# Decoding surface processes from escarpment to watershed: Insights from karst landscapes using cosmogenic nuclides and geochemical data

Rogerio Uagoda, Lionel Siame, Jérémie Garnier, Laëtitia Leanni, Dandara Caldeira, Régis Braucher, Rémi Freydier, Patrick Seyler, Georges Aumaitre, Karim Keddadouche, et al.

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## ► To cite this version:

Rogerio Uagoda, Lionel Siame, Jérémie Garnier, Laëtitia Leanni, Dandara Caldeira, et al. Decoding surface processes from escarpment to watershed: Insights from karst landscapes using cosmogenic nuclides and geochemical data. Geomorphology, 2025, 482, pp.109794. 10.1016/j geomorph.2025.109794. hal-05048266

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1 Highlights

2 Decoding surface processes from escarpment to watershed: Insights

3 from karst landscapes using cosmogenic nuclides and geochemical data
4

5 Rogerio Uagoda, Lionel L. Siame, Jérémie Garnier, Laëtitia Leanni, Dandara Caldeira, Régis

6 Braucher, Rémi Freydier, Patrick Seyler, ASTER Team

7 • Cosmogenic nuclides reveal sediment mixing and erosion in tropical karst watersheds.

8 • Flatter terrain erodes slowly with long residence, unlike steep escarpment slopes.

9 • Burial age gaps challenge full burial, stressing pre-depositional process roles.
Decoding surface processes from escarpment to watershed: Insights
from karst landscapes using cosmogenic nuclides and geochemical
data

Rogerio Uagodaª, Lionel L. Siameb,*, Jérémie Garnierc, Laëtitia Leannib, Dandara Caldeira d, Régis Braucherb, Rémi Freydier, Patrick Seylere, ASTER Teamb,f

ªDepartment of Geography, Graduate Program in Geography, University of Brasília, Brasília, 70910-900, Federal District, Brazil

ᵇAix Marseille Univ, CNRS, IRD, INRAE, CEREGE, Aix-en-Provence, France ᶜInstitute of Geosciences, Graduate Program in Geosciences, University of Brasília, Brasília, 70910-900, Brazil

ᵈInstitute of Geosciences, Graduate Program in Applied Geosciences and Geodynamics, University of Brasília, Brasília, 70910-900, Brazil

ᵉHydrosciences Montpellier, Univ. Montpellier, CNRS, IRD, Montpellier, France

fASTER Team: Georges Aumaître, Karim Keddadouche, Fawzi Zaidi, Aix-en-Provence, France

*corresponding author : siame@cerege.fr

**Abstract**

Tropical karst landscapes are marked by complex sediment dynamics resulting from the interplay
between geomorphic processes and sediment transport. In the Vermelho Watershed (Brazilian
savanna), we use paired cosmogenic nuclides (¹⁰Be and ²⁶Al) to quantify denudation rates, burial
durations, and sediment mixing. The spatial distribution of Al-Be ratios reveals rapid erosion and
prolonged burial on escarpments, in contrast to the more stable conditions of flatter areas, where
erosion is subdued, and sediment residence time is longer.

Comparisons with Iraquara and Serra das Mesas emphasize the influence of topography and
sediment sources on nuclide inventories. Downstream increases in freshly eroded material point to
fluvial mixing, while discrepancies between cosmogenic burial and OSL ages (Tarimba Cave)
suggest partial burial and pre-depositional histories.
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The integration of cosmogenic, geochemical, and geomorphic data underscores the complexity of tropical karst systems, where vertical mixing and uneven erosion are key processes. These results contribute to a broader understanding of landscape evolution and offer a comparative basis for interpreting cosmogenic signals in fluvio-karst environments worldwide.

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Keywords: Cosmogenic nuclides, Fluvio-karst systems, Sediment dynamics

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# 1. Introduction

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Quantifying the geomorphic processes that shape topographic escarpments in cuesta like landscapes within continental interiors remains a significant challenge. Although the mechanisms driving the retreat of the escarpment are well documented, the long-term rates at which these processes operate are not yet fully understood (e.g., Duszyński et al., 2019). On the other hand, cosmogenic nuclides have emerged as powerful tools to quantify the rates of surface processes related to landscape evolution, particularly in passive margin escarpment settings (Seidl et al., 1996; Fleming et al., 1999; Vanacker et al., 2007; Salgado et al., 2014; Sordi et al., 2018; Godard et al., 2019; Wang and Willett, 2021; Wang et al., 2021; Duszyński et al., 2024).

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In surface denudation studies using cosmogenic nuclides, concentrations measured in bedrock or river sediments are most often interpreted through a steady-state lens (e.g., Von Blanckenburg, 2005). This approach focuses on time-averaged accumulation near the surface, which can be problematic in areas where surface processes make the geomorphic context deviate from the secular equilibrium conditions. These processes can for example be related to mass wasting along an escarpment, long residence of a thick regolith, or sediment transfer through a karstic system. This can lead to an

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erroneous overestimation of basinwide denudation rates, as the steady-state assumption fails to
account for dynamic changes in surface processes that may significantly alter the cosmogenic signal.

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Although testing the steady-state assumption with multiple cosmogenic nuclides of different
radioactive half-lives was proposed decades ago (e.g., Lal, 1991), its application to transient surface
processes has only recently proven effective (Mudd, 2016; Hippe, 2017; Godard et al., 2021, 2024).

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Conversely, the ²⁶Al/¹⁰Be isotopic ratio (Al-Be ratio) has been widely applied to calculate sediment
burial ages, for shielding durations exceeding roughly 200 kyr, (Granger and Muzikar, 2001; Balco
and Rovey, 2008; Granger, 2006) and to investigate complex burial-erosion histories in diverse
geomorphic settings (e.g., Knudsen and Egholm, 2018; Struck et al., 2018; Wittmann et al., 2020;
Halsted et al., 2024). In slowly eroding environments such as cratonic landscapes, prolonged
residence time in the production layer allows differential decay rates to significantly decrease the Al-
Be ratio from its initial value of 6-7 (Balco et al., 2008; Borchers et al., 2016). This also makes the
Al-Be pair a promising tool for identifying and analyzing surface processes that complicate
cosmogenic nuclide signals at the basin scale, advancing beyond the simple steady-state model to
better quantify long-term denudation rates.

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We chose to explore this at the toe of the Serra Geral de Goiás in central Brazil (Fig. 1), where
long-term escarpment retreat has generated a regional colluvial surface, incised by the drainage
system and partially exhuming an extensive karst complex. This karst complex acts as a buffer for
fluvial sediment transport resulting from escarpment erosion. This study site serves as a natural
laboratory to evaluate whether the cosmogenic signal measured in river-borne material is dominated
by stochastic sediment production via mass wasting, vertical dynamic mixing in the production layer,
or burial of fluvial sediments within the karst system.

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To achieve this goal, we applied a multi proxy methodology that incorporates geomatic techniques to calculate a karstification index, *in situ*-produced cosmogenic nuclides to determine denudation rates and burial ages, as well as to identify potential inherited signatures in fluvial sediment. In addition, trace element analysis and XRD were performed on fluvial, cave, soil, and rock sediments to determine their origins and pathways from upstream sources. This study emphasizes the value of combining *in situ*-produced cosmogenic isotopes with upstream source data to unravel the geological and geomorphic factors shaping the role of caves and landslides in landscape evolution. Contextualized within previous Brazilian research conducted in analogous settings (Laureano et al., 2016; Barreto et al., 2022), the results of this study raise broader questions about the impacts of landslides, alluvial cover, and karst sediment transport on the cosmogenic nuclide signals carried by riverine sediments.

## 2. Geological and geomorphic setting of the Vermelho Basin

### 2.1. Brief overview of karstification processes in Brazil

Karst areas are renowned for their varied hydrological conditions, stemming from their unique formation processes and functionality (e.g., Harmand et al., 2017). Karst systems can obtain their water from precipitation, infiltration, and underground flow. These karst systems can also derive their water from autogenic or allogeneic sources (Ford and Williams, 2007). Autogenic systems are nourished by direct rainfall infiltration into carbonate rocks, while allogenic systems are fed by water flowing from surrounding non-soluble rock formations. The key characteristics of karst systems include inputs such as dolines or sinkholes and outputs such as springs and residual landforms that show evidence of the system's water flow and erosion processes.
101 Fluvial erosion from allogenic sources upstream of sinks influences erosional processes, creating
102 dry valleys and directing water and sediments into fluvio-karst systems (Benac et al., 2013). River
103 flow from surrounding areas carries allochthonous clastic sediments into the karst, while
104 autochthonous water drives chemical transport and deposition. Clastic sediments deposited in caves
105 reflect surface processes, but the unique sedimentary dynamics of subterranean environments can
106 result in complex stratigraphic configurations (Osborne, 1986; Gillieson, 2021; Ford and Williams,
107 2007). These subaerial clastic sediments are particularly valuable for identifying their source
108 material, a key factor in understanding regional erosion dynamics (Monod et al., 2006).

109 Beyond the classic karst in carbonate rocks, quartzite and sandstone karst systems are also
110 widespread in tropical regions, especially in Brazil (Fig. 1). These landscapes feature ruiniform relief,
111 caves, dolines, and dissolutional landforms, with notable examples in Serra das Confusões, Chapada
das Mesas, Chapada Diamantina, and Ibitipoca State Park (Wray and Sauro, 2017; Martins et al.,
112 2017; Auler et al., 2019). Their development involves silica dissolution under warm, humid tropical
113 conditions, followed by rapid erosion in high runoff environments, and involving similar process of
114 allogenic water source and sediments (Sauro, 2014; Auler and Sauro, 2019). Joint systems and ceiling
115 collapses control the formation of shallow sandstone caves, shaping the evolution of tableland
116 landscapes (Martins et al., 2017; Auler and Sauro, 2019).

118 2.2. Karst processes and Patamares formation

119 The Serra Geral de Goiás presents a distinct geomorphic structure, where the escarpment acts as
120 a major drainage divide between the São Francisco and Tocantins rivers, separating the Chapadão
121 Central from the Patamares do Chapadão (Fig. 1). According to Souza et al. (2018), the Chapadão
122 Central is a structural plateau formed by Cretaceous Urucuia sandstones, while the Patamares,
positioned at the foot of the escarpment, form an intermediate geomorphic surface that stands above
the regional base level in the Vão do Paranã. Dissected and covered by pebbles, gravels and boulders,
the Patamares are remnants of past fluvial dissection, which led to the exhumation of karstic reliefs
that developed within the Neoproterozoic Bambuí Group limestones. Although this description
primarily focuses on the role of fluvial processes, it does not directly associate the Patamares with
active karst dynamics, instead considering this regional surface as the product of pediplanation and
erosional processes linked to the retreat of the escarpment that exposed the underlying carbonate
terrains.

The Vermelho Watershed region is situated on Neoproterozoic carbonates and pelites of the Lagoa
do Jacaré Formation and the Bambuí Group occurring at approximately 650 m, with springs
originating in the Cretaceous sandstones of the Urucuia Group at around 1005 m. These domains are
separated by an escarpment, where basins exhibit higher erosive power. In contrast, lower-energy
basins form Quaternary detrital and lateritic covers, primarily sourced from sandstone erosion,
especially in karstic areas. Figure 2 presents a detailed lithological map of the Vermelho Watershed,
highlighting sampling locations upstream, within, and downstream of the karst areas to study burial
ages and denudation rates pairing *in situ*-produced ¹⁰Be and ²⁶Al cosmogenic nuclides. This map also
pays particular attention to the Quaternary alluvial material covering the carbonates to emphasize the
process of escarpment retreat and the resulting exhumation of the Bambuí Group and associated karst
features.

Deep Oxisols dominate the sandstone regions, while Acrisols and Chernozems develop over
carbonates and pelites. The fluvial karst system features high-velocity flows through horizontal caves,
internal canyons, and vertical ducts, which discharge into steep-gradient canyons (Uagoda and
Hussain, 2020). Sedimentary records in this area are episodic, with abandoned fluvial ducts filling
146 with sandy, conglomeratic, and brecciated deposits derived from Quaternary covers and pelitic rock
147 fragments (Caldeira et al., 2021). Canyon formation is attributed to the progressive growth of
148 conduits between sinkholes and springs, followed by roof collapses.

149 The geological and geomorphic features of the Vermelho Basin and the Serra Geral Escarpment
150 are illustrated in Figure 3, highlighting the interplay between the structural plateau, alluvial fans, and
151 karst processes. The schematic cross-section (Fig. 3A) illustrates the stratigraphic relationship
152 between the Upper Cretaceous (ca. 89 Ma) Urucuia sandstones (Schobbenhaus, 1984) and the
153 underlying Neoproterozoic carbonates (ca. 635 Ma) of the Bambuí Group (Moreira et al., 2020),
154 showing how escarpment retreat has led to the development of colluvial deposits and exhumed karstic
155 features. Field photographs (Fig. 3B–J) provide a detailed view of key geomorphic and karstic
156 elements, including duricrust cappings, escarpment profiles, colluvial benches, fluvio-karst
157 landscapes, canyons, and cave systems with sedimentary infills. These features exemplify the
158 dynamic interactions between fluvial and karstic processes shaping the Patamares and the regional
159 karst terrain.

160 At the toe of the Serra Geral Escarpment, the connection between the karstic relief and cave
161 system, as well as the evolution of the regional Patamares surface and its colluvial cover is crucial
162 for understanding the geomorphic evolution of the Vermelho Basin. The sedimentary infill within the
163 karst systems (e.g., caves shown in Fig. 3H–J) reveals the role of karst cavities as sediment sinks and
164 provides insights into sediment transport processes associated with escarpment retreat and
165 karstification.

166 Based on the work by Ferreira et al. (2022), we determined the karst index pattern to identify
167 areas with a high concentration of caves and dolines, with values ranging from zero to three features
168 per square kilometer (Fig. 2). This analysis highlighted regions with more pronounced karst
development, primarily aligned parallel to the Vermelho River and its canyon, and a secondary trend-oriented NE-SW near the border of the Bambuí carbonates. This spatial organization suggests a strong hydrological correlation between upstream recharge areas, marked by dolines and caves in the vadose zones, and phreatic cave entrances located near the canyons.

The Tarimba fluvial cave (Fig. 2) formed through underground drainage, linking a doline to a phreatic sink where the Tarimba River connects to the Extrema River (Fig. 4). Ancient sediments are preserved in the upper vadose sections, while mixed sediments accumulate in the phreatic zones, highlighting the hydro-sedimentological connection between vadose and phreatic systems. OSL dating by Caldeira et al. (2021) indicates three depositional phases: Phase 1 (>197 kyr) with alternating water flows, flooding, and erosion; Phase 2 (≈197 kyr) following an erosive event, with deposition of sandy and gravelly sediments; and Phase 3 (87-52 kyr) marked by dynamic flows depositing silt and clay fractions. This relationship between karst relief, cave systems at the Serra Geral Escarpment, and the evolution of the Patamares is shown in the schematic cross-section and photographs (Fig. 4C-).

## 3. Material and methods

### 3.1. Sampling strategy

The sampling campaign covered thirty-five sites (Fig. 2), chosen to capture the geomorphic and hydrological diversity of the study area. Samples were categorized into three groups based on the dominant lithologies: those primarily derived from the Urucuia Group sandstones near the escarpment and plateau (Escarpment Group); those influenced by the limestones of the Bambuí Group, Urucuia sandstones, and Quaternary alluvial deposits in the Patamares (Patamares Group);
190 and those representing a mix of these lithologies, without a single dominant source (Mixed Group).

191 This classification provides insight into sediment contributions from high-relief areas, karstic and
192 alluvial processes, and transitional zones.

193 Cosmogenic nuclide samples ($^{10}$Be and $^{26}$Al) were collected upstream, within, and downstream
194 of the fluvial karst system to track variations in sediment transport and exposure to surface processes.

195 Upstream samples represent freshly eroded sediments from weathered bedrock in the escarpment or
196 clastic materials in the Patamares and are unaffected by burial in cave or older material
197 contamination, reflecting active erosion dynamics. Within the karst system, features such as caves,
198 sinkholes, and subsurface drainage modify sedimentary processes, shielding sediments from cosmic
199 radiation and introducing potential mixing with fluvial material. Downstream, sediments reflect
200 cumulative mixing of materials from downstream erosion and karstic contributions.

201 A total of nineteen river-borne sand samples were collected from the Vermelho Basin, along the
202 main river trunk and its tributaries (Fig. 2). Six samples were taken upstream of the karst (RU-V1,
203 RU-V2, RU-P1, RU-Vt1, RU-E1, RU-D1), five within the karst (RU-V3, RU-P4, RU-Vt3, RU-E2,
204 RU-D3), seven downstream of the karst (RU-V4, RU-V5, RU-P9, RU-Vt5, RU-E3, RU-D4, RU-
205 C1), and one at the karst exit (RU-V6). The sample labels indicate specific locations: C, D, E, P, and
206 Vt denote the Chumbada, Dores, Extrema, Pedras, and Ventura channels, respectively, while V refers
207 to samples collected along the Vermelho River trunk.

208 Additionally, sixteen source samples were gathered from rock outcrops, soils, and cave deposits.
209 These source samples were designated for trace elements analysis and X-ray diffraction (XRD)
210 studies (Fig. 2). The trace elements analysis provides insights into the geological sources of the
211 sediment, while XRD helps identifying the mineralogical composition of the samples.

212 3.2. In situ-produced $^{10}$Be and $^{26}$Al cosmogenic nuclides concentrations
213 **3.2.1. Analytical procedures**

214 The 250-1000 µm fraction was first submitted to sequential magnetic separation with Frantz
215 magnetic separator (three steps at 0.5, 1.0 and 1.5 A). Preparation of in situ-produced cosmogenic
216 ¹⁰Be and ²⁶Al for Accelerator Mass Spectrometry (AMS) followed procedures adapted from Brown
217 et al. (1991) and Merchel and Herpers (1999). The non-magnetic fractions were first leached with
218 37% HCl to remove eventual carbonate fragments then repetitively leached with a mixture of HCl
219 and H₂SiF₆ and submitted to vigorous mechanical shaking until pure quartz was obtained.
220 Decontamination from atmospheric ¹⁰Be was achieved through a series of three successive leaching
221 in concentrated HF, each removing 10% of the remaining sample mass (Brown et al., 1991). The
222 remaining pure quartz was then fully digested in concentrated HF after the addition of an in-house
223 ⁹Be carrier solution (≈150 µl at 3025±9 ppm), derived from a deep-mined phenakite (Merchel et al.,
224 2008). To determine if an ²⁷Al spike was needed, natural concentrations of ²⁷Al were determined in
225 liquid aliquots by inductively coupled plasma-optical emission spectrometry (ICP-OES, Thermo
226 Icap6500). When necessary, the samples were then spiked using a ²⁷Al carrier solution (Merck
227 Certipur at 984±4 ppm). Resulting solution were fumed to remove fluorides and followed cation and
228 anion exchange chromatography to separate beryllium and aluminum from other elements.
229

229 All resulting beryllium and aluminum hydroxides were oxidized at 800°C to form beryllium and
230 aluminum oxides, which were then respectively mixed with niobium or silver powder and loaded in
231 copper targets for AMS measurements of isotopic ¹⁰Be/⁹Be and ²⁶Al/²⁷Al ratios. These analyses were
232 performed at ASTER (Arnold et al., 2010), the French AMS National Facility (CEREGE, Aix-en-
233 Provence). Beryllium isotopic ratios were calibrated against the in-house STD-11 standard (¹⁰Be/⁹Be
234 = (1.191 ± 0.013) × 10⁻¹¹), equivalent to the National Institute of Standards and Technology standard
235 reference material NIST-27900 (Braucher et al., 2015), and the ¹⁰Be half-life of (1.387±0.012)×10⁶
236 years (Chmeleff et al., 2010; Korschinek et al., 2010). Aluminum isotopic ratios were calibrated
237 against the in-house SM-AL-11 standard ($^{26}$Al/$^{27}$Al = (7.401 ± 0.064) × 10$^{-12}$), which has been cross-
238 calibrated against the primary standards certified by a round-robin exercise (Merchel and Bremser,
239 2004), and the $^{26}$Al half-life of (7.17 ± 0.17) × 10$^{5}$ years (Granger, 2006). Reported analytical
240 uncertainties ($1\sigma$) include uncertainties on AMS counting statistics, the isotopic ratios of standards,
241 chemical blank measurements, and an external AMS error of 0.5% (Arnold et al., 2010).

242 In our samples, the natural aluminum content ranges from 52.2±1 to 84±2 ppm, consistent with
243 the quartzitic nature of the Urucuia Formation, and confirming the high purity of our samples.
244 Additionally, the absence of residual solid phases after re-dissolution in HCl reassures us that no
245 significant aluminum losses occurred during the process. All the raw data of the AMS measurements
246 and calculated $^{10}$Be and $^{26}$Al concentrations are summarized in the supplementary tables S1 and S2
247 provided by Uagoda et al. (2025).

## 3.3. From cosmogenic concentrations to denudation rates and burial durations

249 In modern, river-borne sediments, *in situ*-produced cosmogenic concentrations are interpreted as
250 a proxy for the denudation processes occurring in the upstream catchments (Von Blanckenburg,
251 2005). Indeed, cosmogenic build-up in surface rocks and soils records hillslope denudation history,
252 as the material is vertically advected to the surface (e.g., Knudsen et al., 2019). Since rivers transport
253 and mix sediment eroded from hillslopes, they act as natural spatial integrators for both mechanical
254 and chemical erosion processes associated with surface dynamics and pedogenesis processes (Brown
255 et al., 1995; Granger et al., 1996; Von Blanckenburg, 2005). Assuming the landscape has reached
256 secular equilibrium (e.g., Lal, 1991), where cosmogenic production balances losses due to radioactive
257 decay and denudation, and considering minimal sediment export time through the watershed, without
258 significant long-term burial or storage along the transport pathway, concentrations of *in situ*-produced
259 cosmogenic $^{10}$Be are inversely proportional to basin-wide denudation rates (Von Blanckenburg, 2005;
260 Granger and Schaller, 2014).

261 To convert *in situ*-produced cosmogenic $^{10}$Be and $^{26}$Al concentrations into denudation rates, a
262 sea-level high-latitude production rate of 4.02±0.33 atoms g$^{-1}$yr$^{-1}$ (Borchers et al., 2016) was used,
263 along with a spallation production Al-Be ratio of 6.61±0.52, as calibrated at ASTER, the French
264 AMS facility (Rixhon et al., 2011). To determine basin-wide surface production rates and account
265 for geomorphic shielding potentially caused by surrounding topography, we applied the scaling
266 scheme of Stone (2000) and the shielding formalism of Dunne et al. (1999) to a regional digital
267 elevation model (DEM) sourced from the FABDEM database (Hawker et al., 2022). Calculations
268 were carried out using in-house MATLAB scripts, tools developed by Balco et al. (2008), and the
269 TopoToolbox suite (Schwanghart and Scherler, 2014). This approach allows estimation of
270 geomorphic shielding and cosmogenic scaling factors for both latitude–elevation-dependent high-
271 energy neutrons (Stone, 2000) and elevation-dependent fast and stopping muons (Braucher et al.,
272 2011). Although recent studies have questioned whether this scaling procedure may introduce a
273 slope-dependent systematic error (e.g., DiBiase, 2018), we retained it in our calculations, as the
274 debate remains unresolved and its effect on denudation rates is limited to a few percent (Uagoda
275 et al., 2025).

276 3.3.1. *Denudation rates from cosmogenic nuclide concentrations*

277 In river-borne sediment, the cosmogenic concentration N(ϵ,t) as a function of time (t, in year)
278 and denudation (ϵ, in g cm⁻².yr⁻¹) can be written as (e.g., Lal, 1991; Dunai, 2010): N(ϵ, t) =

$$
279 \quad \sum_i \frac{P_i}{\lambda + \frac{\rho\epsilon}{\Lambda_i}} \left(1 - e^{-\left(\lambda + \frac{\rho\epsilon}{\Lambda_i}\right)t}\right) \quad (1)
$$
where $\Lambda_i$ represents the effective apparent attenuation lengths of neutrons ($\Lambda_n$, ≈150 g cm⁻²), stopping muons ($\Lambda_{\mu s}$, ≈1500 g cm⁻²), and fast muons ($\Lambda_{\mu f}$, ≈4320 g cm⁻²), respectively (e.g., Braucher et al., 2011); $\lambda$ is the radioactive decay constant of the considered cosmogenic nuclide (¹⁰Be or ²⁶Al), and $\rho$ (in g cm⁻³) is the density of the material exposed to secondary cosmogenic particles in the source area.

Using equation 1 to derive denudation rates from *in situ*-produced cosmogenic ¹⁰Be or ²⁶Al concentrations requires that these quantities have reached their secular equilibrium values, which implies that the landscape has been exposed to the flux of cosmic particles for enough time (e.g., Lal, 1991), so that:

$$N(\epsilon) = \sum_{i} \frac{P_i}{\lambda + \frac{\rho\epsilon}{\Lambda_i}} \quad (2)$$

Within this context, equation 2 represents the accumulation of cosmogenic nuclides under a steady-state denudation rate sustained over a period long enough to reach secular equilibrium. The time needed to achieve this equilibrium, generally termed the “effective time” (e.g., Lal, 1991), can be expressed to incorporate all production pathways (neutrons and muons) as (Oliveira et al., 2025):

$$T_{\text{eff}} = \frac{1}{(\lambda + \frac{\rho\epsilon}{\Lambda_n}) + (\lambda + \frac{\rho\epsilon}{\Lambda_{\mu s}}) + (\lambda + \frac{\rho\epsilon}{\Lambda_{\mu f}})} \quad (3)$$

### 3.3.2. Burial dating

For river-borne samples with Al-Be ratios lower than the steady-state surface value (6.61±0.52 for denudation rates above 20 m Myr⁻¹), accounting for burial effects is crucial when interpreting denudation rates. The burial dating method relies on analyzing materials initially exposed to
cosmic rays before being buried deep enough so that *in situ* muonic production is reduced to 1% of the total surface production (Braucher et al., 2011). Once buried, the *in situ* production of cosmogenic nuclides ceases, and their concentrations evolve solely by radioactive decay. By measuring the concentrations of two cosmogenic nuclides with different half-lives like $^{26}$Al and $^{10}$Be, it is thus possible to compute burial durations and date burial events that occurred within the last ≈5 Myr (e.g., Granger and Muzikar, 2001).

To do so accurately, it is necessary to have prior knowledge of the pre-burial cosmogenic nuclide ratios and ensure that quartz had sufficient surface exposure time to accumulate detectable nuclide concentrations (Blard et al., 2019a,b). In environments dominated by erosional surface processes, sediment transport times must be short relative to their exposure duration before burial, and sediment storage within the catchment should be minimal. Moreover, burial must occur rapidly and deeply enough to effectively halt post-burial nuclide production. This is why this approach is particularly well-suited for dating sediment infill within caves (e.g., Häuselmann and Granger, 2005; Häuselmann, 2007; Sartégou et al., 2018; Häuselmann et al., 2020; Sartégou et al., 2020).

Pre-burial nuclide concentrations are connected to average denudation rates at the time of burial through the following relationship (Blard et al., 2006):

$$316 \qquad \bar{\epsilon} = \sum_{i} \frac{\overline{P_{i} \times \Lambda_{i}}}{\rho \times \epsilon} \qquad (4)$$

Where again i denotes different cosmogenic production pathways of neutrons, slow and fast muons, $\Lambda_i$ represents their attenuation lengths, and $P_i$ their corresponding averaged nuclide production rates.
In context of slow denudation rates, pre-burial nuclide ratios may drop below the production ratio (see above), leading to potential overestimation of burial ages. To address this issue, Blard et al. (2019a,b) proposed to consider the watershed's elevation and apply the following equation:

$$ \frac{P_{26}}{N_{26}} \exp(-\lambda_{26} \cdot t_B) - \frac{P_{10}}{N_{10}} \exp(-\lambda_{10} \cdot t_B) = \frac{\lambda_{26} - \lambda_{10}}{S} \quad (5) $$

where S is a scaling factor for latitude and altitude, $t_B$ is the burial duration, $P_{10}$ and $P_{26}$, $N_{10}$ and $N_{26}$, and $\lambda_{10}$ and $\lambda_{26}$ are the production rates, concentrations, and decay constants of $^{10}$Be and $^{26}$Al cosmogenic nuclides.

Because an analytical solution is not possible, burial durations are determined through a Monte Carlo simulation involving 10,000 iterations, using the Matlab script provided by Blard et al. (2019b). This method treats the cosmogenic nuclides concentrations as normally distributed variables, within their respective analytical uncertainties. The final burial age estimates and their uncertainties are derived from the mean and standard deviation of the simulation outcomes (Blard et al., 2019a,b).

### 3.3.3. Partial-burial and dynamic mixing

The complexity of cosmogenic signals is not always limited to burial alone. In regions with low denudation rates, prolonged residence time within the production layer, including the regolith and saprolite, can approach the half-lives of $^{26}$Al and $^{10}$Be. This extended exposure can lead to significant nuclide losses due to radioactive decay. Over such long periods, dynamic processes like bioturbation and pedogenesis (e.g., translocation of fine particles and organic matter) may further complicate the signal by introducing a mixing effect. These processes can alter the steady-state Al-
340 Be ratio of sediments before they are transported into the drainage system (Makhubela et al., 2019),
341 resulting in sediments already imprinted with depleted Al-Be ratios upon entering the river.

342 To account for these complexities, we adopted the formalism of Foster et al. (2015), which
343 expresses ¹⁰Be and ²⁶Al concentrations as a function of the mixed layer’s depth (H, in meters) and
344 the denudation rate (ε). In this approach, the mixed soil layer is considered in a steady state,
345 balancing the regolith production rate and surface denudation rate at the catchment scale (Godard
346 et al., 2024). The resulting equation is:

$$347 N = \frac{\bar{P}_H}{\frac{\epsilon\beta}{1 + \frac{\lambda H}{\epsilon\beta}}} + N_b \quad (6)$$

348 where P̄ represents the depth-averaged production rate in the soil, accounting for both spallation
349 and muogenic production, β is the rock-to-soil density ratio, and N<sub>b</sub> is the nuclide concentration at
350 the bedrock-soil interface, which depends on both H and ε.

### 3.3.4. Sediment mixing during routing

352 To estimate the proportion of sediment mixing during routing through the fluvio-karst system,
353 we also applied a straightforward two-source mixing model, where freshly eroded material (f) is
354 combined with a fraction of previously buried sediments (1-f). To estimate the fraction of freshly
355 eroded material, we adapted the approach of Hu et al. (2011), which incorporates the Al-Be ratio
356 in the source area (R'), the measured Al-Be ratio in the river sediments (R<sub>meas</sub>), the mean life of
357 ¹⁰Be (τ<sub>10</sub> = 2.01 × 10<sup>6</sup> years), and the burial duration before mixing (t<sub>B</sub>):

$$358 f = \frac{\left(\frac{R_{\text{meas}}}{R'} - 1\right)}{\left(e^{-2t_B/\tau_{10}-1}\right) - \left(R_{\text{meas}} - R'\right)\left(e^{-t_B/\tau_{10}-1}\right)} \quad (7)$$

359 where R' approximates the secular Al-Be in the source area:
$$360 \quad R' = \frac{P_{26}}{P_{10}} \cdot \frac{1}{1+N_{10}^*} \quad (8)$$

and $N_{10}^*$ is the measured concentration of $^{10}$Be normalized to the secular equilibrium value set by local production and decay (e.g., Hu et al., 2011):

$$363 \quad N_{10}^* = \frac{N_{10}}{P_{10} \times \tau_{10}} \quad (9)$$

Based on measured isotopic concentrations, such a simple two-source model helps estimating the respective contributions from both recently eroded material and older, previously buried sediments within the fluvio-karst. Results are detailed in the supplementary table S3 provided by Uagoda et al. (2025).

## 3.4. Trace elements and XRD

Sample preparation involved air-drying, crushing, and homogenization using an agate mill, followed by digestion. Major elements were determined using alkaline fusion with lithium metaborate in a furnace at 950°C for 60 minutes. The fused material was then dissolved in 2 mol L⁻¹ HCl, and the concentrations were quantified by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) using an Agilent 5100 instrument at the Geochemistry Laboratory, University of Brasília, Brazil.

Other major and trace elements were determined following a 4-step total hot acid digestion procedure, which included the use of hydrofluoric acid (HF) in a Savillex® PFA reactor (Tônhá et al., 2021). The digested samples were then analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) with a Thermo Scientific Q model instrument at the HydroSciences Montpellier (HSM) laboratory, Montpellier, France.
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To ensure data quality, the accuracy of the analyses was verified using the Certified Reference Material (CRM) NIST 1646a. The recoveries ranged from 92% to 106% (n=3), as shown in the supplementary table S4 provided by Uagoda et al. (2025). The NIST 1646a standard was digested and analyzed following the same protocol as the samples. The precision of the methods was assessed by calculating the Relative Standard Deviation (RSD) of the mean of two duplicates. The RSD was below 3% for most elements, including trace elements, and below 5% for all elements.

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A qualitative mineralogical analysis of the total fraction of the sediments was conducted on twelve selected samples using X-ray diffraction (XRD) at the Diffractometry Laboratory of the University of Brasília. The analysis employed a RIGAKU ULTIMA IV diffractometer, which is equipped with a copper tube and a nickel filter. The instrument was operated at 35 kV and 15 mA, with a scanning speed of 2° per minute over a range from 2° to 60°, using a velocity of 5° per minute and step intervals of 0.05°. The resulting diffractograms were analyzed to identify the minerals present in the samples. This identification was performed using the Jade XRD 9.0 program (Materials Data), which utilized the ICDD pdf-2 and pdf4 databases (Power Diffraction File – PDF to PC – ICDD). This comprehensive approach ensured accurate mineral identification and provided valuable insights into the mineralogical composition of the sediment samples. All the raw data for the trace elements and XRD analyses are summarized in the supplementary table S4 and figure S5 provided by Uagoda et al. (2025).

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# 4. Results

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## 4.1. Mineralogical and geochemical compositions
The mineralogical analysis of the sediment samples consistently revealed the presence of quartz and kaolinite across all samples, highlighting their important role in the region's sedimentary framework. Samples from the Aeolian sandstone/Urucuia (BR19) group showed a major presence of quartz and kaolinite-type minerals, attributable to weathering processes. In contrast, samples from the Bambuí Group, which includes limestone, siltstone, and marble, exhibited calcite in the limestone and a predominance of quartz in the siltstone and marble, reflecting common impurities in such carbonate formations. Soil samples from the Patamares, composed of Neoproterozoic carbonates and Quaternary alluvial cover (S1 to S11), revealed the presence of quartz and illite, while those from sandstone areas contained a higher presence of quartz and kaolinite, indicative of well-drained environments (see the supplementary figure S5 provided by Uagoda et al. (2025)).

The analysis indicates that all samples collected from rivers and caves trace back to either the Urucuia sandstone or the Patamares, with soil derived from mudstone, marble, limestone, as well as Quaternary alluvial cover, reflecting soil formation in a well-drained tropical environment. Beyond these shared components, the samples fall into two distinct groups, differentiated by variations in other clay minerals.

The first group (G1 on Fig. 5A), comprising samples derived from the erosion of Urucuia sandstones—including samples P1, P4, P9, and V1 to V4—is marked by notably low concentrations of illite and an absence of smectite. In contrast, groups G2 and M can be combined, aligning with geomorphic controls (Table 1, Fig. 2 and 5A). These groups, which include samples C1, D1 to D4, E1 to E3, Vt1 to Vt3, and V5, display higher concentrations of illite along with a significant presence of smectite-type clay, with this distinct smectite component distinguishing them from the first group.
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A unique feature of sample C1 is its calcite content, which introduces a distinctive mineralogical element. These variations in illite, smectite, and calcite distributions provide valuable insights into the sediment's provenance and the processes involved in its deposition and post-depositional evolution. Illite-type clays suggest the weathering of pelitic and impure carbonate rocks, while the presence of smectite-type clay seems linked to conditions of moderate to low leaching that allowed its preservation.

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The residual presence of quartz and kaolinite corresponds to the well-drained soils of Urucuia sandstone and Quaternary alluvial cover. Meanwhile, illite and smectite clays relate to the weathering of pelitic and carbonate rocks and to the subsequent formation of less well-drained chernozems.

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The geochemical analysis of the sediment samples reveals that Loss on Ignition (LOI) values range from 3.3% to 12.2%, while in rock and soil samples, the variation is even more pronounced, with LOI values reaching up to 41.3%. Silicon dioxide (SiO₂) is the dominant component in the sediment samples, with concentrations ranging from 66.3% to 88.3%, followed by aluminum oxide (Al₂O₃) and iron oxide (Fe₂O₃), which range from 3.4% to 12.2% and 1.9% to 6.5%, respectively (see the supplementary figure S5 provided by Uagoda et al. (2025)). In contrast, geochemical variability is considerably greater in rock and soil samples. SiO₂ concentrations span from as low as 0.5% to as high as 96.5%, while Al₂O₃ and Fe₂O₃ range from 0.5% to 35.8% and 0.4% to 13.8%, respectively. These broader ranges reflect the diverse mineralogical composition of parent rocks and the varying intensity of weathering processes affecting the soils. Calcium oxide (CaO) concentrations are generally low, staying below 2% in all samples except for the carbonate-rich rock samples (RC and RC2), where they reach 55% and 41.3%, respectively. Other oxides,
including MnO, MgO, Na₂O, K₂O, and P₂O₅, are present in consistently low amounts across the sediment, soil, and rock samples.

Notably, rubidium (Rb) concentrations help differentiate two groups of sediment samples (Fig. 5A): one group exhibits Rb concentrations below 24 mg kg⁻¹, while the other ranges from 35 to 126 mg kg⁻¹. In rock and soil samples, Rb concentrations vary more widely, from 0.8 to 151 mg kg⁻¹, reflecting the influence of mineral weathering and differentiation processes. Additionally, the Lanthanum/Ytterbium (La/Yb) ratio shows significant variability, with values ranging from 4.2 to 12.3 in sediment samples and from 5.6 to 46 in rock and soil samples.

In the context of this study, specific minerals and geochemical markers provide important insights into sediment provenance and dynamics. Illite and smectite offer clues about the degree of weathering and environmental conditions during sediment transport. Illite, which forms under moderate to high weathering conditions, suggests a source area with more intense leaching, while smectite, typically associated with less weathered or more alkaline environments, points to a source with reduced chemical alteration. Additionally, the Rb concentration reflects the mobility of potassium-bearing minerals during weathering, providing insight into the mineral composition of the source material. The La/Yb ratio, which varies with the stability of rare earth elements during weathering, allows for further refinement of provenance analysis. These variations in rare earth element ratio suggest differences in source material across the different sample types (Fig. 5A), with one source derived from the Urucuia sandstones (G1, Escarpment), one source derived from the Bambuí mudstone and soil colluvium (G2, Patamares), and a third intermediate source corresponding to the mixing of the two previous ones (M, Mixed).

## 4.2. Cosmogenic concentrations and Al-Be ratios
Measured ¹⁰Be concentrations range from (1.9±0.3)×10⁴ to (3.7±0.1)×10⁵ atoms g⁻¹, with analytical uncertainties associated to the measured ¹⁰Be/⁹Be ratio ranging from 3.1% to 16.9%, with a median at 3.5% (Fig. 6A). The ²⁶Al concentrations range from (9.5±2.3)×10⁴ to (1.91±0.08)×10⁶ atoms g⁻¹, with analytical uncertainties associated to the measured ²⁶Al/²⁷Al ratio ranging from 3.9% to 37.3%, with a median at 6.5% (Fig. 6A; see also the supplementary tables S1 and S2 provided by Uagoda et al. (2025)). The samples showing the highest analytical uncertainties are also those showing the largest lithological contribution from the sandstones of the Urucuia Formation cropping out along the escarpment (Fig. 6A). These measured ²⁶Al and ¹⁰Be concentrations yield Al-Be ratios ranging from 2.8±0.7 to 6.1±0.5 (Fig. 6B), which correspond to a depletion of 8% to 58% with respect to the secular Al-Be ratio of 6.61±0.52 for constant denudation rates higher than 20 m Myr⁻¹ (Fig. 6B).

Interestingly, the grouping of the samples based on their mineralogical and rare earth element contents aligns with the distribution of Al-Be ratios (Fig. 5B). Samples from the first group (G1, Escarpment), characterized by low La/Yb ratios, show a much wider dispersion of Al-Be values. Conversely, samples from the second group (G2, Patamares), which have high La/Yb ratios, cluster in the Al-Be space between 4.5 and 5.5. Samples with mixed source signatures occupy either the Patamares group or an intermediate position in the La/Yb - Al-Be space (Fig. 5B).

### 4.3. Denudation rates, integration and burial durations

Assuming long exposure and constant denudation to achieve the secular equilibrium (i.e., equation 2), the ¹⁰Be concentrations convert into denudation rates ranging from 10.9±0.7 to 248.5±44.1 m Myr⁻¹ (Table 1). The denudation rates derived from ²⁶Al concentrations range from 15.4±1.1 to 360.9±89.1 m Myr⁻¹ (Fig. 6C). They are roughly 1.2 to 1.8 times higher than those
calculated from ¹⁰Be concentrations, yielding fluvial ratios (e.g., Halsted et al., 2024) comprised between 0.5 and 0.9 (Fig. 6C; see also the supplementary table S3 provided by Uagoda et al. (2025)).

The three groups (Escarpment; Patamares; Mixed) are also evident when plotting the data in the space of the Al-Be ratio versus ¹⁰Be concentrations (Fig. 7A). While the large analytical uncertainties on the ²⁶Al measurements for the Escarpment Group prevent a definitive conclusion about whether secular equilibrium is reached or not, the other samples (Patamares and Mixed) are clearly positioned beneath the curves defining the "surface erosion" domain (e.g., Lal, 1991), indicating an apparent burial signature. It is also noteworthy that the samples from the Mixed Group are situated between the Escarpment and Patamares groups, and consistent with the samples collected inside the Tarimba Cave (Fig. 7A).

Using this grouping, we conducted a statistical analysis to determine key parameters, including the mean, median, and weighted mean values for ¹⁰Be and ²⁶Al-derived denudation rates, ¹⁰Be-derived-integration time scales, Al-Be ratios, burial durations, and pre-burial corrected denudation rates (Table 2). To ensure robust confidence intervals for the estimated central values, we applied bootstrapping, a method particularly suited for datasets with nonnormal distributions or potential outliers. Among the computed metrics, we highlight the weighted means as they are more representative, reflecting the relative importance of each measurement.

Denudation rates are found to be highest in the Escarpment compartment, with a mean value of 121.7±11.8 m Myr⁻¹, significantly exceeding those in the Mixed (24.5±2.6 m Myr⁻¹) and Patamares (12.0±0.5 m Myr⁻¹) groups. Integration durations are observed to be shortest for the Escarpment Group (3996±536 years), while much longer durations are recorded for the Mixed (20169±2507 years) and Patamares (43817±2871 years) groups. However, this average is skewed
512 downward by samples with integration times below 35 kyr. The older samples in this group, with
513 integration times closer to 50 kyr, are therefore more representative of the characteristic timescales
514 of the Patamares (Fig. 7B). This is consistent with the values observed for the Mixed Group (Table
515 2), again indicating a mixture between a younger source (Escarpment) and an older source
516 (Patamares).

517 **5. Discussion**

518 5.1. Comparative analysis of fluvio-karst systems and sediment dynamics in the
519 Brazilian savanna

520 The Chapada Diamantina border (Laureano et al., 2016) comprises Neoproterozoic
521 metasedimentary rocks (Una Group) and Mesoproterozoic sandstones (Chapada Diamantina Group),
522 forming plateaus (≈1050 m). Perennial rivers disappear into carbonate sinkholes (i.e., Lapa Doce
523 Cave, 662 m), with Cenozoic colluvial-alluvial terraces formed from sandstone erosion. Deep
524 Ferralsols dominate plateaus, while Arenosols and Chromic Luvisols develop on terraces and
525 carbonates. The fluvio-karst system includes dolines, canyons, and springs connected by
526 subterranean drainage, with caves preserving paleo-soil breccias and conglomerates. In contrast,
527 Chapadas das Mesas (Barreto et al., 2022) comprises Neoproterozoic-Eoproterozoic sedimentary-
528 volcanic sequences (Parnaíba Group), with tablelands (600 m) and steep canyons (120 m floor, >50%
529 slopes). Valley fills consist of quartzarenitic Arenosols, while plateaus host lateritic Leptosols and
530 localized Ferralsols on basalts. High sandstone permeability limits surface runoff, and lateritic crusts
531 stabilize plateaus. Though previously interpreted as collapsed caves, canyons represent sandstone
532 pseudo-karst without apparent karst hydrology (i.e., Ibitipoca; Willems et al., 2005).
533 Iraquara shares similarities with Vermelho, including fluvio-karst development on
534 Neoproterozoic limestones and colluvial-alluvial sediment sources. However, the gentle
535 topography in Iraquara preserves Pleistocene terraces as key sediment reservoirs, whereas steeper
536 gradients in the Vermelho enhance karst dynamics but reduce sediment preservation. Chapadas
537 das Mesas differs markedly, with mesa landscapes controlled by lateritic crusts and pseudo-karst
538 features lacking integrated drainage. Sediments derive from laterite and sandstone breakdown,
539 accumulating in valleys. While Vermelho and Chapadas das Mesas both exhibit steep escarpments,
540 Vermelho and Iraquara share Quaternary detrital covers in source areas.

541 5.2. Burial or not burial, that is the question

542 Upstream samples in the Vermelho exhibit Al-Be ratios lower than the steady-state value
543 (6.61±0.52), regardless of source areas. High analytical uncertainties in the samples derived from
544 the escarpment complicate distinguishing them from secular equilibrium (Fig. 7A). Interestingly,
545 a similar pattern is observed in the dataset of Barreto et al. (2022) from the Chapadas das Mesas
546 in Maranhão (Fig. 7A). In contrast, samples from the Mixed and Patamares groups align closely
547 with those collected in the Tarimba Cave. Although for a lower range of denudation rates, such an
548 apparent burial pattern is also evident in the dataset of Laureano et al. (2016), near the Chapada
549 Diamantina border (Fig. 7A).

550 The Vermelho exhibits a weighted mean burial age of 0.61±0.21 Myr with a broad distribution,
551 whereas the Tarimba samples display a narrower distribution (Fig. 7C). The Al-Be ratios are
552 comparable between the Mixed (5.2±0.3) and the Patamares (5.0±0.1), while the Escarpment has
553 distinctly lower ratios (4.2±0.4). Consequently, burial times are longest for the samples originating
554 from the escarpment (0.84±0.15 Myr), whereas shorter durations are observed in the Mixed
(0.44±0.08 Myr) and Patamares (0.49±0.05 Myr) groups (Table 2). These values are comparable to the mean burial duration for the Tarimba samples (0.38±0.07 Myr). To ensure consistency, burial durations were recalculated for samples analyzed in the studies by Laureano et al. (2016) and Barreto et al. (2022). While the high uncertainties in the Sierra das Mesas dataset prevent detailed interpretations, the Iraquara dataset reveals a distribution closely resembling that of the Vermelho Watershed (Fig. 7C).

Assuming complete burial, pre-burial corrected denudation rates (e.g., Blard et al., 2019b), derived from measured Al-Be ratios, are highest in the Escarpment group (40.0±5.6 m Myr⁻¹), followed by the Mixed (10.9±1.0 m Myr⁻¹) and Patamares (5.8±0.3 m Myr⁻¹) groups (Table 2). Although speculative, these corrected rates highlight significant variations in erosion processes and sediment dynamics across landscape units.

An alternative approach for the interpretation involves estimating the respective contributions of freshly eroded material (f, at secular equilibrium in the source area) and buried material (1-f), stored in the fluvio-karst, to the measured Al-Be ratios (e.g., Hu et al., 2011). Within this framework, the distance from the headwaters to the sampling site becomes a key indicator of the sediment mixing process in the Vermelho Watershed.

Samples collected close to the headwaters, with trunk lengths shorter than 25 km, show no clear pattern, although the fraction f is generally higher for the Patamares compared to the Escarpment (Fig. 8A). Samples from the Patamares form a distinct cluster with f values between 30 and 43% and trunk lengths under 10 km. In contrast, Escarpment samples collected within this range (trunk lengths <25 km) show lower f values (18–33%) that thus reflect a higher proportion of material with a burial signature.
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For samples collected farther downstream along the main trunk of the Vermelho River (trunk
lengths >25 km), a clear linear trend emerges, with f progressively increasing with distance
downstream (Fig. 8A). This trend reflects the increasing incorporation of freshly eroded material
along the main trunk, likely sourced from tributaries and surrounding slopes.

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Additionally, areas with a higher fluvial ratio (e.g., Halsted et al., 2024) tend to have a higher
fraction of freshly eroded material, indicating that fluvial processes play a significant role in
erosion and material transport in the Vermelho fluvio-karst. The Vermelho dataset shows a positive
correlation between the fluvial ratio and the fraction of freshly eroded material (Fig. 8B), with
distinct clusters for Escarpment, Mixed, and Patamares regions, whereas the dataset from
Laureano et al. (2016) exhibits a similar trend but with generally higher fractions of freshly eroded
material at comparable fluvial ratios. Additionally, the Vermelho dataset displays more variability,
as indicated by larger error bars, compared to the more tightly clustered data from Iraquara.

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As sediments travel further downstream, they become increasingly mixed with freshly eroded
material, approaching secular equilibrium. This pattern may be explained by enhanced erosion or
sediment input along the main trunk, progressively diluting the previously buried material.
Additionally, the increasing sediment flux downstream likely facilitates greater incorporation of
freshly eroded material near equilibrium.

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The OSL dates obtained by Caldeira et al. (2021) in the Tarimba Cave challenge the full burial
hypothesis in the Vermelho fluvio-karst. Burial durations of approximately 200 kyr would be
required for the Al-Be ratio to decrease significantly from the theoretical secular equilibrium value
at the surface. Indeed, the samples from the Tarimba Cave exhibit Al-Be ratios of 5.4±0.2,
corresponding to burial durations of 0.38±0.07 Myr (Table 2). These apparent burial durations are

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however significantly longer than the OSL ages determined by Caldeira et al. (2021) for the same cave samples, which range from 48 to 213 ka (Fig. 4C).

## 5.3. Processes driving Al-Be variability

The discrepancies in Al-Be ratios suggest that depletion primarily occurs before sediment deposition in caves, highlighting the complexity of cosmogenic signals in river sediments. In the Escarpment, steep slopes lead to high denudation rates driven by mass wasting and fluvial incision. Material eroded from escarpments and slopes often contains pre-imprinted low Al-Be values due to landslides and gully incisions. The large uncertainties should however warrant caution when associating cosmogenic nuclide concentrations with specific processes. In fact, the data from the Vermelho and the Eastern Amazonian region can be explained by the stochastic delivery of partly shielded sediment to the watershed due to the retreat of the escarpments bordering the sandstone tablelands, rather than solely by the erosion of a karst system, exhuming previously buried material, as initially claimed by Barreto et al. (2022).

Conversely, the gentler slopes of the Patamares, dominated by limestone and Quaternary covers, exhibit lower denudation rates, reflecting the stability of low-relief terrain and the influence of well-developed karst systems. Denudation rates derived from ¹⁰Be concentrations strongly correlate with topographic variations (Fig. 6D), where the Escarpment shows high rates driven by gravitational processes, while the Patamares are characterized by subdued erosional dynamics such as surface wash and soil creep. The Mixed Group, with intermediate values, highlights the combined effects of Escarpment and Patamares processes, and probable contamination with previously buried material.
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To estimate the possibility for the Al-Be ratio to be depleted within the production layer in the Patamares, we applied dynamic vertical mixing models using the measured cosmogenic concentrations together with the modified formalism of Foster et al. (2015) for steady-state conditions where basin-wide surface denudation equals the rate of the saproliteregolith conversion (e.g., Godard et al., 2024). Within this framework, we tested the samples from the Vermelho, and those from the Lapa Doce Cave, in Iraquara (Fig. 9A-D), excluding the samples originating from the escarpment.

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In the Patamares sources, the flatter topography significantly influences sediment dynamics by stabilizing the production layer. This stability allows sediment grains to remain within the uppermost layers of the soil column for extended periods, resulting in longer residence times compared to the steeper escarpment (Table 2. Despite this stability, the Al-Be ratios observed for the Patamares dataset suggest the influence of additional processes beyond steady-state erosion. Vertical mixing emerges as a key process to explain these discrepancies. Such vertical movement disrupts the systematic accumulation of cosmogenic nuclides by exposing sediment grains to varying cosmic ray fluxes over time. This mixing effectively alters the exposure histories, resulting in systematically lower Al-Be ratios and apparent burial signatures of the sediment.

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The bootstrap-derived mean production layer thickness that are estimated for the Mixed and Patamares samples are ranging from 16 to 27 m and from 10 to 14 m, respectively (Fig. 9E). For the Lapa Doce samples, the estimated thickness is only 4 to 5 m, which is in good agreement with the differences in geomorphic setting between the two studied regions. The denudation rates, corrected for vertical dynamic mixing in the production layers appears to be in good agreement with the pre-burial corrected rates using the complete burial framework (Fig. 9E): 11-19 m Myr⁻¹ for the Mixed samples; 4-7 m Myr⁻¹ for the Patamares; 0.9-1.3 m Myr⁻¹ for Lapa Doce.
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The mean production layer for Patamares is relatively thick, indicating that sediments spend extended periods within the near-surface zone where vertical mixing processes are active. Meanwhile, the low denudation rates reflect the reduced rates of sediment removal, providing additional time for these mixing processes to influence the nuclide inventories. When compared with Laureano et al. (2016)'s dataset, a similar trend can be observed, where flatter terrains and lower erosion rates also lead to comparable Al-Be patterns. This consistency across datasets underscores the importance of vertical mixing in regolithic sources to modify the cosmogenic Al-Be ratios in regions with low-relief topography.

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# 6. Conclusion

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This study investigates the sedimentary dynamics and geomorphic processes within the Vermelho Watershed, offering new insights into sediment transport, burial histories, and denudation rates in tropical karst environments. By comparing our findings with those from the Iraquara and Chapadas das Mesas regions, we highlight the intricate interplay between landscape morphology, sediment sources, and cosmogenic nuclide signals.

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The burial durations derived from Al-Be ratios (0.61±0.21 Myr) reveal significant variability across geomorphic units. While Escarpment samples exhibit lower Al-Be ratios and longer burial times (0.84±0.15 Myr), samples from the Patamares and Mixed groups show shorter burial durations (0.49±0.05 and 0.44±0.08 Myr, respectively). This pattern suggests that the depleted cosmogenic nuclide ratios are primarily acquired upstream, reflecting the combined effects of rapid erosion in steep escarpments and prolonged residence in flatter terrains.

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The fraction of freshly eroded material (f) systematically increases with distance downstream, as sediments mix with material near secular equilibrium. These findings underscore the importance
665 of fluvial processes in progressively diluting the cosmogenic signal of previously buried material
666 and show how sediment mixing reflects the geomorphic and hydrological settings of the
667 watershed.

668 Broader implications emerge from comparing the Vermelho with Iraquara and Chapadas das
669 Mesas. While steep slopes dominate the Vermelho and Chapadas das Mesas, facilitating rapid
670 erosion and sediment delivery, the flatter terrains of Iraquara promote sediment preservation in
671 terraces. These regional contrasts emphasize the influence of geomorphic context in shaping
672 sediment transport dynamics and cosmogenic nuclide patterns.

673 Finally, the results demonstrate the complexity of interpreting cosmogenic nuclide data in
674 tropical karst landscapes. Processes such as vertical mixing, differential erosion, and sediment
675 reworking introduce nuances that extend beyond steady-state assumptions. Indeed, corrected
676 denudation rates for either full burial or vertical mixing are significantly lower than those
677 determined using solely ¹⁰Be concentrations and the steady-state assumption. These findings
678 enhance our understanding of sedimentary dynamics in tropical karst systems and provide a
679 valuable framework for integrating cosmogenic data with geomorphic and sedimentological
680 insights.

681 **7. Data availability**

682 The data that support the findings of this study are openly available in Zenodo repository. Data
683 reuse is granted under CC-BY license (doi: 10.5281/zenodo.15088305) (Uagoda et al., 2025).
684 During the review process the supplementary material is temporarily accessible on this link to the
685 dataset.
686 **8. Acknowledgments**

687 The authors would like to thank both the Franco-Brazilian framework for scientific
688 collaboration CAPES-COFECUB (projects 869/15 and 981/20) and the CAPES PRINT for their
689 continuous support. The authors also thanks TCCE 01 Vale-ICMBio for logistic, sampling and
690 analysis funds. The ASTER AMS national facility (CEREGE, Aix-en-Provence) is supported by
691 INSU/CNRS and IRD, and is a member of Aix-Marseille technological platforms and REGEF
692 networks. Geochemical and mineralogical analyses were partly supported by CNPq grant
693 310750/2014-8 and 302722/2018-1, FAP-DF00193-00000308/2023-1. Lionel Siame and Rogerio
694 Uagoda are grateful to IRD for the support through the “Mission de Longue Durée” and the
695 “Mobilités Sud Nord” mobility programs, respectively. The authors declare no conflicts of interest
696 relevant to this study.

697
698 Tables and Figures captions

699 Table 1: ¹⁰Be and ²⁶Al-derived denudation rates (Equation 2) using the secular equilibrium
700 assumption, with geomorphic and lithological characteristics of the sampled watersheds. Fluvial
701 ratio and fraction of freshly eroded material are after Halsted et al. (2024) and Hu et al. (2011),
702 respectively.

703
<table><caption>Table 1</caption><thead><tr><th>Group</th><th>Sample ID</th><th><sup>10</sup>Be Denudation<br>(m Myr<sup>-1</sup>)</th><th><sup>26</sup>Al Denudation<br>(m Myr<sup>-1</sup>)</th><th>Length<br>(km)</th><th>Fluvial ratio</th><th>Fraction of freshly eroded material</th><th>Relief<br>(km)</th><th>Slope<br>(m km<sup>-1</sup>)</th><th>Area<br>(km<sup>2</sup>)</th><th>Bambui</th><th>Quaternary</th><th>Urucuia</th></tr></thead><tbody><tr><td rowspan="5">Patamares</td><td>D1</td><td>10.9±0.7</td><td>17.1±1.2</td><td>5.36</td><td>0.64±0.06</td><td>0.31</td><td>0.14</td><td>26.87</td><td>14.18</td><td>0.22</td><td>0.70</td><td>0.08</td></tr><tr><td>D3</td><td>11.3±0.8</td><td>18.2±1.3</td><td>9.46</td><td>0.62±0.06</td><td>0.30</td><td>0.20</td><td>21.25</td><td>32.68</td><td>0.48</td><td>0.47</td><td>0.06</td></tr><tr><td>E3</td><td>11.4±0.8</td><td>15.4±1.1</td><td>9.09</td><td>0.74±0.07</td><td>0.43</td><td>0.19</td><td>21.01</td><td>25.27</td><td>0.31</td><td>0.53</td><td>0.16</td></tr><tr><td>D4</td><td>10.6±0.7</td><td>15.7±1.2</td><td>1.01</td><td>0.68±0.07</td><td>0.35</td><td>0.22</td><td>21.39</td><td>32.95</td><td>0.48</td><td>0.46</td><td>0.05</td></tr><tr><td>E2</td><td>10.6±0.7</td><td>14.7±1.1</td><td>2.15</td><td>0.72±0.07</td><td>0.40</td><td>0.07</td><td>25.47</td><td>4.44</td><td>0.33</td><td>0.62</td><td>0.05</td></tr><tr><td>E1</td><td>15.0±1.0</td><td>21.3±1.5</td><td>6.89</td><td>0.70±0.07</td><td>0.36</td><td>0.21</td><td>31.06</td><td>16.23</td><td>0.12</td><td>0.64</td><td>0.24</td></tr><tr><td rowspan="6">Mixed</td><td>Vt3</td><td>23.2±2.1</td><td>29.1±2.8</td><td>17.31</td><td>0.80±0.11</td><td>0.51</td><td>0.28</td><td>16.12</td><td>158.78</td><td>0.16</td><td>0.45</td><td>0.39</td></tr><tr><td>Vt1</td><td>26.0±1.8</td><td>46.7±4.8</td><td>15.84</td><td>0.56±0.07</td><td>0.25</td><td>0.27</td><td>17.05</td><td>141.82</td><td>0.12</td><td>0.45</td><td>0.42</td></tr><tr><td>C1</td><td>17.4±1.2</td><td>24.7±2.1</td><td>8.23</td><td>0.71±0.08</td><td>0.36</td><td>0.16</td><td>18.83</td><td>36.65</td><td>0.79</td><td>0.17</td><td>0.04</td></tr><tr><td>V6</td><td>40.3±3.0</td><td>48.4±4.3</td><td>47.96</td><td>0.84±0.10</td><td>0.58</td><td>0.41</td><td>8.59</td><td>687.80</td><td>0.43</td><td>0.22</td><td>0.35</td></tr><tr><td>Vt5</td><td>21.0±1.5</td><td>30.4±2.6</td><td>19.10</td><td>0.69±0.08</td><td>0.34</td><td>0.30</td><td>15.92</td><td>164.77</td><td>0.18</td><td>0.44</td><td>0.37</td></tr><tr><td>V5</td><td>29.1±2.1</td><td>40.6±3.7</td><td>37.91</td><td>0.72±0.08</td><td>0.35</td><td>0.36</td><td>9.44</td><td>598.97</td><td>0.36</td><td>0.24</td><td>0.40</td></tr><tr><td rowspan="6">Escarpment</td><td>V1</td><td>178.2±22.3</td><td>300.1±66.3</td><td>18.79</td><td>0.60±0.15</td><td>0.25</td><td>0.26</td><td>13.94</td><td>140.10</td><td>0.23</td><td>0.14</td><td>0.64</td></tr><tr><td>V2</td><td>106.7±19.2</td><td>160.7±61.0</td><td>22.26</td><td>0.67±0.28</td><td>0.25</td><td>0.27</td><td>12.08</td><td>153.35</td><td>0.29</td><td>0.13</td><td>0.58</td></tr><tr><td>P4</td><td>170.5±24.7</td><td>237.6±36.8</td><td>15.02</td><td>0.72±0.15</td><td>0.32</td><td>0.32</td><td>21.37</td><td>106.55</td><td>0.34</td><td>0.12</td><td>0.54</td></tr><tr><td>P9</td><td>121.4±11.2</td><td>167.1±25.7</td><td>16.53</td><td>0.73±0.13</td><td>0.33</td><td>0.28</td><td>17.00</td><td>119.08</td><td>0.21</td><td>0.13</td><td>0.66</td></tr><tr><td>P1</td><td>248.5±44.1</td><td>366.0±91.6</td><td>11.90</td><td>0.69±0.21</td><td>0.28</td><td>0.27</td><td>22.77</td><td>58.12</td><td>0.13</td><td>0.09</td><td>0.78</td></tr><tr><td>V3</td><td>97.6±13.5</td><td>264.9±55.7</td><td>22.90</td><td>0.37±0.09</td><td>0.18</td><td>0.27</td><td>11.83</td><td>153.91</td><td>0.29</td><td>0.13</td><td>0.58</td></tr><tr><td>V4</td><td>93.3±8.0</td><td>171.4±19.6</td><td>31.13</td><td>0.56±0.08</td><td>0.24</td><td>0.34</td><td>10.95</td><td>310.47</td><td>0.16</td><td>0.12</td><td>0.72</td></tr></tbody></table>
704 Table 2: Statistical summary of the parameters derived from the measured cosmogenic
705 concentrations. The values represent the weighted means with their respective uncertainties.

706
<table><caption>Table 2</caption><thead><tr><th>Parameter</th><th>Escarpment</th><th>Mixed</th><th>Patamares</th><th>Tarimba</th><th>Lapa Doce</th></tr></thead><tbody><tr><td><sup>10</sup>Be Denudation rate (m Myr<sup>-1</sup>)</td><td>121.7±11.8</td><td>24.5±2.6</td><td>12.0±0.5</td><td>27.2±3.22</td><td>10.9±8.9</td></tr><tr><td><sup>10</sup>Be Integration time (yr)</td><td>3996±536</td><td>20169±2507</td><td>43817±2871</td><td>18056±2078</td><td>14768±2035</td></tr><tr><td>Al-Be ratio</td><td>4.2±0.4</td><td>5.2±0.3</td><td>5.0±0.1</td><td>5.4±0.2</td><td>4.3±0.2</td></tr><tr><td>Burial time (Myr)</td><td>0.84±0.15</td><td>0.44±0.08</td><td>0.49±0.05</td><td>0.38±0.07</td><td>0.56±0.07</td></tr><tr><td>Pre-burial corrected denudation rate (m Myr<sup>-1</sup>)</td><td>40.0±5.6</td><td>10.9±1.0</td><td>5.8±0.3</td><td>13.4±1.7</td><td>1.6±0.1</td></tr></tbody></table>
<figure><img src="image_3.png" /><figcaption>Figure 1: Location of the studied region on a topographic map of Brazil, highlighting areas with elevations above 1000 meters (in yellowish hues) and karstified carbonate regions (in purple). The red dotted line depicts the Serra Geral Escarpment. The black open box locates the studied area presented with more details in Figure 2. Previous studies using cosmogenic nuclides in karstic settings are also indicated: (1) Laureano et al. (2016) and (2) Barreto et al. (2022).</figcaption></figure>
<figure><img src="image_4.png" /></figure>

713

714

715

716

717

718

719

720

721

722

Figure 2: Geological Map of the studied area (Rio Vermelho), highlighting the sampling locations upstream, within, and downstream of the karst area. A gradient overlay in shades of grey is used to indicate the karst index of the distribution of caves and dolines (dark grey dots), ranging from zero to three features per km². The catchments upstream of each sampling point are delineated (black contours) as well as the position of the Tarimba Cave (green line). Red and black circles locate sampling positions along the river trunks and inside the caves, respectively. Yellow triangles indicate the position of source samples (rock and soil). Numbers with * refer to averaged denudation rates calculated using averaged ¹⁰Be concentrations and the secular equilibrium assumption using equation 2.
<figure><img src="image_5.png" /><figcaption>Figure 3: A. Schematic geological profile of the Vermelho Basin and Serra Geral Escarpment, showing the sandstone of the Urucuia Group that makes the Western Bahia Plateau (see Fig. 1) and the regional escarpment. The lower scarp is constituted by colluvium forming fans. The long-term escarpment retreat has generated a flat, regional surface above the unconformity between the Cretaceous sandstones and the Neoproterozoic pelites and carbonates from the Bambuí Group, hosting the studied caves and canyons system. B. Duricrust capping the Serra Geral. C. View of the Serra Geral, showing the escarpment and the colluvial bench (Dornas et al., 2022). D.</figcaption></figure>
731 Colluvium surrounding a mesa. E. Fluviokarst landscape, with a river flowing out at a karst

732 resurgence. F. Canyon where the Vermelho River is entrenched along its middle and lower course.

733 G. Eroded relief of the Corente River, into which the Vermelho River discharges in the Vão do

734 Paranã. H. Entrance to an upper gallery of a cave within a doline at the top of a slope. I. Upper

735 conduits of a cave filled with clastic sediments. J. Alluvial fan formed from external sedimentary

736 material deposited inside a subterranean river.
<figure><img src="image_6.png" /><figcaption>Figure 4: A. Topography of the Tarimba Cave, starting at a large doline and extending to a perched valley of the Extrema River (E). B. Schematic profile of Tarimba Cave, showing upper levels filled</figcaption></figure>
with ancient sediments, while the lower levels are phreatic. C. Sampling conducted by Caldeira et al. (2021) in the upper ducts, filled with clastic sediments, for optically stimulated luminescence dating (TCM1-10: 87.6±8.0 ka; TCM2-10: 197.2±16.1 ka; TP-30: 82.0±7.5 ka; T3-10: 59.7±5.0 ka; TSE-80: 52.2±4.5 ka). D. Doline where the main channel of Tarimba becomes exposed, the site where sample E2 was collected. E. Spring of the Extrema River emerging from the cave of the same name, where the Tarimba channel converges.

<figure><img src="image_7.png" /></figure>

746

Figure 5: Geochemical patterns of soil, rock, and river-borne samples. A. Geochemical distribution of rock and soil samples based on their Rb (Rubidium) concentrations and La/Yb (Lanthanum/Ytterbium) ratios. Rock samples are grouped into the following categories: RASA (Serra das Araras Sandstone - Jurassic, eolian), RAP (Posse Sandstone - Cretaceous, fluvial), RP (Mudstone - Neoproterozoic), RM (Carbonate - Neoproterozoic), and RC (Limestone - Neoproterozoic). River-borne samples are highlighted to show distinct patterns for two relief groups: G1 (Escarpment) and G2 (Patamares). B. Plot illustrating the relationship between La/Yb and Al-Be ratios in river-borne samples, highlighting distinct patterns across relief groups: G1 from the escarpment (dark gold circles), G2 from the Patamares (light gold circles), and mixed sources (light gold circles with red outlines).
<figure><img src="image_8.png" /><figcaption>Figure 6: *In situ*-produced cosmogenic $^{10}$Be and $^{26}$Al measurements. A. Analytical uncertainties of the isotopic ratios measured at SMA-ASTER (Aix-en-Provence, France). Circles are scaled according to the contribution of the Upper Urucuia Formation (% of Urucuia Fm in the catchment upstream the sampled position, see Table 1), and colored according to their main source provenances (Escarpment, Patamares and Mixed). The Tarimba Cave samples are also indicated (solid pink circles). B. $^{26}$Al concentrations as a function of $^{10}$Be concentrations for the Rio Vermelho dataset (same colors than A). Samples from Laureano et al. (2016) and Barreto et al. (2022) are shown in dark and light grey, respectively. Black solid line shows the steady state Al-Be value for denudation rates higher than 20 m Myr$^{-1}$. Black dotted line is a forced-to-origin linear regression for the Vermelho dataset, using the bootstrap mean of the Al-Be ratios (excluding the samples from the Tarimba Cave). C. $^{10}$Be-derived against $^{26}$Al-derived denudation rates (same</figcaption></figure>
769 colors than A). Black solid line shows the 1:1 relationship. Black dotted line is a forced-to-origin
770 linear regression for the Vermelho dataset, using the bootstrap mean of the fluvial ratios (excluding
771 the samples from the Tarimba Cave). D. Cosmogenic $^{10}$Be-derived denudation rates as a function
772 of averaged slopes in the catchments upstream of the sampled positions (same colors than A). The
773 expected positive correlation is observed for larger basins with a source provenance from the
774 escarpment and is lost for smaller catchments with mixed and Patamares sources. For C and D, the
775 circles are scaled using the upstream catchment area.

<figure><img src="image_9.png" /></figure>

776
777 Figure 7: A. Two nuclide-plot for the Vermelho dataset showing that samples with escarpment
778 source are clearly distinct from the samples with mixed and Patamares sources, which plot together
779 with the buried samples collected inside the Tarimba Cave. Black solid lines depict increasing
780 apparent burial durations (increment 0.5 Myr). Grey solid lines depict denudation rates in m Myr⁻¹
781 (values are indicated between 0 and 2, then increment is 2 m Myr⁻¹). The datasets from Laureano
782 et al. (2016) and Barreto et al. (2022) are also shown in dark and light grey, respectively. This
783 panel was elaborated using Godard (2022)'s set of utilities under the software R (TCNtools). B.
Whisker boxes represent integration timescales derived from ¹⁰Be concentrations, distinguishing two endmembers: E (Escarpment) and P (Patamares), as well as their mixed contributions. C. Density plot for apparent burial durations (in Myr) for the Vermelho and the Tarimba Cave compared to those of Laureano et al. (2016) and Barreto et al. (2022), recalculated for consistency with the Matlab script provided by Blard et al. (2019a). Values in Myr are given for the main peaks (excepted for Barreto et al. (2022)'s data whose uncertainties are too large).

<figure><img src="image_10.png" /></figure>

790

Figure 8: Fraction of freshly eroded material (f) estimated using equation 7 after Hu et al. (2011). A. Fraction f plotted as a function of trunk lengths. B. Fraction f plotted as a function of fluvial ratios, as defined by Halsted et al. (2024). The dataset from Laureano et al. (2016) is also plotted for comparison.

791

792

793

794
<figure><img src="image_11.png" /></figure>

Figure 9: Results of the dynamic vertical mixing models using *in situ*-produced cosmogenic $^{10}$Be and $^{26}$Al concentrations together with the modified formalism of Foster et al. (2015) for steady-state conditions where basin-wide surface denudation equals the rate of saprolite-regolith conversion ($\dot{w}$) in the source area (e.g., Godard et al., 2024). A. Two-nuclide plots showing the data distribution below the steady-state erosion and constant exposure limiting curves for a range of denudation rates ($\epsilon \approx \dot{w}$) and production layer thickness (H). B-D: Production layer thickness as a function of denudation rate with dynamic mixing for the mixed sources and Tarimba Cave (B), the Patamares source (C) and the Lapa Doce samples (D). E. Central values (at $2\sigma$) and probability distribution for the same three groups of samples. We used 10000 bootstrap resamples to estimate the mean and uncertainty associated to denudation rates corrected for vertical mixing and to production layer thicknesses. The figures and the models were elaborated using Godard (2022)'s set of utilities under the software R (TCNtools).

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