نبذة مختصرة : Ponds are common features on salt marshes, yet it is unclear how they affect large-scale marsh evolution. We developed a spatiallyexplicit model that combines cellular automata for pond formation, expansion, and drainage, and partial differential equations for elevationdynamics. We use the mesotidal Barnstable marsh (MA, USA) as a case study, for which we measured pond expansion rate by remote sensing analysis over a 41 year time span. We estimated the pond formation rate by comparing observed and modeled pond size distribution, and we estimated pond deepening by comparing modeled and measured pond depth. The Barnstable marsh is currently in the pond recovery regime, i.e., every pond revegetates and recovers the necessary elevation to support plant growth after re-connecting to the channel network. This pond dynamic creates an equivalent (i.e., spatially and temporally averaged over the whole marsh) 2 mm/yr elevation loss that needs to be supplemented by excess vertical accretion. We explore how the pond regime would change with decreased sediment supply and increased relative sea- level rise (RSLR) rate, focusing on the case in which the vegetated marsh keeps pace with RSLR. If the RSLR rate remains below the minimum unvegetated deposition rate, the pond dynamics is nearly unaltered and ponds always occupies ~10% of the marsh area. If RSLR rate exceeds this threshold, the ponds in the marsh interior - which receive the least amount of suspended sediment - do not recover after drainage. In this partial pond runaway regime, mudflats start to form and permanently occupy up to 30% of the marsh area depending on RSLR rate. If marshes with a small tidal range are considered, such as the microtidal Sage Lot Pond marsh on the opposite side of the peninsula from Barnstable marsh, high RSLR rates could bring every portion of the marsh into the pond runaway regime, with the marsh eventually converting into mudflats. In this regime, the existing marsh would disappear within centuries to millennia depending on the RSLR ...
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