000167881 001__ 167881
000167881 005__ 20260121151420.0
000167881 0247_ $$2doi$$a10.1002/2014WR016604
000167881 0248_ $$2sideral$$a143917
000167881 037__ $$aART-2015-143917
000167881 041__ $$aeng
000167881 100__ $$0(orcid)0000-0002-3800-5304$$aTejedor, Alejandro
000167881 245__ $$aDelta channel networks: 2. Metrics of topologic and dynamic complexity for delta comparison, physical inference, and vulnerability assessment
000167881 260__ $$c2015
000167881 5060_ $$aAccess copy available to the general public$$fUnrestricted
000167881 5203_ $$aDeltas are landforms that deliver water, sediment and nutrient fluxes from upstream rivers to the deltaic surface and eventually to oceans or inland water bodies via multiple pathways. Despite their importance, quantitative frameworks for their analysis lack behind those available for tributary networks. In a companion paper, delta channel networks were conceptualized as directed graphs and spectral graph theory was used to design a quantitative framework for exploring delta connectivity and flux dynamics. Here we use this framework to introduce a suite of graph-theoretic and entropy-based metrics, to quantify two components of a delta's complexity: (1)Topologic, imposed by the network connectivity and (2)Dynamic, dictated by the flux partitioning and distribution. The metrics are aimed to facilitate comparing, contrasting, and establishing connections between deltaic structure, process, and form. We illustrate the proposed analysis using seven deltas in diverse morphodynamic environments and of various degrees of channel complexity. By projecting deltas into a topo-dynamic space whose coordinates are given by topologic and dynamic delta complexity metrics, we show that this space provides a basis for delta comparison and physical insight into their dynamic behavior. The examined metrics are demonstrated to relate to the intuitive notion of vulnerability, measured by the impact of upstream flux changes to the shoreline flux, and reveal that complexity and vulnerability are inversely related. Finally, a spatially explicit metric, akin to a delta width function, is introduced to classify shapes of different delta types.
000167881 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000167881 590__ $$a3.792$$b2015
000167881 591__ $$aENVIRONMENTAL SCIENCES$$b35 / 224 = 0.156$$c2015$$dQ1$$eT1
000167881 591__ $$aWATER RESOURCES$$b5 / 84 = 0.06$$c2015$$dQ1$$eT1
000167881 591__ $$aLIMNOLOGY$$b1 / 20 = 0.05$$c2015$$dQ1$$eT1
000167881 592__ $$a2.525$$b2015
000167881 593__ $$aWater Science and Technology$$c2015$$dQ1
000167881 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000167881 700__ $$aLongjas, Anthony
000167881 700__ $$aZaliapin, Ilya
000167881 700__ $$aFoufoula-Georgiou, Efi
000167881 773__ $$g51, 6 (2015), 4019-4045$$pWater resour. res.$$tWATER RESOURCES RESEARCH$$x0043-1397
000167881 8564_ $$s7515242$$uhttps://zaguan.unizar.es/record/167881/files/texto_completo.pdf$$yPostprint
000167881 8564_ $$s612790$$uhttps://zaguan.unizar.es/record/167881/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000167881 909CO $$ooai:zaguan.unizar.es:167881$$particulos$$pdriver
000167881 951__ $$a2026-01-21-14:55:31
000167881 980__ $$aARTICLE