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Abstract Rock glaciers dominate the cryosphere in mid‐latitude alpine settings, yet their activity and their histories remain challenging to constrain. We focus on the Thomas Lake rock glacier on Mt. Sopris in Colorado, USA. We measure surface velocities by feature tracking of image pairs and document Holocene¹⁰Be exposure ages on surface debris. The surface speeds average 0.8 m/yr and peak at 2 m/yr in a steep reach. Exposure ages range from 1.4 to 13.2 kyr and monotonically increase down‐glaciers. Ages exceeding 6 kyr occur in the bottom quarter of the landform, coinciding with sporadic tree cover. These constraints constrain a numerical model of Holocene rock glacier activity. In our model, surface velocity is entirely explained by the deformation of the ice‐rich core with the extra load of the rocky carapace. Surface mass balance is simplified to an accumulation area of ice and debris equivalent to the avalanche cone, and very low, uniform ablation in the remaining rock glacier where rock cover minimizes melt. Climate drives the activity through a history of ice accumulation in the avalanche cone. Matching the observed age and speed structure requires: (a) Early Holocene growth of the rock glacier, (b) low accumulation during the middle Holocene warm period (Hypsithermal), and (c) two Neoglacial accumulation pulses, the most recent being the Little Ice Age. Pulses travel down the valley as kinematic waves, re‐activating the landform. The headwall retreat rate of 4 mm/yr, inferred from rocky layer thickness and surface speed, far outpaces bedrock down wearing rates. 

Effects of a changing climate on agricultural system productivity are poorly understood, and likely to be met with as yet undefined agricultural adaptations by farmers and associated business and governmental entities. The continued vitality of agricultural systems depends on economic conditions that support farmers’ livelihoods. Exploring the long-term effects of adaptations requires modeling agricultural and economic conditions to engage stakeholders upon whom the burden of any adaptation will rest. Here, we use a new freeware model FEWCalc (Food-Energy-Water Calculator) to project farm incomes based on climate, crop selection, irrigation practices, water availability, and economic adaptation of adding renewable energy production. Thus, FEWCalc addresses United Nations Global Sustainability Goals No Hunger and Affordable and Clean Energy. Here, future climate scenario impacts on crop production and farm incomes are simulated when current agricultural practices continue so that no agricultural adaptations are enabled. The model Decision Support System for Agrotechnology Transfer (DSSAT) with added arid-region dynamics is used to simulate agricultural dynamics. Demonstrations at a site in the midwest USA with 2008–2017 historical data and two 2018–2098 RCP climate scenarios provide an initial quantification of increased agricultural challenges under climate change, such as reduced crop yields and increased financial losses. Results show how this finding is largely driven by increasing temperatures and changed distribution of precipitation throughout the year. Without effective technological advances and operational and policy changes, the simulations show how rural areas could increasingly depend economically on local renewable energy, while agricultural production from arid regions declines by 50% or more. 

Abstract Hillslope topographic change in response to climate and climate change is a key aspect of landscape evolution. The impact of short‐duration rainstorms on hillslope evolution in arid regions is persistently questioned but often not directly examined in landscape evolution studies, which are commonly based on mean climate proxies. This study focuses on hillslope surface processes responding to rainstorms in the driest regions of Earth. We present a numerical model for arid, rocky hillslopes with lithology of a softer rock layer capped by a cliff‐forming resistant layer. By representing the combined action of bedrock and clast weathering, cliff‐debris ravel, and runoff‐driven erosion, the model can reproduce commonly observed cliff‐profile morphology. Numerical experiments with a fixed base level were used to test hillslope response to cliff‐debris grain size, rainstorm intensities, and alternation between rainstorm patterns. The persistence of vertical cliffs and the pattern of sediment sorting depend on rainstorm intensities and the size of cliff debris. Numerical experiments confirm that these two variables could have driven the landscape in the Negev Desert (Israel) toward an observed spatial contrast in topographic form over the past 10⁵–10⁶ years. For a given total storm rain depth, short‐duration higher‐intensity rainstorms are more erosive, resulting in greater cliff retreat distances relative to longer, low‐intensity storms. Temporal alternation between rainstorm regimes produces hillslope profiles similar to those previously attributed to Quaternary oscillations in the mean climate. We suggest that arid hillslopes may undergo considerable geomorphic transitions solely by alternating intra‐storm patterns regardless of rainfall amounts. 

Abstract The impact of climate on topography, which is a theme in landscape evolution studies, has been demonstrated, mostly, at mountain range scales and across climate zones. However, in drylands, spatiotemporal discontinuities of rainfall and the crucial role of extreme rainstorms raise questions and challenges in identifying climate properties that govern surface processes. Here, we combine methods to examine hyperarid escarpment sensitivity to storm‐scale forcing. Using a high‐resolution DEM and field measurements, we analyzed the topography of a 40‐km‐long escarpment in the Negev desert (Israel). We also used rainfall intensity data from a convection‐permitting numerical weather model for storm‐scale statistical analysis. We conducted hydrological simulations of synthetic rainstorms, revealing the frequency of sediment mobilization along the sub‐cliff slopes. Results show that cliff gradients along the hyperarid escarpment increase systematically from the wetter (90 mm yr⁻¹) southwestern to the drier (45 mm yr⁻¹) northeastern sides. Also, sub‐cliff slopes at the southwestern study site are longer and associated with milder gradients and coarser sediments. Storm‐scale statistical analysis reveals a trend of increasing extreme (>10 years return‐period) intensities toward the northeast site, opposite to the trend in mean annual rainfall. Hydrological simulations based on these statistics indicate a higher frequency of sediment mobilization in the northeast, which can explain the pronounced topographic differences between the sites. The variations in landscape and rainstorm properties across a relatively short distance highlight the sensitivity of arid landforms to extreme events. 

Abstract Generalizable relationships for how subdaily rainfall statistics imprint into runoff statistics are lacking. We use the Colorado Front Range, known for destructive rainfall‐triggered floods and landslides, to assess whether orographic patterns in runoff generation are a direct consequence of rainstorm climatology. Climatological analysis relies on a dense network of tipping‐bucket rain gauges and gridded precipitation frequency estimates from the National Oceanic and Atmospheric Administration to evaluate relationships among subdaily rainfall statistics, topography, and flood frequency throughout the South Platte River basin. We find that event‐scale rainfall statistics only weakly depend on elevation, suggesting that orographic gradients in runoff “extremes” are not simply a consequence of rainfall patterns. In contrast, bedrock exposure strongly varies with elevation in a way that plausibly explains enhanced runoff generation at lower elevations via reduced water storage capacity. These findings are suggestive of feedbacks between bedrock river evolution and hillslope hydrology not typically included in models of landscape evolution. 

Abstract Long‐term erosion can threaten infrastructure and buried waste, with consequences for management of natural systems. We develop erosion projections over 10 ky for a 5 km²watershed in New York, USA. Because there is no single landscape evolution model appropriate for the study site, we assess uncertainty in projections associated withmodel structureby considering a set of alternative models, each with a slightly different governing equation. In addition to model structure uncertainty, we consider the following uncertainty sources: selection of a final model set; each model's parameter values estimated through calibration; simulation boundary conditions such as the future incision of downstream rivers and future climate; and initial conditions (e.g., site topography which may undergo near‐term anthropogenic modification). We use an analysis‐of‐variance approach to assess and partition uncertainty in projected erosion into the variance attributable to each source. Our results suggest one sixth of the watershed will experience erosion exceeding 5 m in the next 10 ky. Uncertainty in projected erosion increases with time, and the projection uncertainty attributable to each source manifests in a distinct spatial pattern. Model structure uncertainty is relatively low, which reflects our ability to constrain parameter values and reduce the model set through calibration to the recent geologic past. Beyond site‐specific findings, our work demonstrates what information prediction‐under‐uncertainty studies can provide about geomorphic systems. Our results represent the first application of a comprehensive multi‐model uncertainty analysis for long‐term erosion forecasting. 

We review select mature geomorphic transport laws for use in temperate ridge and valley landscapes and compile parameter estimates for use in applications. This work is motivated by a case study of sensitivity analysis, calibration, validation, multimodel comparison, and prediction under uncertainty, which required bounding values for parameter ranges. Considered geomorphic transport formulae span hillslope sediment transport, soil production, and erosion by surface water. We compile or derive estimates for the parameters in these transport formulae. Additionally, we address a common challenge—connecting changes in precipitation distribution to changes in effective erodibility—by using a simple hydrologic model and a method to estimate precipitation distribution parameters using commonly available data. While some parameters are reasonably well constrained, others span orders of magnitude. Some, such as soil infiltration capacity, have a direct physical meaning but are challenging to measure on geologically relevant timescales. Through the process of compiling these ranges we identify common challenges in parameter determination. The issue of comparable units derives from considering an exponent as an empirically inferred coefficient rather than as an expression of a fundamental relationship. The issue of appropriate timescales derives from the mismatch between human measurement and geologic timescales. This contribution thus serves both as a practical compilation for applications and as a synthesis of outstanding challenges in parameter selection for geomorphic transport laws.