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The topographic signature of a mountain belt depends on the interplay of tectonic, climatic and erosional processes, whose relative importance changes over times, while quantifying these processes and their rates at specific times remains a challenge. The eastern Andes of central Bolivia offer a natural laboratory in which such interplay has been debated. Here, we investigate the Rio Grande catchment which crosses orthogonally the eastern Andes orogen from the Eastern Cordillera into the Subandean Zone, exhibiting a catchment relief of up to 5000 m. Despite an enhanced tectonic activity in the Subandes, local relief, mean and modal slopes and channel steepness indices are largely similar compared to the Eastern Cordillera and the intervening Interandean Zone. Nevertheless, a dataset of 57 new cosmogenic 10Be and 26AI catchment wide denudation rates from the Rio Grande catchment reveals up to one order of magnitude higher denudation rates in the Subandean Zone (mean 0.8 mm/yr) compared to the upstream physiographic regions. We infer that tectonic activity in the thrusting dominated Subandean belt causes higher denudation rates based on cumulative rock uplift investigations and due to the absence of a pronounced climate gradient. Furthermore, the lower rock strength of the Subandean sedimentary units correlates with mean slopes similar to the ones of the Eastern Cordillera and Interandean Zone, highlighting the fact, that lithology and rock strength can control high denudation rates at low slopes.
Low denudation rates measured at the outlet of the Rio Grande catchment (Abapo) are interpreted to be a result of a biased cosmogenic nuclide mixing that is dominated by headwater signals from the Eastern Cordillera and the Interandean zone and limited catchment sediment connectivity in the lower river reaches. Therefore, comparisons of short- (i.e., sediment yield) and millennial denudation rates require caution when postulating tectonic and/or climatic forcing without detailed studies. (C) 2015 The Authors. Published by Elsevier B.V.
Earthquakes impart an impressive force on epicentral landscapes, with immediate catastrophic hillslope response. However, their legacy on geomorphic process rates remains poorly constrained. We have determined the evolution of landslide rates in the epicentral areas of four intermediate to large earthquakes (M-w, 6.6-7.6). In each area, landsliding correlates with the cumulative precipitation during a given interval. Normalizing for this meteorological forcing, landslide rates have been found to peak after an earthquake and decay to background values in 1-4 yr, with the decay time scale probably proportional to the earthquake magnitude. The transient pulse of landsliding is not related to external forcing such as rainfall or aftershocks, and we tentatively attribute it to the reduction and subsequent recovery of ground strength. Observed geomorphic trends are not linked with groundwater level changes or root system damage, both of which could affect substrate strength. We propose that they are caused by reversible damage of rock mass and/or loosening of regolith. Qualitative accounts of ground cracking due to strong ground motion abound, and our observations are circumstantial evidence of its potential importance in setting landscape sensitivity to meteorological forcing after large earthquakes.
Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area-frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area-frequency distribution, resulting from amalgamation, may be up to 200 and 50 %, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m(2), tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7-3.6% incorrectly amalgamated landslides missed and 3.9-4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
Large, compressional earthquakes cause surface uplift aswell as widespread mass wasting. Knowledge of their trade-off is fragmentary. Combining a seismologically consistent model of earthquake-triggered landsliding and an analytical solution of coseismic surface displacement, we assess how the mass balance of single earthquakes and earthquake sequences depends on fault size and other geophysical parameters. We find that intermediate size earthquakes (M-w 6-7.3) may cause more erosion than uplift, controlled primarily by seismic source depth and landscape steepness, and less so by fault dip and rake. Such earthquakes can limit topographic growth, but our model indicates that both smaller and larger earthquakes (M-w < 6, M-w > 7.3) systematically cause mountain building. Earthquake sequences with a Gutenberg-Richter distribution have a greater tendency to lead to predominant erosion, than repeating earthquakes of the same magnitude, unless a fault can produce earthquakes with M-w > 8 or more.
Earthquakes deform Earth's surface, building long-lasting topographic features and contributing to landscape and mountain formation.
However, seismic waves produced by earthquakes may also destabilize hillslopes, leading to large amounts of soil and bedrock moving downslope. Moreover, static deformation and shaking are suspected to damage the surface bedrock and therefore alter its future properties, affecting hydrological and erosional dynamics. Thus, earthquakes participate both in mountain building and stimulate directly or indirectly their erosion. Moreover, the impact of earthquakes on hillslopes has important implications for the amount of sediment and organic matter delivered to rivers, and ultimately to oceans, during episodic catastrophic seismic crises, the magnitude of life and property losses associated with landsliding, the perturbation and recovery of landscape properties after shaking, and the long term topographic evolution of mountain belts. Several of these aspects have been addressed recently through individual case studies but additional data compilation as well as theoretical or numerical modelling are required to tackle these issues in a more systematic and rigorous manner.
This dissertation combines data compilation of earthquake characteristics, landslide mapping, and seismological data interpretation with physically-based modeling in order to address how earthquakes impact on erosional processes and landscape evolution. Over short time scales (10-100 s) and intermediate length scales (10 km), I have attempted to improve our understanding and ability to predict the amount of landslide debris triggered by seismic shaking in epicentral areas. Over long time scales (1-100 ky) and across a mountain belt (100 km) I have modeled the competition between erosional unloading and building of topography associated with earthquakes. Finally, over intermediate time scales (1-10 y) and at the hillslope scale (0.1-1 km) I have collected geomorphological and seismological data that highlight persistent effects of earthquakes on landscape properties and behaviour.
First, I compiled a database on earthquakes that produced significant landsliding, including an estimate of the total landslide volume and area, and earthquake characteristics such as seismic moment and source depth. A key issue is the accurate conversion of landslide maps into volume estimates. Therefore I also estimated how amalgamation - when mapping errors lead to the bundling of multiple landslide into a single polygon - affects volume estimates from various earthquake-induced landslide inventories and developed an algorithm to automatically detect this artifact. The database was used to test a physically-based prediction of the total landslide area and volume caused by earthquakes, based on seismological scaling relationships and a statistical description of the landscape properties. The model outperforms empirical fits in accuracy, with 25 out of 40 cases well predicted, and allows interpretation of many outliers in physical terms. Apart from seismological complexities neglected by the model I found that exceptional rock strength properties or antecedent conditions may explain most outliers.
Second, I assessed the geomorphic effects of large earthquakes on landscape dynamics by surveying the temporal evolution of precipitation-normalized landslide rate. I found strongly elevated landslide rates following earthquakes that progressively recover over 1 to 4 years, indicating that regolith strength drops and recovers. The relaxation is clearly non-linear for at least one case, and does not seem to correlate with coseismic landslide reactivation, water table level increase or tree root-system recovery. I suggested that shallow bedrock is damaged by the earthquake and then heals on annual timescales. Such variations in ground strength must be translated into shallow subsurface seismic velocities that are increasingly surveyed with ambient seismic noise correlations. With seismic noise autocorrelation I computed the seismic velocity in the epicentral areas of three earthquakes where I constrained a change in landslide rate. We found similar recovery dynamics and timescales, suggesting that seismic noise correlation techniques could be further developed to meaningfully assess ground strength variations for landscape dynamics. These two measurements are also in good agreement with the temporal dynamics of post-seismic surface displacement measured by GPS. This correlation suggests that the surface healing mechanism may be driven by tectonic deformation, and that the surface regolith and fractured bedrock may behave as a granular media that slowly compacts as it is sheared or vibrated.
Last, I compared our model of earthquake-induced landsliding with a standard formulation of surface deformation caused by earthquakes to understand which parameters govern the competition between the building and destruction of topography caused by earthquakes. In contrast with previous studies I found that very large (Mw>8) earthquakes always increase the average topography, whereas only intermediate (Mw ~ 7) earthquakes in steep landscapes may reduce topography. Moreover, I illustrated how the net effect of earthquakes varies with depth or landscape steepness implying a complex and ambivalent role through the life of a mountain belt. Further I showed that faults producing a Gutenberg-Richter distribution of earthquake sizes, will limit topography over a larger range of fault sizes than faults producing repeated earthquakes with a characteristic size.
We present a new, seismologically consistent expression for the total area and volume of populations of earthquake-triggered landslides. This model builds on a set of scaling relationships between key parameters, such as landslide spatial density, seismic ground acceleration, fault length, earthquake source depth, and seismic moment. To assess the model we have assembled and normalized a catalog of landslide inventories for 40 shallow, continental earthquakes. Low landscape steepness causes systematic overprediction of the total area and volume of landslides. When this effect is accounted for, the model predicts the total landslide volume of 63% of 40 cases to within a factor 2 of the volume estimated from observations (R-2 = 0.76). The prediction of total landslide area is also sensitive to the landscape steepness, but less so than the total volume, and it appears to be sensitive to controls on the landslide size-frequency distribution, and possibly the shaking duration. Some outliers are likely associated with exceptionally strong rock mass in the epicentral area, while others may be related to seismic source complexities ignored by the model. However, the close match between prediction and estimate for about two thirds of cases in our database suggests that rock mass strength is similar in many cases and that our simple seismic model is often adequate, despite the variety of lithologies and tectonic settings covered. This makes our expression suitable for integration into landscape evolution models and application to the anticipation or rapid assessment of secondary hazards associated with earthquakes.
Bedrock landslides, by excavating deep below saprolite-rock interfaces, create conditions for weathering in which all mineral phases in a lithology are initially unweathered within landslide deposits. As a result, the most labile phases dominate the weathering immediately after mobilisation and during a transient period of depletion. This mode of dissolution can strongly alter the overall output of solutes from catchments and their contribution to global chemical cycles if landslide-derived material is retained in catchments for extended periods after mass wasting.
A link between chemical weathering and physical erosion exists at the catchment scale over a wide range of erosion rates(1,2). However, in mountain environments, where erosion rates are highest, weathering may be kinetically limited(3-5) and therefore decoupled from erosion. In active mountain belts, erosion is driven by bedrock landsliding(6) at rates that depend strongly on the occurrence of extreme rainfall or seismicity(7). Although landslides affect only a small proportion of the landscape, bedrock landsliding can promote the collection and slow percolation of surface runoff in highly fragmented rock debris and create favourable conditions for weathering. Here we show from analysis of surface water chemistry in the Southern Alps of New Zealand that weathering in bedrock landslides controls the variability in solute load of these mountain rivers. We find that systematic patterns in surface water chemistry are strongly associated with landslide occurrence at scales from a single hillslope to an entire mountain belt, and that landslides boost weathering rates and river solute loads over decades. We conclude that landslides couple erosion and weathering in fast-eroding uplands and, thus, mountain weathering is a stochastic process that is sensitive to climatic and tectonic controls on mass wasting processes.
Presentation and Analysis of a Worldwide Database of Earthquake-Induced Landslide Inventories
(2017)
Earthquake-induced landslide (EQIL) inventories are essential tools to extend our knowledge of the relationship between earthquakes and the landslides they can trigger. Regrettably, such inventories are difficult to generate and therefore scarce, and the available ones differ in terms of their quality and level of completeness. Moreover, access to existing EQIL inventories is currently difficult because there is no centralized database. To address these issues, we compiled EQIL inventories from around the globe based on an extensive literature study. The database contains information on 363 landslide-triggering earthquakes and includes 66 digital landslide inventories. To make these data openly available, we created a repository to host the digital inventories that we have permission to redistribute through the U.S. Geological Survey ScienceBase platform. It can grow over time as more authors contribute their inventories. We analyze the distribution of EQIL events by time period and location, more specifically breaking down the distribution by continent, country, and mountain region. Additionally, we analyze frequency distributions of EQIL characteristics, such as the approximate area affected by landslides, total number of landslides, maximum distance from fault rupture zone, and distance from epicenter when the fault plane location is unknown. For the available digital EQIL inventories, we examine the underlying characteristics of landslide size, topographic slope, roughness, local relief, distance to streams, peak ground acceleration, peak ground velocity, and Modified Mercalli Intensity. Also, we present an evaluation system to help users assess the suitability of the available inventories for different types of EQIL studies and model development.
Prediction of the area affected by earthquake-induced landsliding based on seismological parameters
(2017)
We present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95% of the total landslide area. Without any empirical calibration the model explains 56% of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor of 2, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95% of the total landslide area. Aspects ignored by the model that could explain the residuals include local variations of the threshold of acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop, and rupture directivity. Nevertheless, its simplicity and first-order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines.