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Post‐fire debris flows represent one of the most erosive consequences associated with increasing wildfire severity and investigations into their downstream impacts have been limited. Recent advances have linked existing hydrogeomorphic models to predict potential impacts of post‐fire erosion at watershed scales on downstream water resources. Here we address two key limitations in current models: (1) accurate predictions of post‐fire debris flow volumes in the absence of triggering storm rainfall intensities and (2) understanding controls on grain sizes produced by post‐fire debris flows. We compiled and analysed a novel dataset of depositional volumes and grain size distributions (GSDs) for 59 post‐fire debris flows across the Intermountain West (IMW) collected via fieldwork and from the literature. We first evaluated the utility of existing models for post‐fire debris flow volume prediction, which were largely developed for Southern California. We then constructed a new post‐fire debris flow volume prediction model for the IMW using a combination of Random Forest modelling and regression analysis. We found topography and burn severity to be important variables, and that the percentage of pre‐fire soil organic matter was an essential predictor variable. Our model was also capable of predicting debris flow volumes without data for the triggering storm, suggesting that rainfall may be more important as a presence/absence predictor, rather than a scaling variable. We also constructed the first models that predict the median, 16th percentile, and 84th percentile grain sizes, as well as boulder size, produced by post‐fire debris flows. These models demonstrate consistent landscape controls on debris flow GSDs that are related to land cover, physical and chemical weathering, and hillslope sediment transport processes. This work advances our ability to predict how post‐fire sediment pulses are transported through watersheds. Our models allow for improved pre‐ and post‐fire risk assessments across diverse ranges of watersheds in the IMW.

River meander migration plays a key role in the unsteady “conveyor belt” of sediment redistribution from source to sink areas. The ubiquity of river meandering is evident from remotely sensed imagery, which has allowed for long‐term, high‐resolution studies of river channel change and form‐process relationships. Empirical, experimental, and theoretical research approaches have described two distinct relationships between channel curvature and river channel migration rates. In this study, we employ a novel application of time‐series algorithms to calculate migration rates and channel curvature at sub‐meander bend length scales using 6 decades of aerial imagery spanning 205 km of the Minnesota River and Root River, Minnesota, USA. Results from the Minnesota River provide the first empirical evidence demonstrating how migration‐curvature relations break down for rivers with low sediment supply, which is supported by the Root River data set. This not only highlights the importance of sediment supply as a driver of river migration, but also supports a simple means to detect river reaches lacking sediment supply. Furthermore, results from both rivers demonstrate that sub‐meander bend measurement scales are most appropriate for studying channel migration rates and further indicate that a quasi‐linear relationship—rather than the more commonly inferred peaked relationship—exists between channel curvature and migration rates. The highest migration rates are associated with the highest measured channel curvatures in our data set, after accounting for a spatial lag ofchannel widths. These findings are consistent with flume experiments and empirical data across diverse geologic and climatic environments.

Mountain rivers often receive sediment in the form of episodic, discrete pulses from a variety of natural and anthropogenic processes. Once emplaced in the river, the movement of this sediment depends on flow, grain size distribution, and channel and network geometry. Here, we simulate downstream bed elevation changes that result from discrete inputs of sediment (∼10,000 m³), differing in volume and grain size distribution, under medium and high flow conditions. We specifically focus on comparing bed responses between mixed and uniform grain size sediment pulses. This work builds on a Lagrangian, bed‐material sediment transport model and applies it to a 27 km reach of the mainstem Nisqually River, Washington, USA. We compare observed bed elevation change and accumulation rates in a downstream lake to simulation results. Then we investigate the magnitude, timing, and persistence of downstream changes due to the introduction of synthetic sediment pulses by comparing the results against a baseline condition (without pulse). Our findings suggest that bed response is primarily influenced by the sediment‐pulse grain size and distribution. Intermediate mixed‐size pulses (∼50% of the median bed gravel size) are likely to have the largest downstream impact because finer sizes translate quickly and coarser sizes (median bed gravel size and larger) disperse slowly. Furthermore, a mixed‐size pulse, with a smaller median grain size than the bed, increases bed mobility more than a uniform‐size pulse. This work has important implications for river management, as it allows us to better understand fluvial geomorphic responses to variations in sediment supply.