Depositional dynamics and vegetation succession in self-organizing processes of deltaic marshes.

Global deltaic marshes are currently facing a multitude of pressures, including insufficient sediment supply, rising sea levels, and habitat loss. Consequently, unraveling the internal regulatory mechanisms within deltaic marshes is of paramount importance. Here, we harness years of observational data and high-resolution numerical models to uncover depositional dynamics and vegetation succession in self-organizing processes of deltaic marshes. Our findings indicate that the colonization of salt marsh vegetation triggered a robust phase of growth in the initial stages of river deltas formation. However, as vertical accretion intensifies and inundation decreases, the delta is driven towards a state of critical slowing down due to insufficient sediment supply. We have captured a pivotal turning point in the evolution of deltaic marshes. In accordance with the critical submergence threshold we have established, when the inundation time of deltaic marshes exceeds 0.97 h/d, these salt marsh platforms sustain a higher annual growth rate. Conversely, when the inundation time of deltaic marshes falls below 0.97 h/d, the interannual accretion rate continues to decrease. Our research reveals that, in the absence of human disturbances, the deposition rate in deltaic marshes transitions from growth to decline. During this period, the delta undergoes an interesting succession of pioneer salt marshes (Suaeda salsa) and high-elevation salt marshes (Phragmites australis). Even without reductions in sediment input due to human activities, the vertical deposition rate within deltaic marshes will still shift from acceleration to deceleration under the influence of this internal negative feedback regulation. This adaptive capacity of marshes may foreshadow that when observing a slowdown in vertical accretion on deltaic marsh platforms, it cannot be solely attributed to reductions in sediment input caused by human activities.

Sea-level rise versus salt marsh colonization: The adversarial game of self-organized elevation maintenance in tidal marsh.

Tidal marshes globally face escalating threats from rising sea levels. As critical determinants of tidal marsh platform elevation maintenance, the contributions of marsh soil compaction and subsidence (SCS) are often overshadowed by vertical accretion (VA). Here, we reveal the pervasive presence of the SCS within tidal marshes and its driving forces. Our results demonstrate that while vegetated regions can organize more efficient sediment accumulation, thereby promoting marsh elevation rise, they also contribute to an increase in SCS occurrences, which somewhat hinders marsh elevation growth. Through the established empirical model of SCS, we found that the amount of SCS in the investigated marshes with vegetation cover is twice that of marshes without vegetation. Therefore, from the perspective of SCS, it is imperative to account for the detrimental impact of vegetation on marsh elevation, as we have uncovered that this oversight may lead to an underestimation of the vulnerability of the investigated tidal marsh ecosystem by approximately 13.55 %. We also find that the adversarial game between vegetation colonization and sea-level rise governs the SCS in the self-organization of tidal marshes, but the intensifying inundation from sea-level rise ultimately determines the fate of the SCS. Our study emphasizes the crucial role of the game between sea-level rise and vegetation colonization in the self-organized elevation maintenance of tidal marshes.

Development and evaluation of a GPU-based coupled three-dimensional hydrodynamic and water quality model.

In this study, a graphics processing unit (GPU)-based three-dimensional coupled hydrodynamic and water quality numerical model (GPUOM-WQ) was developed for the first time, which introduces pollution sources of atmospheric deposition, aquaculture wastewater, and oil platform emission to describe marine pollution comprehensively. A test case with analytical solutions and a real case with measured data were used to validate the accuracy of GPUOM-WQ. Simulation results indicate that the maximum error between the numerical and analytical solutions is 0.9 %, and the average relative error between simulated and measured values of 5 water quality variables at 38 stations in spring, summer, fall and winter is 14.63 %. In the real case simulation, GPUOM-WQ accelerates the computation 62.48 times, which is 3.23 times faster than in 64-core central processing unit (CPU) parallel mode. This study makes it possible to accurately simulate the marine water quality variation and spatiotemporal distribution in a high-resolution and efficient way.