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Title: Resilience of River Deltas in the Anthropocene

At a global scale, delta morphologies are subject to rapid change as a result of direct and indirect effects of human activity. This jeopardizes the ecosystem services of deltas, including protection against flood hazards, facilitation of navigation, and biodiversity. Direct manifestations of delta morphological instability include river bank failure, which may lead to avulsion, persistent channel incision or aggregation, and a change of the sedimentary regime to hyperturbid conditions. Notwithstanding the in‐depth knowledge developed over the past decades about those topics, existing understanding is fragmented, and the predictive capacity of morphodynamic models is limited. The advancement of potential resilience analysis tools may proceed from improved models, continuous observations, and the application of novel analysis techniques. Progress will benefit from synergy between approaches. Empirical and numerical models are built using field observations, and, in turn, model simulations can inform observationists about where to measure. Information theory offers a systematic approach to test the realism of alternative model concepts. Once the key mechanism responsible for a morphodynamic instability phenomenon is understood, concepts from dynamic system theory can be employed to develop early warning indicators. In the development of reliable tools to design resilient deltas, one of the first challenges is to close the sediment balance at multiple scales, such that morphodynamic model predictions match with fully independent measurements. Such a high ambition level is rarely adopted and is urgently needed to address the ongoing global changes causing sea level rise and reduced sediment input by reservoir building.

 
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Award ID(s):
1719670 1600222 1350336
NSF-PAR ID:
10457967
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Journal of Geophysical Research: Earth Surface
Volume:
125
Issue:
3
ISSN:
2169-9003
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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