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In recent years, noticeable subsidence depressions have occurred along the coastal zone of the Yellow River Delta. In some coastal areas, the average annual subsidence varies from tens of millimeters to hundreds of millimeters. Although some studies have discovered a significant land subsidence funnel in the coastal zone of the Yellow River Delta, it has rarely been reported in recent years. Using Sentinel-1A/1B images from the last five years and permanent scatterers interferometric synthetic aperture radar technology, we found a typical subsidence bowl in the northeastern part of the delta, with a cumulative settlement of nearly 1 m over five years. In addition, we used the approach of soil mechanics to simulate the settlement of confined brine layers with different thicknesses under drainage conditions. We found that the 15 m thick confined aquifer can produce 1 m of settlement for every 15% decrease in water content. The simulation results explain the large settlement of the brine industrial area. This study can provide guidance for brine mining in the future. If we continue to overexploit underground brine, there will be more severe land subsidence in the delta in the future. [ABSTRACT FROM AUTHOR]

The Yellow River Delta, which is the second-largest delta in China, has experienced varying degrees of land subsidence since the late 1970s. Although recent studies have identified the natural consolidation and compaction of sediment among the most important contributors to geologic processes, their processes have rarely been quantified. We estimated the sediment compaction over different time ranges to determine the temporal evolution of subsidence parameters (i.e., cumulative compaction). Estimates of primary consolidation, secondary consolidation, and the degree of consolidation in 152 boreholes revealed the spatial–temporal characteristics of sediment compaction and consolidation using geotechnical parameters collected from 152 boreholes, soil mechanics equations and the Kriging interplolation method. In addition, these estimates were partially constrained and cross-validated using the interferometric synthetic aperture radar (InSAR) results from early 2007 to late 2010 which were provided in a previous study. By performing a comparison analysis between theoretical evaluations of compaction for borehole data and InSAR observations, we were able to quantify subsidence due to sediment compaction. The comparison results suggest that the theoretical solutions agreed well with the measurements recorded by the well-validated, advanced InSAR method and that the deviations between the InSAR technique and geotechnical evaluations ranged from −22 to 3 mm. The results reveal that the land subsidence of the chosen borehole sites during the investigative period was dominated by the primary consolidation and compaction of sediment. The underprediction of subsidence may be explained by fluid withdrawal, oil exploitation and engineering construction. To speculate, more geological disasters may occur if the current subsidence condition extends into the future. [ABSTRACT FROM AUTHOR]

The power law particle size distribution (PSD) slope parameter is commonly used to characterize sediment fluxes, resuspension, aggregates, and settling rates in coastal and estuarine waters. However, particle size distribution metrics are also very useful for understanding sediment source and dynamic processes. In this study, a method was proposed to employ the particle size parameters commonly used in sedimentary geology (average particle size (ø), sorting, skewness, and kurtosis) as indicators of changes in sediment dynamic processes, and MODIS images were used to estimate these parameters. The particle size parameters were estimated using a Mie scattering model, Quasi-Analytical Algorithm (QAA) analysis algorithm, and least squares QR decomposition (LSQR) solution method based on the relationship between the power law distribution of the suspended particles and their optical scattering properties. The estimates were verified by field measurements in the Yellow Sea and Bohai Sea regions of China. This method provided good estimates of the average particle size (ø), sorting, and kurtosis. A greater number of wavebands (39) was associated with more accurate particle size distribution curves. Furthermore, the method was used to monitor changes in suspended particulate matter in the vicinity of the Heini Bay of China before and after the passage of a strong storm in August 2011. The particle size parameters represented the influence of a strong typhoon on the distribution of the near-shore sediment and, together with the PSD slope, comprehensively reflected the changes in the near-shore suspended particulate matter. This method not only established the relationship between remote sensing monitoring and the historical sediment record, it also extends the power law model to the application of sediment source and dynamic processes in coastal waters. [ABSTRACT FROM AUTHOR]

Islands are one of the most sensitive interfaces between global changes and land and sea dynamic effects, with high sensitivity and low stability. Therefore, under the dynamic coupling effect of human activities and frequent natural disasters, the vulnerability of the ecological environment of islands shows the characteristics of complexity and diversity. For the protection of island ecosystems, a system for the assessment of island ecosystems and studies on the mechanism of island ecological vulnerability are highly crucial. In this study, the North and South Changshan Islands of China were selected as the study area. Considering various impact factors of island ecological vulnerability, the geographical information systems (GIS) spatial analysis, field surveys, data sampling were used to evaluate island ecological vulnerability. The Bayesian network model was used to explore the impact mechanism of ecological vulnerability. The results showed that the ecological vulnerability of the North Changshan Island is higher than that of the South Changshan Island. Among all the indicators, the proportion of net primary productivity (NPP) and the steep slope has the strongest correlation with ecological vulnerability. This study can be used as references in the relevant departments to formulate management policies and promote the sustainable development of islands and their surrounding waters.