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流域尺度建模预测河谷中河流-风沙沉积物连通性

Landscape-Scale Modeling to Forecast Fluvial-Aeolian Sediment Connectivity in River Valleys.

作者信息

Kasprak Alan, Sankey Joel B, Caster Joshua

机构信息

U.S. Environmental Protection Agency, Center for Public Health and Environmental Assessment, Pacific Ecological Systems Division, Corvallis, OR, USA.

U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, Flagstaff, AZ, USA.

出版信息

Geophys Res Lett. 2024 Aug 20;51(16):e2024GL110106. doi: 10.1029/2024gl110106.

DOI:10.1029/2024gl110106
PMID:39440119
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11492980/
Abstract

Sedimentary landforms on Earth and other planetary bodies are built through scour, transport, and deposition of sediment. refers to the hypothesis that pathways of sediment transport do not occur in isolation, but rather are mechanistically linked. In dryland river systems, one such example of sediment connectivity is the transport of fluvially deposited sediment by wind. However, predictive tools that can forecast fluvial-aeolian sediment connectivity at meaningful scales are rare. Here we develop a suite of models for quantifying the availability of river-sourced sediment for aeolian transport as a function of river flow, wind regime, and land cover across 168 km of the Colorado River in Grand Canyon, USA. We compare and validate these models using topographic changes observed over 10 years in a coupled river sandbar-aeolian dunefield setting. The models provide a path forward for directly linking fluvial hydrology with the management and understanding of aeolian landscapes.

摘要

地球和其他行星体上的沉积地貌是通过沉积物的冲刷、搬运和沉积形成的。沉积物连通性是指沉积物搬运路径并非孤立发生,而是存在机械联系的假说。在旱地河流系统中,沉积物连通性的一个例子是风对河流沉积的沉积物的搬运。然而,能够在有意义的尺度上预测河流 - 风沙沉积物连通性的预测工具很少。在这里,我们开发了一套模型,用于量化在美国大峡谷168公里长的科罗拉多河上,作为河流流量、风况和土地覆盖函数的河流源沉积物用于风沙搬运的可用性。我们在河流沙洲 - 风沙沙丘场耦合环境中,利用10年观测到的地形变化对这些模型进行比较和验证。这些模型为直接将河流水文学与风沙地貌的管理和理解联系起来提供了一条途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/4d998e5412cf/nihms-2018160-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/c03572632176/nihms-2018160-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/4820df83288b/nihms-2018160-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/d8221f575f56/nihms-2018160-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/4d998e5412cf/nihms-2018160-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/c03572632176/nihms-2018160-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/4820df83288b/nihms-2018160-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/d8221f575f56/nihms-2018160-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a1f/11492980/4d998e5412cf/nihms-2018160-f0004.jpg

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本文引用的文献

1
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J Environ Manage. 2023 Sep 15;342:118036. doi: 10.1016/j.jenvman.2023.118036. Epub 2023 May 12.
2
Estimation of river flow using CubeSats remote sensing.利用立方体卫星遥感技术估算河川流量。
Sci Total Environ. 2021 Sep 20;788:147762. doi: 10.1016/j.scitotenv.2021.147762. Epub 2021 May 15.