Comparison of basin-scale in situ and meteoric ¹⁰Be erosion and denudation rates in felsic lithologies across an elevation gradient at the George River, northeast Tasmania, Australia

Long-term erosion rates in Tasmania, at the southern end of Australia's Great Dividing Range, are poorly known; yet, this knowledge is critical for making informed land-use decisions and improving the ecological health of coastal ecosystems. Here, we present quantitative, geologically relevant estimates of erosion rates for the George River basin, in northeast Tasmania, based on in situ-produced ¹⁰Be (¹⁰Be_i) measured from stream sand at two trunk channel sites and seven tributaries (mean: 24.1±1.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$; 1σ). These new ¹⁰Be_i-based erosion rates are strongly related to elevation, which appears to control mean annual precipitation and temperature, suggesting that elevation-dependent surface processes influence rates of erosion in northeast Tasmania. Erosion rates are not correlated with slope in contrast to erosion rates along the mainland portions of Australia's Great Dividing Range. We also extracted and measured meteoric ¹⁰Be (¹⁰Be_m) from grain coatings of sand-sized stream sediment at each site, which we normalize to measured concentrations of reactive ⁹Be and use to estimate ¹⁰Be_m-based denudation rates for the George River. ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates replicate ¹⁰Be_i erosion rates within a factor of 3 but are highly sensitive to the value of ⁹Be that is found in bedrock (⁹Be_parent), which was unmeasured in this study. ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates seem sensitive to recent mining, forestry, and agricultural land use, all of which resulted in widespread topsoil disturbance. Our findings suggest that ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation metrics will be most useful in drainage basins that are geologically homogeneous, where recent disturbances to topsoil profiles are minimal, and where ⁹Be_parent is well constrained.

1 Introduction and the importance of the George River, Tasmania

Erosion rates of river basins derived from measurements of the in situ-produced cosmogenic isotope, ¹⁰Be_i, have been used to infer topographic, tectonic, and climatic drivers of landscape evolution for thousands of individual river basins (Codilean et al., 2018; Harel et al., 2016; Mishra et al., 2019; Portenga and Bierman, 2011; Wittmann et al., 2020) and to contextualize the effects of land use on erosion and sediment dynamics (Portenga et al., 2019; Schmidt et al., 2018). Sufficient data now exist that erosion rates from individual studies have been compiled and analyzed at the scale of entire continental orogens to demonstrate primary and secondary controls on erosion across thousands to tens of thousands of years (Aguilar et al., 2014; Carretier et al., 2018; Codilean et al., 2021; Delunel et al., 2020; Starke et al., 2020). For example, Delunel et al. (2020) find that ¹⁰Be_i erosion rates across the European Alps are strongly linked to mean basin slope and influenced by uplift and glaciation. A number of north–south latitudinal studies from the South American Andes show that erosion in some segments of the range is driven by uplift (Carretier et al., 2015; Starke et al., 2017) and slope (Carretier et al., 2018) but not necessarily by rainfall unless one considers the effects of vegetation in driving soil weathering rates (Carretier et al., 2015; Starke et al., 2020). A new compilation and analysis of ¹⁰Be_i erosion rates across the Great Dividing Range of eastern Australia is the first to analyze landscape dynamics across a continent-spanning, passive, post-orogenic rift margin and finds that basin slope is most closely related to erosion at all spatial scales, more so than any other potential driver of erosion (Codilean et al., 2021). While Codilean et al.'s (2021) analysis comprises erosion rates from the western and eastern flanks of the Great Dividing Range – from tropical rainforests in northern Queensland to temperate southeast Victoria – it is restricted to mainland Australia.

Despite the widespread measurement of ¹⁰Be_i to elucidate erosion rates globally, erosion rate data do not exist for many areas of Earth's surface. An understanding of drivers of erosion will be improved by measuring erosion rates in these understudied areas. In this study, we supplement Codilean et al.'s (2021) erosion compilation with the first ¹⁰Be_i-based erosion rates from the southernmost end of the eastern Australian passive margin on the island state of Tasmania, specifically the George River basin (Fig. 1). Data in this study are also the first erosion rates measured in temperate rainforests of the Southern Hemisphere (cf. Adams and Ehlers, 2017; Belmont et al., 2007). Quantitative erosion rate data for Tasmania and many of its fluvial systems are currently lacking (Jerie et al., 2003; Koehnken, 2001); data, such as we provide here, are useful information for land managers and for estuary restoration efforts.

Figure 1 Generalized tectonic map of the eastern Southern Ocean and southwest Pacific Ocean, surrounding Tasmania, including large-scale geologic structures in southeast Australia and Tasmania: double-black lines are active mid-ocean ridges; bold dashed black line are convergent plate boundaries; thin solid black lines are transform boundaries. Inset shows detailed topography of Tasmania. The main George River basin is shown outlined in black. Major estuaries of other Tasmanian river systems are indicated for reference: Derwent Estuary (DE), Macquarie Harbour (MH), Tamar Estuary (TE), Georges Bay (GB). Cities are shown with black dots for reference: Hobart (H), Launceston (L), St. Helens (SH).

The George River empties into Georges Bay (with an “s”), which is known for its oyster stocks (Mitchell et al., 2000) but has been degraded by a history of timber production, tin mining, and agriculture. Historical land-use practices in the catchment have supplied > 10⁶ m³ of sediment to Georges Bay since the late 19th century (Knighton, 1991) and continue to release pollutants into the bay (Bleaney et al., 2015; Crawford and White, 2005). The success of efforts to rehabilitate Georges Bay relies in part on reducing sediment delivery from the George River to Georges Bay to pre-disturbance levels (Batley et al., 2010; Crawford and White, 2005; Kragt and Newham, 2009; McKenny and Shepherd, 1999; Mount et al., 2005), but no pre-disturbance erosion data exist for the George River, nor do any geologically relevant erosion rates exist for any part of Tasmania. Measuring erosion rates for the George River contributes to the growing geomorphological understanding of the drivers of erosion in Tasmania, across Australia, and in similar geological settings elsewhere.

Quantifying landscape dynamics with in situ and meteoric ¹⁰Be

The primary goal of this study is to provide background rates (over millennia) of landscape change in the George River basin using the in situ cosmogenic isotope beryllium-10 (¹⁰Be_i) in fluvial sediment (Bierman and Steig, 1996; Brown et al., 1995; Granger et al., 1996). ¹⁰Be_i production decreases exponentially with depth in rock and sediment near Earth's surface such that ¹⁰Be_i concentrations at depths > 2 m are much lower compared to those measured closer to Earth's surface (Gosse and Phillips, 2001; Lal, 1991). ¹⁰Be_i produced by muons dominates at depths > 2 m (Braucher et al., 2003; Gosse and Phillips, 2001; Heisinger et al., 1997), but muogenic ¹⁰Be_i production is negligible when compared to near-surface spallogenic ¹⁰Be_i production, except in rapidly eroding landscapes or landscapes with steep terrain (e.g., Dethier et al., 2014; Fellin et al., 2017; Rosenkranz et al., 2018; Scherler et al., 2014; Siame et al., 2011). Bioturbation homogenizes ¹⁰Be_i concentrations in soils, in many places to depths of at least ∼ 1 m (Brown et al., 1995; Schaller et al., 2018), and thus ¹⁰Be_i erosion rates are largely insensitive to widespread shallow erosion. This insensitivity allows ¹⁰Be_i erosion rates to be a useful gauge of pre-disturbance rates of landscape change (Ferrier et al., 2005; Portenga et al., 2019; Schmidt et al., 2018; Vanacker et al., 2007), except where human land use is intensive (i.e., Schmidt et al., 2016) or the effects of human land use are exacerbated by climate extremes (i.e., Rosenkranz et al., 2018). Pre-disturbance ¹⁰Be_i erosion data can thus inform approaches to reducing sediment delivery from the George River and support efforts to improve the ecological health of the Georges Bay estuary and possibly other watersheds in northeast Tasmania that share similar bedrock and topographic characteristics by providing a benchmark against which to compare modern sediment loads.

In addition to ¹⁰Be_i, which is produced in rock and sediment, ¹⁰Be is also produced via spallation of oxygen and nitrogen in the atmosphere; this ¹⁰Be rains out or falls to Earth's surface (meteoric ¹⁰Be; ¹⁰Be_m; Heikkilä and von Blanckenburg, 2015; Monaghan et al., 1986; Reusser et al., 2010) where it is readily adsorbed into sediment grain coatings. ¹⁰Be_m has traditionally been used to trace sediment through landscapes (Brown et al., 1988; Helz et al., 1992; Portenga et al., 2017; Reusser and Bierman, 2010; Valette-Silver et al., 1986), but recently derived equations (along with a series of assumptions) now allow denudation rates to be calculated from measurements of ¹⁰Be_m that are normalized to non-cosmogenic, stable ⁹Be, which weathers out of mineral grains (⁹Be_reac; von Blanckenburg et al., 2012). ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates have been used to quantify landscape evolution over a variety of spatial scales for different river basins (Dannhaus et al., 2018; Deng et al., 2020; Portenga et al., 2019; Rahaman et al., 2017; Wittmann et al., 2012, 2015; in some cases ¹⁰Be_m is referred to as the reactive phase of ¹⁰Be_m [¹⁰Be_reac], and denudation rates may be referred to as ¹⁰Be_reac/⁹Be_reac denudation rates) and have shown promise in quantifying landscape dynamics in quartz-poor landscapes (Deng et al., 2020; Rahaman et al., 2017).

In this study, we use both ¹⁰Be_i and ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ to measure the rates at which mass is lost from the George River basin's slopes. Over timescales sufficiently long that the assumption of steady state is approached, all of this mass will transported to the Georges Bay. Such mass loss from the George River basin is both chemical (dissolved load) and physical (sediment transport). The partitioning between these phases differs dramatically around the world depending on rock type, topography, and weathering regime and likely differs within the study basin. The assumptions underlying these two methods (¹⁰Be_i and ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$) differ; thus, results from each method may not be the same. The concentration of ¹⁰Be_i is biased towards mass loss within the upper meters of Earth's surface where rates of neutron spallation are high. Both chemical and physical mass losses within this surface layer of regolith are reflected by ¹⁰Be_i concentrations. ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$, if the assumptions of the analytical model are met, reflects both physical and chemical mass loss throughout the regolith, regardless of depth.

The terms “erosion” and “denudation” have been used without precision in the literature, often as a replacement for one another. Erosion is applied more often to rates calculated using the concentration of ¹⁰Be_i; rates calculated using ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ are more frequently referred to as denudation. We follow that convention in this paper. Because we have dissolved and suspended load data as well as river flow over time from the mouth of the George River, we attempt to provide a full discussion of what the rates we measure mean for landscape dynamics within the George River basin.

The small size and relatively uniform bedrock geology of the George River basin provide an ideal location to compare ¹⁰Be_i erosion rates with ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates (von Blanckenburg et al., 2012). ¹⁰Be_m can be desorbed from sediment grain coatings under low-pH conditions (Aldahan et al., 1999; You et al., 1989), but ¹⁰Be_m loss from soil profiles in solution is likely minimal in the George River basin, because measured soil pH values in the catchment range from 4.0–5.5 (Kidd et al., 2015) and long-term monitoring of stream water pH at two gauging stations – one in Ransom Creek and the other at the George River in St. Helens – shows that stream pH is consistently > 5 and mostly > 6 (DPIPWE, 2021a, b). The George River basin is a landscape of relative geological homogeneity in comparison to more geologically diverse landscapes with similar datasets (i.e., Deng et al., 2020; Portenga et al., 2019; Rahaman et al., 2017). Although the George River has a simple bedrock geology, it also has a long history of forestry and lode and placer tin mining that has, in the past, disturbed the hillslopes and fluvial systems (Knighton, 1991; Preston, 2012). Given that land use is speculated to affect the results of ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-derived denudation rate calculations elsewhere (Portenga et al., 2019), we also explore how land use in the George River affects our interpretations of ¹⁰Be-based erosion and denudation calculations in this study.

2 Field area

Tasmania separated from mainland Australia during Cretaceous rifting of Antarctica and Australia and sits at the southern end of the Great Australian Escarpment – a steep arch-type escarpment that formed during the separation of Zealandia from mainland Australia in the middle to Late Cretaceous (Fig. 1; Codilean et al., 2021; Crowder et al., 2019; Etheridge et al., 1987; Gaina et al., 1998; Griffiths, 1971; Gunn, 1975; Hayes and Ringis, 1973; Lanyon et al., 1993; Matmon et al., 2002; McDougall and van der Lingen, 1974; Mortimer et al., 2017; Persano et al., 2002; Sutherland et al., 2001; Weissel and Hayes, 1977). Bedrock of the George River basin is granodiorite and granite associated with the Blue Tier Batholith (S-type granites), which was emplaced into sediments of the Mathinna Supergroup in the Devonian (Fig. 2; Foster et al., 2000; Gee and Groves, 1971; Gray and Foster, 2004; Higgins et al., 1985; McCarthy and Groves, 1979; Seymour et al., 2006). Siluro-Devonian sedimentary rocks and Neogene basalts underlie small areas, primarily along drainage divides in the central and the western George River basin (Seymour et al., 2006).

Figure 2 (a) Elevation map of the topography of the George River basin. Sample collection sites (white circles), active and inactive Australian Bureau of Meteorology rainfall gauging stations (upright and inverted cyan triangles, respectively), and temperature logger locations (green stars) are shown (Webb et al., 2018, 2020). (b) Bedrock geology map of George River shows the widespread occurrence of Devonian felsic intrusions of the Blue Tier Batholith, which underlies the vast majority of the field area. Note that basins TG-2, TG-4, TG-5, and TG-8 are almost entirely underlain by Devonian felsic intrusions. Areas of historic mining are shown (pink squares and polygons; Knighton, 1991), the action of which delivered > 10⁶ m³ to the George River delta in Georges Bay (GB). Locations of boreholes that strike bedrock are shown by yellow diamonds (BoM, 2015). Maps are projected in UTM Zone 55S; coordinates shown in panel (b) are the same for panel (a). Topographic relief base maps come from the ArcGIS Online World Topographic Map (Esri, 2012).

Table 1 Meteorological and bedrock data for the George River basin.

^a Years listed in data ranges are the first and last years for which 12 months of data are available. ^b Temperature logger data sourced from the State of Tasmania Air Temperature Logger Recording Database, used by Webb et al. (2018, 2020). Each year has temperature recorded for at least 30 % of days (average = 71 %). ^c Depth to regolith measured in boreholes (BoM, 2015).

The George River basin, located in northeastern Tasmania, is of modest size (557 km²) with low elevation (mean: 386 m) and gentle hillslopes (mean: 10^∘). It drains the eastern slopes of the Rattler Range, which currently has a warm, temperate climate (Kottek et al., 2006). Despite eastern Tasmania being in the rain shadow of the central Tasmanian Highlands and western coast ranges, measurements from rainfall gauging stations and temperature data loggers within and near the George River basin show that the local topography of the Ben Lomond Plateau induces strong relationships across the basin between elevation, mean annual precipitation, and mean annual temperature (Fig. 3; Table 1; BoM, 2021; Webb et al., 2018, 2020).

Figure 3 (a) Mean annual precipitation from active (cyan triangles) and inactive (inverted cyan triangles) Australian Bureau of Meteorology rainfall gauging stations across George River basin that have at least 1 full year of recorded data exhibiting a strong correlation with station elevation. (b) Mean annual temperature (green stars) taken from temperature loggers with > 2 years of nearly daily data showing a strong inverse correlation with elevation. Precipitation and temperature data shown in Table 1.

Human land use in Tasmania begins > 35 ka, when Aboriginal Australians crossed to the island from the Australian mainland (Cosgrove, 1995; Cosgrove et al., 1990), possibly corresponding to subaerial exposure of the Bass Strait ∼ 56–40 ka (MacIntosh et al., 2006) and localized ice advances in the central Tasmanian highlands (Barrows et al., 2001, 2002; Colhoun, 2002; MacIntosh et al., 2006). Ecological habitat suitability models, based on characteristics and locations of thousands of archeological sites across Tasmania, indicate that Aboriginal communities were located close to freshwater sources and coastal resources, such as the landscapes around Georges Bay and the lower elevations within tributaries to the George River (Jones et al., 2019). Human arrival in Tasmania has been linked to widespread erosion events in mid-elevation landscapes (McIntosh et al., 2009).

More recently, decades of intensive tin lode mining in isolated headwaters of some tributaries and pockets of hydraulic sluice mining for tin in lowland floodplains introduced > 10⁶ m³ of tailings to the George River and its tributaries (Fig. 2a). Knighton (1991) notes that the pre-mining average grain size of alluvium for the George River was 30–50 mm, and that this was reduced to 1–2 mm during the mining era; however, it is not clear whether the 30–50 mm average grain size was specific to one sample site, or for the George River as a whole. Knighton (1991) notes that bedload characteristics have since returned to their pre-disturbance values following widespread alluvium storage in floodplains and aggradation at the George River delta in Georges Bay (Cheetham and Martin, 2018; Martin and Cheetham, 2018). Despite the George River's return to pre-disturbance channel and bedload characteristics, a study from an experimental forest in the Gentle Annie tributary to the George River shows that sediment yields from logged plots continue to be elevated relative to sediment yields from unlogged plots (Wilson, 1999). More recently, land use within the George River basin in 2008, at the time of sample collection, consisted primarily of forestry production from relatively natural environments and secondarily of conservation land (Fig. 4); intensive land use (i.e., built structures, permanent land alteration) and agricultural production from unirrigated land occur in equal proportion, though much less than the primary and secondary land uses. Only a small percentage of the George River basin is used for agricultural production from irrigated lands (ABARES, 2016).

Figure 4 Land cover for each sampled tributary catchment in the George River basin from 2001 (top), 2005 (center), and 2010 (bottom) – the period of leading up to and immediately following sample collection in 2008. The Australian Land Use and Management Classification system groups land use into five primary classes based on their potential to impact the natural environment (ABARES, 2016). The white square denotes location of the Gentle Annie experimental catchment (Wilson, 1999). Stippled areas outlined in white are areas that have been affected by forest fires or prescribed burns in the past (Land Tasmania, 2020). Maps are projected in UTM Zone 55S. Topographic relief base maps come from the ArcGIS Online World Topographic Map (Esri, 2012).

Table 2 Sample locations and topographical basin data.

^a Based or derived from Satellite Radar Topography Mission data, 90 m resolution (Gallant et al., 2011). Mean local relief calculated using a 10-cell (∼ 900 m) circular moving window. ^b Used in the calculation of the meteoric ¹⁰Be delivery rate, ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$, for each catchment (Graly et al., 2011). Calculated using the basin average elevation and using the regression equation between elevation and mean annual precipitation at Australian Bureau of Meteorology stations (Figs. 2 and 3; Table 1). ^c Erosivity ratings from Kidd et al. (2014, 2015).

3 Methods

3.1 Sample collection and measurement

Sediment samples for this study were collected in 2008 from several locations along the trunk (n = 2) and tributaries (n = 7) of the George River (samples TG-1 through TG-9; Fig. 2; Table 2), upstream of which channels are generally concave-up and therefore in geomorphic steady state (Fig. 5). At each site, sediment was collected from the streambed and/or in-channel bars to ensure active fluvial transport and mixing. Samples were sieved in the field to the 250–850 µm grain-size fraction. Although this grain size is finer than the mean natural grain size (30–50 mm; Knighton, 1991), previous studies show that ¹⁰Be_i grain-size bias is minimal or not present in small, low-elevation, low-relief, temperate landscapes where landslides are uncommon (van Dongen et al., 2019); thus, ¹⁰Be_i measured from the 250–850 µm grain-size fraction at George River can be interpreted as a geological erosion rate.

Figure 5 Stream profiles of sampled sites along the George River trunk channel (TG-1, TG-9) and its tributaries (TG-2 through TG-8).

¹⁰Be_m and the weathered reactive and silicate-bound in situ phases of ⁹Be (⁹Be_reac and ⁹Be_min, respectively) were measured only from the 250–850 µm grain-size fraction from all seven tributary sites (TG-2 through TG-8) and one of the trunk channel sites (TG-9). When ¹⁰Be_m is normalized to ⁹Be_reac following von Blanckenburg et al.'s (2012) denudation rate equation, grain-size biases in resulting ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates are diminished (Wittmann et al., 2012). Singleton et al. (2016) also showed the diminishment of grain-size bias in stream sand for ¹⁰Be_m measurements when normalized to ⁹Be_reac. Although it is possible to calculate erosion rates from ¹⁰Be_m alone (Brown et al., 1988; Harrison et al., 2021; Willenbring and von Blanckenburg, 2010), this method does not include any normalization to ⁹Be_reac, and ¹⁰Be_m erosion rates are thus susceptible to grain-size bias, especially if the full grain-size distribution is not known and/or has not been analyzed. As our samples are of one grain-size fraction and were collected and sieved in the field prior to ¹⁰Be_m erosion rate derivations, we only present ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates in this study.

Table 3 Isotope data.

^a In situ batch 432 blank ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{i}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{carr}}$ ratio $=\mathrm{1.25}\times {\mathrm{10}}^{-\mathrm{14}}\pm \mathrm{5.87}\times {\mathrm{10}}^{-\mathrm{16}}$.
^b In situ batch 438 blank ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{i}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{carr}}$ ratio $=\mathrm{1.22}\times {\mathrm{10}}^{-\mathrm{14}}\pm \mathrm{1.82}\times {\mathrm{10}}^{-\mathrm{15}}$.
^c In situ batch 446 blank ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{i}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{carr}}$ ratio = $\mathrm{1.27}\times {\mathrm{10}}^{-\mathrm{14}}\pm \mathrm{6.70}\times {\mathrm{10}}^{-\mathrm{16}}$.
^d Meteoric batch MB-15 blank ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{carr}}$ ratio $=\mathrm{1.65}\times {\mathrm{10}}^{-\mathrm{14}}\pm \mathrm{1.72}\times {\mathrm{10}}^{-\mathrm{15}}$.

Table 4 In situ and meteoric beryllium isotopic data.

^a Balco et al. (2008), Gosse and Phillips (2001). ^b Scaled for each basin following Lal (1991) and Stone (2000). ^c Half-life of ¹⁰Be = 1.36 Myr. ^d von Blanckenburg et al. (2012). ^e Various values used; see Sect. 5.4 for full discussion.

Table 5 ¹⁰Be_i-based erosion rates and ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates.

^* 10Be_i erosion rates calculated using the CRONUS erosion rate calculator version 3.0, wrapper version 3.0, erates version 3.0, muons version 3.1 (Balco et al., 2008).

¹⁰Be_i was extracted at the University of Vermont from quartz from each sample following standard methods, during which a known amount of a ⁹Be carrier (⁹Be_carr) was added to each sample (Kohl and Nishiizumi, 1992; Corbett et al., 2016); relative to the amount of ⁹Be_carr, no significant native Be was found in quartz concentrates from any sample, which can otherwise lead to significant overestimates of ¹⁰Be_i-based erosion rates (Portenga et al., 2015). ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{i}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{carr}}$ ratios were measured by accelerator mass spectrometry at the Lawrence Livermore National Laboratory CAMS facility (Table 3); ¹⁰Be_i measurements were blank-corrected (the average ratio of three blanks was subtracted from the ratio of each unknown sample) and normalized to the 07KNSTD3110 accelerator mass spectrometry ¹⁰Be standard material, which has a nominal ${}^{\mathrm{10}}\mathrm{Be}/{}^{\mathrm{9}}\mathrm{Be}$ ratio of 2.85 × 10⁻¹² (Nishiizumi et al., 2007). ¹⁰Be_i production was averaged across all sampled basins to a single point following Portenga and Bierman (2011), and the online erosion rate calculator described by Balco et al. (2008), which has been subsequently updated, was used to derive ¹⁰Be_i erosion rates following the Lal (1991) and Stone (2000) scaling schemes (ε, Tables 4 and 5). Here, ε is presented in units of $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{kyr}}^{-\mathrm{1}}$ (Table 5) allowing us to compare measurements of ε directly with ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates (D_m; see below). Muogenic production of ¹⁰Be_i is incorporated into ε; however, muogenic ¹⁰Be_i is negligible relative to spallogenic ¹⁰Be_i production given the George River's post-orogenic, low-elevation, low-relief setting.

¹⁰Be_m was extracted following Stone's (1998) fusion method, and a ⁹Be carrier solution was added to each sample. Through this process, some amount of ¹⁰Be_i from bulk sediment is incorporated into the ¹⁰Be_m sample; however, the amount of ¹⁰Be_i is negligible, consistently 2 orders of magnitude less than ¹⁰Be_m measurements (Table 3). ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{carr}}$ ratios of these fusion extracts were measured at the Lawrence Livermore National Laboratory CAMS facility, blank-corrected (ratio of one blank was subtracted from ratio of each unknown sample; Table 3) and normalized to the 07KNSTD3110 standard material (Nishiizumi et al., 2007). Sample material used to calculate ⁹Be_reac was first subject to 6 N HCl acid leaching to remove sediment grain coatings (Greene, 2016; Portenga et al., 2019, their supplement); it was then fully digested in HF, and ⁹Be_min was measured in that solution. Both ⁹Be_reac from sediment grain coatings and ⁹Be_min from the remaining mineral material were measured by inductively coupled plasma-optical emission spectrometry (ICP-OES) at the University of Vermont. Together, these data were used to derive denudation rates following von Blanckenburg et al. (2012; Table 4); two variables required to calculate denudation rates that we did not or were not able to measure are the deposition rate of meteoric ¹⁰Be (${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$) and the amount of ⁹Be that is naturally occurring in bedrock (⁹Be_parent). We use estimated values of ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ based on global deposition models presented in Graly et al. (2011), because it provides an estimate of ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ that is specific for each sampled basin (8.55 × 10⁵ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ to 1.46 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$). At the time of sample collection (2008), the equations to calculate D_m had not been published, and bedrock samples from the field area were not collected. We therefore use a value of 4.1 ppm for the amount of ⁹Be_parent in our samples because the George River basin is underlain by biotite granites, and the average ⁹Be_parent value of biotite granites comprising a subset from over 200 felsic intrusions measured across China and the Soviet Union in the mid-1900s was reported to be 4.1 ppm (Beus, 1962; additionally reported in Sainsbury, 1964). We discuss the use of Graly et al.'s (2011) ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ estimates and Beus's (1962) average ⁹Be_parent for biotite granites in the Discussion section. In this study, D_m is presented in units of $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ (Table 5).

3.2 Topographic, climatic, and anthropogenic characterization of the George River basin

We compare ε and D_m to various topographic and land-use factors to assess possible processes driving or related to background landscape evolution in the George River (Tables 1 and 2). Topographic data are derived from the Shuttle Radar Topography Mission (SRTM) 90 m resolution global dataset (Gallant et al., 2011). Mean local relief was calculated over a moving 10-cell (∼ 900 m) circular window. We do not compare ε or D_m to climate data from global gridded datasets for mean annual temperature and mean annual precipitation, although such data are available. This is because the gridded datasets are all models based on limited measurements and include a strong elevation component in their interpolation scheme (e.g., WorldClim, Fick and Hijmans, 2017) or have spatial resolutions that do not provide sufficient detail for the small size of the George River basin (e.g., TRMM, Huffman, 2021). These characteristics of gridded climate datasets make it difficult to attribute erosion to climatic drivers independent of their self-correlation with elevation. Thus, we rely on observed relationships between elevation and precipitation and temperature data from precipitation gauges (n = 10, each with > 4 years of daily data; Table 1, Figs. 2 and 3) and temperature loggers (n = 5, each with > 2 years of hourly data from at least 30 % of days reporting, average = 70 % of days reporting; Table 1, Figs. 2 and 3). Although the spatial coverage of rainfall gauges and temperature loggers is small relative to the coverage of interpolated, modeled, gridded data, they provide us an opportunity to work with measured, basin-specific data.

Proper interpretation of ¹⁰Be_m-derived denudation rates requires an understanding of the potential for beryllium weathering and desorption from sediment grain coatings and mobility through regolith (von Blanckenburg et al., 2012). To this end, information on (1) the depth of regolith and (2) chemical weathering data across the George River basin is needed. A potentially relevant dataset available for Tasmania is an interpolated gridded map of the depth of regolith (Wilford et al., 2016). However, like the WorldClim precipitation and temperature datasets, the gridded regolith dataset was created by interpolating measured data from around Australia using a model and has an implicit dependence on elevation that does not reflect measured depths to bedrock in the George River basin. Only three boreholes exist in the George River basin that clearly go through regolith to bedrock, from which we extracted regolith depth (BoM, 2015; Fig. 2a; Table 1). They do not match the model results. These three boreholes, and others in the study area, have some units that could be alluvium or regolith; this differentiation is not clear, and therefore the depth of regolith could be overestimated if alluvium is marked as regolith. Thus, we do not know with certainty the depth of regolith across our field area, and we therefore cannot draw any clear conclusions about beryllium mobility in deep, weathered soils from the borehole data alone and do not explore it further.

Qualitative ratings of soil erosivity have previously been determined for Tasmania (Kidd et al., 2014, 2015) based on modeled soil loss should substantial vegetation and ground cover be removed; these ratings are strongly tied to hillslope angle within the George River basin (Fig. 6). Additionally, slope and erosion are strongly linked across the Great Dividing Range on the Australian mainland (Codilean et al., 2021). Thus, we compare erosion and denudation metrics against basin slope metrics, which enables us to compare our measurements of ε and D_m to basin slope to assess how Kidd et al.'s (2014, 2015) metrics for hillslope erodibility and erosion in the George River are related and to compare these new ¹⁰Be_i erosion rates to those presented by Codilean et al. (2021) for the Australian mainland.

Figure 6 Analysis of variance, showing hillslope angles associated with categories of landscape erosivity (Kidd et al., 2014, 2015) at George River. Boxes and whiskers cover ± 1.5× the interquartile range; black dots are the mean slope for the erosivity category. The mean slope for each erosivity category is significantly different from every other category, illustrated by the Connecting Letters Report (if the mean slope in any two erosivity categories were statistically indistinguishable, they would otherwise share a letter in the report). We therefore use hillslope angle as a quantitative proxy for erosivity in the George River basin.

3.3 Calculating the dissolved and suspended loads of George River at St. Helens

There is one long-term water quality and stream gauging station in the George River basin at the inlet to the local water treatment plant drawing water from the trunk channel of the George River in the town of St. Helens (Fig. 2). Thus, we can only estimate the dissolved load for the entire George River basin, not individual tributaries. Chemical weathering rates for the George River at St. Helens were calculated using these water quality data (i.e., dissolved major and trace element data) and discharge data (John Fawcett, TasWater, personal communication, 2021). Discharge measurements were taken at intervals ranging from 4 to 96 times per day from 1968 to 2021; 26 complete years of discharge data were available. Water quality measurements have been conducted since 2015 and we used the data from July 2015 to September 2021 in our derivation of the dissolved load for the George River basin.

Table 6 Water quality data for the George River at St. Helens.

We matched water quality measurements with the nearest discharge measurement in time; when times did not line up exactly, we used the average of the nearest two discharge measurements. We then explored the relationship between discharge and each water quality parameter. For parameters that are invariant with discharge (iron, potassium, sulfate, silica), we calculated the mean concentration of the parameter (Table 6). For parameters that scale with discharge (calcium, magnesium), we used a rating curve to determine how discharge relates to each water quality parameter; we then applied the mean measured values and rating curves, as appropriate, to every discharge measurement for years with complete discharge records (Table 6). Sodium and chlorine were balanced (suggesting a sea salt contribution) and were thus omitted from the calculation. Carbonate that balanced the calcium and magnesium present was included; the rest was assumed to be from atmospheric sources (Table 6). Silica concentrations were measured independently, once annually from 1974 to 1981 (John Fawcett, TasWater, personal communication, 2021), and we used all eight of those measurements; measurements in individual years were taken in March, June, August, October, and November (Table 6). We report total dissolved solids (TDS) measurements that are the sum of potassium, sulfate, silica, calcium, magnesium, and carbonate concentrations following West et al.'s (2005) chemical weathering rate calculation. We used a similar method to calculate the total suspended sediment (TSS) for each year of complete discharge data; TSS scales with discharge and so we applied a rating curve (Table 6).

4 Results

4.1 ¹⁰Be_i erosion rates, ε

Erosion rates, ε, based on measured concentrations of ¹⁰Be_i, range from 13.1 to 66.2 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$. They have integrated landscape dynamics in the George River basin since ∼ 24–122 ka (Table 4). The average ε from tributaries (36.8±1.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) is greater than from either of the trunk channel samples (TG-1 $=\mathrm{25.9}\pm \mathrm{2.2}$ $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$; TG-9 $=\mathrm{22.4}\pm \mathrm{1.9}$ $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$). Tributary values for ε are greater in the high-elevation, western headwaters of the George River basin and decrease systematically eastwards towards the lower-elevation coast (Fig. 6; R²=0.91, p<0.001). Relationships between ε in tributary catchments and mean local relief, mean basin slope, and the percent of each basin that is categorized as being greater than or equal to “High” erosivity are weak and not significant (R²=0.28, R²=0.17, R²=0.05, respectively, p≥0.13). Taking the product of ε and basin area provides us with the average annual mass loss for each catchment. Making the assumption of steady state and no change in storage over time, we can then compare mass export rates across the catchment. Following this approach, we find that a similar mass exited sampled tributaries (10 511±390 Mg yr⁻¹) as the mass that passes through the trunk channel sites (TG-1 = 10 286 ± 860 Mg yr⁻¹; TG-9 $=\mathrm{9555}\pm \mathrm{820}$ Mg yr⁻¹). This comparison suggests little to no contribution of mass from the lowland, mainstem George River valley below the tributaries and above the basin outlet sampling sites.

4.2 ¹⁰Be_m denudation rates, D_m

Based on an assumed ⁹Be_parent value of 4.1 ppm (Beus, 1962), ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates, D_m, range from 16.7 to 36.9 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$. Most values for D_m in tributaries do not replicate well the ¹⁰Be_i-derived erosion rates, ε, with the exception of TG-4 (Fig. 8). The ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rate at the trunk channel site, TG-9 (23.4±0.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$), replicates the ¹⁰Be_i erosion rate (22.4±1.9 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$). In general, ¹⁰Be_m-based measures D_m of tributaries are not significantly related to any topographic or basin metric such as mean basin elevation, mean local relief, or mean basin slope (R²=0.12, R²=0.06, R²=0.11, respectively; p>0.44). ¹⁰Be_m-based measures D_m of tributaries appear to be moderately related to the percentage of each basin that Kidd et al. (2014, 2015) categorizes with a land use of “High” to “Extreme” erosivity, though we note this relationship is not significant at high-confidence levels (R²=0.42; p=0.18; Fig. 9).

4.3 Dissolved load and suspended sediment fluxes

The annual dissolved load in the George River at St. Helens for the 26 years between 1969 and 2020 is between 1820 and 10 770 Mg yr⁻¹ (mean: 4400±2230 Mg yr⁻¹, 1σ) and the total suspended sediment load ranges from 280 to 10 560 Mg yr⁻¹ (mean: 1830±2180 Mg yr⁻¹, 1σ). The water treatment plant from which the dissolved load data were obtained is close to site TG-9, and data from this site allow us to place ¹⁰Be-inferred erosion and denudation rates for the whole George River basin in context. These data show that the dissolved load export rate averages to about 10.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{1}}{\mathrm{yr}}^{-\mathrm{1}}$, which is < 50 % of ε (22.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$), based on decades of flow records and 5 years of discontinuous water sampling at the same sampling location. The suspended sediment export rate out of the George River basin is lower, at 4.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$.

5 Discussion

The multi-methodological approach we employ in this study provides four new datasets, all of which quantify some component of landscape change at different spatial scales: (1) mass loss rates inferred ¹⁰Be_i at seven tributary and two trunk channel sites, (2) denudation rates from ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ from seven tributary sites and one trunk channel site, (3) suspended sediment export at the mouth of the George River, and (4) the dissolved load of the George River from the water quality and flow data at the mouth of the catchment. Comparing and interpreting these new datasets improves our understanding of the rate of landscape change over time in the George River basin. Given that the only location for which we have data from all four of datasets is at the mouth of the George River in St. Helens, we explore what the different rates presented in this study might mean for landscape change across the whole river basin, recognizing that without more data, we cannot be more specific in our interpretation of ε or D_m at tributary sites beyond the traditional meanings of erosion or denudation, respectively.

5.1 Relationships between ε, elevation-dependent climate conditions and land use

Erosion rates in the George River basin are strongly related to mean basin elevation, which varies greatly across the catchment as the study area extends east from the Rattler Range and Mt. Victoria (1213 m) to the coast at sea level (Fig. 2). In contrast, we find no evidence to suggest that ε is related to slope in the George River over millennial timescales. This result differs from many studies, which show strong correlations between ε and mean basin slope at a global scale (Portenga and Bierman, 2011) and at regional scales across the Great Dividing Range on Australia's mainland (Fig. 10; Codilean et al., 2021; Nichols et al., 2014). Our results also differ from prior assessments of the George River basin using measured climate data, bedrock structure, topographic analysis, water quality models, and geographical landscape characterization that suggest slope imparts a large control over erosion and sediment generation in the catchment on human timescales (Jerie et al., 2003; Kragt and Newham, 2009).

Any process-based explanation for the correlation of erosion rates with elevation requires that we consider how relevant geomorphic and geochemical processes vary across the George River basin. Climatic data collected from stations in and near the George River basin indicate that both mean annual temperature and mean annual precipitation are strongly correlated with elevation (Fig. 3). At higher elevations, rocks are experiencing lower temperatures more frequently and receive more precipitation than those at lower elevations, increasing the potential for both mechanical (frost cracking) and chemical weathering (dissolution). Frost cracking rates are greatest in rocks where mean annual temperature is above freezing (which is the case for all of the George River basin), but temperatures go below freezing both long and frequently enough to crack rocks, which is also the case across much of the basin (Delunel et al., 2010; Hales and Roering, 2007). In the George River basin, the only temperature-related metric that correlates with elevation is mean annual temperature, in contrast to, for example, the time spent below freezing, likely because temperature inversions, with cold air drainage to lower elevation valleys, are common (Webb et al., 2018, 2020). Additionally, the underlying mechanics that lead to rock fracturing in the first place have been demonstrated to be strongly linked to climate and the availability of water (Eppes and Keanini, 2017; Eppes et al., 2018). While water is plentiful across the George River basin, we see that ε is greater at higher elevations where rainfall is also greater, facilitating faster breakdown of rock.

Mean annual precipitation at meteorology stations in the George River basin varies less (2.7-fold) from low to high elevations (681–1836 mm yr⁻¹; Fig. 3) than ε (4.8–24.5 mm kyr⁻¹; a 5.1-fold difference; Table 4). The elevation-induced precipitation and erosion rate gradients we observe are consistent with suggestions made at regional and global scales that the relationship between slope and erosion becomes secondary to precipitation in low-slope, low-elevation, post-tectonic settings (Henck et al., 2011; Mishra et al., 2019). We note that Mishra et al. (2019) also suggest that at the global scale, the erosional effects of increased precipitation may be balanced by increased vegetation cover, which serves to stymie erosion. However, the George River basin is densely vegetated throughout, and forests are no more prevalent at higher than lower elevations in our field area. We propose that in the George River basin, ε is related to elevation in large part because precipitation is strongly correlated with elevation. This interpretation seems to hold true for bedrock outcrops, the erosion rates of which are most closely correlated to mean annual rainfall in aseismic landscapes, globally; however, basin-wide erosion rates in aseismic areas globally remain more strongly correlated to mean basin slope and subsequently to elevation and climate-related processes (Portenga and Bierman, 2011), which stands in contrast to the relationship we observe here between elevation and ε.

The concave-up geometry of sampled streams (Fig. 5) demonstrates that values of ε presented here come from streams that are in steady state. Thus, the very strong relationship between elevation, climate (both mean annual rainfall and temperature), and ε would likely not have emerged had our ¹⁰Be_i samples been affected by clast attrition (Carretier et al., 2009); deep-seated landslides (Aguilar et al., 2014; Gonzalez et al., 2016; Puchol et al., 2014); or intensive erosion associated with mining, forestry, or agriculture (Barreto et al., 2014; Neilson et al., 2017). Even intensive tin mining, which supplied > 10⁶ m³ to the George River over the last two centuries (Knighton, 1991) seems not to have had a long-lasting diluting effect on ¹⁰Be_i in sampled stream sediment. It is possible that mining efforts, especially sluice mining, did not lead to ¹⁰Be_i dilution because of the homogenizing effect of ¹⁰Be_i in bioturbated soils (Brown et al., 1995; Schaller et al., 2018) or because the size of the George River basin is large enough to buffer the effects of mining efforts in a similar way that large catchments may buffer the effects of landslide material (Niemi et al., 2005; Yanites et al., 2009). It is also possible that mining activity did lead to ¹⁰Be_i dilution, but concentrations have returned to pre-disturbance levels in the same way that bedload characteristics returned to pre-disturbance levels (Knighton, 1991) and similar to the rapid, two-year recovery of ¹⁰Be_i concentrations following storm-triggered landslides in Puerto Rico (Grande et al., 2021).

Overall, the close relationship between ¹⁰Be_i erosion rates and climate across the George River basin demonstrates that ¹⁰Be_i erosion rates reflect background, geologically meaningful rates of landscape evolution on millennial timescales, even in areas with long histories of intensive human land use (e.g., Barreto et al., 2014; Rosenkranz et al., 2018; Vanacker et al., 2007). Secondarily, that higher values of ε are observed where there is more rainfall and there are colder temperatures suggests that more sediment is being generated per unit area in the western portion of the catchment. There, larger volumes of rainfall and colder temperatures facilitate the generation, erosion, entrainment, and delivery of more sediment to trunk channels than in the eastern portion of the catchment.

Since pre-disturbance stream flow and bedload conditions were re-established by the 1990s (Knighton, 1991), it appears the greatest risk of enhanced sediment flux from the George River to Georges Bay in the future comes from land-use changes involving the widespread disturbance of surficial soils, such as through forestry (Wilson, 1999). The percentage of land used for production forestry in native environments has been decreasing throughout the 21st century (Fig. 4). Although some land previously used for production forestry in native environments is being supplanted by conservation and protected native land cover, which could buffer the effects of widespread erosion, much is being replaced by grazing and agriculture, which would likely increase erosion, particularly in the headwater catchments where geological erosion rates are naturally higher (Fig. 4). Given recent land-use trends, the ¹⁰Be_i erosion rates presented here provide a useful benchmark level of sediment delivery to the George River, Georges Bay, and other fluvial systems in northeast Tasmania that share topographic and geologic characteristics similar to those of the George River basin.

5.2 Considerations of ε for trunk channel versus tributary sites

Taking the product of ε and basin area calculates the annual mass exported from sampled basins. The mass leaving the tributaries (mean: 10 510±390 Mg yr⁻¹) is about the same as the mass passing through TG-1 (10 290±860 Mg yr⁻¹) and the mass of sediment leaving TG-9 (9560±820 Mg yr⁻¹). We infer from these data that the ¹⁰Be_i measured at TG-1 and TG-9 trunk channel locations is dominated by mass produced in the higher-elevation tributary basins with minimal sediment input from the George River valley bottoms. Similar interpretations have been made elsewhere, albeit in much larger river basins (i.e., Wittmann et al., 2009, 2011, 2016). Given these similarities, we average ε from the two trunk channel sites to produce a nominal average erosion rate for the George River basin as a whole (24.1±1.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$; or 8.9±0.5 mm kyr⁻¹ when dividing ε by rock density, ρ=2.7 g cm⁻³), which is of the same magnitude as the average erosion rate of catchments draining the eastern flanks of the Great Dividing Range along the southeastern passive margin of mainland Australia (11.6 mm kyr⁻¹; Fig. 10; Codilean et al., 2021). Average ε from the George River basin is most consistent with erosion of basins across the Bass Strait, which share similar topographic characteristics and geological histories to the George River basin (Codilean et al., 2021). The similarity between the geology, topography, and climate of newly sampled basins and derived ¹⁰Be_i erosion rates in Tasmania from this study and those from southeast mainland Australia supports the notion that evolution of landscapes that share similar climatic, topographic, and geologic characteristics is similar.

5.3 Comparing ¹⁰Be_i-based erosion rates and ¹⁰Be_m-based denudation rates

Once delivered to Earth's surface in temperate regions, ¹⁰Be_m concentrates in the uppermost soil horizons (Graly et al., 2010; Willenbring and von Blanckenburg, 2010). This behavior differs from that of ¹⁰Be_i, the concentration of which remains homogenous in well-mixed, bioturbated soils for millennia (Jungers et al., 2009). Thus, any disturbance of large volumes of topsoil (i.e., agriculture, forestry, wildfire erosion, or mining activities) strips material with the highest concentrations of ¹⁰Be_m and introduces that material into streams, a process similar to that identified following early land-use changes and deforestation in the Chesapeake Bay and San Francisco Bay (Portenga et al., 2019; Valette-Silver et al., 1986; van Geen et al., 1999). In contrast, the strong relationship between ¹⁰Be_i erosion rates and elevation, and thus both precipitation and temperature, across the George River basin (Fig. 7) suggests that ¹⁰Be_i erosion rates, ε, are unaffected by land use.

Figure 7 A strong correlation between ¹⁰Be_i-based erosion rates (ε) and mean basin elevation for the seven tributary samples collected in this study. We do not include trunk-channel sites because erosion rates here also incorporate erosion occurring in tributary catchments.

Assuming a ⁹Be_parent value of 4.1 ppm (Beus, 1962), calculated values of D_m do not consistently replicate ε (Fig. 8), nor does D_m replicate the spatial patterns or yield the same relationships with topographic parameters that we observe with ε in the small, geologically homogeneous landscape of the George River basin (e.g., Fig. 7). In fact, we calculate similar D_m values at TG-2 and TG-7, which have the lowest and highest calculated values for ε (Fig. 8). We know that decades-old historical mining activities and historical bushfires in the George River were restricted to lower catchment areas and tributaries where measurements of D_m are highest (Figs. 4 and 9). Additionally, we infer from the moderate correlation observed between D_m and the percent of tributary basins classified as “High” to “Extreme” erosivity (R² = 0.42; Fig. 9; Kidd et al., 2014, 2015) that ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-derived denudation rates appear to be sensitive to recent land-use practices that disturb soils. The highest denudation rates, D_m, we measured are those from basins with past histories of intense surface disruption through mining and forestry (i.e., TG-4, TG-5).

Figure 8 ¹⁰Be_i-based erosion rates (ε) compared ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates (D_m) for tributary basins (open circles) and the trunk channel site, TG-9 (closed circle). Measures of ε and D_m are different at each site, but similar within a factor of 3. D_m is calculated using a ⁹Be_parent value of 4.1 ppm, taken from average values of a suite of biotite granites across the former Soviet Union and China (Beus, 1962; also reported in Sainsbury, 1964); horizontal grey bars, however, show the range of D_m values calculated using low estimates of crustal ⁹Be_parent (2.5 ppm; high end of D_m values; von Blanckenburg et al., 2012) and the average measured ⁹Be_parent values of S-type and tin-bearing granites (18 ppm; n=11; low end of D_m values; London and Evanson, 2002).

Figure 9 ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates, D_m (gray squares), from tributary basins measured at George River are related to the percentage of the basin that is classified as “High,” “Very High,” or “Extreme” erosivity (Kidd et al., 2014, 2015), though this relationship is not significant (p = 0.18). The basins with the highest denudation rates are those with histories of intensive mining and/or recent forestry, both of which disturb topsoils.

The similarity of D_m and ε for the entire George River basin, however – within a factor of 3 (Fig. 8) – provides general support for the hypothesis that ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates more-closely resemble ¹⁰Be_i-based erosion rates in small river basins where geological heterogeneity is minimized. This observed similarity between D_m and ε supports the continued exploration and application of ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates in geomorphological studies (i.e., Dannhaus et al., 2017; Deng et al., 2020; Portenga et al., 2019; Rahaman et al., 2017; Wittmann et al., 2012, 2015). However, data presented here suggest that this method should be used with caution in landscapes with recent soil disturbance.

5.4 Sensitivity analysis of ⁹Be_parent and ${}^{{}^{\mathrm{10}}\mathrm{Be}}$F_met

The values of D_m we present in this study are calculated with assumed values for the amount of ⁹Be naturally occurring in bedrock in the field area (⁹Be_parent) and the rate at which meteoric ¹⁰Be is delivered from the atmosphere to Earth's surface (${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$) because we did not measure these values specifically for the field area. Thus, we carry out a sensitivity analysis of both variables to assess how much D_m responds to changes in these values.

Figure 10 (a) Map of river basins draining east off the Great Australian Escarpment, where ¹⁰Be_i erosion rate data are available; figure adapted from Codilean et al. (2021). Filled circles are trunk streams and open circles are tributaries. Orange data include previously published data (Codilean et al., 2021; Croke et al., 2015; Fülöp et al., 2020; Godard et al., 2019; Nichols et al., 2014; Tomkins et al., 2007). Blue data are new data presented in this study from the George River basin, Tasmania. The average ¹⁰Be_i erosion rates from the George River (8.9 mm kyr⁻¹) are consistent with erosion rates from southeast mainland Australia (average 11.6 mm kyr⁻¹; Codilean et al., 2021). (b) Comparison of ¹⁰Be_i erosion rates from the George River basin (blue circles; tributaries) and the eastern flanks of the Great Australian Escarpment (orange circles) to basin average slope. (c) Comparison of ¹⁰Be_i erosion rates from the George River basin (blue circles) and the eastern flanks of the Great Australian Escarpment (orange circles) to mean annual precipitation; in this comparison, mean annual precipitation for George River samples comes from the elevation scaling for measured rainfall at meteorological gauging stations (Figs. 2 and 3, Table 1), whereas Codilean et al. (2021) summarize precipitation data for mainland basins from the WorldClim database (Fick and Hijamans, 2017).

Grew (2002) suggests that Earth's crustal average concentration of ⁹Be_parent is 3 ppm, though it is not unheard of for ⁹Be_parent to be < 1 ppm in (ultra)mafic lithologies and that ⁹Be_parent can vary 10-fold within the same igneous complex. Von Blanckenburg et al. (2012), who first present calculations for D_m, cite a slightly lower crustal average for ⁹Be_parent of 2.5 ppm. London and Evensen (2002) present ⁹Be_parent concentrations measured from felsic granites, which range from 1.6–160 ppm; for S-type granites or those that are tin-bearing – the same as the Blue Tier batholith in our field area (Higgins, 1985) – ⁹Be_parent ranges from 2.3–130 ppm (n = 11, mean: 18 ppm). Additionally, Sainsbury (1964) presents data from a tin-bearing biotite granite in Alaska, showing that ⁹Be_parent concentrations range from 2–26 ppm (n = 5, mean: 16.6 ppm). Thus, it seems a reasonable range of values for ⁹Be_parent that might apply to bedrock in this study are as low as crustal averages (2.5 ppm) or as high as tin-bearing biotite granites elsewhere (> 100 ppm). We choose to calculate and analyze D_m from a more modest estimate of 4.1 ppm (Beus, 1962), because single-digit concentrations of Be are most common for felsic igneous intrusions (London and Evensen, 2002). At lower ⁹Be_parent concentrations (2.5 ppm), D_m values across the George River basin increase such that D_m values replicate ε within a factor of two. However, when conservative but higher ⁹Be_parent concentrations are used (18 ppm; the average of values presented for S-type and tin-bearing granites presented by London and Evensen, 2002), D_m values decrease across the field area such that all D_m values are lower than ε by at least a factor of 3 (Fig. 8). The results of this sensitivity analysis highlight the importance of collecting representative bedrock samples throughout a field area to ascertain appropriate measures of ⁹Be_parent when using von Blanckenburg et al.'s (2012) ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rate method because of the highly sensitive dependency of D_m on ⁹Be_parent.

Figure 11 Comparison of denudation rates, D_m, using the von Blanckenburg et al. (2012) method; a bedrock beryllium concentration, ⁹Be_parent, value of 4.1 ppm (Beus, 1962), measured values from stream sand (Table 3); and meteoric ¹⁰Be delivery rates, ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$, of 1.68 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ to 1.72 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ (Reusser et al., 2010; blue, square), 1.9 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ to 2.7 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ (Graham et al., 2003; turquoise, black X), 1.0 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ to 1.5 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ (Heikkilä and von Blanckenburg, 2015; orange, triangle), ∼ 7 × 10⁵ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ (Masarik and Beer, 2009; Willenbring and von Blanckenburg, 2010; purple, star), and 8.5 × 10⁵ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ to 1.5 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ (Graly et al., 2011; white circle with dashed black line).

Values for the rate at which ¹⁰Be_m is delivered from the atmosphere to Earth's surface (${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$) have been measured and modeled in various ways at both local and global scales, each with its own strengths. In the South Pacific region, for instance, Reusser et al. (2010a) directly measured ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ in a dated New Zealand paleosol (1.68 to 1.72 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) and Graham et al. (2003) report ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values measured from rainfall across New Zealand, finding a wider range of ¹⁰Be_m deposition rates (1.7 to 2.9 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$). In the absence of direct measurement, ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ must be estimated or modeled. Heikkilä and von Blanckenburg (2015) integrate ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ through the Holocene while others integrate ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ for total atmospheric thickness, all at a global scale (Masarik and Beer, 2009; Willenbring and von Blanckenburg, 2010), but the resolution of these models is coarse, relative to the small spatial scale of this study, and ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ would be the same for each sampled basin (1.0–1.5 × 10⁶ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ for Holocene integrated or ∼ 7 × 10⁵ $\mathrm{atoms}{\mathrm{cm}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ for atmospheric depth-integrated ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$). Graly et al. (2011), however, present an equation that estimates ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ from a location's mean annual precipitation and latitude, which provides a more specific value for ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ for a given study site. We choose to use ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ modeled from Graly et al.'s (2011) equation because of its ability to provide basin-specific values of ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$, but we present D_m calculations for all basins using other ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values to assess the sensitivity of D_m to ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ (Fig. 11). In doing so, we find that D_m calculated from Reusser et al.'s (2010a) and Graham et al.'s (2003) values of ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ are consistently higher than using the Graly et al.'s (2011) model, likely owing to precipitation rate differences between northeast Tasmania and New Zealand, thousands of kilometers away. D_m calculated using ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values integrated through total atmospheric thickness (Masarik and Beer, 2009; Willenbring and von Blanckenburg, 2010) are consistently lower than those calculated using Graly et al.'s (2011) model, but those using ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values averaged through the Holocene (Heikkilä and von Blanckenburg, 2015) are remarkably consistent with results from the Graly et al. (2011) model. We suggest that the consistency of D_m modeled using the Graly et al. (2011) ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values and D_m calculated using Heikkilä and von Blanckenburg's (2015) ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values provides support for our decision to use Graly et al.'s model. Additionally, we suggest our use of Graly et al.'s (2011) estimates of ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ is reasonable because D_m values using Graly et al.'s ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values plot between D_m values calculated using ${}^{{}^{\mathrm{10}}\mathrm{Be}}{\mathrm{F}}_{\mathrm{met}}$ values from both global climate models (Heikkilä and von Blanckenburg, 2015; Masarik and Beer, 2009; Willenbring and von Blanckenburg, 2010), at least for northeast Tasmania.

5.5 Where does the dissolved load originate in the George River basin?

If chemical weathering occurs primarily in the uppermost meters of the landscape, where most ¹⁰Be_i is produced, then the erosion rate, ε, we calculate represents total landscape mass loss over time – a combination of physical and chemical mass loss. We could then partition ε along the trunk channel at the mouth of the George River basin (TG-9 = 22.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) into mass flux removed in the measured dissolved load (10.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) and the remainder, mass flux removed as solid sediment (12.1 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$). Of the sediment mass flux, it appears that 4.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ is transported as suspended load (measured from water quality data), and the difference of 7.8 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ is bedload (i.e., 12.1 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$ minus 4.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$). Our measure of ε at TG-9 (22.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) is similar to the ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ measure of denudation at this site (23.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$), which, if the assumptions of the method are met, represents total physical and chemical mass loss. Taken at face value, D_m assuming ⁹Be_parent = 4.1 ppm is an accurate measure of total mass loss from the George basin at TG-9. However, given the wide range of D_m possible using other reasonable values for ⁹Be_parent, it is difficult to know how well the two measures of landscape change, ε and D_m, truly compare.

If the majority of chemical weathering occurs below the penetration depth of most cosmic rays (< 2 m), then the chemical denudation and physical mass loss are at least in part and perhaps wholly disconnected. In this case, ε (TG-9 = 22.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) would need to be summed with the measured chemical mass flux (10.3 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$), and together (30.7 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$) they would estimate the total mass loss from the landscape. In this case, the summed total is ∼ 24 % greater than D_m at TG-9. The presence of bedrock outcrops in some of the George River basin channels suggests that regolith thickness is limited in places, and in that case ¹⁰Be_i measurements incorporate much of the chemical mass loss from the basin. However, the few boreholes that extend to unweathered bedrock (n = 3; Fig. 2; Table 1) clearly indicate that regolith is deeper in some parts of the catchment. With the paucity of available data, we cannot determine how much of the dissolved load is coming from below the penetration depth of cosmic-ray neutrons, but it could be significant.

Thus, despite the fact that ε and D_m at TG-9 are similar (22.4 and 23.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$, respectively), ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{met}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$-based denudation rates appear to have little correlation with landscape-scale metrics suggesting that they do not reflect the rate of geomorphic processes controlling mass loss over time. D_m is highest in basins with known histories of intensive land-use disturbance and high erosivity (Figs. 2 and 8), a relationship that exists regardless of what value is used for ⁹Be_parent. In contrast, ε is well-correlated to elevation and thus temperature and precipitation across the George River basin.

6 Conclusions

The ¹⁰Be_i-based erosion rates we present in this study are the first measured for any river system for Tasmania. In contrast to erosion across the Great Dividing Range on mainland Australia, where erosion rates and mean basin slope are closely linked, erosion in the George River basin has a strong relationship with mean basin elevation, and thus with mean annual precipitation and temperature, both of which are strongly correlated with elevation. The mean ¹⁰Be_i erosion rate in the George River basin, 24.1±1.4 $\mathrm{Mg}{\mathrm{km}}^{-\mathrm{2}}{\mathrm{yr}}^{-\mathrm{1}}$, reflects erosion in tributaries to the George River where precipitation is greatest and temperatures are lowest; little sediment is generated in trunk channel valley bottoms. These findings support the notion that precipitation imparts a significant influence on landscape development in low-slope, low-elevation landscapes, which are often located in post-orogenic, passive margin settings. We also suspect that low but positive mean annual temperatures with frequent excursions below zero drive the mechanical breakdown of rock, thereby increasing sediment production in high-elevation basins through frost cracking. Although hillslope erosion associated with mining, agricultural, and forestry land-use practices occurred in the George River basin during the 19th and 20th centuries, ¹⁰Be_i-based erosion rates in the basin appear to reflect pre-disturbance rates of landscape change. Such rates are useful as part of Tasmania's current efforts to re-establish healthy and sustainable ecological conditions in its many estuarine environments, particularly those in northeast Tasmania where estuary tributaries have similar geological and topographic characteristics to those found in the George River basin. ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates generally replicate ¹⁰Be_i-based erosion within a factor of 3 but show no correlation with landscape-scale metrics. Calculated ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates are highly sensitive to the concentration of native beryllium in bedrock (⁹Be_parent) and appear to be affected by intensive topsoil disturbance by mining, forestry, and agricultural land use. Data from the George River basin suggest that ${}^{\mathrm{10}}{\mathrm{Be}}_{\mathrm{m}}/{}^{\mathrm{9}}{\mathrm{Be}}_{\mathrm{reac}}$ denudation rates will be most meaningful in small, lithologically homogeneous basins with limited amounts of topsoil disturbance and where the value of ⁹Be_parent is well constrained by sampling and measurement of local bedrock.