Coastal marine sediment, air and seawater samples were collected at six sampling stations in the Eastern Mediterranean Sea distant from pollutant point sources. All sediment samples were analyzed to determine polycyclic aromatic hydrocarbon (PAH), black carbon (BC) and organic carbon (OC) contents. The PAH contents of gaseous and seawater samples of the study were determined in order to evaluate the role of air–sea exchange as PAH nonpoint source to the marine sediments. The average concentration of the total PAHs (∑PAHs) in the sediments varied from 2.2 to 1056.2 ng g−1 dry weight. The average BC and OC contents varied from 0.3 to 5.6 and from 2.9 to 21.4 mg g−1 dry weight, respectively. ∑PAH concentration in the marine atmosphere varied from 20.0 to 83.2 ng m−3. Air–water exchange flux (FA–W) estimation has indicated air transport as a significant source of PAHs to pristine marine sediments of Eastern Mediterranean. In addition, the significant correlation between the PAHs and the organic and soot carbon content further suggests the importance of atmospheric input of PAHs to the sediments. 相似文献
Reservoir characterization involves describing different reservoir properties quantitatively using various techniques in spatial variability. Nevertheless, the entire reservoir cannot be examined directly and there still exist uncertainties associated with the nature of geological data. Such uncertainties can lead to errors in the estimation of the ultimate recoverable oil. To cope with uncertainties, intelligent mathematical techniques to predict the spatial distribution of reservoir properties appear as strong tools. The goal here is to construct a reservoir model with lower uncertainties and realistic assumptions. Permeability is a petrophysical property that relates the amount of fluids in place and their potential for displacement. This fundamental property is a key factor in selecting proper enhanced oil recovery schemes and reservoir management. In this paper, a soft sensor on the basis of a feed‐forward artificial neural network was implemented to forecast permeability of a reservoir. Then, optimization of the neural network‐based soft sensor was performed using a hybrid genetic algorithm and particle swarm optimization method. The proposed genetic method was used for initial weighting of the parameters in the neural network. The developed methodology was examined using real field data. Results from the hybrid method‐based soft sensor were compared with the results obtained from the conventional artificial neural network. A good agreement between the results was observed, which demonstrates the usefulness of the developed hybrid genetic algorithm and particle swarm optimization in prediction of reservoir permeability. 相似文献
AbstractArtificial neural networks (ANNs) have recently been used to predict the hydraulic head in well locations. In the present work, the particle swarm optimization (PSO) algorithm was used to train a feed-forward multi-layer ANN for the simulation of hydraulic head change at an observation well in the region of Agia, Chania, Greece. Three variants of the PSO algorithm were considered, the classic one with inertia weight improvement, PSO with time varying acceleration coefficients (PSO-TVAC) and global best PSO (GLBest-PSO). The best performance was achieved by GLBest-PSO when implemented using field data from the region of interest, providing improved training results compared to the back-propagation training algorithm. The trained ANN was subsequently used for mid-term prediction of the hydraulic head, as well as for the study of three climate change scenarios. Data time series were created using a stochastic weather generator, and the scenarios were examined for the period 2010–2020.
Editor Z.W. Kundzewicz; Associate editor L. SeeCitation Tapoglou, E., Trichakis, I.C., Dokou, Z., Nikolos, I.K., and Karatzas, G.P., 2014. Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization. Hydrological Sciences Journal, 59(6), 1225–1239. http://dx.doi.org/10.1080/02626667.2013.838005相似文献
Spain is a low-to-moderate seismicity area with relatively low seismic hazard. However, several strong shallow earthquakes have shaken the country causing casualties and extensive damage. Regional seismicity is monitored and surveyed by means of the Spanish National Seismic Network, maintenance and control of which are entrusted to the Instituto Geográfico Nacional. This array currently comprises 120 seismic stations distributed throughout Spanish territory (mainland and islands). Basically, we are interested in checking the noise conditions, reliability, and seismic detection capability of the Spanish network by analyzing the background noise level affecting the array stations, errors in hypocentral location, and detection threshold, which provides knowledge about network performance. It also enables testing of the suitability of the velocity model used in the routine process of earthquake location. To perform this study we use a method that relies on P and S wave travel times, which are computed by simulation of seismic rays from virtual seismic sources placed at the nodes of a regular grid covering the study area. Given the characteristics of the seismicity of Spain, we drew maps for ML magnitudes 2.0, 2.5, and 3.0, at a focal depth of 10 km and a confidence level 95 %. The results relate to the number of stations involved in the hypocentral location process, how these stations are distributed spatially, and the uncertainties of focal data (errors in origin time, longitude, latitude, and depth). To assess the extent to which principal seismogenic areas are well monitored by the network, we estimated the average error in the location of a seismic source from the semiaxes of the ellipsoid of confidence by calculating the radius of the equivalent sphere. Finally, the detection threshold was determined as the magnitude of the smallest seismic event detected at least by four stations. The northwest of the peninsula, the Pyrenees, especially the westernmost segment, the Betic Cordillera, and Tenerife Island are the best-monitored zones. Origin time and focal depth are data that are far from being constrained by regional events. The two Iberian areas with moderate seismicity and the highest seismic hazard, the Pyrenees and Betic Cordillera, and the northwestern quadrant of the peninsula, are the areas wherein the focus of an earthquake is determined with an approximate error of 3 km. For ML 2.5 and ML 3.0 this error is common for almost the whole peninsula and the Canary Islands. In general, errors in epicenter latitude and longitude are small for near-surface earthquakes, increasing gradually as the depth increases, but remaining close to 5 km even at a depth of 60 km. The hypocentral depth seems to be well constrained to a depth of 40 km beneath the zones with the highest density of stations, with an error of less than 5 km. The ML magnitude detection threshold of the network is approximately 2.0 for most of Spain and still less, almost 1.0, for the western sector of the Pyrenean region and the Canary Islands. 相似文献
A statistical analysis of the cosmic-ray intensity (CR) daily means, registered at three Neutron Monitor stations with different cut-off rigidities (Deep River, Climax and Alma-Ata), as well as, of the solar hard X-ray flares fluence recorded by Venera-13, -14 space-probes, has been performed for the time interval 1981–1983. Various methods of time series spectrum analysis, such as Fast Fourier Analysis (FFT) and Maximum Entropy (MESA), accompanied by appropriate statistical tests, have been employed to detect periodicities, while the method of Successive Approximations (SA) is used independently in order to define the amplitude and the phase of each fluctuation. New short-term periodicities of 100, 70, 50 and 32 days, in addition to the known ones of 152, 27 and 14 days, appeared in cosmic ray data. During this particular time interval, similar spectral behaviour has been reported in the solar hard X-ray flares data. The influence of the solar hard X-ray flares variability in the energy range 50–500 keV, expressed by their fluence values, upon the cosmic-ray modulation, is discussed. 相似文献
Boundary-Layer Meteorology - Lagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations... 相似文献
This paper presents an application of the rock engineering system (RES) in an attempt to assess the proper landslide parameters and estimate the instability index, using two disastrous landslides in Greece which took place in Panagopoula (1971) and Malakasa (1995). RES has been developed by Hudson (Rock engineering systems: theory and practice. Ellis Horwood Limited, 1992) to determine interaction of a number of parameters in rock engineering design and calculate instability index for rock slopes. In this paper, an attempt is made to prove, how RES can be implemented in large-scale instability areas where natural slopes are associated with a variety of geomaterials (soils, rocks, weathering mantle, etc.), by selecting each time the most appropriate parameters that are relevant to the ad hoc potential slope failure and which can be quantified easiest than those of time and money consuming ones. RES approach allows the utilization of those parameters which are particularly active at the site, evaluates the importance of their interactions, taking into account the particular problems at any investigated site. The instability index for both study areas were calculated and found 89.47 for Panagopoula site and 81.59 for Malakasa (out of 100). According to the classification for landslide susceptibility by Brabb et al. (Landslide susceptibility in San Mateo County, California, 1972), both the examined case studies are classified as landslides, approving their existence as two serious slope failures. Thus, RES could be a simple and efficient tool in calculating the instability index and consequently in getting the prognosis of a potential slope failure in landslide susceptible areas, for land use and development planning processes. 相似文献
France experiences catastrophic floods on a yearly basis, with significant societal impacts. In this study, we use multiple sources (insurance datasets, scientific articles, satellite data, and grey literature) to (1) analyze modern flood disasters in the PACA Region; (2) discuss the efficiency of French public policy instruments; (3) perform a SWOT analysis of French flood risk governance (FRG); and (4) suggest improvements to the FRG framework. Despite persistent government efforts, the impacts of flood events in the region have not lessened over time. Identical losses in the same locations are observed after repeated catastrophic events. Relative exposure to flooding has increased in France, apparently due to intense urbanization of flood-prone land. We suggest that the French FRG could benefit from the following improvements: (1) regular updates of risk prevention plans and tools; (2) the adoption of a build back better logic; (3) taking undeclared damages into account in flood risk models; (4) better communication between the actors at the different steps of each cycle (preparation, control, organization, etc.); (5) better communication between those responsible for risk prevention, emergency management, and disaster recovery; (6) an approach that extends the risk analysis outside the borders of the drainage basin; and (7) increased participation in FRG from local populations.