基于ZY-3遥感影像的不同地貌水边线提取方法

水边线的精确提取对于沿海地区的经济开发和海域的使用管理具有重要意义。以雷州半岛东北部为研究区域,利用2017年资源三号(ZY-3)卫星数据为数据源,基于不同海岸地貌特征为划分依据,运用阈值分割法、神经元网络分类法和面向对象法对多光谱数据的人工海岸、砂质海岸、淤泥质海岸和红树林海岸进行水边线提取。通过目视解译提取融合图像的海岸线为基线,将提取的水边线与基线进行定性、定量分析。研究结果表明,对于人工岸线,神经元网络分类法最优,均方根误差为6.4m;对于砂质岸线,阈值分割法最优,均方根误差为5.4m;对于淤泥质及红树林岸线,面向对象法最优,均方根误差分别为23.3m和15.2m。该研究对于不同岸线的提取具有重要的借鉴和指导意义。     

Numerical modeling of flow characteristics in a rotating annular flume

A rotating annular flume (RALF) has been constructed at the Center of Coastal and Land-Margin Research (CCALMR) to study the biogeochemistry of sediment–water interfaces. The flume was designed to allow for evolving, integrated measurements of physical, chemical, and biological parameters, as often as possible in a real-time, computer-controlled mode. Several numerical models have or are being developed/applied to provide a virtual representation of the flume, with the dual objective of assisting the design of experiments and of assessing our level of understanding of processes and process interactions. We will concentrate here on the characterization of the flow in the flume, a basic but interestingly complex problem. The operational challenge is to minimize secondary circulation and lateral variability of shear stress, factors that prevent the flume flow to match the idealized concept of an endless channel flow. Satisfactory minimization of these factors can be achieved by allowing both the top and the bottom rings of the flume to rotate in contrary directions, a concept introduced by earlier research efforts and verified in RALF via Acoustic Doppler Velocimeter (ADV) measurements and 3D numerical modeling. Once logistics (e.g., in the form of the size of the ADV's sampling volume and of the vertical discretization of the numerical grids) are appropriately handled, observations and model results show good agreement. This agreement legitimates the use of the model as a design and investigative tool, in particular to define optimal rotation ratios of the top and bottom rings. The ratios that minimize secondary flow and lateral variability of shear stress are distinct. This is a logical (generating mechanisms are different) but often not recognized aspect of the operation of annular flumes.     

渤海重现期波高的数值计算

利用RAMS大气模式给出的20年风场资料,利用SWAN近海波浪模式对渤海海域的波浪进行了20 a数值计算.通过与一般过程和大风过程的实测资料的对比后发现.波浪模拟值与实潮值符合地较好,SWAN模式适合渤海海域波浪的计算。通过分析发现.辽东湾常浪向为SSW。强浪向为SSW;渤海中部常浪向为S,强浪向为NE;渤海海峡常浪向为NNW,强浪向为NNW;莱州湾常浪向为S,强浪向为NNE;渤海湾常浪向为S.强浪向为NE。渤中偏东南海域(38°～39°N,119.5°～120.5°E)多年一遇有效波高最大.其中百年一遇有效波高最大值达到6.7m。     

A modeling study of coastal inundation induced by storm surge,sea-level rise,and subsidence in the Gulf of Mexico

The northern coasts of the Gulf of Mexico (GoM) are highly vulnerable to the direct threats of climate change, such as hurricane-induced storm surge, and such risks are exacerbated by land subsidence and global sea-level rise. This paper presents an application of a coastal storm surge model to study the coastal inundation process induced by tide and storm surge, and its response to the effects of land subsidence and sea-level rise in the northern Gulf coast. The unstructured-grid finite-volume coastal ocean model was used to simulate tides and hurricane-induced storm surges in the GoM. Simulated distributions of co-amplitude and co-phase lines for semi-diurnal and diurnal tides are in good agreement with previous modeling studies. The storm surges induced by four historical hurricanes (Rita, Katrina, Ivan, and Dolly) were simulated and compared to observed water levels at National Oceanic and Atmospheric Administration tide stations. Effects of coastal subsidence and future global sea-level rise on coastal inundation in the Louisiana coast were evaluated using a “change of inundation depth” parameter through sensitivity simulations that were based on a projected future subsidence scenario and 1-m global sea-level rise by the end of the century. Model results suggested that hurricane-induced storm surge height and coastal inundation could be exacerbated by future global sea-level rise and subsidence, and that responses of storm surge and coastal inundation to the effects of sea-level rise and subsidence are highly nonlinear and vary on temporal and spatial scales.