Bayesian Analysis of the Impact of Rainfall Data Product on Simulated Slope Failure for North Carolina Locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the factor of safety, Fs) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated Fs values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantles properties (hydraulic, geotechnical, and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference truth Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and null periods using multivariate frequency distribution-based metrics such as the false discovery and false omission rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicates their inability to accurately characterize hillslope stability

Strong variation in weathering of layered rock maintains hillslope‐scale strength under high precipitation

The evolution of volcanic landscapes and their landslide potential are both dependent upon the weathering of layered volcanic rock sequences. We characterize critical zone structure using shallow seismic Vp and Vs profiles and vertical exposures of rock across a basaltic climosequence on Kohala peninsula, Hawai’i, and exploit the dramatic gradient in mean annual precipitation (MAP) across the peninsula as a proxy for weathering intensity. Seismic velocity increases rapidly with depth and the velocity–depth gradient is uniform across three sites with 500–600 mm/yr MAP, where the transition to unaltered bedrock occurs at a depth of 4 to 10 m. In contrast, velocity increases with depth less rapidly at wetter sites, but this gradient remains constant across increasing MAP from 1000 to 3000 mm/yr and the transition to unaltered bedrock is near the maximum depth of investigation (15–25 m). In detail, the profiles of seismic velocity and of weathering at wet sites are nowhere monotonic functions of depth. The uniform average velocity gradient and the greater depths of low velocities may be explained by the averaging of velocities over intercalated highly weathered sites with less weathered layers at sites where MAP > 1000 mm/yr. Hence, the main effect of climate is not the progressive deepening of a near‐surface altered layer, but rather the rapid weathering of high permeability zones within rock subjected to precipitation greater than ~1000 mm/yr. Although weathering suggests mechanical weakening, the nearly horizontal orientation of alternating weathered and unweathered horizons with respect to topography also plays a role in the slope stability of these heterogeneous rock masses. We speculate that where steep, rapidly evolving hillslopes exist, the sub‐horizontal orientation of weak/strong horizons allows such sites to remain nearly as strong as their less weathered counterparts at drier sites, as is exemplified by the 50°–60° slopes maintained in the amphitheater canyons on the northwest flank of the island. Copyright © 2017 John Wiley & Sons, Ltd.Seismic velocity profiles across a basalt climosequence in Hawai’i reveal that above a particular precipitation threshold, rapid weathering of high‐permeability layers produces intercalated low‐velocity horizons and dramatically lowers the average seismic velocity of the rock section. However, less permeable layers remain relatively unweathered and thus still contribute significantly to the mechanical competence of the profile, which may explain maintenance of steep‐walled canyons under high precipitation rates. Such observations challenge a top‐down model of progressive weathering (i.e. weakening) of the substrate and therefore suggest that high strength can be maintained even under high precipitation rates, if horizontally layered horizons of different weathering potential exist.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143701/1/esp4290.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143701/2/esp4290_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143701/3/esp4290-sup-0001-SupplementaFiles_FINAL.pd

Application of a process-based shallow landslide hazard model over a broad area in Central Italy

Process-based models are widely used for rainfallinduced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available

Field and Laboratory Hydraulic Characterization of Landslide-Prone Soils in the Oregon Coast Range and Implications for Hydrologic Simulation

Unsaturated zone flow processes are an important focus of landslide hazard estimation. Differences in soil hydraulic behavior between wetting and drying conditions (i.e., hydraulic hysteresis) may be important in landslide triggering. Hydraulic hysteresis can complicate soil hydraulic parameter estimates and impact prediction capability. This investigation focused on hydraulic property estimation for soil in a landslide-prone area where the relative importance of hysteresis is unclear. Laboratory measurements of soil-water retention from field soils in the Oregon Coast Range during wetting and drying show that pronounced hydraulic hysteresis is present. In contrast, a 4-yr field data record of pore-water pressure and soil-water content from multiple soil pits at the same landslide-prone area shows relatively minor hydraulic hysteresis compared with the laboratory estimates. Simulated subsurface hydrologic response parameterized using estimates from field data more closely matched hydrologic observations relative to model parameterization based on laboratory analysis of repacked soil samples. Our results suggest that (i) unsaturated hydraulic parameter estimates based on in situ field data, as opposed to laboratory measurements alone, may lead to more accurate simulation of the hydrologic response to rainfall, (ii) in situ data of soil-water retention may need to include values at both high suctions and near saturation to improve estimates of soil hydraulic parameters for slope failure applications, and (iii) laboratory measurements of soil-water retention made under dynamic conditions may overestimate hydraulic hysteresis

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 Mw7.8 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.ISSN:0169-555xISSN:1872-695