Geology topics

Nan Wang

Publications and source records attributed to Nan Wang.

5 recordsLinked to original sources

USGS2025

Apatite geo-thermochronology and geochemistry constrain Oligocene-Miocene growth and geodynamics of the northeastern Tibetan Plateau

Understanding the geodynamics of plateau evolution requires examining the spatial and temporal aspects of mountain building in the northeastern Tibetan Plateau, which are still under debate. Here we integrate apatite geo-thermochronological and geochemical data from the Oligocene-Miocene succession of the Xunhua Basin to elucidate the evolution of the regional topography. The results suggest sediment provenance changes, at ca. 28, 20 and 12 Ma, indicating topographic growth of the West Qinling, Laji Shan, and Jishi Shan source areas, respectively. Our findings reveal Oligocene-Miocene stepwise deformation and middle Miocene stress reorganization within the northeastern Tibetan Plateau. We attribute this to Oligocene lithospheric foundering beneath the south-central Tibetan Plateau and the middle Miocene initiation of sinistral strike-slip faults due to the underthrusting of India and North China. This study highlights the roles of lithospheric removal and continental underthrusting in plateau growth, and the value of multi-proxy apatite analyses in provenance studies.

Northeastern Tibetan Plateau↗

USGS2023

Monitoring of wave, current, and sediment dynamics along the Chincoteague living shoreline, Virginia

Nature-based features, also called living shorelines, are increasingly applied in coastal protection and restoration. However, the processes and mechanisms (feedbacks and interactions) of wave attenuation, current velocity change, and sediment deposition and erosion along the living shoreline remain unclear, thus limiting the adaptive management of living shoreline restoration projects for coastal shoreline resilience under future storm conditions. In this study, wave, current, and sediment dynamics along the Little Toms Cove living shoreline, Chincoteague National Wildlife Refuge, Virginia, a low wave energy environment, were investigated during a 2-month winter period in 2019 to examine the effects of living shoreline structures on shoreline protection and oyster habitat enhancement. It was found that wave attenuation by the living shoreline structures (oyster castles or constructed oyster reefs) is dependent on water depth, wind speed, wind direction, and local bathymetry. Analysis of observed data indicate that the oyster castles along the Little Toms Cove living shoreline play a limited role in wave attenuation in this low wave energy environment. During the 2-month winter period, wave energy was attenuated by 39.7 percent when oyster castles were emergent or slightly submerged with southwest winds. In contrast, when the oyster castles were fully submerged, wave energy behind the oyster castles increased by 38.6 percent. The construction of oyster castles affected circulation patterns with increase or decrease in velocity at nearshore waters protected by the castles depending on locations of measurements in relation to the oyster castles. Bottom shear stress analysis indicates that tidal currents play a larger role than waves on shoreline and marsh edge erosion along the Little Toms Cove shoreline during the 2 months of field monitoring. The oyster castles protecting the marsh edge and tidal flat from erosion resulted in higher fine sediment concentration in the water column landward of the castles because more sediment was retained in the lee side of the castles. It is important to maximize sediment within the wetlands and adjacent mudflats behind the oyster castles. Erosion from the marsh edge and interior serves as the major source of sediment for this wetland system due to the limited sediment supply in Assateague Channel. Furthermore, it was found that the oyster castles along the Little Toms Cove living shoreline were inundated more than 60 percent of the time, leading to the enhanced oyster habitat as evidenced by suitable velocity (less than 10 centimeters per second) and mean grain size (less than 0.08 millimeters) for oyster feeding and the increased oyster shell density and growth in the intertidal zone protected by the castles than in the control area. More field data (for example, concurrent monitoring of sediment concentration and salinity) over other seasons (for example, summer) could help examine the long term and combined engineering and ecological benefits of living shoreline restoration projects under seasonal and enhanced future storm conditions.

Virginia↗

USGS2023

Field observations and long short-term memory modeling of spectral wave evolution at living shorelines in Chesapeake Bay, USA

Living shorelines as a nature-based solution for climate change adaptation were constructed in many places around the world. The success of this type of projects requires long-term monitoring for adaptive management. The paper presents a novel framework leveraging scientific machine learning methods for accurate and rapid prediction of long-term hydrodynamic forcing impacting living shorelines using short-term measurements of water levels and wind waves in the largest estuary in the U.S. Different from existing data-driven wave prediction models focusing on significant wave heights, this study is focused on the prediction of wave energy spectra in shallow water using winds and tides as the input feature and short-term measurements of wave spectra and water depths as the label. Long Short-Term Memory (LSTM) models were developed using four-month wave measurements in the stormy seasons to predict integral wave parameters and energy spectra for multiple years. The developed models accurately predicted wave heights, peak periods, and energy spectra around the living shorelines, capturing complex wave dynamics, such as wave generation by wind, nonlinear wave-wave interactions, and depth-limited wave breaking in the shallow water of a large estuary. The validated models were then used to determine the long-term wave forcing impacting the living shorelines based on the modeled wave characteristics and spectra. Model results show that the surrogate models utilizing LSTM to predict wave spectra in the frequency domain enable long-term predictions of spectral wave evolution with a minimal computational cost. Our findings provide valuable insights into the efficacy of living shorelines in attenuating wave energy and demonstrate the utility of this approach in assessing the effectiveness of such living shoreline structures.

Applied Ocean Research↗

USGS2023

Modeling surface wave dynamics in upper Delaware Bay with living shorelines

Living shorelines gain increasing attention because they stabilize shorelines and reduce erosion. This study leverages physics-based models and bagged regression tree (BRT) machine learning algorithm to simulate wave dynamics at a living shoreline composed of constructed oyster reefs (CORs) in upper Delaware Bay. The physics-based models consist of coupled Delft3D-FLOW and SWAN in four-level nested domains. The model accuracy converges with increasing mesh resolution. The simulated wave-induced current circulation substantiates the effectiveness of CORs in trapping sediments. The simulated yearly-averaged wave power correlates qualitatively with historical shoreline retreat rates. BRT is adopted to improve the model accuracy, identify key processes responsible for simulation errors in wave height ( H 8 ) and wave period ( T p ), and quantify their importance. In the CORs sheltered area, BRT reveals that simulation errors of wind seas mainly arise from wind forcing, wave breaking and wave triad interactions. Wave breaking is seven times more important than wind forcing for simulating H 8 , while wind forcing and triad interactions are of equal importance for simulating T p . Simulation errors of swells mostly stem from bottom friction and offshore wave boundary conditions. Results from this study can help the assessment and adaptive management of CORs-based living shoreline restoration projects under climate change.

New Jersey↗

USGS2022

Data-driven modeling of wind waves in upper Delaware Bay with living shorelines

Living shoreline projects have been built to preserve coastal ecosystems under future climate change and sea level rise. To quantify the wave power variation across living shorelines, the wave characteristics around the constructed oyster reefs (CORs) in upper Delaware Bay were investigated in this study. Wave parameters seaward and shoreward of CORs were recorded by wave gauges in early 2018. Four winter storms happened in this period and induced strong winds and coastal flooding at the study site. To estimate the wind wave characteristics across the CORs on a yearly basis, soft computing-based models combining fully connected neural networks and long short-term memory were developed to extend the two-month energetic wave measurements. The results show that when CORs were emergent or slightly submerged, the averaged wave height attenuation was about 39.8% from the offshore gauge to the nearshore gauge (behind CORs) during 2018–2020, owing to the combined effect of nearshore bathymetric changes and CORs. Furthermore, it was found that the annually averaged wave power reduction from offshore to nearshore at the study site was about 30.0% in 2018, 2019, and 2020. This study provides a novel framework to predict long-term wave characteristics based on short-term wave measurements using soft computing-based models.

New Jersey↗