Satellite image data and stereo-derived topography data

Morphological mapping of the martian landslide object of this study (Coprates Chasma, 67.75W-11.80S) was conducted using Mars Reconnaissance Orbiter imagery (CTX22 and HiRISE23 cameras) provided by the NASA Planetary Data System. This study has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS)34 package to pre-process CTX stereo-pair images (Supplementary Table 3). The processed CTX images were imported in SOCET SET commercial suite from BAE Systems to obtain digital elevation models and ortho-rectified images using well-validated previous methods34. These image products were post-processed with ISIS to create final images that could be used in ArcGIS.

Morphological characterisation methods

In ArcGIS, longitudinal ridges are traced in correspondence of the crest. Two sets of transversal topographic profiles were traced (Fig. 1c, d) so that the most external ridges (at the left and right end) were always the same ones in every profile. Distances between ridges were measured manually with the ruler tool. The number of ridges and their density along each profile were obtained using a custom Python script (see the Code availability section). In order to assess the average thickness of the landslide deposit in the correspondence of every profile, we built the topography of the valley floor underneath the deposit by interpolating topographic contours of Valles Marineris floor around the landslide (Supplementary Figs. 1 and 2). Because the CTX-derived DEM and the newly built DEM representing the valley floor have different resolution, the number of elevation points available is different, therefore preventing a direct correlation and thickness assessment point by point. We overcame this aspect by taking elevation points of the valley floor and the correspondent closest elevation points (one before and one after) of the landslide deposit. We then averaged the elevation between these two points and calculated the thickness. The thickness values obtained per each point of the valley floor were finally averaged. We automated these steps by means of a custom Python script (see the Code availability section).

Landslide deposit thickness error estimation

We traced profiles transversal and longitudinal to the valley floor, adjacent to the central and east areas of the study (Supplementary Fig. 3). This set of transects (yellow lines), in the specific their linear fits (burgundy lines), is compared with a mirror set of transects traced in the correspondence of the landslide deposit (blue lines) so to assess the plausibility of the overall elevations of our reconstructed bottom surface, and to provide an error estimation of the average thickness that we provide in the paper.

As the floor of Valles Marineris gently dips towards east (in the figure, from left to right), the higher elevations of the blue lines 1 and 2 are plausible. However, we are also expecting a random natural roughness of the valley floor at various scales so that also blue lines 3 and 4 appear plausible, as their maximum offset (blue line 3) is ~80 m, which is within a reasonable magnitude of topographic variation (as seen in profile 1, Supplementary Fig. 3).

We use these profiles to evaluate the errors on the deposit thickness, and we do so by accounting for the standard deviation of the elevation in the topographic profiles (Supplementary Table 4). To do so, we use the topographic profiles that we traced in the valley floor, adjacent to the central and east areas of study (yellow lines). As the topographic profiles that we traced for the morphometric analysis are parallel to neither transversal nor longitudinal direction, we determine the final error taking into account the propagation of error along these two axes (Eq. (1)), that is combining standard deviation for yellow lines 1 and 2 to obtain the error in the central area of study (c) and yellow lines 3 and 4 for the error in the east area of study (d), represented as error bars in Fig. 2b of the main text:

$${\mathrm{\sigma }}_k = \sqrt {\sigma _i^2 + \sigma _j^2}$$ (1)

Velocity estimation

The experimental work of Börzsönyi et al.19 identified a range of scaled downstream surface velocity.

The flow velocity u is scaled with \(\sqrt {g\ast d}\), where g is the gravitational acceleration and d is the grain size, providing the normalised downstream surface velocity \(\tilde u^S\):

$$\tilde u^S = \frac{{u^S}}{{\sqrt {g \ast d} }}$$ (2)

From the data in Fig. 3 of Börzsönyi et al.19, we consider \(\tilde u^S = 40\), as this is a value for which the longitudinal ridges develop. We use the gravitational acceleration for Mars, 3.71 m/s2, and the largest grain sizes recognisable on the surface deposit of the martian landslide, d = 1–20 m (Supplementary Fig. 4), using HiRISE images (resolution 25 cm/px). We infer that the velocity of the martian landslide could range between 77 m/s and 345 m/s. Note that our estimation of the grain size may be biased towards higher values by resolution limitation and by a possible grain size segregation effect that brings larger grains closer to the surface. As such, we are aware that the range provided may exaggerate the most effective grain size and, therefore, the inferred velocity may be overestimated.