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":14.7000,"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.
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.