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Title: A global delta dataset and the environmental variables that predict delta formation on marine coastlines
Abstract. River deltas are sites of sediment accumulation along thecoastline that form critical biological habitats, host megacities, andcontain significant quantities of hydrocarbons. Despite their importance, wedo not know which factors most significantly promote sediment accumulationand dominate delta formation. To investigate this issue, we present a globaldataset of 5399 coastal rivers and data on eight environmental variables.Of these rivers, 40 % (n=2174) have geomorphic deltas defined eitherby a protrusion from the regional shoreline, a distributary channel network,or both. Globally, coastlines average one delta forevery ∼300 km of shoreline, but there are hotspots of delta formation, for examplein Southeast Asia where there is one delta per 100 km of shoreline. Ouranalysis shows that the likelihood of a river to form a delta increases withincreasing water discharge, sediment discharge, and drainage basin area. Onthe other hand, delta likelihood decreases with increasing wave height andtidal range. Delta likelihood has a non-monotonic relationship withreceiving-basin slope: it decreases with steeper slopes, but for slopes >0.006 delta likelihood increases. This reflects differentcontrols on delta formation on active versus passive margins. Sedimentconcentration and recent sea level change do not affect delta likelihood. Alogistic regression shows that water discharge, sediment discharge, waveheight, and tidal range are most important for delta formation. The logisticregression correctly predicts delta formation 74 % of the time. Our globalanalysis illustrates that delta formation and morphology represent a balancebetween constructive and destructive forces, and this framework may helppredict tipping points at which deltas rapidly shift morphologies.  more » « less
Award ID(s):
1812019
NSF-PAR ID:
10166403
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Earth Surface Dynamics
Volume:
7
Issue:
3
ISSN:
2196-632X
Page Range / eLocation ID:
773 to 787
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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