6 research outputs found
Beyond the angle of repose: A review and synthesis of landslide processes in response to rapid uplift, Eel River, Northern California
In mountainous settings, increases in rock uplift are often followed by a commensurate uptick in denudation as rivers incise and steepen hillslopes, making them increasingly prone to landsliding as slope angles approach a limiting value. For decades, the threshold slope model has been invoked to account for landslide-driven increases in sediment flux that limit topographic relief, but the manner by which slope failures organize themselves spatially and temporally in order for erosion to keep pace with rock uplift has not been well documented. Here, we review past work and present new findings from remote sensing, cosmogenic radionuclides, suspended sediment records, and airborne lidar data, to decipher patterns of landslide activity and geomorphic processes related to rapid uplift along the northward-migrating Mendocino Triple Junction in Northern California. From historical air photos and airborne lidar, we estimated the velocity and sediment flux associated with active, slow-moving landslides (or earthflows) in the mĂ©lange- and argillite-dominated Eel River watershed using the downslope displacement of surface markers such as trees and shrubs. Although active landslides that directly convey sediment into the channel network account for only 7% of the landscape surface, their sediment flux amounts to more than 50% of the suspended load recorded at downstream sediment gaging stations. These active slides tend to exhibit seasonal variations in velocity as satellite-based interferometry has demonstrated that rapid acceleration commences within 1 to 2 months of the onset of autumn rainfall events before slower deceleration ensues in the spring and summer months. Curiously, this seasonal velocity pattern does not appear to vary with landslide size, suggesting that complex hydrologicâmechanical feedbacks (rather than 1-D pore pressure diffusion) may govern slide dynamics. A new analysis of 14 yrs of discharge and sediment concentration data for the Eel River indicates that the characteristic mid-winter timing of earthflow acceleration corresponds with increased suspended concentration values, suggesting that the seasonal onset of landslide motion each year may be reflected in the export of sediments to the continental margin. The vast majority of active slides exhibit gullied surfaces and the gully networks, which are also seasonally active, may facilitate sediment export although the proportion of material produced by this pathway is poorly known. Along Kekawaka Creek, a prominent tributary to the Eel River, new analyses of catchment-averaged erosion rates derived from cosmogenic radionuclides reveal rapid erosion (0.76 mm/yr) below a prominent knickpoint and slower erosion (0.29 mm/yr) upstream. Such knickpoints are frequently observed in Eel tributaries and are usually comprised of massive (> 10 m) interlocking resistant boulders that likely persist in the landscape for long periods of time (> 105 yr). Upstream of these knickpoints, active landslides tend to be less frequent and average slope angles are slightly gentler than in downstream areas, which indicates that landslide density and average slope angle appear to increase with erosion rate. Lastly, we synthesize evidence for the role of large, catastrophic landslides in regulating sediment flux and landscape form. The emergence of resistant blocks within the mĂ©lange bedrock has promoted large catastrophic slides that have dammed the Eel River and perhaps generated outburst events in the past. The frequency and impact of these landslide dams likely depend on the spatial and size distributions of resistant blocks relative to the width and drainage area of adjacent valley networks. Overall, our findings demonstrate that landslides within the Eel River catchment do not occur randomly, but instead exhibit spatial and temporal patterns related to baselevel lowering, climate forcing, and lithologic variations. Combined with recent landscape evolution models that incorporate landslides, these results provide predictive capability for estimating erosion rates and managing hazards in mountainous regions
Landslides and Landscape Evolution over Decades to MillenniaâUsing Tephrochronology, Air Photos, Lidar, and Geophysical Investigations to Reconstruct Past Landscapes
Landscapes respond to external perturbations over a variety of timescales, including million-year tectonic forcing, millennial to decadal climate fluctuations, and minutes-long high intensity storms or large magnitude earthquakes. In mountainous regions, understanding the role of landslides in driving the hillslope response to these perturbations is paramount for understanding landscape evolution over geologic timescales and hazards over human timescales. Here I analyze the landslide-driven hillslope response over millennial to decadal timescales using a variety of tools and techniques (e.g. tephrochronology, lidar and air photo analysis, field and subsurface investigations, and seismic refraction) in the Waipaoa Basin (New Zealand) and Oregon Coast Range (USA). For the Waipaoa study catchment, pervasive landslides have been sculpting >99% of the hillslopes in response to >50 m of fluvial incision following the shift to a warmer, wetter climate after the Last Glacial Maximum (LGM) (~18 ka). Then, starting in the late 1800s, European settlement resulted in deforestation and conversion of >90% of the landscape to pasturelandâspurring a rapid increase in landslide-driven erosion. To quantify the landscape response, I first reconstruct LGM and younger paleosurfaces using tephrochronology and lidar-derived surface roughness to estimate the volume, timing, and distribution of hillslope destabilization. From these reconstructions, I calculate the post-LGM catchment-averaged erosion rate (1.6 mm/yr) and determine that the timing of the initial hillslope adjustment was rapid and occurred by ~10 ka. Second, I quantify the rate and volume of historic hillslope degradation using a 1956-2010 sequence of aerial photographs, lidar, and field reconnaissance to map the spatial extent of active landslides, create a âturf indexâ based on the extent and style of pastoral ground disruption, correlate that with downslope velocity, and calculate the average annual sediment flux. From the sediment flux, I calculate an erosion rate over the past ~50 years (~20 mm/yr) that is 10x greater than post-LGM. Lastly, in Western Oregon, I confirm that seismic refraction can determine the size (e.g. depth) and failure style of landslides in western Oregonâdata needed to incorporate these poorly studied landslides into future landscape evolution or hazard models.
This dissertation includes both previously published and unpublished co-authored material
Whereâs the Rock: Using Convolutional Neural Networks to Improve Land Cover Classification
While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock (rock) from soil cover (other). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDAâs 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95 F 1 score. Comparatively, the classical OBIA approach gives only a 0.84 F 1 score. This is an improvement over existing land cover maps, which underestimate rock by almost 90%. The resulting CNN approach is likely scalable but dependent on high-quality imagery and high-performance algorithms using representative training sets informed by expert mapping. As image quality and quantity continue to increase globally, machine learning models that incorporate high-quality training data informed by geologic, topographic, or other topical maps may be applied to more effectively identify exposed rock in large image collections
Smoothed lidar-derived bare-earth DEM and gradient geotiffs, Little Lake, OR, USA
<p>Digital elevation model (e11.tif) and gradient (g11.tif) geotiffs
generated from clipped, smoothed bare earth lidar data collected by NCALM as
part of a seed grant to C. Cerovksi-Darriau.  The original data can
be found on the Open Topography website (see DOI in the reference link).</p>
<p>For 3D interactive viewing of the DEM at high
resolution, we suggest downloading the free QTReader. </p>
<p>The lidar data required smoothing
of the 1 m x 1 m gridded bare earth data set. Noise in the bare earth data
arises from two sources: (1) errors in point classification and (2) natural
topographic roughness associated with tree throw pit and mounds, animal mounds,
sediment piles, and large woody debris jams. In the Oregon Coast Range the
topographic signature of pit and mound features from tree turnover dominates at
length scales <7.5 m [Roering et al.,2010]. Thus, we smoothed the topography
with a 2-D, second-order polynomial applied to a 10 m x 10 m moving window
[Wood, 1996].</p>
<p>Data projection is NAD1983/UTM Zone 10.</p><p><br></p>
<p>Roering, J.J., Marshall,
J., Booth, A.M., Mort, M. and Jin, Q., 2010. Evidence for biotic controls on
topography and soil production. <i>Earth and Planetary Science Letters</i>, <i>298</i>(1),
pp.183-190.</p>
<p>Wood, J. (1996), The
geomorphological characterisation of digital elevation models, PhD
dissertation, Univ. of Leicester, U. K.</p>
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Dust on a Hawaiian volcano: A regional model using field measurements to estimate transport and deposition
The western slopes of Hawaii's Mauna Kea volcano are mantled by fineâgrained soils, the record of volcanic airfall and eolian deposition. Where exposed, strong winds transport this sediment across West Hawaii, affecting tourism and local communities with decreased air and water quality. Operations on US Army's Ke'amuku Maneuver Area (KMA) have the potential to increase dust flux from these deposits. The USGS established 18 ground monitoring sites and sampling locations surrounding KMA. For over 3âyears, each station measured vertical and horizontal dust flux, while coâlocated anemometers measured wind speed and direction. We used these datasets to develop a parsimonious regional model for dust supply and transport to assess whether KMA is a net dust sink or source.
We found that dust transport is most highly correlated with threshold wind speeds of 8âm/s. We used this value as the regional average threshold wind speed for dust entrainment. Using a model that partitions measured horizontal dust flux into inwardâ and outwardâdirected components, we estimate that KMA is currently a net dust sink. Geochemical analysis of dust samples illustrates that local organics and carbonate make up 64% of dust mass, the remainder being volcanic silt and fine sand. Measured vertical dust deposition rates of 0.006âmm/yr are similar to 0.004âmm/yr of deposition predicted from taking the divergence of dust across KMA's boundary. These rates are low compared with preâhistoric rates of ~0.2â0.3âmm/yr, from radiocarbon dating of buried soils.
KMA's soils record persistent deposition over millennia, at rates that imply episodic dust storms. Such events created a soilâmantled landscape in the middle of a largely Pleistocene rocky landscape. A substantial portion of fineâgrained soils in other leeward Hawaiian Island landscapes may have formed from similar eolian deposition, and not direct weathering of parent rock. Published 2018. This article is a U.S. Government work and is in the public domain in the USA