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Abstract Blue crab (Callinectes sapidus) supports lucrative Mid‐Atlantic crustacean fisheries and plays an important role in estuarine ecology, so their larval transport and recruitment dynamics in the Maryland Coastal Bays system were investigated using simulated and observed surface drifters. Relative contributions of winds, tides, density gradients, and waves to larval recruitment success were identified during the spawning season, particularly under hurricane conditions in 2014. Based on temperature (e.g., 19–29°C) and salinity conditions (e.g., 23–33 PSU), particles representing virtual blue crab larvae were released into the model domain from early June to late October 2014. During the spawning season, variations in the larval recruitment success caused by wind speed and direction, tides (e.g., affecting through inlets), density gradients (e.g., salinity variations), and surface gravity waves were 17%, 4%, −9%, and 17%, respectively. During Hurricane Arthur (2014), variability of self‐recruitment success caused by density gradients are negligible while by other three factors are comparable at 3%–4%. Surface drifter experiments support the modeling results that larval recruitment success is strongly associated with the coastal circulation. The high (low) self‐recruitment success in the Assawoman and Chincoteague Bays (Sinepuxent Bay) is related to the locally weak (strong) circulation; released larvae escape from inlets are likely recruited to southern Fenwick and northern Assateague Islands, and the coastal regions outside the Chincoteague Inlet. Understanding physical factors influencing larval recruitment success helps resource managers make informed decisions about habitat restoration and harvest regulations, in addition to seafood‐related food security. 

Lagoon systems are more heavily impacted by hurricanes, whereas the relevant stormsurge modeling studies have been paid little attention to lagoon systems and the storm-induced exchange in lagoon systems is even less understood. To address this gap, a three-dimensional unstructured grid-based model was configured for the Maryland Coastal Bays, a typical lagoon system with two unique inlets (Ocean City Inlet (OCI) and Chincoteague Inlet (CI)), to investigate how Hurricane Sandy impacted inlet dynamics. A nesting model framework was applied to provide the necessary remote forcing from a large model domain and maintain the intricate shoreline and bathymetry of an inner model domain. Results indicated that the flux patterns varied in response to the change in wind direction and rising/falling high water levels from the coastal ocean, rather than a single flow pattern during the passage of Sandy. FromOctober 29 05:00 to 17:00 UTC, mild (> 10 m/s) and strong (> 15m/s) northerly winds accompanied by the rising high water level from the coastal ocean promoted a mean inflow pattern at the OCI and amean outflow pattern at the CI. Strong southwesterly winds (> 15 m/s) dominated in the bays from October 30 03:00 to 15:00 UTC. Under strong southwesterly winds and falling high water levels from the coastal ocean, flux was transported landward at the CI and seaward at the OCI. Sensitivity experiments on various storm temporal scales showed that a net inflow pattern occurred in the bays, and the net exchange amounts became smaller in response to longer storm durations. Residual effect of relatively high river flow from Sandy could still influence the salinity at the OCI, whereas the CI salinity was not affected by river flow owing to a long distance between the CI and river locations.