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Tectonic control on landsliding revealed by the 2015 Gorkha earthquake

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Tectonic control on landsliding revealed by the 2015 Gorkha earthquake

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Content TECTONIC CONTROL ON LANDSLIDING REVEALED BY THE 2015 GORKHA
EARTHQUAKE

by

Paul Joseph Maffei Quackenbush
___________________________________________________________

A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(Geological Sciences)
August 2018

Copyright 2018 Paul Quackenbush

1

ACKNOWLEDGMENTS

Thank you to my collaborators on this project: A. Joshua West, Marin K. Clark,
Dimitrios Zekkos, Gen Li, Deepak Chamlagain, and Maxwell P. Dahlquist. This work benefitted
from discussions with William Medwedeff, Kendra Murray, and Nathan Niemi at the University
of Michigan, as well as Malcolm White and Trina Gregory at the University of Southern
California. Thank you to Amanda Carey for sample preparation and helium measurements. I
would also like to thank Raju Kunwar, Bibek Giri, Nirmal Raila, Laxman Subedhi, and Logan
Knopper for their contributions to fieldwork in Nepal.
I wish to express my gratitude to my advisor, Josh West, for his support and guidance
during my time at USC, as well as for his support in helping me to pursue my future life
directions. I have learned a lot from Josh these past two years. On a personal note, I wish to
thank Audrey Martino and my family for being a grounding force and source of joy in my life
and for taking my evening calls despite the three-hour time difference. Thank you also to my
fellow students at USC for their camaraderie and support, and to the staff and faculty in the Earth
Sciences Department for their assistance.
Finally, I would like to acknowledge and thank my Thesis Committee, Josh West, James
Dolan, and David Okaya for their support in completing the Master’s. Funding for this project
was provided by National Science Foundation awards 1546630 and 1640894.

2
TABLE OF CONTENTS

ACKNOWLEGEMENTS ............................................................................................................................. 1
LIST OF TABLES ........................................................................................................................................ 3
LIST OF FIGURES ...................................................................................................................................... 4
ABSTRACT .................................................................................................................................................. 5
INTRODUCTION ........................................................................................................................................ 5
SETTING ..................................................................................................................................................... 8
METHODS AND DATA SOURCES........................................................................................................... 9
RESULTS ................................................................................................................................................... 18
DISCUSSION ............................................................................................................................................. 22
CONCLUSIONS......................................................................................................................................... 25
REFERENCES CITED ............................................................................................................................... 26

3
LIST OF TABLES

TABLE 1: Sample locations and mean (U-Th)/He ages in apatite and zircon ........................................... 45
SUPPLEMENTARY TABLE 1: Single-grain (U-Th-Sm)/He apatite analyses ........................................ 46
SUPPLEMENTARY TABLE 2: Single-grain (U-Th)/He zircon analyses ................................................ 51

4
LIST OF FIGURES

FIGURE 1: Sample locations in the Melamchi Valley ............................................................................... 34
FIGURE 2: Catchment mean (U-Th)/He ages ............................................................................................ 35
FIGURE 3: South-north swath profile of the Melamchi Valley ................................................................. 36
FIGURE 4: Topographic metrics and landsliding ................................................................................. 37
FIGURE 5: Normalized channel steepness and landsliding ....................................................................... 38
FIGURE 6: Normalized channel steepness, slope, and percent failure ...................................................... 39
SUPPLEMENTARY FIGURE 1: Location of the Melamchi Valley in the context of regional lithology
and peak ground acceleration in the Gorkha earthquake ............................................................................ 40

SUPPLEMENTARY FIGURE 2: Catchment landslide density and slope for valleys in the landslide-
affected region ........................................................................................................................................... 41
SUPPLEMENTARY FIGURE 3: Catchment landslide density and normalized channel steepness for
valleys in the landslide-affected region ...................................................................................................... 42
SUPPLEMENTARY FIGURE 4: Average apatite-helium and zircon-helium ages for detrital and bedrock
samples from the Melamchi Valley ............................................................................................................ 43
SUPPLEMENTARY FIGURE 5: Apatite (U-Th)/He age-elevation relationships for bedrock elevation
transect ........................................................................................................................................................ 44

5
ABSTRACT
Landslides are a primary erosional agent in active orogens and a key natural hazard in
mountainous parts of the world. The threshold hillslope concept describes the role of landslides
in landscape development: in response to tectonic uplift, rivers cut downward, steepening slope
angles until they eventually reach a threshold, beyond which erosion rates increase via
landsliding. Many slopes near the threshold angle remain stable until perturbed, often by heavy
rainfall or earthquakes. Earthquakes trigger large numbers of landslides in a single event,
generating “cascading hazards” as well as feedbacks between seismicity and erosion. While
multi-decadal landslide distributions fit predictions of the threshold hillslope model, similar
evidence has not been observed for landslides triggered by a major earthquake. Here, we
investigate the distribution of landslides triggered by the 2015 Gorkha Earthquake, in relation to
metrics describing landscape steepness and new (U-Th)/He thermochronometric data.
Susceptibility to landslide failure in the event increased with proximity to channels of higher
normalized channel steepness and was correlated with younger thermochronometric ages,
consistent with a threshold slope control on earthquake-triggered landsliding and suggesting that
fluvial response to tectonics may help inform landslide hazard prediction.

INTRODUCTION
The threshold hillslope model describes the evolution of landscapes based on the erosive
power of rivers, which allows them to cut vertically into bedrock at a rate that maintains long-
term equilibrium between incision and rock uplift (Burbank et al., 1996). As valleys cut deeper,
surrounding hillslopes steepen, facilitating downslope transport of regolith (Roering et al., 1999)
until slopes eventually reach a threshold angle associated with landslide failure (Burbank et al.,

6
1996; Montgomery and Brandon, 2002). This threshold is reflected in the clustering of hillslope
angles in mountainous terrain around a central value determined by material strength (Strahler,
1950; Burbank et al., 1996; Schmidt and Montgomery, 1995; Montgomery, 2001). Once slopes
reach a threshold angle, hillslopes no longer record increases in erosion rate (Binnie et al., 2007;
DiBiase et al., 2010), but river channels continue to steepen and gain stream power, allowing
them to incise more rapidly and transport a larger volume of material downstream (Ouimet et al.,
2009), thus keeping pace with uplift.
Bedrock landslides act as the crucial connection between steepening rivers and erosion of
surrounding hillslopes. Correlations of landslide erosion with long-term exhumation rates
(Larsen and Montgomery, 2012), and with rock uplift rates inferred from indices of channel
steepness (Gallen et al., 2011; Bennett et al., 2016), suggest effective coupling between uplift,
incision, and landsliding, but the mechanisms and timescales of this coupling remain largely
unknown. In particular, most landsliding is thought to be triggered in large events, such as
earthquakes and storms (Densmore and Hovius, 2000). In many tectonically active regions,
estimates of seismically induced landslide denudation rates over multiple earthquake cycles are
similar to sediment fluxes (Keefer, 1994) and rates of landscape denudation measured by
cosmogenic nuclides and low-temperature thermochronometry (Li et al., 2017). If earthquake-
triggered landsliding is a dominant mechanism of hillslope erosion, then the occurrence of
coseismic landslides should be set by bedrock uplift and channel incision, at least if the threshold
hillslope model accurately describes landscape evolution – yet identifying a threshold slope
control on earthquake-triggered landsliding has proven to be elusive.
For many earthquakes, peak ground acceleration (PGA) is a primary predictor of
coseismic landsliding (Meunier et al., 2007; Li et al., 2017), although other factors, including

7
rock strength and topography, play a role (Gallen et al., 2015; Marc et al., 2016). Models of
slope stability, such as the Newmark model (Newmark, 1965; Jibson, 2007), combine estimates
of rock strength, landslide thickness, and slope geometry to evaluate whether peak ground
acceleration produces a finite displacement that exceeds a threshold value for failure at a given
point on a landscape (Wieczorek et al., 1985; Godt et al., 2007). Application of these models to
earthquake-preparedness and rapid post-earthquake response efforts (Allstadt et al., 2013; Gallen
et al., 2016) is motivated by the significant contribution of landslides to seismic hazard (Marano
et al., 2010; Petley, 2012). Whereas these models consider the role of slope angle, they do not
capture the links to uplift and incision, nor the prediction from the threshold slope model that
landsliding should increase with faster incision even when slope angles reach threshold values.
The Mw = 7.8 Gorkha earthquake, occurring on April 25
th
, 2015 in central Nepal, triggered
more than 25,000 landslides and provides a rare opportunity to gain new understanding of
earthquake-triggered landsliding. In other events, active seismogenic faulting and associated
ground shaking intensity have often been spatially coincident with the highest density of
earthquake-triggered landsliding, making it difficult to isolate the relationships between
landsliding, topography, and tectonics, a challenge further complicated by rock weakening due to
focused precipitation and active faulting (Gallen et al., 2015). Along the north-south river valleys
in central Nepal, however, dramatic gradients in topography, exhumation rate, and landsliding
were not coincident with major gradients in shaking during the Gorkha event (Martha et al.,
2017; Roback et al., 2017), offering a window into the role played by tectono-topographic rather
than seismic factors.
In this study, we focus on one river valley, the Melamchi Valley, to investigate controls on
coseismic landsliding by comparing a published landslide inventory for the Gorkha event

8
(Roback et al., 2017) with DEM-derived topographic and channel metrics, and spatial trends in
long-term exhumation as measured by (U-Th)/He thermochronology. We expand on the results
from this valley to explore how the overall distribution of landslides from the Gorkha earthquake
fits into the long-term evolution of the Nepal Himalaya, in the context of the threshold hillslope
model.

SETTING
The MW = 7.8 Gorkha event occurred on April 25
th
, 2015 and ruptured a ~140-km-long, east-
west segment of the Main Himalayan Thrust (MHT). The Melamchi Valley (Fig. 1) is located in
the central Nepal Himalaya towards the center of the landslide-affected region, approximately 75
km east of the Gorkha earthquake mainshock epicenter and 50 km west of the largest aftershock
(Supplementary Fig. 1), which occurred on May 12
th
, 2015. The topography of the Melamchi
Valley changes distinctly in local relief and elevation at latitude ~27.75 °N, marking what is
known as the physiographic transition 2 (PT 2) between the Himalayan foothills and the High
Himalaya (Harrison and Grove, 1998; Hodges et al., 2001). PT 2 is typically defined by a sharp
northward increase in thermochronometric-derived exhumation rates,
10
Be-derived denduation
rates, and normalized channel steepness (Wobus et al., 2003, 2006; Godard et al., 2014).
The lithology of the Melamchi Valley consists of High Himalayan Crystalline Series rocks,
dominated by Proterozoic gneisses, schists, quartzites, and migmatites (Dhital, 2015;
Supplementary Fig. 1). Metamorphic grade increases from south to north (Dhital, 2015), but
unlike many other Himalayan valleys, a major change in lithology does not coincide with the
physiographic transition, due to the position of the Kathmandu Nappe. The Melamchi Valley
thus provides an opportunity to study interactions between earthquake-triggered landsliding,

9
topography, and tectonics, while minimizing the additional imprint from changes in lithology
that coincide with topography elsewhere in the Himalaya.
Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS)
data suggest that the Gorkha event and aftershock sequence uplifted the foothills south of PT 2
and downdropped the High Himalaya to the north (Lindsey et al., 2015) . Estimates of PGA for
the Gorkha event suggest that the Melamchi Valley did not experience major gradients in ground
shaking (Supplementary Figure 2), helping to isolate the tectono-topographic role in landsliding.

METHODS AND DATA SOURCES
Landslide inventory
We utilized a published Gorkha landslide inventory (Roback et al., 2017), which includes
24,915 mapped landslides from the main event and aftershock sequence. A vector digital data set
of mapped landslides is publicly available for download via a USGS data release:
https://doi.org/10.5066/F7DZ06F9. Roback et al. (2017) mapped landslides manually by
comparing pre- and post-event high-resolution satellite photographs, with a spatial resolution of
20-50 cm in most areas. Acquisition dates of post-event imagery used to map the landslides
ranged from April 26
th
to June 15
th
, 2015, with most images collected between May 2
nd
and May
8
th
, 2015. The landslide inventory includes both source (landslide scar) and full (landslide scar
and deposit) areas for nearly all landslides in the inventory, permitting analysis of the factors
influencing landslide initiation and susceptibility (source areas), as well as the contribution of
landsliding to denudational fluxes (full areas).

10
Topographic analysis
We used SRTM30 digital elevation model (DEM) data for topographic analysis (Farr et
al., 2007). This dataset is incomplete for the eastern edge of the landslide-affected region, so
voids were patched using ASTER GDEM data with 30m spatial resolution (Abrams, 2000). We
utilized these digital elevation data along with standard algorithms in the ArcGIS platform to
generate rasters of the study area for slope and relief, with the latter defined as the range of
elevation over a 500m circular window. To examine the spatial distribution of landslides in the
Melamchi Valley, tributary catchments of the Melamchi River were delineated by flow routing
using the hydrological routines in ArcGIS. We used the size of the smallest tributary catchment
sampled for detrital thermochronology (1.16 km
2
) as the minimum size for tributary catchment
delineation. Using the Zonal Statistics tool in the ArcGIS platform, we calculated mean
topographic metrics for each catchment including mean slope, mean normalized channel
steepness (ksn), and mean relief. We calculated landslide density (m
2
/km
2
) for each tributary
catchment by dividing the sum of mapped landslide full areas within the catchment by the area of
the catchment as calculated in ArcGIS. Swath profiles (Fig. 3) of average slope, average
normalized channel steepness, and average elevation were extracted along a latitudinal transect
for the Melamchi Valley in ArcGIS after applying an averaging rectangular moving window
with a height of 50 DEM cells and a width greater than the maximum width of the valley.
Landslide density for swath profiles was computed in m
2
/km
2
for rectangles with a height of 50
DEM calls and a width equal to the width of the valley. An averaging rectangular moving
window with a height of 200 DEM cells was then applied before landslide density values were
extracted along a latitudinal transect.

11
To analyze topographic metrics for small catchments across the landslide-affected region
beyond the Melamchi Valley (Supplementary Figs. 3, 4), we automated catchment delineation
using TopoToolbox, a MATLAB program for the analysis of digital elevation models
(Schwanghart and Scherler, 2014). We defined the threshold for fluvial channels at an
accumulation area of 0.48 km
2
following previous studies in this area (Roback et al., 2017) and
used the Modify function in TopoToolbox to remove all channels of Strahler stream order four or
greater. We then automated catchment delineation using the remaining stream network and the
Drainagebasins function in TopoToolbox. This action resulted in the delineation of all
catchments in the landslide-affected area containing streams of Strahler stream order 3 or less.
To exclude any small catchment artifacts associated with the automated catchment delineation
process, we defined a threshold catchment area of 1.5 km
2
or greater and excluded catchments
smaller than this value in our catchment analysis for the landslide-affected region. We calculated
catchment mean topographic metrics including slope and normalized channel steepness for each
catchment using the Zonal Statistics tool in the ArcGIS platform.

Normalized channel steepness (ksn) analysis
Normalized channel steepness is a measure of channel gradient adjusted for upstream
drainage area (Wobus et al., 2006) and is defined as:
ksn = SA
θref

where A is the upstream drainage area, S is the local slope, and θ
ref
is the reference channel
concavity. Assuming variability in controls such as rock type, climate, and sediment flux are
minimal or sufficiently constrained across the area of interest, normalized channel steepness
represents a measure of bedrock-channel response to differential rock uplift (Kirby et al., 2003).

12
We hypothesize that as hillslopes steepen in response to high rates of river incision in areas of
high ksn, a greater proportion of hillslopes are primed to fail in response to seismic forcing. To
calculate ksn for our study region, we first defined the transition between colluvial and fluvial
channels at a drainage area of 0.48 km
2
based on steepening of the slope gradient-contributing
area (G-A) relationship for the Gorkha landslide-affected region (Roback et al., 2017). We
determined ksn for the fluvial portion of the landscape in TopoToolbox, utilizing standard values
for smoothing distance of 1 km and reference concavity of 0.45 (Ouimet et al., 2009). We
inspected longitudinal profiles for rivers in central Nepal and found that a smoothing distance of
1 km minimizes oversmoothing, while highlighting major transitions in river steepness. We plot
ksn in bins as shown in Figure 5.
To determine whether landslides in the Gorkha event were more likely to occur near
channels with high normalized channel steepness, we performed a 3D search in ArcGIS using
the Near 3D tool to locate the nearest channel to every landslide source polygon in the landslide
inventory. This process assigned each landslide source polygon the ksn value associated with the
nearest channel. To understand how landsliding in the Gorkha event varied proximal to channels
of different ksn value, we summed the total landslide source area for all source polygons
associated with each ksn value bin. We compared this distribution with the background
distribution of normalized channel steepness in the landslide-affected area by summing the total
stream length of all channels in each ksn value bin (Fig. 6a). We used bins of 20 ksn units for this
analysis but note that different choice of bin intervals does not change our interpretations.
To further examine how the likelihood of slope failure in the Gorkha event changed
with proximity to channels of different ksn value, we used the Euclidian Allocation tool in
ArcGIS to create a raster with a 30m spatial resolution in which each cell was assigned the ksn

13
value of the nearest channel. We restricted our analysis to the landslide-affected area by drawing
a bounding box surrounding the extent of the Gorkha landslide inventory. Using the standard
algorithm in the ArcGIS platform, we generated a slope raster from our 30m DEM and converted
the raster to points. Utilizing the raster created using Euclidian Allocation and the Extract Value
to Points tool in ArcGIS, we assigned each point from the slope raster the ksn value of the nearest
channel. We resampled all landside source polygons to 1-meter raster resolution and performed
the same procedure to additionally assign each point from the slope raster a binary value
indicating whether it had failed in the Gorkha earthquake sequence. After exporting the data for
all DEM points in the landslide-affected region to a .csv file, we binned all DEM cells by the ksn
value of the nearest channel and calculated percent failure for each ksn bin as the number of cells
that failed over the total number of cells (Fig. 6b). We followed a similar procedure to derive a
percent failure distribution for the landslide-affected area for each degree of slope (Fig. 6c). To
explore the relationship between normalized channel steepness and slope, we also calculated the
average slope of all DEM cells for each ksn value bin (Fig. 6d).

(U-Th)/He thermochronology
(U-Th)/He ratios in apatite and zircon provide information about long-term exhumation,
which should be reflected by landslide denudation in a steady-state landscape (Larsen and
Montgomery, 2012). We collected samples of fine-to-coarse-grained sand (~0.1-1.5mm) from
the active channels of 12 tributary streams to the Melamchi and Indrawati Rivers (Fig. 1), and
from the mainstem of the Indrawati River. To provide context for the detrital data, we also
collected and analyzed 17 bedrock samples: six from a latitudinal transect along the Melamchi
River, four from a latitudinal transect along the eastern ridge of the Melamchi Valley, and seven

14
from locations of increasing elevation along the western side of the valley. Detrital samples were
collected from small tributary basins (1-51 km
2
) along a latitudinal transect, with basin relief
ranging from 875 to 2,416 meters. Additionally, we collected a single detrital sample from the
larger Indrawati watershed. We separated and measured (U-Th)/He single grain ages on 5-20
apatite grains and 3-5 zircon grains from each detrital sample, and 4-5 apatite and 3-5 zircon
grains from each bedrock sample, for a total of 290 single-grain (U-Th-Sm)/He apatite analyses
and 63 single-grain (U-Th)/He zircon analyses (see analytical results in Supplementary Tables 1,
2).
Samples were collected in October 2015 and May 2017 and returned to the University of
Michigan where all samples were dried and sieved using standard mineral separation techniques,
with apatite and zircon separated by exploiting differences in density and magnetic
susceptibility. Using a high-power binocular microscope, individual mineral grains were hand-
selected, screening for optimal clarity, crystal morphology, and minimal inclusions of other
potential radiogenic minerals. Selected grains were photographed and measured, then packaged
into individual Pt (apatite) or Nb (zircon) tubes and analyzed for
4
He content using an Australian
Scientific Instruments Helium Instrument (Alphachron) at the University of Michigan. Apatite
grains were heated for 5 minutes at 900°C using a diode laser, while zircon grains were heated
for 10 minutes at 1200°C. Temperature was monitored via a 4-color optical pyrometer that
adjusts laser power to maintain a constant temperature. Released
4
He was spiked with
3
He, and
the
4
He/
3
He ratio was measured on a Pfeiffer quadrupole mass spectrometer to determine the
quantity of
4
He in the mineral grain. Following initial
4
He measurement, the above analytical
procedures were repeated to check for any additional extraction of
4
He that might be indicative
of micro-inclusions of high-temperature radiogenic minerals that were not observed optically

15
during grain selection. To ensure accuracy of measurements of unknown age, the Durango
apatite age standard was analyzed along with apatite grains of unknown age. After extraction and
measurement of
4
He, apatite grains were dissolved and analyzed for U, Th and Sm
concentrations at the University of Arizona under the direction of Dr. Peter Reiners, following
standard procedures (Reiners and Nicolescu, 2006). Zircon grains were dissolved in Parr bombs
and analyzed for U and Th concentrations at the University of Arizona.
Individual grain dates were solved for numerically in Matlab using parent and daughter
nuclide concentrations and the age equation. Analytical uncertainties were propagated through
the age equation using Monte Carlo methods. Grains with low uranium concentrations are
particularly susceptible to age biases that result from uranium-implantation from surrounding U-
rich phases (Spiegel et al., 2009). Grains with uranium concentrations under 5 ppm were
excluded as outliers. For bedrock data, we identified outliers following Dean and Dixon (1951)
for the 90 percent confident interval at two significant digits. We applied this outlier test only to
bedrock samples with a 2-sigma standard error greater than 15 percent of the mean age.
Identification of outlier data from detrital data is complicated by the fact that individual
grains have experienced different cooling histories, and therefore have respectively different
thermal ages. However, we devised a strategy based on the expected age range of the data for
reasonable cooling rates to identify potential “old” outliers, which is a common phenomenon in
bedrock helium data due to the effect of implantation from neighboring radiogenic phases and
incision of radiogenic phases not detected by microscope screening. We identified “old” outliers
in our detrital data by deriving an estimate of the maximum potential age difference that is
expected between single grains from a given catchment due to catchment relief. Specifically, the
relief of sampled catchments, measured as the difference between the highest and lowest

16
elevations found in a catchment, ranges from 0.9 km to 2.4 km with an average of 1.6 km.
Hypsometric analysis of sampled catchments reveals that the frequency of elevations found
within each catchment approximates a normal distribution, indicating that the majority of grains
in a catchment detrital sample are likely to be sourced from mid-elevations. However, we used
the entire relief of each sampled catchment, and a conservative exhumation rate for the study
area of 0.3 mm/yr (Herman et al., 2010), to calculate the maximum potential elevation-derived
age difference expected for two grains from a given catchment. Following this approach, a
catchment with 1.5 km relief yields a maximum expected age difference between grains of 5
Myr. This approach relies on the assumption of simplified vertical exhumation pathways, but our
calculation provides a conservative estimate of potential elevation-derived age differences due to
the slow exhumation rate used and the low probability that two analyzed grains in a detrital
sample are sourced from the maximum and minimum elevations in a catchment. For each
catchment detrital sample, we examined the mean grain age and the maximum elevation-derived
age difference expected for the catchment. If a single grain age from a detrital sample exceeded
the sum of these two values for the catchment, then this grain was identified as an outlier.
Applying this approach to both apatite and zircon grains from each catchment, we identified 8
apatite grains and 1 zircon grain as outliers out of the 262 detrital grains that were analyzed
(Supplementary Tables 1, 2). These ages were excluded in the calculation of mean ages for the
respective catchments.
Using the remaining grain ages, we calculated a mean apatite (U-Th)/He and zircon (U-
Th)/He age for each bedrock and detrital sample (Table 1, Supplementary Fig. 4). Because the
observed variability in our (U-Th)/He ages for individual samples is larger than the analytical
error, we report mean ages for bedrock samples with the 2-sigma standard error of the mean.

17
Since detrital samples are composed of grains that are sourced from a range of elevations within
a catchment, we report mean ages for detrital samples with the range of ages of sample replicate
analyses after outlier removal.
We utilize the one-sigma standard deviation of replicate analyses to evaluate the
reproducibility of individual samples. After exclusion of outliers, the average one-sigma
uncertainty for bedrock zircon (U-Th)/He samples is 9.2% and ranges from 4.1-16% of the mean
sample age. The average one-sigma uncertainty for bedrock apatite (U-Th-Sm)/He samples is
26% and ranges from 4.3-96% of the mean sample age. Uncertainties are higher for detrital
samples, averaging 21% for zircon (U-Th)/He samples and ranging from 2.2-57% of the mean
sample age, and averaging 44% for apatite (U-Th-Sm)/He samples with a range from 28-86% of
the mean sample age. We consider bedrock samples that have a one-sigma standard deviation
greater than 45 percent of the mean age to have low reproducibility and we do not report mean
ages for the three bedrock apatite (U-Th)/He samples that meet this criterion.
We examined our data to identify any existing grainsize-age or eU-age trends for
individual samples. Grainsize-age trends may indicate the effect of crystal size on closure
temperature (Reiners and Farley, 2001), whereas trends between effective uranium (eU) and age
may reflect the effects of radiation damage on helium diffusion (Flowers et al., 2009; Guenthner
et al., 2013). We do not observe significant eU-age or grainsize-age trends in our bedrock data.
Samples taken from locations of increasing elevation can help to constrain rates and
patterns of exhumation through time. We collected seven bedrock samples from elevations
ranging from 2,699 to 4,656 meters AMSL for apatite (U-Th)/He analysis. Due to sampling
constraints, samples were separated along a horizontal distance of ~10km. The lowest- and
highest-elevation samples located in the age-elevation transect (17-MK-28 and 17-MK-21,

18
respectively) exhibit poor reproducibility of analyzed grains relative to the other five samples in
the transect. Although plotting sample ages against sample elevations from a vertical transect can
sometimes yield a positive slope that provides an estimate of past exhumation rates, our data do
not follow a clear age-elevation trend (Supplementary Fig. 5). Replicate analyses from our five
most reproducible samples suggest a relatively vertical or slightly negative-sloping age-elevation
relationship. This result may reflect high rates of exhumation, since rapid exhumation may lead
to topographic disturbance of the closure isotherm and an overestimation of exhumation rates
from age-elevation relationships (Mancktelow and Grasemann, 1997). The lack of a clear age-
elevation relationship may also reflect changes in the depth of the closure isotherm over the ~10
km of horizontal distance that span the extent of these samples.
We also collected four bedrock samples along the eastern drainage divide of the
Melamchi Valley for apatite (U-Th)/He analysis. Mean ages from these four samples decrease
from south to north, consistent with trends exhibited in our other thermochronometric data (Fig.
3). Mean apatite (U-Th)/He ages from these four samples are close to detrital and bedrock apatite
(U-Th)/He ages from samples taken from similar latitudes within the valley. This observation
helps to support our approach of using detrital ages to infer spatial trends in long-term
exhumation by suggesting that material sourced from different elevations within a catchment
may not vary widely in age.

RESULTS
Results from (U-Th)/He thermochronology
Average apatite (U-Th-Sm)/He ages for each sample range from 0.9-5.5 Ma, whereas
average zircon (U-Th)/He ages range from 1.0-5.2 Ma (Table 1). Our young (U-Th)/He ages

19
suggest that samples have been exhumed recently and quickly from above the closure
temperature for the zircon (U-Th)/He and apatite (U-Th-Sm)/He systems, of ~180-200 °C and
~40-70 °C, respectively, corresponding to depths of 5-8 km and 2-4 km for typical geothermal
gradients of ~20-40 °C/km (Reiners et al., 2002; Farley, 2002). Average zircon (U-Th)/He and
apatite (U-Th-Sm)/He ages are similar for paired samples, suggesting that samples experienced
relatively high rates of exhumation between the closure temperatures of these two systems,
followed by lower rates of exhumation to the present.
Average (U-Th)/He ages in zircon and apatite for both bedrock and detrital samples
decrease from south to north (Figs. 1, 2), suggesting a corollary positive trend in rates of long-
term exhumation. We note the similarity in ages between river bottom and ridge samples,
separated by 501-1442 m elevation (Supplementary Fig. 4), as well as the relative age-invariance
of samples collected along an elevation transect near the town of Melamchigoan (Supplementary
Fig. 5). The infinite age-elevation relationship in these samples implies rapid exhumation, which
is consistent with the relatively narrow age populations observed in detrital samples collected
from small tributary basins. Therefore, we interpret latitudinal trends in detrital (U-Th)/He ages
as a proxy for spatial patters of long-term exhumation. These patterns can then be related to
catchment-averaged metrics including landslide density and channel morphology. We find that
average (U-Th)/He ages for detrital samples generally decrease with increasing catchment
landslide density and increasing catchment mean ksn (Fig. 2). The latitudinal trends in (U-Th)/He
ages match decreases in published muscovite
40
Ar/
39
Ar ages from bedrock from the Melamchi
Valley (Herman et al., 2010) (Fig. 3a), suggesting that spatial trends in exhumation have been
robust over million-year timescales, even though absolute rates appear to have varied in a
systematic manner.

20

Relationships between topographic metrics and landsliding
Landslide density in the Melamchi Valley increases nonlinearly from south to north
before peaking between 28 and 28.1°N (Fig. 3). Along the south-to-north swath profile, the
highest landslide density is approximately coincident with peaks in average slope and average
normalized channel steepness, whereas average elevation continues to rise until the valley’s
northernmost extent (Fig. 3a). These patterns are reflected in positive correlations between
average landslide density in tributary catchments ( ls, in m
2
landslide area/km
2
catchment area)
plotted against catchment mean latitude, slope, normalized channel steepness, and 500m relief
(Fig. 4). We consider normalized channel steepness (ksn) because rivers generally have concave-
up longitudinal profiles, so the steepness of their channel at any given location may reflect the
position along the profile. By normalizing to upstream drainage area, ksn provides a method to
identify landscape response to differential uplift, even when this response is no longer recorded
in hillslopes (Wobus et al., 2006).
Relationships between landslide density and catchment mean slope, and between
landslide density and catchment mean ksn, are very similar for the Melamchi Valley and the two
adjacent valleys, the Tadi and the Indrawati (Supplementary Fig. 3). In this region, estimates of
PGA suggest that ground shaking did not vary widely (Supplementary Fig. 1). Relationships
between catchment landslide density and catchment mean slope and ksn become less strongly
correlated towards either end of the fault rupture (Supplementary Figs. 3, 4), which may reflect a
greater influence of localized variations in peak ground acceleration and fault rupture dynamics
on landslide distribution in these areas (Meunier et al., 2013; Martha et al., 2017)
(Supplementary Fig. 1), although poor constraints on PGA across the Gorkha region prevent

21
robust quantitative analysis (Roback et al., 2017). Nonetheless, we find that topography and
PGA worked together to determine the overall distribution of landslides from the Gorkha event,
with topography dominating in the central landslide-affected region, including the Melamchi
Valley.

Normalized channel steepness and landsliding
Consistent with previous observations (Wobus et al., 2006), ksn values in central Nepal
are generally low to the south of the physiographic transition (PT 2), increase across PT2, and
peak just north of the Main Central Thrust before decreasing farther to the north, in the approach
to the Tibetan Plateau. Overall, across the landslide-affected region, landslide density from the
Gorkha earthquake sequence was most concentrated near fluvial channels (Zekkos et al., 2017).
Our analysis reveals that landsliding was particularly focused near channels of high ksn, as seen
in map view (Fig. 5) and confirmed by higher ksn in channels proximal to landslide failures
compared to the landscape as a whole (Fig. 6a). Moreover, percent failure calculations for the
landslide-affected region show that the susceptibility to landslide initiation increased
progressively with proximity to channels of increasing normalized channel steepness (Fig. 6c).
Percent failure for each degree of slope follows an approximately normal distribution centered
around 60 degrees, but with a right tail that falls off sharply around 70 degrees (Fig. 6b).
Average slope in the landslide-affected region increases with proximity to channels of increasing
ksn, but plateaus at a slope of 35 degrees for ksn values greater than 300 (Fig. 6d). Although
previous studies have indicated relationships between landslide frequency and ksn in some
settings (Bennett et al., 2016), our data are the first to show these landscape-level relationships
for earthquake-triggered landsliding.

22

DISCUSSION
Implications for co-seismic landslide hazard
Our analysis of the Gorkha landslide distribution suggests earthquake-triggered
landsliding is most likely to occur in the fluvial High Himalaya, where steep slopes coincide with
high normalized channel steepness and thus high inferred rates of fluvial incision (Fig. 6a,c).
Specifically, we observe a sharp increase in percent failure from the Gorkha event with
proximity to channels above a ksn value of 200 (Fig. 6c), suggesting a possible threshold of
channel steepness above which the susceptibility to earthquake-triggered landsliding increases
markedly. The overall frequency of landslide occurrence peaks at ksn ~ 250 (Fig. 6a, blue
histogram), even though the susceptibility to failure continues to increase for higher ksn values
(Fig. 6c). These observations suggest that the normalized channel steepness index may help
guide future predictions of landslide hazard, with areas close to high ksn channels being
particularly susceptible to failure.

Landslide patterns consistent with threshold hillslope model
In a steady-state landscape, normalized channel steepness should reflect the rate of rock
uplift, modulated by rock mass erodibility (Wobus et al., 2006). Rivers respond to increases in
uplift rates by steepening, thus increasing rates of incision. The threshold hillslope model
predicts that once incision steepens hillslopes beyond a critical angle, increased rates of landslide
erosion accommodate further river down-cutting. If ksn reflects steady state uplift and incision
rates (Wobus et al., 2006; Bennett et al., 2016), this model leads to three predictions: (1) at low
ksn values, we expect little landsliding because uplift and incision are insufficient to steepen most

23
slopes to a critical angle; (2) as ksn increases, slopes steepen and landslide rates increase; and (3)
as ksn keeps increasing, slope gradients plateau at a critical threshold value, while landsliding
continues to increase in order to keep pace with incision.
These predictions are borne out in the Gorkha landslide data: We find a positive
relationship between ksn and landslide susceptibility (Fig. 6c) and a concentration of earthquake-
triggered landsliding near channels with high ksn (Figs. 5, 6a), both reflecting the hillslope
response to increased rates of river incision. Moreover, average hillslope angle increases with
proximity to channels of higher ksn, reaching a plateau at ~35° for ksn of ~300 (Fig. 6d). We
interpret this plateau as reflecting a critical threshold angle for hillslopes, consistent with prior
findings (Burbank et al., 1996; Ouimet et al., 2009; Dibiase et al., 2012; Larsen and
Montgomery, 2012).
Below ksn ~ 300, more landsliding near channels of higher normalized channel steepness
(Fig. 6c) can be explained by increases in the proportion of slopes at a critical angle (Fig. 6d)
(i.e., faster incision rates steepen a larger percentage of hillslopes to a critical threshold, and
these slopes then fail as a result of seismic forcing). Consistent with this conceptual model, along
the north-south swath profile, ksn and hillslope angle track one another closely (Fig. 3b).
Average hillslope angles do not continue to increase with higher ksn above ~ 300, and the
distribution of angles remains symmetric as ksn increases (Fig. 6d) — suggesting that increases in
hillslope steepness are not driving higher landslide susceptibility as normalized channel
steepness continues to rise. As yet unidentified mechanisms must accommodate the observed
continued increases in landsliding in response to more rapid channel incision. Altogether, these
results are consistent with the expectations of threshold hillslopes, revealed here for the first time

24
in response to a major landslide-forcing event such as the large earthquakes that are thought to
dominate the total denudation in seismically active regions (Keefer, 1994; Li et al., 2017).

Tectonic control on landsliding revealed by (U-Th)/He thermochronology
The Gorkha landslide data reveal how long-term patterns of landsliding predicted from
threshold hillslope theory are expressed in a single earthquake. A correlative implication is that
tectonic activity, as a driver of uplift and incision, regulates landslide occurrence. However,
multiple factors, including substrate strength, could influence channel and hillslope morphology,
opening up other possible interpretations for the observed correlations between slope angle, ksn,
and landsliding. Our thermochronometric data help substantiate tectonics as the driver of
observed co-seismic landsliding in the Himalaya. Specifically, correlations between (U-Th)/He
ages and catchment mean ksn (Figs. 2e, f) support the idea that spatial variations in normalized
channel steepness are related to long-term patterns of uplift, river incision, and exhumation —
which in turn are related to Gorkha landsliding.
The Gorkha event thus adds to the growing evidence for earthquake-triggered landsliding
as a key mechanism in explaining long-term exhumation of active orogens (Keefer, 1994;
Hovius et al., 1997; Li et al., 2017). The data from Nepal provide compelling evidence for the
spatial coincidence of landsliding and long-term exhumation, largely because of the latitudinal
gradient in exhumation. Feedbacks between crustal deformation and erosional unloading have
been widely discussed and are hypothesized to regulate mountain building in collisional orogens
(England and Molnar, 1990; Willett, 1999; Godard and Burbank, 2011). By identifying the close
links between topography, exhumation, and landsliding, our results suggest that earthquake-
triggered landsliding helps to modulate these feedbacks in the Nepal Himalaya.

25
CONCLUSIONS
Our findings support three of the central tenets of the threshold hillslope model. First, that
hillslope steepening is limited by material strength – as demonstrated by the invariance of
average slope above a threshold value of normalized channel steepness. Second, that threshold
hillslopes respond to increases in uplift-driven river incision via increased rates of landslide
erosion – as shown by landscape-level relationships between normalized channel steepness and
landsliding. Third, that in steady-state landscapes, landslide erosion is coupled to rates of
exhumation and rock uplift – as evinced by relationships between thermochronometric ages,
normalized channel steepness, and landsliding. While previous work has shown that background
rates of landslide erosion are consistent with the threshold hillslope model (Larsen and
Montgomery, 2012), our findings suggest that the 2015 Gorkha earthquake played a significant
role in modulating feedbacks between tectonics, topography, and landslide-driven denudation. In
doing so, we highlight the importance of earthquake-triggered landsliding in the evolution of
active orogens and suggest that observations of fluvial response to tectonics can inform seismic
hazard prediction.

26
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34

Figure 1: Sample locations in the Melamchi Valley
Locations of bedrock and catchment detrital samples collected in the Melamchi Valley shown
with the mean apatite-helium and zircon-helium age for each sample. Mean ages for detrital
samples are shown with the age range of sample replicate analyses. Mean ages for bedrock
samples are shown with the 2-sigma standard error of replicate analyses. Also shown are the
locations of
40
Ar/
39
Ar in muscovite samples from Herman et al. (2010), the locations of
landslides mapped by Roback et al. (2017), and the locations of subcatchments of the Melamchi
Valley used in Figure 4, which are color-coded according to catchment landslide density.

35

Figure 2: Catchment mean (U-Th)/He ages
Catchment mean (U-Th)/He ages for detrital apatite (left side) and zircon (right side) samples
collected from subcatchments of the Melamchi Valley plotted against latitude (a, b), catchment
landslide density in m
2
/km
2
(c, d), and catchment mean normalized channel steepness (e, f). Also
plotted are mean bedrock (U-Th)/He ages in apatite (a) and zircon (b) from samples collected
from the valley (orange circles). Errors plotted are the age range of replicate analyses for detrital
samples and the 2-sigma standard error for bedrock samples.

36

Figure 3: South-north swath profile of the Melamchi Valley
a) Mean (U-Th)/He bedrock and subcatchment detrital ages for zircon (green diamonds) and
apatite (orange triangles) plotted from south to north, along with
40
Ar/
39
Ar in muscovite ages
from Herman et al. (2010) (blue circles). Also plotted are swath profiles of landslide density and
mean elevation in the Melamchi Valley (Figure 1) from south to north, with gray shading
indicating minimum and maximum elevation values. b) Swath profile of the Melamchi Valley
showing average slope, average normalized channel steepness, and landslide density from south
to north.

37

Figure 4: Topographic metrics and landsliding
Landslide density in m
2
/km
2
(note log scale) for subcatchments of the Melamchi Valley plotted
against latitude (a), catchment mean slope (b), catchment mean normalized channel steepness
(c), and catchment mean relief (d) —with relief defined over a 500-meter circular window.
Subcatchments that were sampled for detrital thermochronology (gray dots) are distinguished
from other Melamchi subcatchments (red dots).

38

Figure 5: Normalized channel steepness and landsliding
Drainage network color-coded by normalized channel steepness shown with the distribution of
landslides (blue polygons) (Roback et al., 2017) for the majority of the region affected by
Gorkha-triggered landslides. An outline of the Melamchi Valley is shown for reference.

39
Figure 6: Normalized channel steepness,
slope, and percent failure
a) Histogram of stream length (gray) for
the landslide-affected region binned by
normalized channel steepness value,
plotted with histogram of landslide source
area (blue) binned by the normalized
channel steepness value of the nearest
channel. b) Percent of DEM cells that
failed in the landslide-affected region for
each degree of slope (blue dots), shown
with the distribution of DEM-derived
slopes in the landscape (gray shading). c)
Percent of DEM cells that failed in the
landslide-affected region, binned by the
normalized channel steepness value of the
nearest channel. Plot shows normalized
channel steepness bins of 100 (blue) and
bins of 50 (black). d) Average slope of
DEM cells, binned by the normalized
channel steepness value of the nearest
channel and shown with first and third data
quartiles.

40

Supplementary Figure 1: Location of the Melamchi Valley in the context of regional lithology
and peak ground acceleration in the Gorkha earthquake
a) Outline of the Melamchi Valley shown with major geologic units of central Nepal from Dhital
(2015). b) Outline of the Melamchi Valley shown with peak ground acceleration (PGA) in the
Gorkha earthquake from USGS ShakeMap: Map Version 5, Code Version 3.5 (March 2017).

41

Supplementary Figure 2: Catchment landslide density and slope angle for valleys in the
landslide-affected region
Landslide density plotted against mean catchment slope for subcatchments of the primary valleys
in the Gorkha landslide-affected region. Catchments included in this analysis are those that
contain only streams of Strahler stream order three or less, have an area greater than 1.5 km
2
, and
contain mapped landslides.

42

Supplementary Figure 3: Catchment landslide density and normalized channel steepness for
valleys in the landslide-affected region
Landslide density plotted against mean catchment normalized channel steepness for
subcatchments of the primary valleys in the Gorkha landslide-affected region. Catchments
included in this analysis are those that contain only streams of Strahler stream order three or less,
have an area greater than 1.5 km
2
, and contain mapped landslides.

43

Supplementary Figure 4: Average apatite-helium and zircon-helium ages for detrital and bedrock
samples from the Melamchi Valley.
Mean apatite-helium and zircon-helium ages shown with sample IDs for detrital samples (green
dots) and bedrock samples (yellow dots) from the Melamchi Valley. Mean ages for detrital
samples are shown with the age range of sample replicate analyses. Mean ages for bedrock
samples are shown with the 2-sigma standard error of replicate analyses. “NR” indicates that the
one-sigma standard deviation of replicate analyses after outlier removal is greater than 45
percent of the mean age for the sample.

44

Supplementary Figure 5: Apatite (U-Th)/He Age-Elevation relationships for bedrock elevation
transect
Ages of apatite (U-Th)/He replicate analyses plotted against elevation for bedrock samples
collected on the western side of the Melamchi Valley.

45

Table 1
Sample locations and mean (U-Th)/He ages in apatite and zircon
Sample Sample Latitude Longitude Elevation Catchment Area Catchment Relief Mean Zircon Age
1
Mean Apatite Age
1
Type (°N) (°E) (m) (km
2
) (m) (Ma) (Ma)
15-MK-2 Detrital 27.9315 85.5566 1182 4.1 1503 3.2 (3.1–3.3) 2.6 (1.8–6.0)
15-MK-3 Detrital 27.9092 85.5443 1083 27.5 2416 3.2 (3.0–3.5) 3.6 (1.8–7.0)
15-MK-5 Detrital 27.8861 85.5390 992 16.8 1645 4.1 (3.8–4.7) 3.3 (2.3–6.8)
15-MK-6 Detrital 27.8680 85.5383 927 28.4 1587 4.2 (3.9–4.6) 4.1 (2.6–9.0)
15-MK-7 Detrital 27.8335 85.5766 812 473.0 5308 3.7 (2.6–4.5) 5.4 (1.2–19)
15-MK-8 Detrital 27.8542 85.5911 887 1.6 875 2.7 (1.4–3.4) 3.2 (2.1–5.9)
15-MK-9 Detrital 27.8473 85.5859 860 4.4 1339 3.6 (3.1–4.0) 3.2 (2.2–7.0)
15-MK-10 Detrital 27.7875 85.5699 760 50.7 1644 4.3 (4.0–4.6) 3.3 (0.76–5.4)
15-MK-11 Detrital 27.7824 85.5696 765 21.6 1429 5.2 (4.3–6.3) 5.5 (3.5–9.8)
15-MK-12 Detrital 27.7445 85.5973 738 34.8 1232 5.1 (4.6–5.5) 5.1 (2.8–8.0)
17-DET-4 Detrital 28.0047 85.5406 1993 3.5 1948 1.0 (0.60–1.3) 2.3 (1.3–4.0)
17-DET-5 Detrital 27.9757 85.5470 1772 7.6 1765 3.8 (1.8–7.0) 2.5 (1.6–4.5)
17-DET-8 Detrital 28.0501 85.5365 2572 1.2 1324 2.9 (2.1–3.8) 1.7 (0.76–3.9)
15-MK-1 Bedrock 27.9623 85.5369 1374 2.6 (0.40) 2.1 (0.58)
15-MK-4 Bedrock 27.9009 85.5438 1050 3.0 (0.56) 3.7 (1.1)
17-MK-1 Bedrock 28.0106 85.5358 1893 2.5 (0.29) 0.90 (0.06)
17-MK-5 Bedrock 27.8389 85.5611 843 3.7 (0.26) 3.2 (0.23)
17-MK-8 Bedrock 27.7825 85.5696 768 4.9 (0.24) 4.2 (0.60)
17-MK-17 Bedrock 28.0517 85.5335 2576 2.0 (0.10) --
2
17-MK-4 Bedrock 27.9925 85.5723 3243 -- 2.5 (0.64)
17-MK-11 Bedrock 27.9239 85.5947 2490 -- 2.8 (0.51)
17-MK-15 Bedrock 28.0496 85.5678 4017 -- 1.8 (0.34)
17-MK-19 Bedrock 28.0148 85.5145 2699 -- --
2
17-MK-21 Bedrock 28.0093 85.5059 3042 -- 1.9 (0.16)
17-MK-22 Bedrock 28.0093 85.5000 3289 -- 1.5 (0.24)
17-MK-23 Bedrock 28.0120 85.4949 3525 -- 2.3 (0.68)
17-MK-24 Bedrock 28.0563 85.4575 3684 -- 1.3 (0.05)
17-MK-26 Bedrock 28.0651 85.4470 4157 -- 1.6 (0.20)
17-MK-28 Bedrock 28.0731 85.4296 4656 -- --
2
17-PN-WP1 Bedrock 27.8470 85.5712 1345 -- 3.4 (0.70)
1
Mean age of detrital samples shown with the age range of grains analyzed for the sample. Mean age of bedrock samples shown with 2-sigma standard error.
2
One-sigma standard deviation of bedrock replicate analyses after outlier removal is greater than 45 percent of mean age. No mean age reported.
"--" indicates that no zircon-helium analysis was performed for the sample.
Supplementary Table 1
Single-grain (U-Th-Sm)/He apatite analyses
Sample Sample U U SD Th Th SD Sm Sm SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief
Type (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg) (um) (um) (Ma) (Ma) (Ma) (m)
15-MK-2b Detrital 35.79 0.51 4.78 0.07 105.98 1.70 0.02 0.00018 8358.757 36.91 0.0026 0.75 np 48.8 133.8 1.7 2.2 0.03 1503
15-MK-2c Detrital 9.28 0.14 11.50 0.20 16.27 0.27 0.01 0.00026 4657.010 11.98 0.0029 0.76 nn 51.0 136.9 2.7 3.5 0.06
15-MK-2e Detrital 20.06 0.29 4.84 0.08 184.12 2.79 0.01 0.00019 4702.947 21.20 0.0023 0.75 np 51.0 108.2 1.5 1.9 0.03
15-MK-2g Detrital 19.17 0.28 2.41 0.04 149.17 2.29 0.01 0.00016 4761.811 19.73 0.0022 0.73 pp 43.9 138.2 1.6 2.2 0.03
15-MK-2i Detrital 20.90 0.30 4.19 0.07 83.56 1.27 0.02 0.00018 5343.772 21.89 0.0040 0.80 np 68.5 105.1 1.8 2.3 0.03
15-MK-2n† Detrital 3.76 0.06 1.58 0.02 13.11 0.19 0.02 0.00021 7700.617 4.14 0.0031 0.77 pp 53.9 133.8 14.0 18.1 0.24
15-MK-2q Detrital 20.15 0.29 1.12 0.02 88.56 1.36 0.02 0.00017 5307.872 20.42 0.0036 0.78 pp 56.3 141.8 1.9 2.4 0.03
15-MK-2r Detrital 40.29 0.58 4.89 0.08 107.66 1.62 0.03 0.00025 10188.396 41.44 0.0028 0.77 np 52.6 126.3 1.9 2.5 0.03
15-MK-2t Detrital 33.87 0.48 2.40 0.04 100.09 1.56 0.02 0.00028 8750.078 34.44 0.0026 0.76 np 49.5 132.1 1.9 2.5 0.03
15-MK-2v Detrital 27.67 0.40 7.12 0.11 73.60 1.15 0.07 0.00026 17424.087 29.34 0.0041 0.79 np 60.1 140.0 4.8 6.0 0.07
15-MK-2w Detrital 12.08 0.19 7.34 0.11 34.61 0.53 0.01 0.00019 2986.441 13.80 0.0035 0.78 np 53.9 151.1 1.4 1.8 0.03
15-MK-2ab Detrital 14.40 0.21 11.48 0.17 26.86 0.42 0.01 0.00014 4456.077 17.10 0.0023 0.74 pp 45.5 138.3 1.7 2.3 0.03
15-MK-2ac Detrital 9.60 0.14 9.57 0.14 21.34 0.33 0.01 0.00016 3598.019 11.85 0.0031 0.76 np 50.1 153.7 2.0 2.7 0.04
15-MK-2ag Detrital 21.30 0.31 1.96 0.03 114.81 1.70 0.02 0.00021 4896.845 21.76 0.0047 0.80 np 64.5 139.6 1.7 2.1 0.03
15-MK-2bb† Detrital 2.83 0.05 5.43 0.09 17.74 0.27 0.01 0.00016 6183.853 4.10 0.0024 0.76 pp 51.9 109.5 10.6 14.0 0.18
15-MK-2bf Detrital 16.18 0.23 2.26 0.04 82.42 1.23 0.01 0.00015 3741.104 16.72 0.0028 0.76 nn 49.5 140.0 1.5 1.9 0.03
15-MK-2bg Detrital 9.44 0.13 14.49 0.21 37.48 0.58 0.01 0.00021 4300.929 12.85 0.0035 0.78 np 54.8 143.1 2.4 3.0 0.04
15-MK-2bh† Detrital 4.35 0.06 2.21 0.03 17.67 0.27 0.01 0.00017 1468.121 4.87 0.0049 0.81 pp 70.7 121.5 1.8 2.2 0.05
15-MK-2br Detrital 24.54 0.37 4.71 0.07 139.77 2.16 0.02 0.00019 7856.244 25.65 0.0020 0.74 np 48.6 103.4 2.2 2.9 0.04
15-MK-2bu† Detrital 2.63 0.11 2.17 0.09 12.65 0.25 0.01 0.00025 4597.638 3.14 0.0028 0.77 pp 56.3 111.3 10.1 13.1 0.40
15-MK-3a Detrital 21.72 0.31 2.88 0.04 74.94 1.10 0.02 0.00018 5640.618 22.39 0.0039 0.78 pp 54.8 162.6 1.9 2.4 0.03 2416
15-MK-3b Detrital 26.81 0.39 2.44 0.04 123.58 1.88 0.02 0.00028 7170.070 27.39 0.0029 0.76 pp 51.7 134.3 1.9 2.5 0.04
15-MK-3c Detrital 22.61 0.32 3.32 0.05 190.20 2.89 0.02 0.00017 5583.954 23.39 0.0034 0.77 pp 51.7 156.8 1.7 2.3 0.03
15-MK-3d Detrital 20.98 0.30 3.42 0.05 182.90 2.69 0.02 0.00024 5708.488 21.79 0.0028 0.75 pp 47.0 158.6 1.9 2.5 0.04
15-MK-3e† Detrital 4.04 0.06 0.94 0.02 22.94 0.35 0.01 0.00032 3026.756 4.26 0.0034 0.78 pp 58.5 121.9 4.6 5.9 0.16
15-MK-3f Detrital 78.81 1.13 10.81 0.16 293.17 4.57 0.17 0.00048 25389.838 81.35 0.0068 0.82 pp 68.5 179.3 2.5 3.1 0.04
15-MK-3g Detrital 13.74 0.20 1.99 0.03 60.28 0.90 0.02 0.00021 5958.408 14.21 0.0036 0.78 np 54.1 153.7 3.1 4.0 0.05
15-MK-3h Detrital 26.55 0.39 1.99 0.03 31.38 0.52 0.02 0.00022 8590.474 27.02 0.0023 0.75 pp 49.5 117.0 2.4 3.1 0.04
15-MK-3i Detrital 25.26 0.36 1.59 0.03 222.46 3.31 0.05 0.00036 15550.357 25.63 0.0033 0.77 np 53.2 142.7 4.8 6.2 0.07
15-MK-3L Detrital 17.86 0.25 9.61 0.14 33.71 0.51 0.04 0.00024 10469.176 20.12 0.0037 0.79 np 61.0 125.0 4.1 5.1 0.06
15-MK-3n Detrital 8.63 0.12 3.43 0.05 107.83 1.61 0.02 0.00025 4665.465 9.44 0.0033 0.77 np 53.2 143.1 3.5 4.5 0.07
15-MK-3p Detrital 23.09 0.33 1.38 0.02 66.22 0.99 0.03 0.00025 5443.457 23.42 0.0052 0.80 np 58.5 188.6 1.8 2.2 0.03
15-MK-3q Detrital 20.48 0.30 1.19 0.02 165.57 2.44 0.02 0.00017 6205.230 20.76 0.0039 0.79 pp 57.9 143.2 2.2 2.8 0.04
15-MK-3r Detrital 17.23 0.25 1.51 0.03 90.82 1.37 0.03 0.00024 9776.040 17.58 0.0033 0.78 pp 54.6 138.7 4.3 5.5 0.07
15-MK-3s Detrital 15.17 0.22 3.12 0.05 110.42 1.73 0.03 0.00022 9872.910 15.90 0.0025 0.74 np 46.4 146.2 4.7 6.3 0.08
15-MK-3t Detrital 13.68 0.20 1.11 0.02 153.45 2.33 0.04 0.00029 9775.694 13.94 0.0041 0.78 np 53.2 181.1 5.4 7.0 0.09
15-MK-3u Detrital 8.73 0.13 1.88 0.03 38.65 0.59 0.01 0.00026 1951.713 9.17 0.0055 0.78 nn 53.2 242.1 1.4 1.8 0.04
15-MK-3v Detrital 16.14 0.24 3.15 0.05 179.81 2.65 0.02 0.00022 4149.296 16.88 0.0039 0.79 np 59.4 138.7 1.8 2.2 0.03
15-MK-3w Detrital 23.06 0.33 2.36 0.03 108.35 1.61 0.02 0.00020 6665.343 23.62 0.0027 0.76 np 52.6 123.2 2.1 2.7 0.04
15-MK-3x Detrital 13.20 0.20 2.46 0.04 40.17 0.66 0.01 0.00023 3505.311 13.77 0.0033 0.78 pp 56.3 129.0 1.7 2.2 0.04
15-MK-5a Detrital 9.00 0.13 3.08 0.04 72.47 1.07 0.02 0.00038 5138.380 9.72 0.0040 0.79 np 58.5 144.9 3.9 4.9 0.09 1645
15-MK-5b Detrital 22.60 0.32 7.65 0.11 91.32 1.41 0.02 0.00018 6543.955 24.40 0.0030 0.77 pp 53.4 130.7 2.0 2.6 0.03
15-MK-5d Detrital 6.44 0.09 2.28 0.03 22.00 0.34 0.01 0.00016 2185.689 6.98 0.0056 0.79 nn 54.8 231.1 2.1 2.7 0.04
15-MK-5e Detrital 14.67 0.21 1.67 0.03 44.90 0.68 0.01 0.00016 4260.937 15.06 0.0033 0.78 np 58.5 120.1 2.0 2.5 0.04
15-MK-5g Detrital 16.83 0.24 2.87 0.06 48.35 0.75 0.01 0.00020 5413.151 17.51 0.0023 0.76 np 51.0 111.3 2.1 2.8 0.05
15-MK-5j Detrital 7.82 0.11 1.77 0.03 35.93 0.58 0.01 0.00024 6015.654 8.23 0.0024 0.76 pp 51.9 109.5 5.1 6.8 0.11
15-MK-5k Detrital 41.31 0.60 2.24 0.03 242.16 3.64 0.07 0.00028 12734.445 41.83 0.0052 0.80 pp 59.4 182.4 2.4 3.0 0.04
15-MK-5L Detrital 6.34 0.09 2.12 0.03 22.04 0.35 0.01 0.00024 2380.912 6.84 0.0047 0.80 np 59.2 165.6 2.3 2.9 0.06
15-MK-5n Detrital 6.45 0.09 2.08 0.03 30.24 0.47 0.02 0.00023 3306.508 6.94 0.0063 0.81 nn 62.5 200.5 3.5 4.4 0.06
15-MK-5o* Detrital 8.11 0.12 2.83 0.04 18.57 0.30 0.06 0.00030 20118.972 8.77 0.0029 0.77 np 51.7 136.9 18.3 23.9 0.26
15-MK-5p Detrital 35.93 0.51 2.10 0.03 211.15 3.16 0.06 0.00031 13343.916 36.43 0.0043 0.77 np 50.1 210.2 2.9 3.8 0.04
15-MK-5q Detrital 14.69 0.21 1.09 0.02 79.46 1.17 0.04 0.00033 5582.666 14.94 0.0066 0.82 pp 69.8 167.4 2.9 3.5 0.05
15-MK-5r Detrital 6.87 0.10 1.18 0.02 30.43 0.46 0.01 0.00023 2627.662 7.14 0.0035 0.78 pp 57.2 132.5 2.3 3.0 0.07
15-MK-5s Detrital 7.01 0.10 3.89 0.06 12.52 0.22 0.01 0.00019 2475.851 7.92 0.0035 0.78 nn 55.4 141.8 2.0 2.5 0.05
15-MK-5t Detrital 24.36 0.35 1.51 0.02 107.34 1.59 0.02 0.00015 7076.396 24.71 0.0033 0.76 np 50.1 164.3 2.2 2.8 0.03
15-MK-5v Detrital 12.61 0.19 3.43 0.05 45.38 0.69 0.01 0.00015 4051.804 13.42 0.0027 0.74 np 45.5 163.0 2.0 2.7 0.04
15-MK-5w Detrital 17.82 0.26 2.41 0.04 85.60 1.30 0.01 0.00015 5562.079 18.39 0.0025 0.76 pp 51.7 114.4 2.1 2.8 0.04
15-MK-5x† Detrital 4.69 0.07 1.21 0.02 21.36 0.33 0.01 0.00018 1729.086 4.97 0.0052 0.80 pp 61.6 170.5 2.2 2.7 0.05
15-MK-5y Detrital 13.07 0.19 4.86 0.47 42.67 0.65 0.01 0.00019 4731.978 14.21 0.0028 0.77 np 53.2 121.5 2.3 3.0 0.05
15-MK-5aa Detrital 9.57 0.19 2.07 0.22 26.42 0.42 0.01 0.00025 2820.432 10.06 0.0035 0.79 pp 62.3 111.3 1.8 2.3 0.06
15-MK-6b Detrital 19.98 0.29 6.18 0.10 95.49 1.43 0.03 0.00021 9554.885 21.44 0.0031 0.76 pp 50.1 152.4 3.4 4.5 0.05 1587
15-MK-6c Detrital 8.93 0.13 3.00 0.05 80.03 1.17 0.02 0.00020 5021.851 9.64 0.0032 0.78 np 57.9 118.0 3.7 4.8 0.07
15-MK-6d Detrital 11.21 0.16 1.82 0.03 39.17 0.57 0.02 0.00022 4070.977 11.63 0.0046 0.79 np 58.5 167.4 2.6 3.2 0.05
15-MK-6e Detrital 24.57 0.36 2.78 0.04 191.83 2.80 0.02 0.00023 7657.732 25.22 0.0032 0.77 pp 51.0 152.7 2.3 3.0 0.04
15-MK-6f† Detrital 3.74 0.05 2.81 0.05 24.22 0.36 0.02 0.00028 5321.731 4.40 0.0034 0.77 pp 50.8 162.6 8.8 11.4 0.18
46

47
Supplementary Table 1

Single-grain (U-Th-Sm)/He apatite analyses

Sample Sample U U SD Th Th SD Sm Sm SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief

Type (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg) (um) (um) (Ma) (Ma) (Ma) (m)
15-MK-6h Detrital 24.65 0.35 1.22 0.02 196.71 3.02 0.02 0.00019 8089.745 24.93 0.0027 0.76 pp 51.0 127.7 2.4 3.2 0.04
15-MK-6k Detrital 26.09 0.37 3.68 0.06 162.58 2.36 0.02 0.00017 8088.695 26.95 0.0023 0.75 pp 48.8 118.4 2.2 2.9 0.04
15-MK-6r Detrital 10.51 0.15 2.56 0.04 11.17 0.18 0.02 0.00016 3787.340 11.11 0.0056 0.81 pp 63.2 173.1 2.5 3.1 0.04
15-MK-6v Detrital 22.80 0.33 2.57 0.04 45.85 0.72 0.02 0.00020 7331.398 23.40 0.0031 0.76 pp 50.8 149.3 2.4 3.1 0.04
15-MK-6x Detrital 22.26 0.32 1.41 0.02 166.58 2.49 0.05 0.00026 16970.062 22.59 0.0028 0.77 np 55.4 112.6 5.9 7.6 0.09
15-MK-6y Detrital 8.69 0.13 0.72 0.01 16.69 0.31 0.01 0.00017 3436.426 8.86 0.0031 0.77 nn 54.8 126.3 2.6 3.3 0.06
15-MK-6ab Detrital 11.80 0.17 0.74 0.02 155.72 2.28 0.02 0.00021 6587.649 11.97 0.0027 0.76 nn 50.1 133.8 4.0 5.2 0.07
15-MK-6ac Detrital 7.99 0.12 1.83 0.03 69.92 1.01 0.01 0.00018 3648.832 8.42 0.0031 0.77 pp 51.0 148.9 2.9 3.8 0.06
15-MK-6ad Detrital 25.68 0.37 1.04 0.02 222.91 3.33 0.03 0.00023 8818.030 25.92 0.0034 0.78 pp 55.7 135.2 2.6 3.3 0.04
15-MK-6af Detrital 32.93 0.48 1.75 0.03 191.32 2.79 0.03 0.00019 16273.105 33.34 0.0016 0.71 pp 40.4 125.0 3.7 5.2 0.06
15-MK-6ag Detrital 8.39 0.12 1.21 0.04 107.67 1.57 0.01 0.00014 3072.873 8.68 0.0034 0.78 pp 54.8 140.0 2.3 3.0 0.05
15-MK-6ah† Detrital 2.81 0.05 6.36 0.09 18.85 0.30 0.01 0.00022 8266.780 4.30 0.0016 0.72 pp 43.5 103.4 13.2 18.4 0.27
15-MK-6ai Detrital 12.57 0.18 1.29 0.02 135.17 1.96 0.02 0.00021 4050.462 12.87 0.0038 0.79 pp 59.4 133.8 2.2 2.8 0.04
15-MK-6aj Detrital 13.42 0.20 2.60 0.04 145.67 2.14 0.03 0.00019 12505.808 14.03 0.0022 0.75 np 49.5 109.6 6.7 9.0 0.10
15-MK-6ak Detrital 13.19 0.20 5.73 0.09 21.02 0.32 0.01 0.00018 4400.644 14.53 0.0022 0.75 pp 49.5 112.6 2.0 2.6 0.05
15-MK-7b Detrital 21.06 0.30 3.77 0.06 179.26 2.70 0.02 0.00021 6922.131 21.94 0.0027 0.77 np 53.2 120.2 2.3 3.0 0.04 5308
15-MK-7d Detrital 16.75 0.24 2.03 0.03 150.43 2.21 0.04 0.00022 9937.771 17.22 0.0043 0.81 pp 70.7 107.8 4.5 5.6 0.07
15-MK-7e Detrital 35.23 0.51 2.70 0.06 213.38 3.14 0.06 0.00027 25047.234 35.86 0.0025 0.75 np 47.9 135.6 5.6 7.4 0.08
15-MK-7g Detrital 20.95 0.63 6.63 0.48 81.18 1.29 0.01 0.00018 3050.749 22.50 0.0047 0.79 nn 56.1 186.0 1.0 1.2 0.03
15-MK-7i Detrital 38.20 0.56 1.38 0.05 267.05 4.16 0.03 0.00018 12620.932 38.53 0.0023 0.74 np 47.1 129.4 2.5 3.4 0.04
15-MK-7n† Detrital 2.49 0.04 2.89 0.05 12.11 0.27 0.01 0.00019 3366.744 3.16 0.0032 0.77 nn 52.6 142.7 7.0 9.1 0.15
15-MK-7o Detrital 15.24 0.22 2.00 0.03 145.73 2.32 0.02 0.00026 5170.477 15.71 0.0029 0.77 pp 52.6 130.8 2.3 3.0 0.05
15-MK-7p Detrital 21.10 0.30 2.12 0.03 136.58 2.10 0.02 0.00018 7301.903 21.60 0.0032 0.79 np 69.1 83.5 2.5 3.2 0.04
15-MK-7u Detrital 7.46 0.11 0.52 0.02 119.19 1.76 0.03 0.00036 10081.431 7.58 0.0034 0.79 np 62.3 108.2 10.1 12.8 0.18
15-MK-7v Detrital 6.44 0.10 33.40 0.48 66.42 1.02 0.02 0.00016 6943.994 14.29 0.0023 0.75 pp 51.1 107.8 3.4 4.6 0.05
15-MK-7w Detrital 5.42 0.08 2.09 0.04 77.13 1.16 0.03 0.00022 7688.542 5.91 0.0034 0.77 nn 51.9 156.8 9.8 12.7 0.16
15-MK-7x Detrital 11.65 0.17 1.55 0.03 65.90 1.02 0.02 0.00016 3959.234 12.01 0.0042 0.80 pp 62.3 135.6 2.4 3.0 0.04
15-MK-7y Detrital 33.71 0.48 4.73 0.08 162.14 2.40 0.02 0.00016 7310.497 34.82 0.0027 0.76 pp 51.0 127.7 1.5 2.0 0.02
15-MK-7z Detrital 22.29 0.89 4.73 0.48 230.23 3.38 0.02 0.00019 9322.438 23.40 0.0021 0.74 pp 46.4 120.1 2.9 3.9 0.11
15-MK-7aa Detrital 17.15 0.25 1.33 0.02 165.98 2.49 0.03 0.00021 4425.248 17.46 0.0060 0.81 nn 62.9 188.6 1.9 2.4 0.03
15-MK-7ae Detrital 14.51 0.21 2.16 0.03 124.62 1.86 0.03 0.00018 3626.005 15.02 0.0071 0.83 nn 72.4 167.4 1.8 2.2 0.03
15-MK-7af Detrital 19.61 0.28 0.67 0.01 132.13 1.97 0.06 0.00042 7488.899 19.76 0.0083 0.84 np 79.7 161.2 3.0 3.6 0.05
15-MK-7ah Detrital 13.41 0.19 6.69 0.10 49.45 0.72 0.02 0.00027 9905.934 14.99 0.0020 0.73 pp 44.8 126.3 4.9 6.7 0.09
15-MK-7ai Detrital 11.29 0.16 2.19 0.04 165.75 2.42 0.06 0.00016 21902.364 11.80 0.0027 0.77 pp 53.2 120.1 14.6 19.0 0.20
15-MK-7aj Detrital 16.00 0.23 1.39 0.02 37.87 0.58 0.03 0.00027 5186.669 16.33 0.0049 0.80 np 62.5 155.5 2.4 3.0 0.04
15-MK-8a Detrital 5.65 0.08 1.62 0.02 8.22 0.14 0.01 0.00015 2608.834 6.03 0.0046 0.80 np 60.1 156.8 2.9 3.7 0.05 875
15-MK-8c† Detrital 4.87 0.07 1.65 0.02 9.02 0.14 0.01 0.00015 1596.467 5.26 0.0051 0.80 pp 61.6 167.4 1.9 2.3 0.04
15-MK-8e Detrital 5.29 0.08 0.97 0.02 14.06 0.22 0.01 0.00015 1500.236 5.52 0.0057 0.81 pp 66.3 161.2 1.7 2.1 0.04
15-MK-8f Detrital 7.23 0.10 1.39 0.02 12.21 0.20 0.01 0.00017 3181.808 7.55 0.0037 0.78 np 54.8 152.4 2.9 3.7 0.06
15-MK-8i Detrital 8.13 0.12 3.03 0.04 12.05 0.21 0.01 0.00024 2506.006 8.84 0.0036 0.78 np 54.1 151.9 1.8 2.3 0.05
15-MK-8j Detrital 14.25 0.20 5.44 0.08 6.56 0.12 0.03 0.00016 5154.687 15.53 0.0053 0.80 pp 62.3 170.5 2.5 3.2 0.04
15-MK-8L† Detrital 4.95 0.10 4.28 0.06 6.40 0.20 0.01 0.00017 4764.857 5.95 0.0018 0.72 pp 43.3 117.0 5.0 6.9 0.13
15-MK-8m† Detrital 3.82 0.06 5.15 0.08 4.99 0.09 0.05 0.00025 14235.922 5.04 0.0037 0.77 np 50.8 178.0 22.4 29.1 0.27
15-MK-8n† Detrital 1.46 0.02 0.95 0.02 1.82 0.04 0.01 0.00019 3728.573 1.69 0.0033 0.78 np 54.8 135.2 15.1 19.5 0.33
15-MK-8o Detrital 23.46 0.34 3.95 0.06 141.18 2.08 0.01 0.00020 6349.339 24.38 0.0018 0.72 np 43.3 118.4 1.7 2.4 0.04
15-MK-8p Detrital 6.73 0.10 1.37 0.02 8.63 0.15 0.01 0.00011 2986.670 7.06 0.0037 0.77 pp 51.7 173.6 2.8 3.7 0.05
15-MK-8q† Detrital 4.76 0.07 0.91 0.02 33.21 0.49 0.02 0.00019 5209.839 4.98 0.0030 0.77 np 51.9 140.0 7.5 9.7 0.14
15-MK-8t Detrital 7.18 0.10 2.10 0.03 23.77 0.37 0.01 0.00012 2432.590 7.68 0.0054 0.81 pp 64.7 159.5 2.2 2.7 0.03
15-MK-8u Detrital 15.77 0.22 2.31 0.03 120.24 1.78 0.02 0.00021 7273.201 16.31 0.0029 0.76 np 50.1 143.6 3.3 4.3 0.06
15-MK-8v Detrital 9.08 0.13 1.31 0.02 10.12 0.16 0.02 0.00017 3736.895 9.39 0.0061 0.81 nn 61.6 199.3 3.0 3.7 0.05
15-MK-8w Detrital 11.01 0.16 3.72 0.05 73.94 1.10 0.02 0.00025 3729.108 11.88 0.0051 0.79 nn 57.2 193.5 2.3 2.9 0.04
15-MK-8y Detrital 6.58 0.10 1.77 0.03 42.69 0.62 0.01 0.00026 4695.684 6.99 0.0020 0.72 nn 41.7 140.0 4.3 5.9 0.13
15-MK-8aa Detrital 9.08 0.13 1.87 0.03 6.63 0.25 0.01 0.00017 2534.583 9.52 0.0034 0.77 np 51.0 163.0 1.7 2.2 0.04
15-MK-8ab Detrital 6.87 0.11 2.09 0.03 7.23 0.15 0.01 0.00011 2149.001 7.36 0.0039 0.77 nn 49.5 196.1 1.8 2.4 0.04
15-MK-8ag* Detrital 7.68 0.11 12.04 0.17 5.78 0.12 0.08 0.00051 38746.877 10.51 0.0021 0.71 pp 40.2 161.2 29.6 41.4 0.38
15-MK-9a Detrital 13.88 0.20 2.99 0.04 23.38 0.35 0.01 0.00020 4495.040 14.58 0.0031 0.76 np 50.4 150.6 2.2 2.8 0.04 1339
15-MK-9b Detrital 24.52 0.35 5.93 0.09 55.35 0.82 0.05 0.00027 17940.808 25.91 0.0028 0.78 np 61.6 92.8 5.5 7.0 0.08
15-MK-9c Detrital 26.69 0.38 3.57 0.05 222.10 3.25 0.06 0.00034 10324.008 27.53 0.0059 0.82 pp 70.0 148.9 3.0 3.6 0.04
15-MK-9d† Detrital 1.44 0.02 2.53 0.04 5.46 0.09 0.01 0.00016 2489.752 2.04 0.0036 0.78 np 54.8 147.5 7.7 9.9 0.17
15-MK-9f* Detrital 12.28 0.18 3.55 0.05 100.50 1.48 0.04 0.00015 11109.166 13.11 0.0032 0.78 np 58.5 115.3 6.5 8.4 0.09
15-MK-9g Detrital 35.45 0.50 2.54 0.04 171.03 2.49 0.06 0.00021 9637.167 36.04 0.0065 0.82 pp 66.9 179.3 2.1 2.6 0.03
15-MK-9h Detrital 24.62 0.35 3.39 0.05 176.79 2.71 0.03 0.00028 7314.573 25.42 0.0038 0.79 pp 59.4 132.1 2.2 2.8 0.04
15-MK-9i† Detrital 3.15 0.05 0.72 0.01 3.08 0.09 0.01 0.00018 1402.525 3.32 0.0057 0.80 np 57.9 211.6 2.6 3.2 0.07
15-MK-9j Detrital 12.82 0.18 1.84 0.04 25.20 0.40 0.02 0.00026 3743.584 13.25 0.0052 0.81 np 70.0 131.2 2.1 2.6 0.04
15-MK-9k Detrital 15.82 0.23 2.78 0.05 76.64 1.16 0.02 0.00018 4882.167 16.47 0.0033 0.79 pp 65.6 95.9 2.1 2.7 0.04

48
Supplementary Table 1

Single-grain (U-Th-Sm)/He apatite analyses

Sample Sample U U SD Th Th SD Sm Sm SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief

Type (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg) (um) (um) (Ma) (Ma) (Ma) (m)
15-MK-9L Detrital 7.48 0.11 12.19 0.18 18.77 0.30 0.02 0.00028 3791.838 10.34 0.0048 0.80 nn 61.0 159.5 2.7 3.3 0.05
15-MK-9m Detrital 10.63 0.15 4.82 0.07 13.19 0.21 0.02 0.00016 2949.679 11.77 0.0061 0.82 np 70.7 150.6 1.8 2.2 0.03
15-MK-9n Detrital 10.59 0.15 1.32 0.02 9.31 0.15 0.02 0.00012 2888.680 10.90 0.0062 0.80 nn 57.9 229.7 1.9 2.4 0.03
15-MK-9o Detrital 9.42 0.13 2.54 0.04 27.43 0.42 0.05 0.00020 5976.656 10.02 0.0081 0.83 nn 69.8 205.4 4.7 5.7 0.07
15-MK-9p Detrital 8.81 0.18 2.66 0.04 64.52 0.99 0.01 0.00017 2693.486 9.44 0.0035 0.77 nn 51.5 162.5 1.8 2.4 0.05
15-MK-9q Detrital 35.19 0.50 3.85 0.06 205.64 3.12 0.07 0.00032 16247.758 36.10 0.0040 0.80 np 63.8 123.2 3.6 4.5 0.05
15-MK-9r Detrital 12.01 0.18 3.25 0.05 31.42 0.50 0.01 0.00020 3536.846 12.77 0.0039 0.78 nn 53.9 168.8 1.9 2.5 0.04
15-MK-9s Detrital 14.95 0.21 4.69 0.07 38.38 0.61 0.02 0.00018 5251.417 16.05 0.0037 0.79 np 61.6 121.9 2.4 3.0 0.04
15-MK-9t Detrital 9.25 0.13 2.03 0.03 11.93 0.19 0.01 0.00029 2483.501 9.73 0.0052 0.80 nn 58.5 187.3 1.8 2.2 0.05
15-MK-9u Detrital 9.06 0.13 2.12 0.03 16.21 0.26 0.02 0.00027 2714.086 9.56 0.0060 0.81 nn 63.2 186.0 2.0 2.5 0.04
15-MK-10a Detrital 10.71 0.15 2.19 0.03 52.95 0.83 0.01 0.00027 3377.006 11.23 0.0040 0.79 pp 57.0 153.8 2.1 2.7 0.05 1644
15-MK-10b Detrital 11.47 0.17 3.41 0.05 16.31 0.25 0.02 0.00018 3664.138 12.27 0.0045 0.79 np 56.1 178.1 2.2 2.7 0.04
15-MK-10c Detrital 14.58 0.21 11.44 0.16 77.38 1.18 0.03 0.00024 7429.948 17.27 0.0046 0.79 np 56.3 179.4 3.3 4.2 0.05
15-MK-10e Detrital 49.79 0.71 2.91 0.04 186.75 2.83 0.03 0.00017 4189.456 50.48 0.0064 0.83 pp 80.0 123.3 0.6 0.8 0.01
15-MK-10f Detrital 10.14 0.14 2.22 0.04 18.19 0.29 0.01 0.00022 3118.647 10.66 0.0039 0.79 np 58.5 141.3 2.0 2.5 0.04
15-MK-10g Detrital 17.93 0.26 3.77 0.06 223.27 3.46 0.02 0.00026 7122.267 18.81 0.0031 0.77 pp 54.8 127.7 2.8 3.6 0.05
15-MK-10h Detrital 6.99 0.10 0.50 0.01 4.69 0.07 0.03 0.00025 2972.453 7.11 0.0110 0.83 nn 70.7 272.5 3.2 3.9 0.05
15-MK-10i Detrital 21.70 0.31 2.25 0.04 21.72 0.35 0.02 0.00013 6917.148 22.23 0.0024 0.76 np 50.8 114.0 2.2 3.0 0.04
15-MK-10j Detrital 14.91 0.22 4.48 0.07 171.00 2.59 0.01 0.00025 4521.479 15.96 0.0023 0.75 pp 50.1 114.0 1.9 2.5 0.05
15-MK-10k Detrital 17.66 0.25 6.87 0.10 80.87 1.25 0.02 0.00033 7837.477 19.27 0.0027 0.78 pp 61.4 88.5 3.0 3.9 0.06
15-MK-10L Detrital 24.21 0.35 5.66 0.08 60.96 0.93 0.04 0.00024 9008.556 25.54 0.0046 0.78 np 53.9 196.1 2.8 3.5 0.04
15-MK-10m Detrital 36.28 0.52 23.35 0.34 142.91 2.23 0.09 0.00036 18242.086 41.76 0.0051 0.80 pp 60.7 170.5 3.5 4.4 0.05
15-MK-10n Detrital 16.65 0.24 63.11 0.90 15.19 0.26 0.04 0.00026 8552.790 31.49 0.0052 0.81 nn 67.9 141.4 2.1 2.6 0.02
15-MK-10o Detrital 7.80 0.11 1.24 0.02 38.82 0.60 0.01 0.00019 2593.264 8.09 0.0047 0.79 np 56.3 185.5 2.2 2.8 0.05
15-MK-10p Detrital 12.87 0.19 1.38 0.02 168.54 2.56 0.02 0.00024 4591.855 13.19 0.0046 0.80 np 61.6 150.7 2.6 3.2 0.05
15-MK-10q Detrital 63.93 0.92 48.46 0.70 161.24 2.50 0.12 0.00037 34092.249 75.31 0.0035 0.79 nn 60.1 121.5 3.7 4.7 0.05
15-MK-10r Detrital 51.95 0.75 1.34 0.04 218.23 3.37 0.11 0.00029 24346.888 52.27 0.0046 0.80 pp 62.3 146.9 3.8 4.7 0.05
15-MK-10s Detrital 11.72 0.17 1.54 0.02 31.17 0.48 0.03 0.00025 3707.451 12.09 0.0081 0.82 nn 63.8 246.6 2.4 2.9 0.04
15-MK-10t Detrital 15.72 0.22 6.78 0.10 145.49 2.27 0.06 0.00021 9761.469 17.31 0.0065 0.82 pp 71.6 158.6 4.5 5.4 0.06
15-MK-10u Detrital 23.43 0.33 1.80 0.03 167.02 2.52 0.03 0.00016 7325.217 23.86 0.0043 0.79 pp 59.4 152.4 2.4 3.0 0.04
15-MK-10v Detrital 57.18 0.82 4.98 0.08 332.34 5.21 0.07 0.00026 18856.641 58.35 0.0035 0.80 pp 66.3 100.3 2.6 3.2 0.04
15-MK-11a† Detrital 3.10 0.05 3.35 0.05 8.51 0.14 0.01 0.00023 3826.609 3.88 0.0038 0.79 nn 59.4 132.1 6.9 8.8 0.14 1429
15-MK-11b Detrital 20.95 0.30 3.56 0.05 123.27 1.93 0.04 0.00031 7805.236 21.79 0.0050 0.79 pp 54.8 205.4 2.8 3.5 0.04
15-MK-11c Detrital 11.24 0.16 3.01 0.05 84.34 1.30 0.03 0.00036 7247.829 11.95 0.0045 0.80 nn 63.2 140.0 4.7 5.8 0.08
15-MK-11d Detrital 25.43 0.37 3.37 0.05 112.54 1.74 0.04 0.00024 15905.576 26.22 0.0023 0.76 pp 54.8 94.6 4.7 6.2 0.07
15-MK-11e Detrital 41.05 0.59 4.85 0.07 132.41 2.03 0.05 0.00020 16048.889 42.19 0.0032 0.78 pp 57.6 118.4 3.0 3.9 0.04
15-MK-11f Detrital 11.60 0.17 4.20 0.06 185.56 2.93 0.02 0.00018 4771.465 12.59 0.0043 0.80 pp 60.7 144.5 2.8 3.5 0.04
15-MK-11h† Detrital 4.60 0.07 2.98 0.04 206.45 3.14 0.01 0.00018 2979.087 5.30 0.0044 0.79 pp 56.3 171.9 3.7 4.7 0.07
15-MK-11i Detrital 22.44 0.32 3.98 0.06 210.01 3.20 0.05 0.00047 14323.680 23.38 0.0033 0.77 pp 53.2 145.8 4.8 6.2 0.08
15-MK-11j Detrital 11.94 0.17 3.27 0.05 189.76 2.94 0.02 0.00018 5344.628 12.70 0.0040 0.77 pp 50.2 196.1 3.1 4.0 0.05
15-MK-11k† Detrital 4.34 0.06 1.46 0.02 9.49 0.15 0.02 0.00022 2039.692 4.69 0.0121 0.84 pp 75.3 265.1 3.3 3.9 0.05
15-MK-11L Detrital 41.68 0.60 2.71 0.04 171.25 2.60 0.14 0.00057 21679.575 42.32 0.0066 0.83 np 78.2 133.9 4.2 5.0 0.06
15-MK-11m† Detrital 4.27 0.06 2.12 0.03 12.46 0.19 0.01 0.00021 2916.236 4.77 0.0042 0.80 nn 63.8 129.4 4.2 5.2 0.09
15-MK-11n Detrital 13.29 0.20 6.42 0.09 73.01 1.19 0.03 0.00031 9285.484 14.80 0.0028 0.75 pp 47.3 153.7 4.7 6.3 0.08
15-MK-11o* Detrital 11.70 0.17 3.04 0.05 40.39 0.61 0.08 0.00040 13639.623 12.42 0.0062 0.81 np 62.3 197.9 8.8 10.9 0.13
15-MK-11r Detrital 19.17 0.27 3.30 0.06 114.55 1.79 0.07 0.00020 19423.888 19.95 0.0034 0.79 pp 63.2 106.4 7.8 9.8 0.11
15-MK-11s Detrital 25.21 0.36 5.51 0.08 170.71 2.66 0.05 0.00024 13922.599 26.50 0.0037 0.79 pp 60.7 124.6 4.1 5.2 0.06
15-MK-11u Detrital 7.59 0.11 3.07 0.05 135.55 2.26 0.02 0.00016 5332.243 8.31 0.0036 0.78 nn 53.9 152.0 4.6 6.0 0.07
15-MK-11v Detrital 9.07 0.14 4.38 0.06 53.17 0.86 0.03 0.00024 8336.786 10.10 0.0031 0.77 nn 54.1 130.7 6.2 8.1 0.10
15-MK-11w Detrital 12.52 0.19 4.72 0.07 43.47 0.68 0.01 0.00016 5597.519 13.63 0.0025 0.75 np 47.9 133.8 2.9 3.8 0.05
15-MK-11x Detrital 29.18 0.42 8.37 0.12 66.09 1.11 0.03 0.00013 13928.332 31.15 0.0021 0.74 nn 46.4 118.8 3.4 4.6 0.05
15-MK-12a† Detrital 3.52 0.06 1.22 0.02 6.92 0.11 0.01 0.00028 1949.709 3.81 0.0042 0.79 np 57.0 159.9 3.1 4.0 0.12 1232
15-MK-12b Detrital 11.03 0.29 3.77 0.06 24.02 0.41 0.02 0.00020 7178.883 11.91 0.0033 0.77 pp 53.2 145.8 4.5 5.9 0.12
15-MK-12c Detrital 19.52 0.28 6.22 0.09 170.49 2.59 0.07 0.00033 16204.231 20.98 0.0042 0.78 nn 53.2 185.5 6.1 7.9 0.09
15-MK-12d Detrital 48.89 0.70 2.18 0.03 191.51 2.95 0.13 0.00024 27659.409 49.41 0.0047 0.81 np 65.6 136.9 4.5 5.6 0.06
15-MK-12e Detrital 11.70 0.18 4.80 0.07 41.25 0.68 0.01 0.00029 6141.628 12.83 0.0018 0.74 np 47.9 97.2 3.2 4.3 0.10
15-MK-12g Detrital 8.48 0.12 2.11 0.03 14.58 0.22 0.02 0.00026 4452.711 8.98 0.0054 0.80 np 59.4 188.6 3.7 4.7 0.07
15-MK-12h Detrital 8.10 0.12 3.02 0.04 139.82 2.30 0.02 0.00029 4998.383 8.81 0.0037 0.79 pp 60.7 125.0 4.1 5.2 0.09
15-MK-12i Detrital 36.77 0.53 4.28 0.06 250.67 3.80 0.18 0.00026 30621.417 37.78 0.0058 0.82 np 73.1 135.6 6.6 8.0 0.09
15-MK-12j Detrital 9.21 0.13 4.03 0.06 45.89 0.73 0.02 0.00027 4945.815 10.16 0.0043 0.80 pp 61.6 140.0 3.6 4.5 0.07
15-MK-12k Detrital 17.76 0.26 7.08 0.10 213.06 3.23 0.06 0.00039 12506.194 19.42 0.0049 0.80 nn 59.4 171.5 5.1 6.4 0.07
15-MK-12L Detrital 5.05 0.11 1.75 0.03 60.33 0.91 0.02 0.00017 2264.280 5.46 0.0067 0.82 nn 65.4 193.5 2.9 3.6 0.07
15-MK-12m * Detrital 18.79 0.27 3.06 0.05 158.61 2.46 0.12 0.00044 29249.024 19.50 0.0043 0.79 pp 60.1 146.2 12.1 15.2 0.17
15-MK-12n Detrital 45.87 0.67 2.76 0.04 184.68 2.85 0.10 0.00035 26406.031 46.52 0.0038 0.79 np 59.9 132.5 4.6 5.8 0.07
15-MK-12o Detrital 15.70 0.23 6.95 0.10 175.73 2.68 0.02 0.00024 7175.235 17.33 0.0034 0.77 np 50.1 169.2 3.1 4.0 0.05

49
Supplementary Table 1

Single-grain (U-Th-Sm)/He apatite analyses

Sample Sample U U SD Th Th SD Sm Sm SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief

Type (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg) (um) (um) (Ma) (Ma) (Ma) (m)
15-MK-12p Detrital 34.40 0.49 5.47 0.08 187.12 2.92 0.06 0.00025 10253.957 35.69 0.0055 0.80 nn 61.6 181.1 2.3 2.8 0.03
15-MK-12q* Detrital 8.63 0.12 2.91 0.04 228.21 3.47 0.09 0.00029 22526.891 9.32 0.0042 0.80 nn 61.0 140.0 19.0 23.9 0.25
15-MK-12r Detrital 25.67 0.37 4.06 0.08 207.82 3.24 0.05 0.00025 11017.343 26.62 0.0045 0.79 pp 58.7 161.2 3.3 4.1 0.05
15-MK-12t Detrital 9.60 0.14 2.55 0.04 76.11 1.18 0.02 0.00018 5091.733 10.20 0.0039 0.78 nn 54.1 167.0 3.7 4.7 0.06
15-MK-12u Detrital 57.87 0.83 2.11 0.03 141.53 2.16 0.12 0.00038 23167.752 58.37 0.0052 0.79 nn 55.4 210.3 3.2 4.1 0.05
15-MK-12v Detrital 6.09 0.09 5.38 0.08 66.08 1.02 0.01 0.00022 3767.145 7.35 0.0026 0.77 np 53.4 114.0 3.3 4.3 0.08
17-DET-04a Detrital 68.01 0.97 3.90 0.06 205.70 3.05 0.0253 0.00023 9141.412 68.93 0.0028 0.76 pp 51.0 132.1 1.0 1.3 0.02 1948
17-DET-04b Detrital 17.24 0.25 1.24 0.02 145.52 2.20 0.0098 0.00015 4088.749 17.53 0.0024 0.73 np 43.5 156.8 1.5 2.1 0.03
17-DET-04d* Detrital 18.31 0.27 2.56 0.04 59.33 0.91 0.0488 0.00026 19806.408 18.91 0.0025 0.75 pp 48.0 132.9 8.3 11.0 0.12
17-DET-04e† Detrital 1.02 0.03 0.27 0.03 1.77 0.20 0.0124 0.00019 12578.398 1.09 0.0010 0.60 nn 27.4 162.5 78.9 130.7 2.42
17-DET-04f Detrital 9.44 0.13 0.47 0.01 111.05 1.73 0.0195 0.00022 4130.754 9.55 0.0047 0.80 np 59.2 167.4 3.2 4.0 0.06
17-DET-04m Detrital 13.26 0.20 2.57 0.14 17.93 0.28 0.0113 0.00012 3889.605 13.87 0.0029 0.77 np 54.1 123.2 1.9 2.5 0.03
17-DET-04o Detrital 18.33 0.28 2.93 0.12 57.77 0.94 0.0128 0.00013 3970.753 19.02 0.0032 0.78 pp 56.3 125.9 1.4 1.9 0.03
17-DET-05a Detrital 17.71 0.25 0.92 0.01 185.78 2.72 0.0286 0.00017 5165.224 17.92 0.0055 0.80 nn 58.5 201.0 2.2 2.7 0.03 1765
17-DET-05b Detrital 12.58 0.18 0.47 0.01 119.22 1.77 0.0241 0.00018 6062.857 12.69 0.0040 0.79 np 57.0 151.9 3.6 4.5 0.06
17-DET-05c Detrital 77.64 1.10 3.38 0.05 217.21 3.24 0.0374 0.00021 13994.446 78.44 0.0027 0.76 pp 51.0 127.7 1.4 1.8 0.02
17-DET-05d Detrital 46.81 0.66 2.99 0.04 205.23 3.02 0.0345 0.00025 8072.024 47.52 0.0043 0.79 nn 60.1 147.1 1.3 1.7 0.02
17-DET-05e Detrital 11.73 0.17 0.43 0.01 120.49 1.76 0.0111 0.00016 2277.802 11.83 0.0049 0.80 pp 60.1 167.4 1.3 1.6 0.03
17-DET-08a Detrital 16.41 0.23 2.23 0.03 95.85 1.40 0.0164 0.00014 2162.326 16.94 0.0076 0.83 pp 71.6 184.2 0.9 1.1 0.01 1324
17-DET-08b Detrital 11.92 0.17 2.06 0.03 27.74 0.45 0.0242 0.00021 5114.638 12.41 0.0047 0.80 np 60.1 162.5 3.1 3.9 0.05
17-DET-08d Detrital 36.27 0.52 11.72 0.17 434.44 6.36 0.0110 0.00008 3342.705 39.02 0.0033 0.74 nn 44.2 208.5 0.6 0.8 0.01
17-DET-08e* Detrital 12.36 0.18 0.42 0.01 69.19 1.02 0.1166 0.00044 12281.551 12.46 0.0095 0.85 np 82.8 171.8 8.0 9.4 0.12
17-DET-08g Detrital 26.72 0.38 2.86 0.04 47.68 0.73 0.0243 0.00017 4258.793 27.39 0.0057 0.81 pp 66.3 161.2 1.2 1.4 0.02
17-DET-08i Detrital 11.23 0.16 1.58 0.02 86.68 1.30 0.0134 0.00008 1914.344 11.60 0.0070 0.82 np 70.7 173.6 1.1 1.4 0.02
15-MK-1a Bedrock 19.65 0.28 5.62 0.14 114.60 2.03 0.01 0.00026 6705.274 20.97 0.0021 0.76 pp 55.4 85.3 2.2 3.0 0.05
15-MK-1b Bedrock 27.87 0.40 3.14 0.06 162.62 2.46 0.02 0.00018 6367.391 28.61 0.0026 0.77 pp 53.9 109.6 1.6 2.1 0.03
15-MK-1c Bedrock 13.81 0.20 2.48 0.04 108.20 1.58 0.01 0.00013 3118.343 14.39 0.0031 0.75 np 47.0 176.7 1.4 1.9 0.03
15-MK-1d Bedrock 19.31 0.47 2.30 0.05 105.47 1.57 0.01 0.00017 3710.248 19.85 0.0030 0.78 np 57.0 115.7 1.3 1.6 0.04
15-MK-4a† Bedrock 3.96 0.07 2.87 0.05 154.82 2.29 0.01 0.00020 4187.981 4.64 0.0030 0.76 nn 51.0 141.3 6.0 7.8 0.13
15-MK-4b Bedrock 9.55 0.14 2.81 0.06 131.80 1.95 0.01 0.00023 3811.379 10.21 0.0036 0.78 np 56.3 141.3 2.6 3.3 0.06
15-MK-4c Bedrock 11.43 0.17 2.39 0.04 94.39 1.47 0.01 0.00017 4917.705 11.99 0.0026 0.77 np 55.7 103.4 2.8 3.7 0.06
15-MK-4e Bedrock 8.24 0.12 4.29 0.07 78.01 1.23 0.01 0.00020 5278.329 9.25 0.0022 0.75 pp 49.5 112.6 3.8 5.1 0.08
15-MK-4f Bedrock 13.69 0.20 1.27 0.02 100.32 1.53 0.02 0.00022 3880.167 13.99 0.0058 0.81 np 61.7 188.6 2.1 2.6 0.04
17-MK-01a Bedrock 34.60 0.49 1.81 0.03 164.04 2.40 0.0121 0.00011 3390.636 35.03 0.0036 0.77 np 51.0 170.5 0.7 0.9 0.01
17-MK-01b†† Bedrock 34.53 0.49 1.42 0.02 161.61 2.34 0.0190 0.00020 6604.692 34.86 0.0029 0.76 pp 50.8 138.3 1.4 1.8 0.02
17-MK-01c Bedrock 65.33 0.93 2.74 0.07 234.39 3.51 0.0148 0.00020 6555.823 65.98 0.0023 0.74 pp 45.7 133.8 0.7 1.0 0.01
17-MK-01d Bedrock 50.06 0.72 1.91 0.03 165.72 2.46 0.0114 0.00013 4936.816 50.51 0.0023 0.75 pp 49.5 117.0 0.7 0.9 0.01
17-MK-05a Bedrock 10.41 0.15 1.24 0.02 14.61 0.23 0.0302 0.00016 3379.834 10.70 0.0089 0.82 nn 62.9 280.1 2.4 3.0 0.04
17-MK-05b Bedrock 7.24 0.10 0.68 0.01 14.31 0.22 0.0211 0.00021 2465.758 7.40 0.0086 0.83 nn 68.5 226.6 2.5 3.0 0.04
17-MK-05c Bedrock 15.61 1.35 1.52 0.02 19.79 0.31 0.0285 0.00014 5805.044 15.97 0.0049 0.81 pp 66.0 140.0 2.8 3.4 0.24
17-MK-05d Bedrock 8.23 0.12 0.68 0.01 14.43 0.22 0.0356 0.00020 2994.029 8.39 0.0119 0.84 np 76.7 250.9 2.8 3.3 0.04
17-MK-08a Bedrock 25.72 0.37 0.77 0.01 112.59 1.65 0.0770 0.00035 10878.685 25.90 0.0071 0.82 pp 66.0 201.4 3.4 4.1 0.05
17-MK-08b Bedrock 29.62 0.42 0.94 0.01 214.85 3.13 0.0479 0.00016 13791.177 29.84 0.0035 0.76 np 48.8 181.1 3.6 4.8 0.05
17-MK-08c Bedrock 34.16 0.49 1.06 0.02 167.73 2.45 0.0765 0.00041 13131.879 34.41 0.0058 0.82 np 70.0 147.5 3.1 3.7 0.05
17-MK-08d†† Bedrock 54.89 0.78 1.72 0.03 215.37 3.16 0.3795 0.00077 53657.781 55.30 0.0071 0.82 np 68.5 187.3 8.0 9.7 0.11
17-MK-17a† Bedrock 0.07 0.01 0.02 0.01 -0.01 0.04 0.1616 0.00039 48885.907 0.07 0.0033 0.77 np 54.1 140.1 3520.1 4544.6 212.08
17-MK-17b** Bedrock 19.33 0.28 0.35 0.01 134.42 1.96 0.1171 0.00035 26046.633 19.41 0.0045 0.79 np 58.5 163.0 10.8 13.6 0.16
17-MK-17c** Bedrock 19.76 0.28 0.30 0.00 185.74 2.78 0.0929 0.00052 10474.071 19.83 0.0089 0.84 np 76.7 187.3 4.2 5.1 0.06
17-MK-17d** Bedrock 38.43 0.55 0.66 0.01 240.72 3.59 0.0227 0.00013 4746.750 38.58 0.0048 0.79 np 54.8 197.9 0.9 1.2 0.01
17-MK-04a Bedrock 34.27 0.49 0.99 0.02 185.87 2.71 0.0255 0.00027 6981.904 34.51 0.0037 0.77 np 52.6 164.3 1.5 2.0 0.03
17-MK-04c Bedrock 38.31 0.56 2.29 0.03 260.39 3.92 0.0203 0.00016 9882.243 38.85 0.0021 0.74 pp 46.4 118.8 1.9 2.5 0.03
17-MK-04d Bedrock 66.36 0.95 1.72 0.25 240.89 3.48 0.0162 0.00018 13190.256 66.76 0.0012 0.69 pp 39.5 97.6 1.4 2.0 0.03
17-MK-04e Bedrock 24.07 0.35 1.27 0.02 191.30 2.76 0.0262 0.00016 8515.590 24.37 0.0031 0.78 pp 61.2 102.0 2.6 3.4 0.04
17-MK-11a Bedrock 6.95 0.10 0.24 0.00 51.80 0.74 0.0167 0.00017 1878.214 7.01 0.0089 0.84 np 75.3 194.3 1.9 2.3 0.03
17-MK-11b Bedrock 33.28 2.52 3.85 0.06 71.21 1.04 0.0566 0.00026 9237.301 34.18 0.0061 0.81 nn 65.4 178.0 2.2 2.6 0.16
17-MK-11c Bedrock 22.33 0.32 5.05 0.07 81.42 1.19 0.0342 0.00021 6982.251 23.52 0.0049 0.80 nn 60.1 168.7 2.3 2.9 0.03
17-MK-11g Bedrock 10.02 0.14 5.26 0.08 41.02 0.64 0.0178 0.00011 4307.486 11.25 0.0041 0.79 pp 59.2 146.2 2.8 3.5 0.04
17-MK-15a Bedrock 21.75 0.31 1.63 0.03 238.15 3.41 0.0142 0.00018 3742.965 22.13 0.0038 0.78 pp 53.5 165.2 1.2 1.5 0.02
17-MK-15b Bedrock 42.70 0.61 2.87 0.04 253.55 3.64 0.0146 0.00010 6793.073 43.38 0.0021 0.75 pp 50.1 106.0 1.1 1.5 0.02
17-MK-15c Bedrock 38.99 0.56 4.03 0.06 259.26 3.78 0.0247 0.00023 8474.134 39.93 0.0029 0.74 nn 43.3 193.5 1.6 2.2 0.03
17-MK-15d Bedrock 21.21 0.30 1.38 0.02 236.43 3.54 0.0157 0.00007 4601.552 21.53 0.0034 0.77 np 51.0 163.0 1.5 2.0 0.02
17-MK-19a** Bedrock 16.63 0.24 0.42 0.01 273.94 3.94 0.0220 0.00010 4384.532 16.73 0.0050 0.80 np 60.7 168.7 1.9 2.4 0.03
17-MK-19b** Bedrock 37.73 0.54 2.29 0.03 280.89 4.16 0.0244 0.00025 6327.708 38.27 0.0039 0.79 pp 57.9 143.1 1.2 1.6 0.02
17-MK-19c** Bedrock 27.31 0.39 0.42 0.01 256.55 3.76 0.0379 0.00020 10064.321 27.40 0.0038 0.77 nn 51.9 173.6 2.8 3.7 0.04
17-MK-19d** Bedrock 10.23 0.15 0.33 0.01 110.71 1.67 0.0293 0.00014 5351.839 10.31 0.0055 0.79 nn 56.1 216.0 3.9 5.0 0.06

50
Supplementary Table 1

Single-grain (U-Th-Sm)/He apatite analyses

Sample Sample U U SD Th Th SD Sm Sm SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief

Type (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg) (um) (um) (Ma) (Ma) (Ma) (m)
17-MK-21f Bedrock 12.92 0.19 1.54 0.03 20.56 0.34 0.0110 0.00016 2720.450 13.28 0.0040 0.79 pp 60.3 138.3 1.4 1.7 0.03
17-MK-21k Bedrock 8.01 0.73 2.57 0.04 23.74 0.36 0.0169 0.00024 2073.075 8.61 0.0082 0.84 np 77.5 168.7 1.7 2.1 0.15
17-MK-21L Bedrock 7.74 0.11 3.86 0.06 29.24 0.45 0.0199 0.00015 1577.652 8.64 0.0126 0.76 multigrain -- -- 1.3 1.8 0.02
17-MK-21m Bedrock 5.61 0.08 4.34 0.06 27.65 0.41 0.0205 0.00015 1341.913 6.63 0.0153 0.78 multigrain -- -- 1.5 1.9 0.02
17-MK-22e† Bedrock 2.84 0.04 4.65 0.07 45.48 0.67 0.0176 0.00006 843.480 3.93 0.0208 0.86 np 84.4 363.6 1.5 1.8 0.02
17-MK-22f Bedrock 5.11 0.07 12.71 0.18 43.60 0.64 0.0438 0.00024 1487.944 8.10 0.0294 0.82 multigrain -- -- 1.4 1.7 0.02
17-MK-22g† Bedrock 3.97 0.06 10.34 0.15 47.29 0.69 0.0197 0.00019 932.830 6.40 0.0212 0.82 multigrain -- -- 1.1 1.3 0.01
17-MK-22h Bedrock 7.47 0.11 23.09 0.33 69.09 1.03 0.0435 0.00019 1961.101 12.90 0.0222 0.81 multigrain -- -- 1.2 1.5 0.01
17-MK-22i Bedrock 5.03 0.07 14.59 0.21 52.20 0.77 0.0196 0.00009 1281.170 8.45 0.0153 0.83 multigrain -- -- 1.1 1.3 0.01
17-MK-23a Bedrock 15.21 0.22 1.96 0.03 173.55 2.59 0.0204 0.00013 3689.391 15.67 0.0055 0.81 np 62.5 175.3 1.7 2.1 0.03
17-MK-23b†† Bedrock 20.56 0.30 1.81 0.04 258.87 3.86 0.0665 0.00025 26197.722 20.98 0.0025 0.76 pp 51.0 121.0 9.9 13.0 0.14
17-MK-23c Bedrock 11.87 0.17 0.90 0.03 167.26 2.54 0.0139 0.00017 3917.923 12.09 0.0035 0.77 pp 53.2 155.0 2.2 2.9 0.04
17-MK-23d Bedrock 25.66 0.37 6.47 0.09 118.62 1.82 0.0415 0.00016 4942.310 27.18 0.0084 0.82 np 66.3 237.6 1.4 1.7 0.02
17-MK-24a Bedrock 37.85 0.54 0.71 0.02 144.28 2.13 0.0164 0.00014 5196.730 38.02 0.0031 0.76 np 47.9 170.1 1.0 1.3 0.02
17-MK-24c Bedrock 36.90 0.52 0.76 0.01 171.01 2.51 0.0269 0.00019 5528.365 37.08 0.0049 0.80 np 60.7 163.9 1.1 1.4 0.02
17-MK-24d Bedrock 14.08 0.21 0.54 0.01 117.35 1.80 0.0169 0.00011 2207.846 14.21 0.0076 0.83 np 71.8 184.2 1.1 1.3 0.02
17-MK-24e Bedrock 12.17 0.17 0.42 0.01 123.41 1.87 0.0190 0.00013 1817.003 12.27 0.0104 0.85 pp 88.3 166.1 1.1 1.3 0.02
17-MK-24f Bedrock 33.19 0.47 1.14 0.07 321.08 4.86 0.0126 0.00010 4950.734 33.46 0.0025 0.76 np 50.1 125.9 1.0 1.3 0.02
17-MK-26a†† Bedrock 14.05 0.21 1.15 0.02 136.15 2.04 0.0514 0.00021 20265.540 14.32 0.0025 0.75 nn 49.3 129.9 11.1 14.7 0.16
17-MK-26c Bedrock 24.67 0.36 1.50 0.02 163.55 2.46 0.0241 0.00019 4275.373 25.02 0.0056 0.81 nn 67.6 153.4 1.3 1.6 0.02
17-MK-26d Bedrock 31.58 0.45 2.64 0.04 184.56 2.82 0.0292 0.00017 6170.894 32.20 0.0047 0.80 np 61.0 158.1 1.5 1.8 0.02
17-MK-26e Bedrock 15.45 0.22 1.12 0.02 112.11 1.65 0.0183 0.00005 2698.389 15.71 0.0068 0.83 np 72.2 161.2 1.2 1.5 0.02
17-MK-28a** Bedrock 14.86 0.58 0.69 0.02 124.49 1.88 0.0135 0.00009 3893.956 15.03 0.0035 0.79 pp 61.0 115.7 1.8 2.3 0.07
17-MK-28b** Bedrock 15.03 0.22 0.61 0.01 187.50 2.82 0.1297 0.00034 18116.950 15.17 0.0072 0.82 pp 69.1 186.0 9.6 11.6 0.14
17-MK-28c†† Bedrock 13.30 0.19 0.34 0.01 188.10 2.78 0.2326 0.00037 54552.733 13.38 0.0043 0.78 nn 55.4 172.3 32.8 41.9 0.47
17-MK-28d** Bedrock 11.93 0.17 0.44 0.01 128.18 1.98 0.0310 0.00015 6026.323 12.03 0.0051 0.80 np 59.9 178.0 3.8 4.8 0.06
17-PN-WP1a Bedrock 7.44 0.11 0.72 0.01 10.40 0.16 0.0225 0.00018 2571.418 7.60 0.0087 0.83 pp 70.9 216.0 2.5 3.1 0.04
17-PN-WP1b Bedrock 6.18 0.09 0.58 0.01 9.70 0.26 0.0121 0.00014 3149.718 6.32 0.0039 0.78 pp 56.1 151.9 3.4 4.3 0.06
17-PN-WP1c Bedrock 5.58 0.08 0.89 0.02 8.95 0.16 0.0114 0.00010 2455.978 5.79 0.0046 0.80 np 60.1 159.9 2.9 3.6 0.05
17-PN-WP1d Bedrock 7.44 0.21 3.78 0.06 10.11 0.20 0.0140 0.00012 2582.244 8.33 0.0054 0.79 np 54.1 229.3 2.2 2.8 0.06
†Age excluded from calculation of mean age and standard error due to low uranium content (<5 ppm).

††Bedrock age identified as an outlier by the statistical test of Dean and Dixon (1951) at the 90 percent confidence interval and excluded from calculation of mean age and standard error.

*Detrital age greater than the sum of the maximum elevation-derived age difference for the catchment and the mean age for the sample after <5 ppm uranium outliers are removed. We calculate the maximum elevation-derived age difference using a conservative exhumation

rate of 0.3mm/yr. Age excluded from calculation of mean age.

**One-sigma standard deviation of bedrock replicate analyses after outlier removal is greater than 45 percent of mean age. No mean age reported.

1
Ft is alpha-ejection correction after Farley et al. (1996).
2
The Following terms refer to the morphology of apatite grains: nn = a grain with two unbroken euhedral tips; pp = a grain with both tips broken such that they are roughly perpendicular to the c-axis;
np = a grain with one unbroken tip and one tip broken roughly perpendicular to the c-axis; multigrain = multiple apatite grains degassed for
4
He within one packet due to low single-grain
4
He yield.

3
The age error reported for single grained ages represents the propagated one-sigma uncertainty based on the analytical error in measuring He, U, Th and Sm.

51
Supplementary Table 2

Single-grain (U-Th)/He zircon analyses

Sample Sample U U SD Th Th SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief

Type (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg)

(um) (um) (Ma) (Ma) (Ma) (m)
15-MK-2 Zra Detrital 486.81 7.06 246.19 3.53 0.3622 0.00163 154073.831 544.67 0.0024 0.72 nn 40.2 180.6 2.3 3.2 0.03 1503
15-MK-2 Zrb Detrital 381.91 5.58 266.37 4.07 0.8472 0.00300 139538.280 444.50 0.0061 0.79 nn 55.5 245.1 2.6 3.3 0.03
15-MK-2 Zrc Detrital 720.90 10.48 423.58 6.15 1.0072 0.00370 238377.852 820.44 0.0042 0.76 nn 48.6 222.2 2.4 3.1 0.03
15-MK-3 Zra Detrital 1506.39 22.23 87.17 1.30 2.5088 0.00794 504776.121 1526.87 0.0050 0.79 nn 54.8 205.4 2.7 3.5 0.04 2416
15-MK-3 Zrb Detrital 797.46 11.64 406.58 6.01 1.0481 0.00421 264016.005 893.01 0.0040 0.76 nn 48.8 206.7 2.4 3.2 0.03
15-MK-3 Zrc Detrital 467.56 6.77 89.67 1.31 0.5552 0.00254 137650.546 488.64 0.0040 0.77 nn 50.1 199.2 2.3 3.0 0.04
15-MK-5 Zra Detrital 1337.10 19.34 492.24 7.51 1.4395 0.00560 500215.829 1452.77 0.0029 0.74 nn 43.5 188.6 2.8 3.9 0.04 1645
15-MK-5 Zrb Detrital 253.74 3.69 148.17 2.21 0.5390 0.00134 127470.491 288.56 0.0042 0.77 nn 50.2 208.5 3.6 4.7 0.05
15-MK-5 Zrc Detrital 1094.92 15.88 546.88 8.19 1.1015 0.00282 409874.341 1223.44 0.0027 0.74 nn 43.5 176.2 2.8 3.8 0.04
15-MK-6 Zra Detrital 1071.62 15.57 182.52 2.77 1.4996 0.00620 448454.292 1114.52 0.0033 0.73 nn 41.1 246.1 3.3 4.6 0.05 1587
15-MK-6 Zrb Detrital 1334.17 19.44 192.15 2.88 1.5299 0.00420 508697.576 1379.33 0.0030 0.75 nn 46.4 173.6 3.1 4.1 0.04
15-MK-6 Zrc Detrital 1621.86 25.24 1069.23 15.96 2.9178 0.00738 691107.075 1873.13 0.0042 0.77 nn 51.7 196.1 3.1 3.9 0.04
15-MK-7 Zra Detrital 577.79 8.75 319.66 4.93 1.1008 0.00360 237884.441 652.91 0.0046 0.74 nn 42.6 316.3 3.0 4.1 0.04 5308
15-MK-7 Zrb Detrital 461.56 6.70 185.02 2.87 0.9618 0.00294 210101.655 505.04 0.0046 0.77 nn 48.6 240.7 3.4 4.5 0.05
15-MK-7 Zrc Detrital 4018.70 58.64 162.79 2.41 2.7945 0.00789 912011.133 4056.96 0.0031 0.72 nn 40.4 232.8 1.9 2.6 0.03
15-MK-8 Zra Detrital 1798.18 27.10 208.67 3.11 1.5057 0.00438 546244.899 1847.22 0.0028 0.73 nn 41.1 202.7 2.4 3.4 0.04 875
15-MK-8 Zrb Detrital 1560.07 22.61 547.72 8.21 0.8569 0.00240 218085.093 1688.79 0.0039 0.76 nn 47.0 220.4 1.1 1.4 0.01
15-MK-8 Zrc Detrital 2171.10 31.71 26.12 0.40 2.0258 0.00701 626662.983 2177.24 0.0032 0.74 nn 43.3 214.2 2.4 3.2 0.04
15-MK-9 Zra Detrital 670.54 10.24 319.02 4.76 1.9641 0.00641 292160.065 745.51 0.0067 0.81 nn 62.9 210.7 3.2 4.0 0.05 1339
15-MK-9 Zrb Detrital 965.80 17.48 80.76 1.37 1.7427 0.00511 294172.063 984.78 0.0059 0.79 nn 54.8 245.1 2.5 3.1 0.04
15-MK-9 Zrc Detrital 1280.53 19.31 147.95 2.46 1.2198 0.00418 425823.713 1315.29 0.0029 0.75 nn 45.5 171.8 2.7 3.6 0.04
15-MK-10 Zra Detrital 562.72 8.20 111.88 1.66 2.0297 0.00717 260014.211 589.02 0.0078 0.82 np 64.7 231.5 3.7 4.5 0.05 1644
15-MK-10 Zrb Detrital 2249.59 33.52 1114.13 16.99 3.4341 0.01616 900555.890 2511.41 0.0038 0.74 nn 43.3 252.6 3.0 4.0 0.04
15-MK-10 Zrc Detrital 2630.78 38.27 399.52 6.02 4.0086 0.01642 1123148.973 2724.67 0.0036 0.75 np 44.8 220.4 3.4 4.6 0.05
15-MK-11 Zra Detrital 1903.08 27.55 177.83 2.84 3.6710 0.01361 902308.045 1944.87 0.0041 0.77 nn 50.4 199.2 3.8 5.0 0.06 1429
15-MK-11 Zrb Detrital 1524.32 22.11 119.10 1.78 4.9369 0.01922 653671.860 1552.31 0.0076 0.81 nn 59.2 267.7 3.5 4.3 0.05
15-MK-11 Zrc Detrital 1239.00 18.00 158.04 2.30 1.9697 0.00829 706950.764 1276.14 0.0028 0.73 nn 42.6 190.4 4.6 6.3 0.07
15-MK-12 Zra Detrital 1410.24 20.57 92.47 1.43 2.9395 0.01167 619930.526 1431.97 0.0047 0.78 nn 51.7 220.4 3.6 4.6 0.05 1232
15-MK-12 Zrb Detrital 1010.12 14.61 96.59 1.42 1.7004 0.00802 510350.857 1032.82 0.0033 0.75 nn 45.7 197.9 4.1 5.5 0.06
15-MK-12 Zrc Detrital 1249.75 18.23 101.73 1.52 5.5531 0.01418 667011.517 1273.66 0.0083 0.81 nn 59.2 295.1 4.3 5.4 0.06
17-DET-04 Zra Detrital 7660.45 108.92 221.79 3.19 0.75 0.00082 392895.085 7712.57 0.0019 0.70 nn 38.6 158.1 0.4 0.6 0.01 1948
17-DET-04 Zrb Detrital 884.11 12.63 86.20 1.57 0.24 0.00057 76376.766 904.37 0.0031 0.75 nn 45.5 184.6 0.7 0.9 0.01
17-DET-04 Zrc Detrital 2137.77 30.43 218.56 3.18 0.55 0.00119 252085.743 2189.13 0.0022 0.71 nn 39.8 170.0 1.0 1.3 0.01
17-DET-05 Zra Detrital 750.78 10.68 381.76 5.69 3.43 0.00409 565991.764 840.49 0.0061 0.79 nn 54.8 250.9 5.6 7.0 0.07 1765
17-DET-05 Zrb Detrital 1276.98 18.16 124.29 2.51 0.73 0.00124 210085.864 1306.19 0.0035 0.75 nn 45.5 209.8 1.3 1.8 0.02
17-DET-05 Zrc Detrital 719.39 10.20 154.78 2.27 1.28 0.00153 325180.389 755.77 0.0039 0.75 nn 43.9 252.2 3.6 4.8 0.05
17-DET-05 Zrd Detrital 700.33 10.09 133.22 1.91 0.5520 0.00061 146535.140 731.64 0.0038 0.75 nn 46.4 217.4 1.7 2.2 0.02
17-DET-05 Zre Detrital 1433.78 20.39 135.72 1.95 1.2142 0.00151 406728.316 1465.68 0.0030 0.74 nn 44.2 189.9 2.3 3.1 0.03
17-DET-08 Zra Detrital 1362.54 19.39 30.23 0.73 1.21 0.00172 406933.361 1369.64 0.0030 0.74 nn 44.0 190.4 2.5 3.3 0.04 1324
17-DET-08 Zrb* Detrital 218.05 3.10 88.62 1.33 1.10 0.00116 261439.506 238.87 0.0042 0.77 np 50.1 208.1 9.0 11.7 0.12
17-DET-08 Zrc Detrital 390.30 5.55 28.98 0.42 0.65 0.00083 93373.814 397.11 0.0069 0.81 nn 60.1 238.5 1.9 2.4 0.03
17-DET-08 Zrd Detrital 278.70 3.97 81.10 1.17 0.6158 0.00049 108984.592 297.76 0.0057 0.79 nn 55.2 230.1 3.0 3.8 0.04
17-DET-08 Zre Detrital 306.98 4.37 100.43 1.45 0.1214 0.00037 61180.076 330.58 0.0020 0.71 nn 40.4 150.8 1.5 2.1 0.02
15-MK-1 Zra Bedrock 564.17 8.15 227.22 3.27 0.3502 0.00047 134094.099 617.56 0.0026 0.73 nn 42.7 178.0 1.8 2.4 0.02
15-MK-1 Zrb Bedrock 369.67 5.35 261.83 3.75 0.5501 0.00248 99752.046 431.20 0.0055 0.80 nn 60.8 185.5 1.9 2.4 0.03
15-MK-1 Zrc Bedrock 321.92 4.67 240.54 3.46 0.4090 0.00171 107028.910 378.44 0.0038 0.77 np 52.3 173.1 2.3 3.0 0.03
15-MK-4 Zra Bedrock 376.32 5.47 57.84 0.85 0.3862 0.00092 89617.727 389.91 0.0043 0.77 nn 48.6 226.6 1.9 2.5 0.03
15-MK-4 Zrb Bedrock 675.02 10.03 198.08 2.93 0.6543 0.00290 215381.666 721.57 0.0030 0.73 nn 41.1 223.5 2.5 3.4 0.04
15-MK-4 Zrc Bedrock 488.48 7.10 275.16 4.12 0.5099 0.00225 161352.187 553.14 0.0032 0.75 nn 46.4 182.4 2.4 3.2 0.03
17-MK-01 Zra Bedrock 990.58 14.17 215.79 3.07 1.38 0.00172 254051.310 1041.29 0.0054 0.78 nn 51.0 258.4 2.0 2.6 0.03
17-MK-01 Zrb Bedrock 1535.98 22.23 299.98 4.35 1.54 0.00268 385990.155 1606.48 0.0040 0.76 nn 48.8 208.5 2.0 2.6 0.03
17-MK-01 Zrc Bedrock 1350.42 19.16 637.14 9.10 1.49 0.00236 305079.550 1500.15 0.0049 0.78 nn 51.7 227.0 1.7 2.2 0.02
17-MK-05 Zra Bedrock 948.06 13.48 72.58 1.04 2.75 0.00318 375286.111 965.12 0.0073 0.81 nn 62.5 232.8 3.2 4.0 0.05
17-MK-05 Zrb†† Bedrock 981.32 14.00 111.88 1.59 1.94 0.00285 603999.994 1007.61 0.0032 0.75 nn 47.0 179.8 5.0 6.6 0.07
17-MK-05 Zrc Bedrock 626.50 8.93 113.57 1.62 1.40 0.00206 221359.970 653.19 0.0063 0.81 nn 63.2 196.1 2.8 3.5 0.04
17-MK-05 Zrd Bedrock 1244.95 17.75 234.18 3.35 1.1871 0.00120 441284.203 1299.98 0.0027 0.74 nn 43.5 176.2 2.8 3.8 0.04
17-MK-05 Zre Bedrock 1274.94 18.18 156.94 2.25 3.2966 0.00414 437731.376 1311.82 0.0075 0.80 nn 57.2 285.8 2.8 3.5 0.04
17-MK-08 Zra Bedrock 173.56 2.72 58.36 0.87 0.33 0.00063 81098.516 187.27 0.0040 0.77 nn 50.6 194.8 3.6 4.6 0.05
17-MK-08 Zrb Bedrock 747.65 10.67 270.20 3.84 1.50 0.00232 368160.458 811.15 0.0041 0.77 nn 49.3 208.5 3.8 4.9 0.05
17-MK-08 Zrc Bedrock 823.04 11.72 167.12 2.40 2.06 0.00172 414141.355 862.31 0.0050 0.79 nn 55.7 199.3 4.0 5.0 0.05

52
Supplementary Table 2

Single-grain (U-Th)/He zircon analyses

Sample Sample U U SD Th Th SD He He error He Effective uranium (eU) Mass FT
1
Shape
2
Radius Length Uncorrected Age Corrected Age Age Error
3
Catchment Relief

Type (ppm) (ppm) (ppm) (ppm) (ncc) (ncc) (ncc/g) (ppm) (mg)

(um) (um) (Ma) (Ma) (Ma) (m)
17-MK-17 Zrb Bedrock 679.03 9.64 63.86 0.93 0.67 0.00154 135839.044 694.03 0.0049 0.78 nn 53.9 210.2 1.6 2.1 0.02
17-MK-17 Zrc Bedrock 902.63 12.90 121.38 1.74 0.91 0.00090 184938.503 931.16 0.0049 0.77 nn 50.4 242.1 1.6 2.1 0.02
17-MK-17 Zrd Bedrock 656.38 9.33 152.05 2.18 0.74 0.00103 129731.456 692.11 0.0057 0.79 nn 55.4 229.7 1.5 2.0 0.02
††Bedrock age identified as an outlier by the statistical test of Dean and Dixon (1951) at the 90 percent confidence interval and excluded from calculation of mean age and standard error.

*Detrital age greater than the sum of the maximum elevation-derived age difference for the catchment and the mean age for the sample. We calculate the maximum elevation-derived age difference using a

conservative exhumation rate of 0.3mm/yr. Age excluded from calculation of mean age.

1
Ft is alpha-ejection correction after Farley et al. (1996).

2
The Following terms refer to the morphology of apatite grains: nn = a grain with two unbroken euhedral tips; np = a grain with one unbroken tip and one tip broken roughly perpendicular to the c-axis.

3
The age error reported for single grained ages represents the propagated one-sigma uncertainty based on the analytical error in measuring He, U, and Th.

Abstract (if available)

Abstract Landslides are a primary erosional agent in active orogens and a key natural hazard in mountainous parts of the world. The threshold hillslope concept describes the role of landslides in landscape development: in response to tectonic uplift, rivers cut downward, steepening slope angles until they eventually reach a threshold, beyond which erosion rates increase via landsliding. Many slopes near the threshold angle remain stable until perturbed, often by heavy rainfall or earthquakes. Earthquakes trigger large numbers of landslides in a single event, generating “cascading hazards” as well as feedbacks between seismicity and erosion. While multi-decadal landslide distributions fit predictions of the threshold hillslope model, similar evidence has not been observed for landslides triggered by a major earthquake. Here, we investigate the distribution of landslides triggered by the 2015 Gorkha Earthquake, in relation to metrics describing landscape steepness and new (U-Th)/He thermochronometric data. Susceptibility to landslide failure in the event increased with proximity to channels of higher normalized channel steepness and was correlated with younger thermochronometric ages, consistent with a threshold slope control on earthquake-triggered landsliding and suggesting that fluvial response to tectonics may help inform landslide hazard prediction.

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Asset Metadata

Creator Quackenbush, Paul Joseph Maffei (author)

Core Title Tectonic control on landsliding revealed by the 2015 Gorkha earthquake

School College of Letters, Arts and Sciences

Degree Master of Science

Degree Program Geological Sciences

Publication Date 07/02/2018

Defense Date 06/26/2018

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag earthquake,fluvial incision,Geomorphology,Gorkha,landscape evolution,Landslides,natural hazards,Nepal, thermochronometry,normalized channel steepness,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor West, A. Joshua (committee chair), Dolan, James (committee member), Okaya, David (committee member)

Creator Email pquacken@usc.edu,pquacken2@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-508995

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Rights Quackenbush, Paul Joseph Maffei

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Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

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