River Research and Applications, Journal Year: 2024, Volume and Issue: 40(6), P. 884 - 886
Published: July 1, 2024
Language: Английский
River Research and Applications, Journal Year: 2024, Volume and Issue: 40(6), P. 887 - 942
Published: April 4, 2024
Abstract In this article, we track the evolution of fluvial biogeomorphology from middle 20th century to present. We consider emergence as an interdisciplinary research area that integrates knowledge drawn primarily geomorphology and plant ecology, but with inputs hydrology landscape ecology. start by assembling evidence for field a keyword search Web Science detailed analysis papers published in two scientific journals: journal—Earth Surface Processes Landforms; multidisciplinary river science journal—River Research Applications. Based on evidence, identify three distinct time periods development biogeomorphology: ‘early years’ before 1990; transitional decade 1990s; period rapid expansion diversification themes, methods investigation scales since 2000. Because literature is vast, can only summarize developments each these periods, refer recent in‐depth reviews conceptual perspectives relevant topics. Thus, rather than full deep review, present annotated bibliographic overview biogeomorphology, whereby text describes broad trends supported tables citations deliver greater detail. end brief consideration likely future developments.
Language: Английский
Citations
10
Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133302 - 133302
Published: April 1, 2025
Language: Английский
Citations
0
Earth Surface Processes and Landforms, Journal Year: 2024, Volume and Issue: 49(1), P. 256 - 276
Published: Jan. 1, 2024
Abstract Large wood drives both the form and function of gravel‐bed rivers draining forested basins. Previously overlooked benefits in are now widely recognized. Together with flow sediment regimes, regime controls rivers' physical ecological integrity. Yet large quantities transported during floods can pose additional hazards, potentially damaging infrastructures like bridges or dams exacerbating flooding. However, unlike water regimes intensively studied over past decades, instream budgeting has been only recently defined thus is still rarely quantified. The budget describes cascading processes from supply recruitment, entrainment, transport to deposition, storage decay (i.e., fragmentation decomposition). These show high spatial temporal variability but be characterized by magnitude, frequency, timing, duration mode. Instream challenging, primarily because lack observations, monitoring stations, standardized protocols acquire data. This contribution reviews most recent advances quantify different components, notably supply, transfer. Case studies showing applications biogeochemistry, videography, artificial intelligence, numerical modelling tracking illustrate current progress. Because critical challenges remain, we identify describe some them discuss how riverine sciences may develop future.
Language: Английский
Citations
2
Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(6)
Published: June 1, 2024
Abstract Predicting wood flux (i.e., piece number per time interval) or discharge (metre cubes of second) in rivers is crucial for adequate integrated river management that balances risk assessment and ecological improvement. To enhance our understanding the transport mechanisms assess their effects various geographical contexts, it necessary to conduct inter‐basin comparative studies preliminary modelling. The two basins was analysed using video monitoring random forest predictions based on hydrological drivers. dynamics Ain Allier were both compared contrasted. Although there shared hysteresis, hourly flux, relative critical flow discharges certain factors exhibited differences between basins. As a next step, models, which trained previously, applied predict then third (the Rhône), order estimate volume export, can be with volumes extracted over series few monthly periods Génissiat reservoir. By modelling, possible Rhône river. Despite absence any training data, noticeable correlation, however, estimated significantly overestimated. resolve this issue, correction factor applied, accounting disparities recruitment basin It found high events are underestimated, emphasizing importance incorporating local annotations additional parameters model. Accurately predicting important watershed management, but field observations still lacking validation process‐based understanding.
Language: Английский
Citations
2
CATENA, Journal Year: 2024, Volume and Issue: 249, P. 108673 - 108673
Published: Dec. 17, 2024
Language: Английский
Citations
2
Earth and Space Science, Journal Year: 2024, Volume and Issue: 11(8)
Published: Aug. 1, 2024
Abstract Large wood is an integral part of many rivers, often defining river‐corridor morphology and habitat, but its occurrence, magnitude, evolution in a river system are much less well understood than the sedimentary hydraulic components, due to methodological limitations, have seldom previously been mapped substantial detail. We present new method for this, representing advance automated deep‐learning‐based image segmentation. From these maps, we measured large sediment deposits from high‐resolution orthoimages explore dynamics two reaches Elwha River, Washington, USA, between 2012 2017 as it adjusted upstream dam removals. The data set consists time series (12.5‐cm resolution) constructed using Structure‐from‐Motion photogrammetry on imagery 14 aerial surveys. Model training was optimized yield maximum accuracy estimated areas, compared manually digitized wood, therefore model development intended application were coupled. These fully reproducible methods resulted 15% error observed total areas deposit size‐distributions over full spatio‐temporal extent data. Areal channel margin approximately doubled years following removal, with greatest increases wider, lower‐gradient sections. Large‐wood deposition increased start removal (2011) winter 2013, then plateaued. Sediment bars continued grow up until 2016/17, assisted by partially static framework deposited predominantly during period 2013.
Language: Английский
Citations
1
EarthArXiv (California Digital Library), Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 9, 2024
Large wood is an integral part of many rivers, often defining river-corridor morphology and habitat, but its occurrence, magnitude, evolution in a river system are much less well understood than the sedimentary hydraulic components, due to methodological limitations, have seldom previously been mapped substantial detail. We present new method for this, representing advance automated deep-learning-based image segmentation. From these maps, we measured large sediment deposits from high-resolution orthoimages explore dynamics two reaches Elwha River, Washington, USA, between 2012 2017 as it adjusted upstream dam removals. The dataset consists time series (12.5-cm resolution) constructed using Structure-from-Motion photogrammetry on imagery 14 aerial surveys. Model training was optimized yield maximum accuracy estimated areas, compared manually digitized wood, therefore model development intended application were coupled. These fully reproducible methods resulted 15% error observed total areas deposit size-distributions over full spatio-temporal extent data. Areal channel margin approximately doubled years following removal, with greatest increases wider, lower-gradient sections. Large-wood deposition increased start removal (2011) winter 2013, then plateaued. Sediment bars continued grow up until 2016/17, assisted by partially static framework deposited predominantly during period 2013.
Language: Английский
Citations
0
River Research and Applications, Journal Year: 2024, Volume and Issue: 40(6), P. 884 - 886
Published: July 1, 2024
Language: Английский
Citations
0