Jun Cheng

Beaches worldwide play an essential role in shore protection under storm conditions. How to identify the threshold beach width for effective shore protection remains largely unresolved due to a scarcity of measured beach profiles with sufficient temporal and spatial resolutions. In this study, weekly to monthly surveys spaced 100 m along the shoreline have been conducted at Ortley Beach, New Jersey since Fall 2023. The survey covered beach changes induced by Hurricane Lee and Tropical Storm Ophelia in Fall 2023. About half of the lost beach volume recovered within 1–2 weeks after the passage of these storms. With the onset of winter, cold fronts caused significant longshore variations in beach/dune erosion. At the erosional hotspots, severe dune line retreat occurred where the dry beach was narrower. Results indicate a critical threshold of dry beach width of about 35 m, below which dune-line retreat becomes more likely, increasing risks to landward infrastructure. As the weather shifted to summer of 2024, the beach gradually recovered, but net shoreline erosion and beach volume loss persisted, which created a more vulnerable condition for the following winter until the renourishment in Spring 2025. A simple empirical equation for threshold beach width was developed by integrating grain size and offshore wave height, supplemented by long-term beach-profile measurements from North Sand Key along the west-central Florida coast. Accurate estimation of this threshold provides a useful indicator for emergency beach management during storm conditions.

Soil spectroscopy offers a rapid, cost-effective alternative to traditional soil analyses for characterization and classification. Previous studies have mainly focused on predicting soil categories using single sensors, particularly visible–near-infrared (vis–NIR) or mid-infrared (MIR) spectroscopy. In this study, we evaluated the performance of vis–NIR, MIR, and their combined spectra for soil classification by partial least-squares discriminant analysis (PLSDA) and random forest (RF). Utilizing 60 typical soil profiles’ data of four soil classes from the global soil spectral library (GSSL), our results demonstrated that in PLSDA models, direct combination (optimal overall accuracy: 70.6%, kappa coefficient: 0.60) and outer product analysis (OPA) fused spectra (optimal overall accuracy: 68.1%, kappa coefficient: 0.57) outperformed vis–NIR (optimal overall accuracy: 62.2%, kappa coefficient: 0.49) but underperformed compared to MIR (optimal overall accuracy: 71.4%, kappa coefficient: 0.62). In RF models, classification accuracy using fused spectra was inferior to single spectral ranges, with MIR achieving the highest classification accuracy (optimal overall accuracy: 89.1%, kappa coefficient: 0.85). Therefore, MIR alone remains the most effective spectral range for accurate soil class discrimination. Our findings highlight the potential of MIR spectroscopy for enhancing global soil classification accuracy and efficiency, with important implications for soil resource management and agricultural planning across diverse environments.

Most river deltas worldwide are located in well-developed, densely populated lowland regions that face challenges from accelerated sea level rise. Deltas with morphological equilibrium are the foundation for associated prosperous economies and societies, as well as for preserving ecological fragile environments. And for deltas to be in morphological equilibrium, sufficient fluvial sediment supplies are fundamental. Severe droughts have significant impacts on the sediment load discharged to the sea, but this is considerably less studied compared to flooding events. This study examines the characteristics of Yangtze River sediment flowing toward the East China Sea during severe droughts. The effect of the Three Gorges Dam (TGD) was investigated by comparing the difference before and after its construction in 2003. Results indicate that the sediment load from the Yangtze River to the sea has experienced a more pronounced decrease during severe drought years since 2003. The primary cause is a substantial reduction in sediment supply from the upper reaches, resulting from the impoundment of the Three Gorges Reservoir created in 2003 and the construction of additional major reservoirs in the upper reach thereafter. Simultaneously, this is accompanied by the fining of sediment grain size. The fining of sediment and considerably reduced sediment load discharged to the sea during severe droughts after 2003 are likely to accelerate the erosion of the Yangtze subaqueous delta. The rating parameter values during severe drought years fall within the range observed in normal years, indicating that these drought events do not align with extreme rating parameter values. Less than 30% of the average discrepancy between measured and reconstructed sediment loads in severe drought years before 2003, and approximately 10% of the discrepancy after 2003, demonstrate the feasibility of reconstructing sediment loads for severe drought events using a sediment rating curve. This rating curve is based on daily water discharge and sediment concentration data collected during the corresponding period. These findings indicate that the rating curve-based reconstruction of sediment load performs well during severe droughts, with relative error slightly exceeding the average error of normal years prior to 2003 and approaching that observed after 2003. This study provides insights on sediment management of the Yangtze River system, including its coastal zone, and is valuable for many other large river systems worldwide.

Field observations on storm induced beach changes are important to improve our effort on beach management. This study compared storm induced beach changes caused by hurricane Hermine in 2016 (4 years after a beach nourishment) and Tropical Storm Eta in 2020 (2 years after a beach renourishment) along the barrier-island coast of west-central Florida. Pre-Eta beach were 1 to 2 times wider than that of pre-Hermine. Since Hurricane Hermine and TS Eta generated a similar hydrodynamic condition for the study site, comparing beach changes induced by these two storms provides a unique opportunity to investigate the response of different antecedent beach conditions to energetic events. The shore protection effect of beach nourishment is apparently evidenced by the fact that post-Eta shoreline was located seaward of those post-Hermine at half of the beach-profile locations in the study area. The shore protection effect in the subaerial portion of the beach, however, is not obvious for the other half of beach profiles where shoreline positions were retreated to similar locations after these two storms. Instead, their shore protection effect occurred in the sub-aqueous portion of the beach and was indicated by higher sandbar crests located closer to the shoreline, which can dissipate and reduce incoming wave energy. The shoreline elevation needs to be properly defined (Mean High Water vs Mean Low Water line) as it is used as a proxy to represent beach volume loss. For Hermine induced beach change, no significant correlation exists between MHW line change and beach volume loss. While a significant correlation exists between MHW line change and beach volume loss induced by TS Eta. This correlation pattern switched if the shoreline here is defined as mean low water line. For efficient beach/shoreline management, multiple proxies (e.g., sandbar height and location of its crest and trough) in addition to shoreline change should be used to assess the performance of beach nourishment project.

Suspended sediment dynamics play an important role in controlling nearshore and estuarine geomorphology and the associated ecological environments. Modeling the transport of suspended sediment is a complicated and challenging research topic. The goal of this study is to improve the accuracy of modeling the suspended sediment concentrations (SSCs) with newly developed techniques. Based on a three-dimensional suspended cohesive sediment transport model, the transport of suspended sediment and SSCs are simulated by assimilating SSCs retrieved from the Geostationary Ocean Color Imager (GOCI) with the adjoint data assimilation in the Hangzhou Bay, a typical strong tidal estuary along the coast of the East China Sea. To improve the effect of the data assimilation, the penalty function method, in which the reasonable constraints of the estimated model parameters are added to the cost function as penalty terms, will be introduced for the first time into the adjoint data assimilation in the SSCs modeling. In twin experiments, the prescribed spatially varying settling velocity is estimated by assimilating the synthetic SSC observations, and the results show that the penalty function method can further improve the effect of data assimilation and parameter estimation, regardless of synthetic SSC observations being contaminated by random artificial errors. In practical experiments, the spatially varying settling velocity is firstly estimated by assimilating the actual GOCI-retrieved SSCs. The results demonstrate that the simulated results can be improved by the adjoint data assimilation, and the penalty function method can additionally reduce the mean absolute error (MAE) between the independent check observations and the corresponding simulated SSCs from 1.44 × 10⁻¹ kg/m³ to 1.30 × 10⁻¹ kg/m³. To pursue greater simulation accuracy, the spatially varying settling velocity, resuspension rate, critical shear stress and initial conditions are simultaneously estimated by assimilating the actual GOCI-retrieved SSCs to simulate the SSCs in the Hangzhou Bay. When the adjoint data assimilation and the penalty function method are simultaneously used, the MAE between the independent check observations and the corresponding simulated SSCs is just 9.90 × 10⁻² kg/m³, which is substantially less than that when only the settling velocity is estimated. The MAE is also considerably less than that when the four model parameters are estimated to be without using the penalty function method. This study indicates that the adjoint data assimilation can effectively improve the SSC simulation accuracy, and the penalty function method can limit the variation range of the estimated model parameters to further improve the effect of data assimilation and parameter estimation.