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This study investigated different sedimentation measurement techniques and examined patterns of short‐term sedimentation in two 1‐ha replicate created freshwater marshes in central Ohio, USA. Short‐term (one‐year) sediment accumulation above feldspar, clay, glitter, and sand artificial marker horizons was compared at different water depths and distances from wetland inflow. A sediment budget was also constructed from turbidity and suspended sediment data for comparison with marker horizons. Glitter and sand marker horizons were the most successful for measuring sediment accumulation (81–100% marker recovery), while clay markers were completely unsuccessful. The sedimentation rate for both wetlands averaged 4.9 cm yr−1 (36 kg m−2 yr−1), and ranged from 1.82 to 9.23 cm yr−1 (12.4 to 69.7 kg m−2 yr−1). Sedimentation rates in deep, open water areas were significantly higher than in shallow, vegetated areas for both wetlands (t test, p < 0.05). However, observed sedimentation patterns may be attributed more to preferential flow through open water areas than to water depth or presence of vegetation. Contrary to the expected spatial distribution, sedimentation was highly variable within the wetlands, suggesting that bioturbation and turbulence may cause significant resuspension or that high hydrologic loads may distribute sediments throughout the basins. A sediment budget estimated sediment retention of approximately 740 g m−2 yr−1 per wetland (43% removal rate), yet gross sediment accumulation was 36 000 g m−2 yr−1 measured by marker horizons. These results suggest that erosive forces may have influenced sedimentation, but also may indicate problems with the sediment budget calculation methodology.

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We present simulations of the capabilities of the Atacama Large Millimeter/submillimeter Array (ALMA) and of a next-generation Very Large Array (ngVLA) to detect and resolve substructures due to terrestrial planets and super-Earths in nearby planet-forming disks. We adopt the results of global 2D hydrodynamical planet–disk simulations that account for the dynamics of gas and dust in a disk with an embedded planet. Our simulations follow the combined evolution of gas and dust for several thousand planetary orbits. We show that long integrations (several tens of hours) with the ngVLA can detect and spatially resolve dust structures due to low-mass rocky planets in the terrestrial planet formation regions of nearby disks (stellocentric radii r = 1–3 au), under the assumption that the disk viscosity in those regions is low (α ≤ 10−5). ALMA is instead unable to resolve these structures in these disk regions. We also show that high-resolution ngVLA observations separated by several days to a few weeks would allow us to detect the proper motion of the azimuthally asymmetric structures expected in the disk regions of terrestrial planet formation.

We present theoretical predictions for the free–free emission at centimeter wavelengths obtained from photoevaporation and magnetohydrodynamic (MHD) wind disk models adjusted to the case of the TW Hydrae young stellar object. For this system, disk photoevaporation with heating due to the high-energy photons from the star has been proposed as a possible mechanism to open the gap observed in the dust emission with the Atacama Large Millimeter/submillimeter Array. We show that the photoevaporation disk model predicts a radial profile for the free–free emission that is made of two main spatial components, one originated from the bound disk atmosphere at 0.5–1 au from the star, and another more extended component from the photoevaporative wind at larger disk radii. We also show that the stellar X-ray luminosity has a significant impact on both these components. The predicted radio emission from the MHD wind model has a smoother radial distribution which extends to closer distances to the star than the photoevaporation case. We also show that a future radio telescope such as the Next Generation Very Large Array would have enough sensitivity and angular resolution to spatially resolve the main structures predicted by these models.