Big data show idiosyncratic patterns and rates of geomorphic river mobility

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Nature Communications Pub Date : 2025-04-05 DOI:10.1038/s41467-025-58427-9
Richard J. Boothroyd, Richard D. Williams, Trevor B. Hoey, Gary J. Brierley, Pamela L. M. Tolentino, Esmael L. Guardian, Juan C. M. O. Reyes, Cathrine J. Sabillo, Laura Quick, John E. G. Perez, Carlos P. C. David
{"title":"Big data show idiosyncratic patterns and rates of geomorphic river mobility","authors":"Richard J. Boothroyd, Richard D. Williams, Trevor B. Hoey, Gary J. Brierley, Pamela L. M. Tolentino, Esmael L. Guardian, Juan C. M. O. Reyes, Cathrine J. Sabillo, Laura Quick, John E. G. Perez, Carlos P. C. David","doi":"10.1038/s41467-025-58427-9","DOIUrl":null,"url":null,"abstract":"<p>Big data present unprecedented opportunities to test long-standing theories regarding patterns and rates of geomorphic river adjustments. Here, we use locational probabilities derived from Landsat imagery (1988-2019) to quantify the dynamics of 600 km<sup>2</sup> of riverbed in 10 Philippine catchments. Analysis of lateral adjustments reveals spatially non-uniform variability in along-valley patterns of geomorphic river mobility, with zones of relative stability interspersed with zones of relative instability. Hotspots of mobility vary in magnitude, size and location between catchments. We could not identify monotonic relationships between local factors (active channel width, valley floor width and confinement ratio) and mobility. No relation between the channel pattern type and rates of adjustment was evident. We contend that satellite-derived locational probabilities provide a spatially continuous dynamic metric that can help unravel and contextualise forms and rates of geomorphic river adjustment, thereby helping to derive insights into idiosyncrasies of river behaviour in dynamic landscapes.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"73 1","pages":""},"PeriodicalIF":15.7000,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-58427-9","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Big data present unprecedented opportunities to test long-standing theories regarding patterns and rates of geomorphic river adjustments. Here, we use locational probabilities derived from Landsat imagery (1988-2019) to quantify the dynamics of 600 km2 of riverbed in 10 Philippine catchments. Analysis of lateral adjustments reveals spatially non-uniform variability in along-valley patterns of geomorphic river mobility, with zones of relative stability interspersed with zones of relative instability. Hotspots of mobility vary in magnitude, size and location between catchments. We could not identify monotonic relationships between local factors (active channel width, valley floor width and confinement ratio) and mobility. No relation between the channel pattern type and rates of adjustment was evident. We contend that satellite-derived locational probabilities provide a spatially continuous dynamic metric that can help unravel and contextualise forms and rates of geomorphic river adjustment, thereby helping to derive insights into idiosyncrasies of river behaviour in dynamic landscapes.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
大数据显示了地貌河流流动的特殊模式和速率
大数据为检验长期存在的关于地貌河流调整模式和速率的理论提供了前所未有的机会。在这里,我们使用来自陆地卫星图像(1988-2019)的位置概率来量化菲律宾10个集水区600平方公里河床的动态。横向调整分析揭示了地貌河流沿流域流动格局在空间上的不均匀变异性,相对稳定带穿插着相对不稳定带。流动热点的大小、大小和位置在汇水区之间各不相同。我们不能确定局部因素(活动通道宽度、谷底宽度和约束比)与流动性之间的单调关系。通道模式类型和调整速率之间没有明显的关系。我们认为,卫星衍生的位置概率提供了一个空间连续的动态度量,可以帮助揭示和背景化地貌河流调整的形式和速度,从而有助于深入了解动态景观中河流行为的特质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
期刊最新文献
Hydrogel with cell-cell adhesion cues enhances neural regeneration. Controlled hierarchical self-assembly of hyperbolic paraboloid molecules into two-dimensional superstructures with second-harmonic generation characteristic. Modeling tissue-specific Drosophila metabolism identifies high sugar diet-induced metabolic dysregulation in muscle at reaction and pathway levels. Longitudinal analysis of body weight reveals homeostatic and adaptive traits linked to lifespan in diversity outbred mice. TidyMass2: advancing LC-MS untargeted metabolomics through metabolite origin inference and metabolic feature-based functional module analysis.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1