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Abstract. TopoToolbox is a MATLAB program for the analysis of digital elevation models (DEMs). With the release of version 2, the software adopts an object-oriented programming (OOP) approach to work with gridded DEMs and derived data such as flow directions and stream networks. The introduction of a novel technique to store flow directions as topologically ordered vectors of indices enables calculation of flow-related attributes such as flow accumulation ∼20 times faster than conventional algorithms while at the same time reducing memory overhead to 33% of that required by the previous version. Graphical user interfaces (GUIs) enable visual exploration and interaction with DEMs and derivatives and provide access to tools targeted at fluvial and tectonic geomorphologists. With its new release, TopoToolbox has become a more memory-efficient and faster tool for basic and advanced digital terrain analysis that can be used as a framework for building hydrological and geomorphological models in MATLAB.

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[1] Erosion in the Himalaya is responsible for one of the greatest mass redistributions on Earth and has fueled models of feedback loops between climate and tectonics. Although the general trends of erosion across the Himalaya are reasonably well known, the relative importance of factors controlling erosion is less well constrained. Here we present 25 10 Be-derived catchment-averaged erosion rates from the Yamuna catchment in the Garhwal Himalaya, northern India. Tributary erosion rates range between~0.1 and 0.5 mm yr À1 in the Lesser Himalaya and~1 and 2 mm yr À1 in the High Himalaya, despite uniform hillslope angles. The erosion-rate data correlate with catchment-averaged values of 5 km radius relief, channel steepness indices, and specific stream power but to varying degrees of nonlinearity. Similar nonlinear relationships and coefficients of determination suggest that topographic steepness is the major control on the spatial variability of erosion and that twofold to threefold differences in annual runoff are of minor importance in this area. Instead, the spatial distribution of erosion in the study area is consistent with a tectonic model in which the rock uplift pattern is largely controlled by the shortening rate and the geometry of the Main Himalayan Thrust fault (MHT). Our data support a shallow dip of the MHT underneath the Lesser Himalaya, followed by a midcrustal ramp underneath the High Himalaya, as indicated by geophysical data. Finally, analysis of sample results from larger main stem rivers indicates significant variability of 10 Be-derived erosion rates, possibly related to nonproportional sediment supply from different tributaries and incomplete mixing in main stem channels.

Rocky debris on glacier surfaces influences ice melt rates and the response of glaciers to climate change. However, scarce data on the extent and evolution of supraglacial debris cover have so far limited its inclusion in regional to global glacier models. Here we present global data sets of supraglacial debris‐cover extents, based on Landsat 8 and Sentinel‐2 optical satellite imagery. We find that about 4.4% (~26,000 km2) of all glacier areas (excluding the Greenland ice sheet and Antarctica) are covered with debris, but that the distribution is heterogeneous. The largest debris‐covered areas are located in high‐mountain ranges, away from the poles. At a global scale, we find a negative scaling relationship between glacier size and percentage of debris. Therefore, the influence of debris cover on glacier mass balances is expected to increase in the future, as glaciers continue to shrink.

[1] As rivers transport water and sediment across Earth's surface, they radiate elastic and acoustic waves. We use seismic and infrasound observations during a controlled flood experiment (CFE) in the Grand Canyon to show that three types of fluvial processes can be monitored from outside the channel. First, bed-load transport under conditions of evolving bed mobility is identified as the dominant seismic source between 15 and 45 Hz. Two lower-frequency seismic bands also excited by the CFE exhibited greater power increases and are consistent with source processes related to fluid rather than sediment transport. The second fluvial seismic source is inferred to be fluid tractions on the rough riverbed, which drive the maximum seismic power increase at 0.73 Hz, but do not excite infrasound. Waves at the fluid-air interface are suggested as a third source, which generates a common 6-7 Hz peak in seismic and infrasound responses to the CFE.

[1] High Asian glacial landscapes have large variations in topographic relief and the size and steepness of snow accumulation areas. Associated differences in glacial cover and dynamics allow a first-order determination of the dominant processes shaping these landscapes. Here we provide a regional synthesis of the topography and flow characteristics of 287 glaciers across High Asia using digital elevation analysis and remotely sensed glacier surface velocities. Glaciers situated in low-relief areas on the Tibetan Plateau are mainly nourished by direct snowfall, have little or no debris cover, and have a relatively symmetrical distribution of velocities along their length. In contrast, avalanche-fed glaciers with steep accumulation areas, which occur at the deeply incised edges of the Tibetan Plateau, are heavily covered with supraglacial debris, and flow velocities are highest along short segments near their headwalls but greatly reduced along their debris-mantled lower parts. The downstream distribution of flow velocities suggests that the glacial erosion potential is progressively shifted upstream as accumulation areas get steeper and hillslope debris fluxes increase. Our data suggest that the coupling of hillslopes and glacial dynamics increases with topographic steepness and debris cover. The melt-lowering effect of thick debris cover allows the existence of glaciers even when they are located entirely below the snow line. However, slow velocities limit the erosion potential of such glaciers, and their main landscape-shaping contribution may simply be the evacuation of debris from the base of glacial headwalls, which inhibits the formation of scree slopes and thereby allows ongoing headwall retreat by periglacial hillslope processes. We propose a conceptual model in which glacially influenced plateau margins evolve from low-relief to high-relief landscapes with distinctive contributions of hillslope processes and glaciers to relief production and decay.

10Be‐derived catchment average erosion rates from the Himalaya and Eastern Tibet show different relationships with normalized channel steepness index (ksn), suggesting differences in erosional efficiency of bedrock river incision. We used a threshold stream power model (SPM) combined with a stochastic distribution of discharges to explore the extent to which this observation can be explained by differences in the mean and variability of discharge between the two regions. Based on the analysis of 199 daily discharge records (record lengths 3–45 years; average 18.5 years), we parameterized monsoonal discharge with a weighted sum of two inverse gamma distributions. During both high‐ and low‐flow conditions, annual and interannual discharge variabilities are similarly low in each region. Channel widths for 36 rivers indicate, on average, 25% wider streams in Eastern Tibet than in the Himalaya. Because most catchments with 10Be data are not gauged, we constrained mean annual discharge in these catchments using gridded precipitation data sets that we calibrated to the available discharge records. Comparing 10Be‐derived with modeled erosion rates, the stochastic‐threshold SPM explains regional differences better than a simple SPM based on drainage area or mean annual runoff. Systematic differences at small ksn values can be reconciled with ksn‐dependent erosion thresholds, whereas substantial scatter for high ksn values persists, likely due to methodological limitations. Sensitivity analysis of the stochastic‐threshold SPM calibrated to the Himalaya indicates that changes in the duration or strength of summer monsoon precipitation have the largest effect on erosional efficiency, while changes in monsoonal discharge variability have almost no effect. The modeling approach presented in this study can in principle be used to assess the impact of precipitation changes on erosion.