We introduce a novel, cost-effective photogrammetry-based method designed for measuring rapidly evolving three-dimensional surface topography in particle-fluid flow experiments. This method offers high-resolution results over a considerable surface area, enabling the capture of dynamic flow events with temporal granularity limited only by removable memory card capacity. Multiple WiFi-enabled security cameras, meticulously calibrated with precision-measured reference points on calibration boards, are employed in this methodology. External synchronization, facilitated by strategically-positioned flash lamps, allows calibration among cameras without additional precise tools. Validating our method through an alluvial fan experiment showcases its efficacy in tracking the growth and evolution of experimental debris flows, particularly in capturing the dynamic evolution of debris flow deposits on a growing alluvial fan. This example illustrates the method's ability to link local flow, evolution, and deposition to multiple channel avulsion events, highlighting its success in capturing distinct slope and height dependencies associated with these phenomena. Overall, our method transcends conventional measurement approaches, providing a significant advancement in capturing the intricacies of rapidly evolving three-dimensional surface topography in particle-fluid flow experiments. Its cost-effectiveness and robustness make it a valuable tool for diverse, dynamic scenarios, presenting a promising solution for experimental laboratory-scale landscape studies.

This article provides a commentary about the state of integrated, coordinated, open, and networked (ICON) principles in Earth and Planetary Science Processes (EPSP) and discussion on the opportunities and challenges of adopting them. This commentary focuses on the challenges with current inclusive, equitable, and accessible science and highlights how research undertaken in the earth and planetary surface processes community currently benefit from and would be able to grow as a discipline with more directed implementation of ICON principles.

Key Points: 8 • Bed heights of bedload-dominated rivers modeled by Distinct Element Method (DEM) 9 simulations follow a Gaussian distribution. 10 • The standard deviation of bed height, s η , increases as the shear stress increases. 11 • Peak entrainment of bed particles occurs at a distance 2s η above the average bed 12 height. Abstract 14 We investigate the statistics of bed height variability and particle entrainment height un-15 der steady state bedload transport conditions using distinct element method (DEM) sim-16 ulations. We do so in the context of a theoretical probabilistic formulation derived to 17 better capture spatial variation in sediment exchange between bed material load and al-18 luvial deposits (Parker et al., 2000). Using DEM simulations, we set the foundation for 19 a physics-based closure of this probabilistic framework toward its practical implemen-20 tation. Towards this, we perform DEM simulations for bedload transport under simi-21 lar boundary conditions to those of Wong et al. (2007) laboratory experiments: a bed 22 of gravel particles of median grain size 7.1mm with lognormal grain size distribution trans-23 ported under bed shear stresses ranging from τ 0 = 8.70 to 13.7 Pa. We first validate 24 these simulations by demonstrating that they capture measurable transport and height 25 variations from experimental measurements. We then compute the statistics of both the 26 bed height and entrainment height as they vary with bed shear stress. We find that vari-27 abilites in both bed height and entrainment height variabilities follow Gaussian distri-28 butions, for which: (1) the standard deviation of bed height variability s η increases with 29 shear stress, and (2) the peak entrainment height occurs a distance of twice the stan-30 dard deviation of bed height variability (2s η) above the mean bed height. We discuss 31 implications of these results and next steps for understanding these transport statistics 32 under a broader range of conditions. 33