Steady erosion rates in the Himalayas through late Cenozoic climatic changes


Sediment accumulation rates and thermal trackers suggest a substantial and global increase in erosion rates over the past few million years. That increase is commonly associated with the impact of the Northern Hemisphere glaciation, but methodological biases have led researchers to debate this hypothesis. Here, we test whether Himalayan erosion rates increased by measuring beryllium-10 (10Be) in the sediment of the Bengal Bay seabed. Sediment originated from rocks that produced 10Be under the impact of cosmic rays during erosion near surface. Thus, the 10Be concentrations indicate erosion rates. The 10Be concentration of the Bengal Bay sediment depends on the contributions of the Ganga and Brahmaputra rivers. Their sediments have distinct 10Be concentrations because of distinct elevations and erosion in their drainage basins. Variable contributions could thus complicate erosion-rate calculation. We traced these contributions by a provenance study using the strontium (Sr) and neodymium (Nd) isotopic sediment compositions. Within uncertainties of ±30%, our reconstructed past erosion rates show no long-term increase for the past six million years. This stability suggests that climatic changes during the late Cenozoic have an undetectable impact on the erosion patterns in the Himalayas, at least on the ten thousand to million year timescales accounted for by our dataset.

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Fig. 1: Map of the Himalayan region and location of study sites in the middle Bengal Fan.
Fig. 2: New 10Be and Sr–Nd isotopic constraints on late Cenozoic Himalayan erosion rates from the Bengal Fan and Lower Meghna River.

Data availability

The datasets generated and analysed during the current study are available in the Pangaea Repository: (sample information, 10Be and Sr–Nd isotopic results, calculated fractions and erosion rates); (10Be duplicate results); (10Be blanks); (major and trace element results); (chemical analyses for river sediment); (Sr–Nd and 10Be data from river sediment used for the fG and K(t) computation). Source data are provided with this paper.

Code availability

The MATLAB and R codes used in this study are available on request from the corresponding author.


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The samples were provided by IODP (International Ocean Discovery Program). We acknowledge the team of IODP Kochi Core Center for their assistance in sample collection, and the teams of CRPG (Centre de Recherches Pétrographiques et Géochimiques), SARM (Service d’Analyses des Roches et des Minéraux) and CEREGE (Centre de Recherche et d’Enseignement de Géosciences de l’Environnement) for their assistance in sample preparation and measurements. We thank A. Galy sharing some Sr-Nd data and providing data quality control. The 10Be measurements were performed at the ASTER AMS national facility (Accélérateur pour les Sciences de la Terre, Environnement, Risques, at CEREGE, Aix en Provence), which is supported by the INSU/CNRS (Institut National des Sciences de l’Univers/Centre National de la Recherche Scientifique), the ANR (Agence Nationale de la Recherche) through the ‘Projets thématiques d’excellence’ programme for the ‘Equipements d’excellence’ ASTER-CEREGE action and IRD (Institut de Recherche pour le Développement). We acknowledge the support of a Université de Lorraine-CRPG PhD fellowship and a Université de Poitiers A.T.E.R. (Attaché Temporaire d’Enseignement et de Recherche) of S.L., the support of IODP France, and the support of the French Agence Nationale de la Recherche (ANR), under grant ANR-17-CE01-0018 (Himal Fan project). G.A., D.L.B. and K.K. are members of the ASTER team.

Author information




C.F.-L. and J.L. designed the study. S.J.P.L., G.A., D.L.B. and K.K. performed the measurements. J.L. and S.J.P.L. performed the computations. S.J.P.L., J.L. and C.F.-L. interpreted the results and wrote the manuscript.

Corresponding authors

Correspondence to Sebastien J. P. Lenard or Christian France-Lanord.

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The authors declare no competing interests.

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Peer review information Primary Handling Editor: James Super.

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Extended data

Extended Data Fig. 1 10Be uncorrected concentration results.

The theoretical radioactive correction curve from the average 10Be concentration of the Lower Meghna is indicated. Same symbols as Fig. 2, 1σ uncertainties. Source data

Extended Data Fig. 2 Effect of the variations of the geomagnetic dipole on the 10Be production rate.

a, 10Be production rate normalised to modern values as a function of time, for a basin of Himalayan hypsometry at a latitude of 28°N. Two dipole temporal databases are explored: (1) the continuous Muscheler-SINT sediment database81,82 and (2) the discrete PINT lava flow database83. A 100 kyr-long averaging sliding window is applied to the PINT record to buffer the data dispersion and fill the data voids. The resulting curve with the 1σ uncertainty envelope is presented. b, 10Be normalised production rate distribution for the two databases. Despite distinct periods (0–2 Ma vs 0–5 Ma) and resolution (0.5 kyr vs ~50 kyr), the distribution of both databases is similar for low frequency (period > 100 kyr) signal variations.

Extended Data Fig. 3 Estimate of fG based on the Sr concentration.

a, Calibration of the fG obtained using Sr concentration versus the fG obtained using Sr-Nd isotopic data, for the Bengal Fan and the Lower Meghna River samples having both measurements. Thanks to the distinct Sr concentrations of the Ganga and Brahmaputra sediment (b), this calibration makes it possible to derive a fraction fG for samples having a Sr concentration measurement without a Sr-Nd isotopic measurement. b, Sr concentration as a function of Al/Si, a proxy for granulometry53, for the Ganga, Brahmaputra and Lower Meghna bulk sediment (this study and ref. 85). The coarser fraction, that is the sandy bedload, of the Lower Meghna sediment overlaps with the composition of Brahmaputra sediment whereas the finer fraction, that is the suspended load, corresponds to a mixing of sediment between the Ganga and the Brahmaputra sediment.

Extended Data Fig. 4 Modern geochemical and granulometric budgets in the Ganga plain.

a, Geochemical budget: Fe/Si vs Al/Si distribution of sediment in the Ganga plain. The geochemical poles for the (1) plain outlet, the (2) range outlet and the (3) plain deposits are represented by colour-filled stars surrounded by border-coloured 1σ uncertainty envelopes. While the plain outlet was previously assessed from (1) data of the Ganga at Harding Bridge53, we estimated the other poles (Methods) with (2) data from the Narayani-Gandak at the Himalayan front76 and (3) data from the Gandak megafan72 and from a new Siwalik section77. For comparison, the shaded black stars and envelopes represent the previous approximations of ref. 53 for these poles. b, Granulometric budget: cumulative distribution of grain size (logarithmic scale) for the Ganga and Narayani measured at variable depth and discharge values. The granulometric fraction favoured for 10Be measurements in this study is 125–250 μm.

Extended Data Fig. 5 Impact of the variable contribution of Ganga and Brahmaputra sediment on 10Be paleoconcentrations.

The chart shows the distribution of 10Be paleoconcentrations of the Bengal Fan and the Lower Meghna River sand as a function of (1) the fraction fG of the Bengal Fan and Lower Meghna sand issued from the Ganga Basin (on the x-axis) and (2) the deposition age of sand (in colour, blue for the Lower Meghna sand, red to yellow for the Bengal Fan sand younger than 0.5 Ma and white to black for the older sand). Each sample is represented by a small dot of colour. For clarity, uncertainties are not presented but are visible in Fig. 2. The average for each interval defined in Fig. 2 is displayed by square dots with 1σ uncertainty bars. The modern Ganga (G) and Brahmaputra (B) poles are shown by pink stars30,31,33,35. The zone of potential values obtained by a mixing of modern Ganga and Brahmaputra sand is shown by the pink polygon. Despite some scattering at ca. 2–4 Ma, the values averaged over the intervals seem independent from the fraction of Ganga sand and appear stable.

Extended Data Fig. 6 Influence of the selected intervals on averaged results.

One might prefer dividing the period of study according to different averaging intervals than the ones we selected (Fig. 2). For instance, one could merge the 4.5–3.5 Ma interval with the 6.5–4.5 Ma interval. This new division does not alter the evolution of the mean 10Be paleoconcentration (a), the mean fG (b) and the mean paleoerosion rate (c), and associated conclusions.

Extended Data Fig. 7 Grain size influence on the 10Be concentration.

A 75–250 μm fraction was selected for the four samples with little coarse material > 125 μm. Despite a limited set of analyses in two different size fractions, 75–125 μm and 125–250 μm, the grain size does not have a major influence on 10Be concentration (variations by less than 20% on average). One sample (U1444A-7H) displays a larger value for the coarsest fraction and might be explained by a larger proportion of Brahmaputra coarse sediment in this fraction (modern 10Be concentrations of the Ganga and Brahmaputra sand in Fig. 2b). The overall agreement between the 75–250 μm and 125–250 μm fractions makes it possible to plot and discuss the data issued from these two granulometric fractions on the same graphs. Source data

Supplementary information

Supplementary Information

The Supplementary Information develops the interpretation of the Sr–Nd isotopic variations and of the Ganga fraction fG.

Source data

Source Data Fig. 1

Sample locations and references.

Source Data Fig. 2

10Be corrected concentrations, Sr–Nd isotopes, fG fractions and Himalayan erosion rates.

Source Data Extended Data Fig. 1

10Be uncorrected concentrations.

Source Data Extended Data Fig. 7

10Be concentrations by sand fractions.

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Lenard, S.J.P., Lavé, J., France-Lanord, C. et al. Steady erosion rates in the Himalayas through late Cenozoic climatic changes. Nat. Geosci. 13, 448–452 (2020).

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