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Abstract Steep landscapes evolve largely by debris flows, in addition to fluvial and hillslope processes. Abundant field observations document that debris flows incise valley bottoms and transport substantial sediment volumes, yet their contributions to steepland morphology remain uncertain. This has, in turn, limited the development of debris‐flow incision rate formulations that produce morphology consistent with natural landscapes. In many landscapes, including the San Gabriel Mountains (SGM), California, steady‐state fluvial channel longitudinal profiles are concave‐up and exhibit a power‐law relationship between channel slope and drainage area. At low drainage areas, however, valley slopes become nearly constant. These topographic forms result in a characteristically curved slope‐area signature in log‐log space. Here, we use a one‐dimensional landform evolution model that incorporates debris‐flow erosion to reproduce the relationship between this curved slope‐area signature and erosion rate in the SGM. Topographic analysis indicates that the drainage area at which steepland valleys transition to fluvial channels correlates with measured erosion rates in the SGM, and our model results reproduce these relationships. Further, the model only produces realistic valley profiles when parameters that dictate the relationship between debris‐flow erosion, valley‐bottom slope, and debris‐flow depth are within a narrow range. This result helps place constraints on the mathematical form of a debris‐flow incision law. Finally, modeled fluvial incision outpaces debris‐flow erosion at drainage areas less than those at which valleys morphologically transition from near‐invariant slopes to concave profiles. This result emphasizes the critical role of debris‐flow incision for setting steepland form, even as fluvial incision becomes the dominant incisional process. 

Predicting where runoff‐generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass‐movement processes in unburned areas indicate that event locations are well‐predicted by rainfall anomaly,R*, in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short‐durationR*metric predicts debris‐flow occurrence more effectively than absolute peak intensity or longer‐duration rainfall metrics, and show that incorporating anR*criterion into an existing debris‐flow likelihood model can reduce false positive predictions and improve accuracy. We testR* at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris‐flow locations in different climates. We also consider howR*can benefit postfire debris‐flow prediction given recent increases in climatological variability within individual burn perimeters. 

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris‐flow initiation are commonly expressed as rainfall intensity‐duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass‐movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff‐generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris‐flow initiation thresholds vary systematically with short‐duration rainfall‐intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much‐needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field‐based hazard assessment. Furthermore, if the observed variation in thresholds reflects long‐term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris‐flow likelihood. 

Abstract. Debris flows regularly traverse bedrock channels that dissect steep landscapes, but our understanding of bedrock erosion by debris flows and their impact on steepland morphology is still rudimentary. Quantitative models of steep bedrock channel networks are based on geomorphic transport laws designed to represent erosion by water-dominated flows. To quantify the impact of debris flow erosion on steep channel network form, it is first necessary to develop methods to estimate spatial variations in bulk debris flow properties (e.g., flow depth, velocity) throughout the channel network that can be integrated into landscape evolution models. Here, we propose and evaluate two methods to estimate spatial variations in bulk debris flow properties along the length of a channel profile. We incorporate both methods into a model designed to simulate the evolution of longitudinal channel profiles that evolve in response to debris flow and fluvial processes. To explore this model framework, we propose a general family of debris flow erosion laws where erosion rate is a function of debris flow depth and channel slope. Model results indicate that erosion by debris flows can explain the occurrence of a scaling break in the slope–area curve at low-drainage areas and that upper-network channel morphology may be useful for inferring catchment-averaged erosion rates in quasi-steady landscapes. Validating specific forms of a debris flow incision law, however, would require more detailed model–data comparisons in specific landscapes where input parameters and channel morphometry can be better constrained. Results improve our ability to interpret topographic signals within steep channel networks and identify observational targets critical for constraining a debris flow incision law.