are less abundant than those at lower elevations, they may have a disproportionate impact on sediment dynamics and cascading hazards, such as landslide reactivation by monsoon rainfall and landslide dams that lead to outburst floods. The overall high fluvial connectivity of coseismic landsliding in the Gorkha event suggests coupling between the earthquake cycle and sediment/geochemical budgets of fluvial systems in the Himalaya.

Geomorphology↗

Application and evaluation of a rapid response earthquake-triggered landslide model to the 25 April 2015 Mw 7.8 Gorkha earthquake, Nepal

The 25 April 2015 M w 7.8 Gorkha earthquake produced strong ground motions across an approximately 250 km by 100 km swath in central Nepal. To assist disaster response activities, we modified an existing earthquake-triggered landslide model based on a Newmark sliding block analysis to estimate the extent and intensity of landsliding and landslide dam hazard. Landslide hazard maps were produced using Shuttle Radar Topography Mission (SRTM) digital topography, peak ground acceleration (PGA) information from the U.S. Geological Survey (USGS) ShakeMap program, and assumptions about the regional rock strength based on end-member values from previous studies. The instrumental record of seismicity in Nepal is poor, so PGA estimates were based on empirical Ground Motion Prediction Equations (GMPEs) constrained by teleseismic data and felt reports. We demonstrate a non-linear dependence of modeled landsliding on aggregate rock strength, where the number of landslides decreases exponentially with increasing rock strength. Model estimates are less sensitive to PGA at steep slopes (> 60°) compared to moderate slopes (30–60°). We compare forward model results to an inventory of landslides triggered by the Gorkha earthquake. We show that moderate rock strength inputs over estimate landsliding in regions beyond the main slip patch, which may in part be related to poorly constrained PGA estimates for this event at far distances from the source area. Directly above the main slip patch, however, the moderate strength model accurately estimates the total number of landslides within the resolution of the model (landslides ≥ 0.0162 km 2 ; observed n = 2214, modeled n = 2987), but the pattern of landsliding differs from observations. This discrepancy is likely due to the unaccounted for effects of variable material strength and local topographic amplification of strong ground motion, as well as other simplifying assumptions about source characteristics and their relationship to landsliding.

Tectonophysics↗

Coseismic landslides reveal near-surface rock strength in a high-relief tectonically active setting

We present quantitative estimates of near-surface rock strength relevant to landscape evolution and landslide hazard assessment for 15 geologic map units of the Longmen Shan, China. Strength estimates are derived from a novel method that inverts earthquake peak ground acceleration models and coseismic landslide inventories to obtain material proper- ties and landslide thickness. Aggregate rock strength is determined by prescribing a friction angle of 30° and solving for effective cohesion. Effective cohesion ranges are from 70 kPa to 107 kPa for 15 geologic map units, and are approximately an order of magnitude less than typical laboratory measurements, probably because laboratory tests on hand-sized specimens do not incorporate the effects of heterogeneity and fracturing that likely control near-surface strength at the hillslope scale. We find that strength among the geologic map units studied varies by less than a factor of two. However, increased weakening of units with proximity to the range front, where precipitation and active fault density are the greatest, suggests that cli- matic and tectonic factors overwhelm lithologic differences in rock strength in this high-relief tectonically active setting.

Geology↗