We evaluate links between climate and simulated river bank erosion for one of the world's largest rivers, the Mekong. We employ a process-based model to reconstruct multidecadal time series of bank erosion at study sites within the Mekong's two main hydrological response zones, defining a new parameter, accumulated excess runoff (AER), pertinent to bank erosion. We employ a hydrological model to isolate how snowmelt, tropical storms and monsoon precipitation each contribute to AER and thus modeled bank erosion. Our results show that melt (23.9% at the upstream study site, declining to 11.1% downstream) and tropical cyclones (17.5% and 26.4% at the upstream and downstream sites, respectively) both force significant fractions of bank erosion on the Mekong. We also show (i) small, but significant, declines in AER and hence assumed bank erosion during the 20th century, and; (ii) that significant correlations exist between AER and the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Of these modes of climate variability, we find that IOD events exert a greater control on simulated bank erosion than ENSO events; but the influences of both ENSO and IOD when averaged over several decades are found to be relatively weak. However, importantly, relationships between ENSO, IOD, and AER and hence inferred river bank erosion are not time invariant. Specifically, we show that there is an intense and prolonged epoch of strong coherence between ENSO and AER from the early 1980s to present, such that in recent decades derived Mekong River bank erosion has been more strongly affected by ENSO.
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http://dx.doi.org/10.1002/wrcr.20205 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
Department of Geography, Rampurhat College, PO-Rampurhat, Dist-Birbhum, 731224, India.
In fluvial environments, the shifting of river channels and bank erosion are frequently caused by both natural and anthropogenic factors. Riverine hazards like bank erosion and course alterations offer severe issues to the riparian villages along the lower basin of the Tista River in India, which substantially influence the livelihoods of inhabitants living there. This research addressed river channel shifting tendency and identified major bank erosion-prone villages along the lower course of the Tista River and challenges to the livelihoods of the riparian people.
View Article and Find Full Text PDFFront Psychol
December 2024
Department of Sociology, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
Background And Objectives: Natural disasters are harmful occurrences caused by the Earth's geological and meteorological processes. Bangladesh is recognized as one of the country's most vulnerable to natural disasters. Therefore, the people of Bangladesh remain at high risk of natural disasters.
View Article and Find Full Text PDFNature
October 2024
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA.
Heliyon
September 2024
Key Laboratory of Port, Waterway and Sedimentation Engineering of Ministry of Transport, Nanjing Hydraulic Research Institute, Nanjing 210029, China.
Bank erosion is a key feature of channel evolution in alluvial rivers, and will occur under the combined effect of hydraulic erosion and frost heave/freeze-thaw process of rivers in seasonal frozen regions. However, most research on bank erosion modeling has seldom considered the impact of the frost heave/freeze-thaw process. Therefore, the variation in the mechanical characteristics of riverbank soil under the freeze-thaw cycle was investigated firstly in the current research and then used in the modeling of bank erosion processes at typical sections of the Songhua River.
View Article and Find Full Text PDFJ Environ Manage
November 2024
Water Systems and Global Change Group, Wageningen University and Research, Wageningen, the Netherlands.
Rampant and illegal river sand mining in the Vietnamese Mekong Delta (VMD) has led to substantial sediment losses and bank erosion. However, regulation of this issue remains a significant challenge due to insufficient monitoring and enforcement efforts, partly attributed to limited data and technology. To support an improved monitoring system in the VMD, this study investigates the spatiotemporal changes in sand mining hotspots and their underlying drivers.
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