The southern highlands of Mars are dissected by hundreds of valley networks, which are evidence that water once sculpted the surface. Characterizing the mechanisms of valley incision may constrain early Mars climate and the search for ancient life. Previous interpretations of the geological record require precipitation and surface water runoff to form the valley networks, in contradiction with climate simulations that predict a cold, icy ancient Mars. Here we present a global comparative study of valley network morphometry, using a principal-component-based analysis with physical models of fluvial, groundwater sapping and glacial and subglacial erosion. We found that valley formation involved all these processes, but that subglacial and fluvial erosion are the predominant mechanisms. This is supported by predictions from models of steady-state erosion and geomorphological comparisons to terrestrial analogues. The inference of subglacial channels among the valley networks supports the presence of ice sheets that covered the southern highlands during the time of valley network emplacement.
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Data analysis codes include the PCA (available as the MATLAB built-in function pca) as well as custom codes specifically generated for data and error extraction, error propagation, confidence analysis and modelling of the synthetic fluvial, glacial, sapping and subglacial valley networks. The authors will provide the custom codes in a MATLAB live script format (.mlx) upon request.
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A.G.G., A.M.J. and G.R.O. were supported through the NSERC Discovery grant program. A.G.G. also received support through an NSERC CREATE-funded fellowship and through an Exploration Fellowship from the School of Earth and Space Exploration, ASU. Arctic fieldwork was supported through PCSP and NSERC Northern Research Supplement Grants to G.R.O. Our appreciation goes to C. Schoof, R. Phillips, K. Whipple and P. Christensen for their insightful comments, and to the MJ-CJ research group for continued support.
The authors declare no competing interests.
Peer review information Primary handling editor: Stefan Lachowycz.
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Examples of the four groups of valley networks as derived from the PCA classification: Warrego valles, fluvial (a), unnamed valley (M68), glacial (b), Abus vallis, sapping (c), and Pallacopas valles, subglacial (d). Images show colorized elevation (MOLA, Goddard Space Flight Center) overlying a THEMIS (ASU/NASA) mosaic.
Supplementary methods including Figs. 1–13 and Table 1.
Main dataset. The table is structured so that each row is a valley network and columns include the ID number, valley name (if applicable), latitude/longitude, and the six metrics and their respective error.
This table includes two sheets. The first is the table of parameters, where each row is a parameter, and columns are the parameter symbol, definition, units, values (lower, average, and upper bounds), and references. The second sheet contains the metric predictions (upper, average, and lower values).
PCA classification and confidence results of the study. Rows correspond to valley networks, whereas columns give their ID, name, latitude/longitude, the distances to each of the synthetic valley network erosional groups, the relative distances, distances minus statistical threshold, and the final classification result (1 is fluvial, 2 is glacial, 3 is sapping, 4 is subglacial, 5 is undifferentiated). The last column, confidence, goes from highest (1) to lowest (4).
Longitudinal profile observations and undulation interpretations. Rows correspond to valley networks, columns are valley network ID, name, and a description of the longitudinal profile undulations and interpretations.
Sensitivity analysis for the principal component results. The first sheet contains the sensitivity analysis summary, columns are the sample size and the five metrics. The second sheet contains a total of 35 individual analysis for different sample sizes, as indicated.
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Grau Galofre, A., Jellinek, A.M. & Osinski, G.R. Valley formation on early Mars by subglacial and fluvial erosion. Nat. Geosci. 13, 663–668 (2020). https://doi.org/10.1038/s41561-020-0618-x
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