The rivers of the world are undergoing accelerated change in the Anthropocene, and need to be managed at much broader spatial and temporal scales than before. Fluvial remote sensing now offers a technical and methodological framework that can be deployed to monitor the processes at work and to assess the trajectories of rivers in the Anthropocene. In this paper, we review research investigating past, present and future fluvial corridor conditions and processes using remote sensing and we consider emerging challenges facing fluvial and riparian research. We introduce a suite of remote sensing methods designed to diagnose river changes at reach to regional scales. We then focus on identification of channel patterns and acting processes from satellite, airborne or ground acquisitions. These techniques range from grain scales to landform scales, and from real time scales to inter-annual scales. We discuss how remote sensing data can now be coupled to catchment scale models that simulate sediment transfer within connected river networks. We also consider future opportunities in terms of datasets and other resources which are likely to impact river management and monitoring at the global scale. We conclude with a summary of challenges and prospects for remotely sensed rivers in the Anthropocene.

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Remotely sensed rivers in the Anthropocene: state of the art and prospects

Random walk models of fluvial sediment transport recognize that grains move intermittently, with short duration steps separated by rests that are comparatively long. These models are built upon the probability distributions of the step length and the resting time. Motivated by these models, tracer experiments have attempted to measure directly the steps and rests of sediment grains in natural streams. This paper describes results from a large tracer experiment designed to test stochastic transport models. We used passive integrated transponder (PIT) tags to label 893 coarse gravel clasts and placed them in Halfmoon Creek, a small alpine stream near Leadville, Colorado, USA. The PIT tags allow us to locate and identify tracers without picking them up or digging them out of the streambed. They also enable us to find a very high percentage of our rocks, 98% after three years and 96% after the fourth year. We use the annual tracer displacement to test two stochastic transport models, the Einstein–Hubbell–Sayre (EHS) model and the Yang–Sayre gamma-exponential model (GEM). We find that the GEM is a better fit to the observations, particularly for slower moving tracers and suggest that the strength of the GEM is that the gamma distribution of step lengths approximates a compound Poisson distribution. Published in 2012. This article is a US Government work and is in the public domain in the USA.

Measuring gravel transport and dispersion in a mountain river using passive radio tracers

[1] Sediment transport is an intrinsically stochastic process, and measurement of bed load in the environment is further complicated by the unsteady nature of river flooding. Here we present a methodology for analyzing sediment tracer data with unsteady forcing. We define a dimensionless impulse by integrating the cumulative excess shear velocity for the duration of measurement, normalized by grain size. We analyze the dispersion of a plume of cobble tracers in a very flashy stream over two years. The mean and variance of transport distance collapse onto well-defined linear and power-law relations, respectively, when plotted against cumulative dimensionless impulse. Data suggest that the asymptotic limit of bed load tracer dispersion is superdiffusive, in line with a broad class of geophysical flows exhibiting strong directional asymmetry (advection), thin-tailed step lengths and heavy-tailed waiting times. The impulse framework justifies the use of quasi-steady flow approximations for long-term river evolution modeling.

/pdf/impulse-framework-for-unsteady-flows-reveals-superdiffusive-4kcimy8naq.pdf

Impulse framework for unsteady flows reveals superdiffusive bed load transport

[1] Previous work highlights the need for data collection to identify appropriate models for temporal evolution of tracer dispersal in rivers Results of 64 gravel-bed field tracer experiments covering a wide range of flow and sediment supply regimes are compiled here to determine the probabilistic character of gravel transport We focus on whether particle travel distances and waits are thin- or heavy-tailed While heavy-tailed travel distance distributions are observed between successive monitoring events in different hydrological and sediment supply regimes, heavy-tailedness does not persist through total travel distance over multiple monitoring events, suggesting that individual monitoring events occur before particle travel distance exceeds the characteristic correlation length for the channel (such that particles that start in fast paths remain in fast paths and particles in slow paths remain in slow paths) After a large number of transport events, super-diffusive spreading was not observed at any of the gravel bed streams Continuous-time tracking of x, y, z coordinates of tracers in natural streams is necessary to capture exact step and waiting time distributions

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2012JF002374

Displacement characteristics of coarse fluvial bed sediment

This paper outlines the various approaches used to calculate bedload transport. As bedload transport exhibits considerable spatial and temporal variations, computing the bedload transport rates and...

https://www.tandfonline.com/doi/pdf/10.1080/00221686.2019.1702594

Bedload transport: a walk between randomness and determinism. Part 1. The state of the art

This paper reports a radiofrequency identification (RFID) tracing experiment implemented in a high-sediment-load mountain stream typical of alpine gravel-bed torrents. The study site is the Bouinenc Torrent, a tributary to the Bleone River in southeast France that drains a 38·9-km² degraded catchment. In spring 2008, we deployed 451 tracers with b-axis ranging from 23 to 520 mm. Tracers were seeded along eight cross-sections located in the upstream part of the lowest 2·3 km of the stream. Three tracer inventories were implemented in July 2008, 2009 and 2010. Recovery rates calculated for mobile tracers declined from 78% in 2008 to 45% in 2009 and 25% in 2010. Observations of tracer displacement revealed very high sediment dispersion, with frontrunners having travelled more than 2 km only three months after their deployment. The declining recovery rate over time was interpreted as resulting from rapid dispersion rather than deep burial. We evaluated that 64% of the tracers deployed in the active channel were exported from the 2·3-km study reach three years after the onset of the tracing experiment. Travel distances were characterized by right-skewed and heavy-tailed distributions, correctly fitted by a power-law function. This supports the idea that in gravel-bed rivers with abundant sediment supply relative to transport capacity, bedload transport can be viewed as a superdiffusive sediment dispersion process. It is also shown that tracers initially deployed in the low-flow channel were characterized by a 15- to 30-fold increase of mobility compared to tracers deployed in gravel bars. Copyright © 2011 John Wiley & Sons, Ltd.

Michaël Deschâtres

Papers

Bedload tracing in a high-sediment-load mountain stream