Modelling groundwater levels in an urban coastal aquifer using artificial neural networks

The prediction of groundwater levels in a basin is of immense importance for the management of groundwater resources, especially in coastal regions where the water table fluctuations are to be limited to avoid seawater intrusion. In this paper, an Artificial Neural Network (ANN) methodology is presented to predict groundwater levels in individual wells with one month lead. Groundwater levels were also predicted in neighboring wells using model parameters from the best network of a well. This methodology is applied to an urban coastal aquifer in Andhra Pradesh state, India. The results suggest that the feed forward neural network with Levenberg Marquardt (LM) algorithm is a good choice for predicting groundwater levels in individual wells. Bayesian Regularization (BR) model parameters of Balaji Nagar well are also used successfully to predict groundwater levels in the study area. It was observed that the ANN‐based algorithms were a better choice for the prediction of groundwater levels with limited hydrological parameters. Copyright © 2007 John Wiley & Sons, Ltd.     

Intelligent reservoir operation system based on evolving artificial neural networks

We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.     

南海海盆新生代的构造演化史

南海海盆地的地壳为洋壳，在新生代它经历了大西洋海底扩张的演化历史，海盆中有三个残留的海底扩张中心，并发生过两次海底扩张。第一次海底扩张发生在晚始新斩新世，扩张方向为北西－南东向，产生了南海西北海盆和西南海盆。     

Morphostructure and evolution of the central and Eastern Bransfield Basins (NW Antarctic Peninsula)

The Bransfield Basin is a narrow and elongated active rift basin located between the Antarctic Peninsula and the South Shetland Islands. The Bransfield Basin is composed of three small basins, and two of them, the Central and Eastern Bransfield Basins, were surveyed during a recent cruise (GEBRA 93). The full swath bathymetry coverage as well as the single-channel seismic reflection and magnetic profiles that have been acquired, help us to better understand the morphostructure and recent evolution of the Bransfield Basin. Six large volcanic edifices aligned with the basin axis stick out of the sedimented seafloor of the Central Bransfield Basin. In contrast, the Eastern Bransfield Basin is characterised by four deep troughs displaying a rhombic-shape, and small, scattered volcanic cones located in the southwestern half basin. Seamount volcanism plays an important role in the formation of new crust in the Bransfield Basin. The larger seamounts of the Central Bransfield Basin are located at the intersection of the two main orthogonal sets of faults (longitudinal ENE-WSW and transversal NNW-SSE). Morphological analysis of the seamounts indicates a multi-staged volcano-tectonic construction. The distribution and shape of these edifices suggests that both volcanism and extension are concentrated at the same preferential areas through time. This might be related to the fracturation style of the continental crust. The Central and Eastern Bransfield Basins are very different in morphostructure, volcanism, and sedimentary cover. The Central Bransfield Basin shows evidence of NW-SE extensional faulting and focused active MORB-volcanism interpreted as result of incipient seafloor spreading. The Eastern Bransfield Basin is still in a rifting stage, mainly dominated by a NW-SE extension and some left-lateral strike-slip component probably related to the South Scotia Ridge.J. Acosta, J. Baraza, P. Bart, A.M. Calafat, J.L. Casamor, M. De Batist, G. Ercilla, G. Francés, E. Ramos, J.L. Sanz, and A. Tassone.     

A Comparison Between GEBCO Sheet 5.17 and the International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 1.0

In 1979, the General Bathymetric Chart of the Oceans (GEBCO) published Sheet 5.17 in the Fifth Edition of its series of global bathymetric maps. Sheet 5.17 covered the northern polar region above 64° N, and was for long the authoritative portrayal of Arctic bathymetry. The GEBCO compilation team had access to an extremely sparse sounding database from the central Arctic Ocean, due to the difficulty of mapping in this permanently ice covered region. In the past decade, there has been a substantial increase in the database of central Arctic Ocean bathymetry, due to the declassification of sounding data collected by US and British Navy nuclear submarines, and to the capability of modern icebreakers to measure ocean depths in heavy ice conditions. From these data sets, evidence has mounted to indicate that many of the smaller (and some larger) bathymetric features of Sheet 5.17 were poorly or wrongly defined. Within the framework of the project to construct the International Bathymetric Chart of the Arctic Ocean (IBCAO), all available historic and modern data sets were compiled to create a digital bathymetric model. In this paper, we compare both generally and in detail the contents of GEBCO Sheet 5.17 and version 1.0 of IBCAO, two bathymetric portrayals that were created more than 20 years apart. The results should be helpful in the analysis and assessment of previously published studies that were based on GEBCO Sheet 5.17. Ron Macnab: Retired.     

新的组合激活函数BP网络模型研究

作者提出了一种新的 BP神经网络模型 ,其隐层激活函数采用中心参数可调的 Gaussian函数 ,输出层采用斜度可调的 Sigmoid函数 ,从而神经元具有了更强的信息存储、处理能力。由于采用组合函数 ,将 Gaussian函数良好的局部性和 Sigmoid函数良好的全局性相结合 ,提高了神经网络的收敛速度。几个典型实验的结果表明 ,与传统 BP网络模型相比 ,新网络模型在学习能力和泛化推广能力方面都有明显提高     

海王星海底长期观测系统的技术分析

美国和加拿大为建立全球最大海洋观测网而联合开展的海王星计划被誉为人类的水下“哈勃”。文中首先介绍了海王星计划的由来与背景,然后分析了其基础架构及实现的关键技术,并对我国海底观测技术的发展提出了建议。     

海洋监测传感器网络概念与应用探讨

通过介绍国外在军用和民用领域海洋监测传感器网络的应用情况,结合我国海洋监测技术发展的现状,分析了传感器网络在海洋监测中应用的概念和内容,并对应用技术研究问题进行了探讨。     

Detailed seafloor geomorphology of the western region of the North Yellow Sea,China: The result of Holocene erosional and depositional processes sculpting the offshore continental shelf

High-resolution multi-beam/single-beam bathymetric data and seismic profiling data from the latest surveys are used to map and interpret the detailed seafloor geomorphology of the western region of the North Yellow Sea (NYS), China. The mapping area covers 156 410 km2, and incorporates a flat shelf plain, subaqueous accumulation shoals, tidal scouring troughs, and tidal sand ridge groups. Offshore areas with water depths less than 50 m in the western region of the NYS are mainly covered by thick, loose sediments, forming wide spread accumulation geomorphological features; these include the Liaodong Peninsula subaqueous accumulation system containing shoals and rugged scouring troughs, and the large mud wedge of the Shandong Peninsula. In the central part of the NYS, there is a relatively flat residual shelf plain with coarser sediment deposits. This flat shelf plain has a water depth larger than 50 m and a thin layer of sediment, on which there is a large pockmark field caused by seafloor seepage. These geomorphological structures indicate that modern sedimentary processes are the main driving force controlling the sculpture of the current seafloor surface landform. Extensive strong tidal current systems and abundant sediment sources provide the critical external forces and essential conditions for the formation of seafloor geomorphology. The tectonic basement controls the macroscopic morphological shape of the NYS, but is reflected very little in the seafloor geomorphic elements. Our results provide a detailed seafloor geomorphological map of the western region of the NYS, an area that has not previously mapped and also provide a scientific framework for further research into offshore seafloor geomorphology, shelf sedimentary processes, and submarine engineering construction in this region.     

基于复杂网络的海洋涡旋移动特征研究——以南海为例

海洋涡旋作为一种快速连续变化的海洋现象,如何分析和挖掘其移动特征成为当前海洋涡旋定量研究的重点。本文引入空间数据挖掘的社区网络划分方法,将涡旋过程看作复杂的移动网络,对涡旋移动的聚集性特征进行探索和分析。首先,以网格为统计单元对1992-2011年近20年南海海洋涡旋移动数据进行组织,基于图论模型构建了涡旋瞬时移动（TP）,涡旋移动起止点（OD）,涡旋最小描述距离的特征点移动网（MDL）和涡旋过程移动再生数据（RSP）4种状态的海洋涡旋的移动网络图;其次,采用基于快速模块度优化的区域划分方法分别得到4种状态下涡旋移动的聚集性区域;最后,利用弦图对区域内和区域间涡旋移动规律进行了可视化分析,发现海洋涡旋的RSP数据能够弥补原始涡旋移动数据在区域划分方法中呈现的数量不足的问题,能够在足够数据量的情况下,有效地发现从起点到终点的主要移动通道和涡旋移动的聚集性区域,这些区域反映了南海涡旋从其产生、发展到结束整个演化过程的聚集性特征。