Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey

In the last decades, landslide hazard assessment has attracted many researchers' attention. A number of parameters are suggested to be responsible to quantitatively explain the mechanism of landslides; many of these parameters are very important and factual. However, some data types and models are site-specific and could not be applied to different locations. Furthermore, the data stored in continuous parameter maps are divided into a number of classes arbitrarily, depending on the vision of the expert. Basically, this division controls the result of bivariate analysis. Besides, the responsible portion of the parameter map controlling the mechanism is also weighted arbitrarily. Based on these two facts, the class boundaries put a prejudice on the produced susceptibility/hazard maps, which result in dependence on the knowledge of the user rather than being dependent on the data and the fact itself. The aim of this study is to refine the previously defined methods in a more data-dependent trend. To achieve this goal, two new concepts: seed cells and percentile maps are introduced. Seed cells are the zones that are considered to represent the best undisturbed morphological decision rules (conditions before landslide occurs) and would be achieved by adding a buffer zone to the crown and flank areas of the landslide. To quantitatively classify the input parameter maps, the data distributions of seed cells in the parameter maps are divided into a number of classes on the basis of their distribution's percentile break-points upon which the parameter maps are directly dependent on the seed cell distributions, hence to the data itself.     

Recent landslide activity in Manaihan,East Belgium

Past landslides have been recognized in the Battice area in E-Belgium. In contrast to the other inactive landslides, the Manaihan landslide responded immediately to heavy rainfall events in the last two decades. This study aims to map its spatial extent and the dominant surface features; to measure surface displacement using GPS; to investigate subsurface structure with Cone penetration test (CPT) and corings; and to determine the depth of the shear surface by inclinometers. Results show a partial landslide reactivation. Surface velocities range between 20 and 40 cm/year and are strongly dependent on winter rainfall. CPT results give clear boundaries between the landslide mass and the undisturbed bedrock in the head scarp. Distinct shear surfaces have been determined with displacement rates up to 15.8 mm in 21 days. Further research should apply geophysical methods for two-dimensional information on the ground, investigate geotechnical properties of the landslide mass, model slope instability, and determine the influence of a sewage pipe crossing the central landslide mass as a potential cause for landslide activity.     

Estuary/ocean exchange and tidal mixing in a Gulf of Maine Estuary: A Lagrangian modeling study

A Lagrangian particle method embedded within a 2-D finite element code, is used to study the transport and ocean–estuary exchange processes in the well-mixed Great Bay Estuarine System in New Hampshire, USA. The 2-D finite element model, driven by residual, semi-diurnal and diurnal tidal constituents, includes the effects of wetting and drying of estuarine mud flats through the use of a porous medium transport module. The particle method includes tidal advection, plus a random walk model in the horizontal that simulates sub-grid scale turbulent transport processes. Our approach involves instantaneous, massive [O(500,000)] particle releases that enable the quantification of ocean–estuary and inter-bay exchanges in a Markovian framework. The effects of the release time, spring–neap cycle, riverine discharge and diffusion strength on the intra-estuary and estuary–ocean exchange are also investigated.The results show a rather dynamic interaction between the ocean and the estuary with a fraction of the exiting particles being caught up in the Gulf of Maine Coastal Current and swept away. Three somewhat different estimates of estuarine residence time are calculated to provide complementary views of estuary flushing. Maps of residence time versus release location uncover a strong spatial dependency of residence time within the estuary that has very important ramifications for local water quality. Simulations with and without the turbulent random walk show that the combined effect of advective shear and turbulent diffusion is very effective at spreading particles throughout the estuary relatively quickly, even at low (1 m²/s) diffusivity. The results presented here show that a first-order Markov Chain approach has applicability and a high potential for improving our understanding of the mixing processes in estuaries.     

海洋测量成果质量控制的探讨

结合实际测量过程中出现的问题,对提高海洋测量成果质量的几个关键环节进行了思考,从标准规范、规章制度到人员素质等三个方面提出了相应的建议,对于提高技术人员的基本素质、严格执行标准规范和规章制度、全面提高测量成果质量具有一定的参考意义。     

机载激光测深技术

首先基于海水的光学特性介绍了机载激光测深原理,然后根据国内外的研究现状介绍了机载激光测深系统的性能指标和系统构成,最后介绍了在海底地形测量、障碍物探测、近岸海洋工程建设等方面的应用。为从事机载激光测深系统研发和应用的技术人员提供相关原理和背景参考。     

Validation of ship manoeuvring models using metamodels

This paper describes how simplified auxiliary models—metamodels—can be used to create benchmarks for validating ship manoeuvring simulation models. A metamodel represents ship performance for a limited range of parameters, such as rudder angles and surge velocity. In contrast to traditional system identification methods, metamodels are identified from multiple trial recordings, each containing data on the ship’s inherent dynamics (similar for all trials) and random disturbances such as environmental effects and slightly different loading conditions. Thus, metamodels can be used to obtain these essential data, where simple averaging is not possible. In addition, metamodels are used to represent a ship’s behaviour and not to obtain physical insights into ship dynamics. The experimental trials used for the identification of metamodels can be found in in-service recorded data. After the metamodel is identified, it is used to simulate trials without substantial deviations from the ship state parameters used for the identification. Subsequently, the predictions of the metamodels are compared with the predictions of a tested manoeuvring simulation model. We present two case studies to demonstrate the application of metamodels for moderate turning motions of two ships.     

A singular evolutive extended Kalman filter to assimilate ocean color data in a coupled physical–biochemical model of the North Atlantic ocean

Within the European DIADEM project, a data assimilation system for coupled ocean circulation and marine ecosystem models has been implemented for the North Atlantic and the Nordic Seas. One objective of this project is to demonstrate the relevance of sophisticated methods to assimilate satellite data such as altimetry, surface temperature and ocean color, into realistic ocean models. In this paper, the singular evolutive extended Kalman (SEEK) filter, which is an advanced assimilation scheme where three-dimensional, multivariate error statistics are taken into account, is used to assimilate ocean color data into the biological component of the coupled system. The marine ecosystem model, derived from the FDM model [J. Mar. Res. 48 (1990) 591], includes 11 nitrogen and carbon compartments and describes the synthesis of organic matter in the euphotic zone, its consumption by animals of upper trophic levels, and the recycling of detritic material in the deep ocean. The circulation model coupled to the ecosystem is the Miami isopycnic coordinate ocean model (MICOM), which covers the Atlantic and the Arctic Oceans with an enhanced resolution in the North Atlantic basin. The model is forced with realistic ECMWF ocean/atmosphere fluxes, which permits to resolve the seasonal variability of the circulation and mixed layer properties. In the twin assimimation experiments reported here, the predictions of the coupled model are corrected every 10 days using pseudo-measurements of surface phytoplankton as a substitute to chlorophyll concentrations measured from space. The diagnostics of these experiments indicate that the assimilation is feasible with a reduced-order Kalman filter of small rank (of order 10) as long as a sufficiently good identification of the error structure is available. In addition, the control of non-observed quantities such as zooplankton and nitrate concentrations is made possible, owing to the multivariate nature of the analysis scheme. However, a too severe truncation of the error sub-space downgrades the propagation of surface information below the mixed layer. The reduction of the actual state vector to the surface layers is therefore investigated to improve the estimation process in the perspective of sea-viewing wide field-of-view sensor (SeaWiFS) data assimilation experiments.