排序方式： 共有10条查询结果，搜索用时 15 毫秒
1
1.
An oil spill-food chain interaction model, composed of a multiphase oil spill model (MOSM) and a food chain model, has been developed to assess the probable impacts of oil spills on several key marine organisms (phytoplankton, zooplankton, small fish, large fish and benthic invertebrates). The MOSM predicts oil slick thickness on the water surface; dissolved, emulsified and particulate oil concentrations in the water column; and dissolved and particulate oil concentrations in bed sediments. This model is used to predict the fate of oil spills and transport with respect to specific organic compounds, while the food chain model addresses the uptake of toxicant by marine organisms. The oil spill-food chain interaction model can be used to assess the environmental impacts of oil spills in marine ecosystems. The model is applied to the recent Evoikos-Orapin Global oil spill that occurred in the Singapore Strait. 相似文献
2.
Wu Qing Luu Quang-Hung Tkalich Pavel Chen Ge 《Theoretical and Applied Climatology》2018,132(1-2):375-385
Theoretical and Applied Climatology - Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical... 相似文献
3.
4.
ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems 总被引：1，自引：0，他引：1
The occurrences of increased atmospheric nitrogen deposition (ADN) in Southeast Asia during smoke haze episodes have undesired consequences on receiving aquatic ecosystems. A successful prediction of episodic ADN will allow a quantitative understanding of its possible impacts. In this study, an artificial neural network (ANN) model is used to estimate atmospheric deposition of total nitrogen (TN) and organic nitrogen (ON) concentrations to coastal aquatic ecosystems. The selected model input variables were nitrogen species from atmospheric deposition, Total Suspended Particulates, Pollutant Standards Index and meteorological parameters. ANN models predictions were also compared with multiple linear regression model having the same inputs and output. ANN model performance was found relatively more accurate in its predictions and adequate even for high-concentration events with acceptable minimum error. The developed ANN model can be used as a forecasting tool to complement the current TN and ON analysis within the atmospheric deposition-monitoring program in the region. 相似文献
5.
Among the semi-enclosed basins of the world ocean, the South China Sea (SCS) is unique in its configuration as it lies under the main southwest-northeast pathway of the seasonal monsoons. The northeast (NE) monsoon (November–February) and southwest (SW) monsoon (June–August) dominate the large-scale sea level dynamics of the SCS. Sunda Shelf at the southwest part of SCS tends to amplify Sea Level Anomalies (SLAs) generated by winds over the sea. The entire region, bounded by Gulf of Thailand on the north, Karimata Strait on the south, east cost of Peninsular Malaysia on the west, and break of Sunda Shelf on the east, could experience positive or negative SLAs depending on the wind direction and speed. Strong sea level surges during NE monsoon, if coincide with spring tide, usually lead to coastal floods in the region. To understand the phenomena, we analyzed the wind-driven sea level anomalies focusing on Singapore Strait (SS), laying at the most southwest point of the region. An analysis of Tanjong Pagar tide gauge data in the SS, as well as satellite altimetry and reanalyzed wind in the region, reveals that the wind over central part of SCS is arguably the most important factor determining the observed variability of SLAs at hourly to monthly scales. Climatological SLAs in SS are found to be positive, and of the order of 30 cm during NE monsoon, but negative, and of the order of 20 cm during SW monsoon. The largest anomalies are associated with intensified winds during NE monsoon, with historical highs exceeding 50 cm. At the hourly and daily time-scales, SLA magnitude is correlated with the NE wind speed over central part of SCS with an average time lag of 36–42 h. An exact solution is derived by approximating the elongated SCS shape with one-dimensional two-step channel. The solution is utilized to derive simple model connecting SLAs in SS with the wind speeds over central part of SCS. Due to delay of sea level anomaly in SS with respect to the remote source at SCS, the simplified solutions could be used for storm surge forecast, with a lead time exceeding 1 day. 相似文献
6.
7.
The forced and free response of the South China Sea to the large-scale monsoon system 总被引：1，自引：0，他引：1
Non-tidal sea level anomalies (SLAs) can be produced by many different dynamical phenomena over many time scales, and they can induce serious damages in coastal regions especially during extreme events. In this work, we focus on the SLAs in the South China Sea (SCS) to understand whether and how they can be related to the large-scale, seasonal monsoon system which dominates the SCS circulation and dynamics. We have two major objectives. The first one is to understand whether the NE (winter) and SW (summer) monsoons can be responsible for the persistent SLAs, both positive and negative, observed at the SCS ends along the main monsoon path. The second objective is to understand the SCS response as a free system upon onset/relaxation or sudden changes in the forcing wind. It is well known that sudden changes in the forcing mechanism induce free oscillations, or seiches, in closed, semi-enclosed basins and harbors, and we want to identify the possible seiche modes of the SCS. To our knowledge, these two objectives have not been previously addressed. We address these objectives both through observational analysis and modeling simulations. Multi-year tide-gauge data from stations along the coastal regions of the SCS are analyzed examining their spatial correlations. Strong negative correlations are found between the northeast and southwest stations at the two ends of the SCS under the path of the NE/SW monsoons. They correspond to wind-induced positive/negative sea level set-ups lasting for the entire monsoon season and changing sign from winter to summer. Short periods of negative correlations are also found between the SLAs at eastern and western stations during El Niño years in which the monsoons are weaker and have an enhanced E/W component inducing corresponding sea level set-ups. The tide-gauge station at Tanjong Pagar at the southwest SCS end near Singapore is chosen to study four extreme SLAs events in the observational record during 1999. Modeling simulations are carried out to reproduce them. The observed and modeled extreme SLAs agree quite well, both in the amplitude of the highest peak and in phase. Three main peaks are identified in the observational energy spectrum of the de-tided SLAs at the same station in 1999. Using Merian’s formula to evaluate the periods of seiches in idealized basins Wilson (Adv Hydrosci 8:1–94, 1972) the first two peaks (24.4 h and 11.9 h) are found to correspond to the first two seiche modes in the direction of the main, longer axis of the SCS. The third peak (8.5 h) is found to correspond to the seiche in the transversal, shorter axis. Finally, modeling simulations are carried out by suddenly dropping a circular bump of water in the quiescent basin at different locations to excite the seiches. The periods of the modeled peaks agree quite well with the observational ones, the first two periods being actually identical. 相似文献
8.
An ANN application for water quality forecasting 总被引：12，自引：0，他引：12
Rapid urban and coastal developments often witness deterioration of regional seawater quality. As part of the management process, it is important to assess the baseline characteristics of the marine environment so that sustainable development can be pursued. In this study, artificial neural networks (ANNs) were used to predict and forecast quantitative characteristics of water bodies. The true power and advantage of this method lie in its ability to (1) represent both linear and non-linear relationships and (2) learn these relationships directly from the data being modeled. The study focuses on Singapore coastal waters. The ANN model is built for quick assessment and forecasting of selected water quality variables at any location in the domain of interest. Respective variables measured at other locations serve as the input parameters. The variables of interest are salinity, temperature, dissolved oxygen, and chlorophyll-a. A time lag up to 2Deltat appeared to suffice to yield good simulation results. To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The results show the ANN's great potential to simulate water quality variables. Simulation accuracy, measured in the Nash-Sutcliffe coefficient of efficiency (R(2)), ranged from 0.8 to 0.9 for the training and overfitting test data. Thus, a trained ANN model may potentially provide simulated values for desired locations at which measured data are unavailable yet required for water quality models. 相似文献
9.
Seasonal and inter-annual variability of the mixed layer temperature in the Southern South China Sea (SSCS) is investigated using a regional ocean circulation model simulation. The mixed layer depth (MLD) over the SSCS exhibits a strong seasonal signal with deeper MLDs during the northeast and southwest monsoons. The main factor that drives the mixed layer temperature variation in the SSCS is the air-sea heat fluxes, with vertical ocean processes acting as a relatively weak negative feedback. In general, the budget analysis demonstrates a net balance between the vertical ocean processes and surface heat flux during the pre-monsoon and southwest monsoon. Northeast monsoon period is noted by an offsetting of surface heat flux, horizontal and vertical ocean processes. The first dominant mode of mixed layer temperature inter-annual variability in the SSCS shows significant correlation (0.34) with the El Nino phenomenon in the Pacific Ocean and is best correlated (0.67) with a lag of 5 months. 相似文献
10.
Vertical mixing of oil droplets by breaking waves 总被引：2，自引：0，他引：2
Oil spilled on a sea surface can be dispersed by a variety of natural processes, of which the influence of breaking waves is dominant. Breaking waves are able to split the slick into small droplets, facilitating oil mixing in the water column. Vertical dynamics of the droplets plays a major role in the oil mass exchange between the slick and the water column. In this paper a mathematical model of oil droplet mixing by breaking waves is developed. The model uses a kinetic approach to describe the vertical exchange of the droplets at the interface between the slick and the water column. The majority of the coefficients and parameters are conveniently combined into a single "mixing factor". The model is verified using sensitivity analysis and empirical formulae of other authors. The model permits a rapid estimation of the amount of dispersed oil under the breaking waves. The ultimate goal of the research is to parameterise influence of breaking waves on vertical mixing of oil droplets to be used in a general 3-D oil spill model. 相似文献
1