the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Sep 2024
Spatiotemporal denudation rates of the Swabian Alb escarpment (Southwest Germany) dominated by base-level lowering and lithology
Abstract. Surface denudation rates, a composite of physical erosion and chemical weathering, are governed by the tectonic, lithologic, climatic, and biotic conditions of a landscape. Disentangling and quantifying these rates is challenging but important for understanding and predicting landscape evolution over space and time. In this study, we focus on a low-relief and mixed lithology mountain range (Swabian Alb escarpment, Southwest Germany), whose 200 to 400 m high escarpment front and foreland drain into the Neckar River to the north and whose plateau drains into the Danube River to the southeast. These two drainage systems are subjected to similar uplift rates and climate/biota but incorporate different lithologies and have different base-levels and topography. We calculate decadal-scale chemical weathering and physical erosion rates based on 30 locations with suspended and dissolved river load measurements and compare them to published longer-term rates to evaluate how these differences influence landscape evolution.
Chemical weathering rates (based on the dissolved river load and corrected for anthropogenic input) range from 0.009 to 0.082 mm/yr, while physical erosion rates (calculated from suspended river load and discharge) range from 0.001 to 0.072 mm/yr. The catchment-wide denudation rates range from 0.005 to 0.137 mm/yr, resulting in chemical depletion fractions between 0.48 and almost 0.99. These high values indicate that chemical weathering is generally the dominant erosion process in this cool to temperate, humid mountain range dominated by chemical sedimentary rocks. Both physical erosion and chemical weathering rates are higher in tributaries draining towards the North/Neckar River than in rivers draining towards the Southeast/Danube River, resulting in southeast escarpment retreat rates of 1.2 to 9.3 mm/yr.
Results indicate that the evolution of the Swabian Alb and its escarpment is dominated by base-level lowering and lithology. Decadal-scale denudation rates based on river load may provide insights into the evolution of the escarpment over million-year timescales. The chemical depletion fractions CDFs of the Swabian Alb are compared to other study areas in different tectonic, lithologic, and climatic settings with CDFs ranging from 0.1 to 1.0. We interpret the high CDF values of >0.5 in the Swabian Alb to result from high chemical weathering rates of the recently exposed lithologies, continuously brought to the surface as a product of late-Cenozoic base-level lowering and consequent south to southeast-directed escarpment retreat across southern Germany. Differences in chemical weathering and physical erosion rates across the escarpment divide may arise from either the contrast in topographic relief, or exposure of bedrock units that are more susceptible to chemical weathering and physical erosion.
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RC1: 'Comment on egusphere-2024-2729', Richard Ott, 14 Oct 2024
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Schaller et al. present decadal rates of physical erosion and chemical weathering for the Swabian Alb and its foreland. The partitioning of denudation into weathering and erosion is calculated analogous to the chemical depletion fraction, and all data are interpreted in the context of climatic, topographic, biologic, and geologic variables. Their findings reveal generally higher and more variable erosion and weathering rates in the Neckar tributaries compared to the Danube, despite notable scatter in the data. The persistence of this general trend is linked to the higher baselevel of the Danube tributaries. The topic of the study is well suited for ESurf. Particularly, the partitioning of denudation in erosion and weathering is of interest—a subject area where more data from carbonate landscapes are essential to better examine the factors that control this ratio. However, anthropogenic influences, which are currently not considered, may significantly affect decadal-scale erosion rates and potentially influence weathering processes. Additionally, a more detailed description of the methods is necessary for clarity and reproducibility.
Human influence: Currently, the study does not take into account human influences on the decadal erosion and weathering rates. The correlations between erosion/weathering and topographic/climatic/geologic variables are weak and a possible explanation would be that the rates are modified by human activity.
Parts of the study area are highly industrialized and virtually all of the catchments host significant amounts of agriculture. Moreover, all rivers are heavily modified, channelized, contain hydropower plants of various sizes, canals for mills and factories, flood retention channels, etc. All of these anthropogenic factors should have an effect on erosion and sediment connectivity. For instance, it has been shown that suspended sediment rates in agricultural catchments in Europe can be 40 times higher compared to natural conditions, but this effect is highly scale-dependent due to sediment connectivity (Vanmaercke et al. 2011, 2015). The moderately-sized catchments studied here should be susceptible to these effects.
Moreover, sediment connectivity and erosion likely change through time due to changes in land use and river engineering. The study cites very long averaging windows for the data of several decades. It has been shown that river sediment yields are decreasing over the past decades in the Northern Hemisphere, and in Germany in particular (Dethier, Renshaw, and Magilligan 2022; Hoffmann et al. 2023). The problem is that the reasons for this decrease are not entirely clear. Since most dams were built earlier, it might rather be related to changes in agricultural practices and/or urban development decreasing hillslope-channel coupling. However, the unknown driver behind these changes make it challenging to select appropriate predictor variables for simple correlations as used here.
All this to say, the human influence on the physical erosion rates needs to be assessed. I encourage the authors to investigate whether variables that capture human activity, such as the human footprint index, % agriculture per catchment, the connectivity status index of rivers (e.g., Grill et al. 2019), etc. better explain the distribution of physical and total erosion rates.
Similarly, chemical weathering may also be affected by human activity. Soil CO2 is the main source of acid for the dissolution of limestone, and is modulated by vegetation, such that land use differences between catchments may matter in terms of weathering. The land use effects on carbonate weathering have been shown on a global scale (Zeng, Liu, and Kaufmann 2019).
The use of CDF: The chemical depletion fraction has been based on the ratio of element concentrations (mainly [Zr]) in the bedrock and regolith and assuming steady-state soil formation and denudation (Riebe, Kirchner, and Finkel 2003). As such, a CDF represents the long-term contribution of weathering to denudation reflected in the bedrock-regolith composition difference. However, the authors present contemporary rates of erosion and weathering from river sediment and water chemistry. Therefore, I find the use of CDF a bit misleading because the data do not reflect the time-scale of standard CDF measurements. I suggest referring to denudation partitioning, percentage weathering, or similar.
Just a suggestion, but since the denudation/erosion/weathering rates are low, mm/ka might be the better to unit to report rates and avoid all the zeros.
The use of Ksn: The interpretation of Ksn is a bit tricky for this study area, when comparing mostly non-karst (Neckar) to karst-side (Danube) catchments. The relationship between drainage area and discharge is non-trivial in karst landscapes. Therefore, a comparison in Ksn can be difficult or even misleading. One could either use the discharge stations to check for drainage area-discharge scaling differences, or at least add a short statement outlining the problems of standard Ksn in karst.
More information on the chemical weathering calculation are required. Currently, it is not mentioned how the authors go from ion concentration to a weathering rate.
- What discharge data are being used?
- What kind of mineral dissolution is assumed? Probably best to show the equations used for the calculation.
- How are uncertainties propagated? Fig. 3 shows asymmetric error bars, and almost all data overlap within error. How where these errors computed?
Significantly more information are required on the calculation of decadal erosion rates. There are a lot of choices to be made to go from a sediment rating curve to a sediment yield estimate:
- The authors should report the equation fitted and the a and b values (assuming Qs = a * Qw^b) as these also hold additional information about sediment transport.
- If the authors fit the rating curve in log-space, what log-transformation bias correction was applied?
- What was the average number of measurements per rating curve? And what r² values did you get?
- Were quality controls applied, such as minimum amount of data points, minimum r² value?
- Did the authors check for hysteresis in the Qw-Qs data? Frequently, many measurements are taking around flood events, which can bias rating curves due to hysteresis.
- The authors cite long time spans for the station records. However, rating curves change over time. Are the entire time periods used for fitting the rating curve? And do rating curves for different river represent different time intervals? Usually rating curves change through time because of human-induced effects on sediment connectivity (Dethier et al. 2022; Warrick 2015) and need to be re-fitted based on a window of interest. For instance, in Germany suspended sediment loads have been decreasing over the past decades (Hoffmann et al. 2023). Therefore, one cannot directly compare erosion rates from rivers with rating curves based on different time intervals or average long-term suspended sediment load. One could decide on a specific decade for analysis or show that temporal trends are negligible.
- Most of these questions are also relevant to the other erosion calculation methods, such as the one with average values.
Working my way through the results, I suggest that the authors use more informative names for their rate estimates instead of numbering them. I found it almost impossible to remember what CWR 1,2,3 , PER 1,2,3, TDR 1,2,3, and CDF1,2,3 mean. Can this be simplified to min, max, best guess? Or PERbed, PERTDS etc.
I find CWR3 a bit distractive in the manuscript. I think it’s good that the authors acknowledge the fact that secondary calcite precipitation is common in the Swabian Alb and that may lead to an underestimation of weathering if only looking at river chemistry. However, the rates are unreasonably high and the plots with CWR3 and CDF3 could be moved to the supplement. Many studies have calculated chemical weathering rates based on spring water chemistry, such as Hoenle 1991. These data should not be biased by secondary calcite precipitation and the average for the Swabian Alb was 52 mm/ka. Therefore, my recommendation would be to give these maximum estimates less exposure in the manuscript making the paper easier to follow. Also, the authors could compare their rates to the ones previously calculated from spring water chemistry to estimate the amount of secondary calcite precipitation.
Line comments:
L10: If we talk about contemporary rates, anthropogenic influences need to be considered.
L52: No need for granitoid lithologies to measure 10Be. Please, replace with quartz-bearing lithologies or similar.
L57-59: I don’t follow. A CDF is based on the ratio of two concentrations (bedrock vs saprolith, saprolith vs soil). No need for corrections. Are the authors referring to the need to correct cosmogenic nuclide-derived denudation rates with CDF measurements for weathering below the production zone? Please, clarify or correct this statement.
L 69-70: Please, make the time-scales more general. River dissolved loads can integrate over hours; cosmogenic nuclide rates can integrate over hundreds of years depending on the rate. Maybe use powers of ten. For instance, 103 to 104 for cosmogenic nuclides.
Fig 1. Make sure it is clear that the right-hand side is only that complicated in the case of weathering. In an arid environment, cosmogenic nuclide measurements would be tracking denudation.
L96: Please, add references.
L102: Please, add references.
L106: It’s not just a regional drainage divide. It’s part of the continental drainage divide.
L 119-124: Can you please add the methods used for estimating these rates?
L121-124: Studies that are missing are for instance the overview work of Hönle 1991 that constrains the average chemical weathering rate of the Swabian Alb to 52 mm/ka, and works from University of Tübingen (!) such as Poppe (1993) and Bauer (1993). Probably, there’s more buried in the German literature.
L 160: Any justification for 0.45? Many studies use 0.45. However, since the authors are using TopoToolbox, one could use the ‘mnoptim’ function to check what works best for steady-state channel sections in the area. Though, I understand that heterogeneous lithology might create difficulties here. Nevertheless, please justify the choice of mn.
L165-172: Would be good to state how the NDVI time window compares to the measurement time window of erosion and weathering rates.
L173-179: Can you explain on what parameter the geologic binning is based on? Is this based on assumed weatherability, erodibility, or something else? I am confused as to why the basement rocks in the Black Forest end up in the same category as the Keuper evaporites, and Jurassic marls.
Table 3: I assume that the categorical variables for geology are converted to % of catchment area? Can you please clarify this in the table or caption, otherwise it is hard to follow what a correlation coefficient of -0.4 between CWR and Lower Triassic is supposed to reflect.
Also Table 3: It just says CWR/PER/TDR. Can you please add the number qualifiers to the column headings? I had to search in the text, which numbers are being displayed.
Discussion 5.1.3. Why are these rates only put into global context, and not with regional studies? And what would these rates mean for long-term landscape evolution of the Swabian Alb foreland How do they compare with previous estimates?
Figure 6: I think this figure would be easier to read if the horizontal bars are removed. The information could be displayed or categorized differently. For some categories different colors refer to geographic location (Danube vs Neckar) for other symbols the color refer to the references. I recommend to revise the layout of this summary figure to make it easier for the readers to follow.
Feel free to contact me in case there are any questions about this review.
Richard Ott.
References
Bauer, Michael. 1993. “Wasserhaushalt Und Losungsaustrag Im Wutachgebiet.” Pp. 189–202 in Eintiefungsgeschichte und Stoffaustrag im Wutachgebiet (SW-Deutschland), edited by G. Einsele and W. Ricken. Tübingen: Tübinger Geowiss. Arbeiten (TGA).
Dethier, Evan N., Carl E. Renshaw, and Francis J. Magilligan. 2022. “Rapid Changes to Global River Suspended Sediment Flux by Humans.” Science (New York, N.Y.) 376(6600):1447–52. doi: 10.1126/SCIENCE.ABN7980/SUPPL_FILE/SCIENCE.ABN7980_SM.PDF.
Grill, G., B. Lehner, M. Thieme, B. Geenen, D. Tickner, F. Antonelli, S. Babu, P. Borrelli, L. Cheng, H. Crochetiere, H. Ehalt Macedo, R. Filgueiras, M. Goichot, J. Higgins, Z. Hogan, B. Lip, M. E. McClain, J. Meng, M. Mulligan, C. Nilsson, J. D. Olden, J. J. Opperman, P. Petry, C. Reidy Liermann, L. Sáenz, S. Salinas-Rodríguez, P. Schelle, R. J. P. Schmitt, J. Snider, F. Tan, K. Tockner, P. H. Valdujo, A. van Soesbergen, and C. Zarfl. 2019. “Mapping the World’s Free-Flowing Rivers.” Nature 569(7755):215–21. doi: 10.1038/s41586-019-1111-9.
Hoffmann, Thomas O., Yannik Baulig, Stefan Vollmer, Jan H. Blöthe, Karl Auerswald, and Peter Fiener. 2023. “Pristine Levels of Suspended Sediment in Large German River Channels during the Anthropocene?” Earth Surface Dynamics 11(2):287–303. doi: 10.5194/esurf-11-287-2023.
Poppe, R. 1993. “Karstsystem Und Lösungsaustrag Im Oberen Jura Des Aitrachtals.” Pp. 181–88 in Eintiefungsgeschichte und Stoffaustrag im Wutachgebiet (SW-Deutschland), edited by G. Einsele and W. Ricken. Tübingen: Tübinger Geowiss. Arbeiten (TGA).
Riebe, Clifford S., James W. Kirchner, and Robert C. Finkel. 2003. “Long-Term Rates of Chemical Weathering and Physical Erosion from Cosmogenic Nuclides and Geochemical Mass Balance.” Geochimica et Cosmochimica Acta 67(22):4411–27. doi: 10.1016/S0016-7037(03)00382-X.
Vanmaercke, Matthias, Jean Poesen, Gerard Govers, and Gert Verstraeten. 2015. “Quantifying Human Impacts on Catchment Sediment Yield: A Continental Approach.” Global and Planetary Change 130:22–36. doi: 10.1016/j.gloplacha.2015.04.001.
Vanmaercke, Matthias, Jean Poesen, Gert Verstraeten, Joris de Vente, and Faruk Ocakoglu. 2011. “Sediment Yield in Europe: Spatial Patterns and Scale Dependency.” Geomorphology 130(3–4):142–61. doi: 10.1016/j.geomorph.2011.03.010.
Warrick, Jonathan A. 2015. “Trend Analyses with River Sediment Rating Curves.” Hydrological Processes 29(6):936–49. doi: 10.1002/HYP.10198.
Zeng, Sibo, Zaihua Liu, and Georg Kaufmann. 2019. “Sensitivity of the Global Carbonate Weathering Carbon-Sink Flux to Climate and Land-Use Changes.” Nature Communications 10(1):1–10. doi: 10.1038/s41467-019-13772-4.
Citation: https://doi.org/10.5194/egusphere-2024-2729-RC1
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