Diurnal vertical migration of Cochlodinium polykrikoides during the red tide in Korean coastal sea waters

The diurnal vertical migration of Cochlodinium polykrikoides (C. polykrikoides), which caused a red tide in the Korean coastal waters of the East Sea/Sea of Japan in September 2003, was examined by determining the time-dependent changes in the density of living cells in relation to the depth of the water column. The ascent of this species into the surface layer (depth of water 2 m) occurred during 1400-1500. The descent started at 1600 and a high distribution rate (86%) at 15-20 m was observed at 0300. During the ascent, the cells were widely distributed at each depth level from 0600 hr and at 0800-1100, the cells were primarily distributed in the middle layer (0-6 m). The concentration of dissolved inorganic nitrogen was generally < or = 2.86 micromol l(-1), but at 1400-1500, the concentration in the surface layer reduced to < or = 0.14 micromol l(-1). Moreover, the concentration gradually increased as the depth increased to > or = 5 m. These results showed that the nutrient-consumption rate associated with the proliferation of C. polykrikoides during a red tide is more influenced by the inorganic-nitrogen resources ratherthan the inorganic-phosphorus compounds.     

Evaluation of SWAT sub-daily runoff estimation at small agricultural watershed in Korea

A study was undertaken for the prediction of runoff flow from 0.8 ha field-sized agricultural watershed in South Korea using Soil and Water Assessment Tool (SWAT) sub-daily. The SWAT model with sub-daily configuration predicted flow from the watershed within the range of acceptable accuracy. The SWAT sub-daily simulations were carried out for a total of 18 rainfall events, 9 each for calibration and validation. Overall trend and extent of matching simulated flow for the rainfall events in 2007-2008 with measured data during the calibration process were coefficient of determination (R²) value of 0.88 and Nash and Sutcliffe Efficiency (E_NS) value of 0.88. For validation, R² and E_NS values were 0.9 and 0.84, respectively. Whereas R² and E_NS values for simulation results using daily rainfall data were 0.79 and -0.01, respectively, that were observed to be out of acceptable limits for the model simulation. The importance of higher time resolution (hourly) precipitation records for flow simulation were evaluated by comparing R² and E_NS with 15 min, 2 h, 6 h and 12 h precipitation data, which resulted in lower statistics with increases in time resolution of precipitation data. The SWAT sub-daily sensitivity analysis was performed with the consideration of hydraulic parameter and was found as in the rank order of CN2 (curve number), ESCO (soil evaporation compensation factor), GW_DELAY (ground water delay time), ALPHA_BF ( base flow alpha factor), GWQMN ( a threshold minimum depth of water in the shallow aquifer required for return flow to occur) , REVAPMN (minimum depth of water in shallow aquifer for re-evaporation to occur) , LAT_TIME (lateral flow travel time) respectively. These sensitive parameters were evaluated at 10% higher and lower values of the parameters, corresponding to 70.5% higher and 23.2% lower in simulated flow out from the SWAT model. From the results obtained in this study, hourly precipitation record for SWAT sub-daily with Green-Ampt infiltration method was proven to be efficient for runoff estimation at field sized watershed with higher accuracies that could be efficiently used to develop site-specific Best Management Practices (BMPs) considering rainfall intensity, rather than simply using daily rainfall data.     

PREDICTION OF MEAN ANNUAL FLOWS IN THE FRASER RIVER CATCHMENT,BRITISH COLUMBIA1

ABSTRACT: A method of predicting annual flows is presented and is applied to the Fraser River catchment. Statistical tests show the annual flow records to be stationary and aerially independent and can be adequately approximated by Gaussian distributions. Estimates are made of the Gaussian parameters for each subbasin. The spatial variations of these parameters are described by third order trend surfaces. The fitted surfaces can then be used to predict parameters of ungaged basins using the latitude and longitude of the basin centroids. The predicted parametric values are substituted into the Gaussian distribution to generate flows of various return periods.     

Discrimination of flicker frequency rates in the reptile tuatara (Sphenodon )

By investigating the mechanisms that underlie the perception of environmental cues, we may begin to understand how the sensory system governs behavioral responses. This is the first empirical study to examine learning and visual sensitivity in a reptile species, the tuatara (Sphenodon punctatus). We established a non-intrusive psychophysical method by employing an instrumental paradigm in order to examine discrimination learning and the ability to distinguish different flicker frequencies in the tuatara. Seventeen tuatara were trained under an operant conditioning task to respond to various discriminative stimuli flickering between 2.65 and 65.09 Hz. Tuatara were able to learn the operant task and discriminate between a constant light and flicker frequency rates between 2.65 and 45.61 Hz, but not at 65.09 Hz. We demonstrated a reliable psychophysical method where these reptiles could learn a basic operant task and discriminate visual stimuli in the form of flicker frequency rates. The tuatara’s ability to perceive flickering light is comparable to that of avian, mammalian, and other reptilian species. This method is thus suitable for more comprehensive examinations of vision and additional sensory abilities in other reptiles. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A comprehensive empirical investigation of the relationships among variables of the groupthink model

Although a quarter of a century has passed since Janis proposed his groupthink model in 1972, there is very little consensus among researchers on the validity of the model. This study conducted a comprehensive empirical investigation of Janis's model by including all 24 variables in the research. Data were collected from 64 four‐person ad hoc groups; the group discussion sessions were videotaped and content‐analysed afterwards. Statistical analyses revealed that Janis's predictions about the causal relationship among four groups of variables in the model are only partially correct; when the effects of individual independent variables on the dependent variables were tested, Janis's predictions were confirmed in only two out of 23 cases. Copyright © 2000 John Wiley & Sons, Ltd.     

Identification of black plastics realized with the aid of Raman spectroscopy and fuzzy radial basis function neural networks classifier

To accomplish the effective classifier and secure the accurate classification capabilities of black plastics, a comprehensive design methodology of fuzzy radial basis function neural networks is developed with the aid of principal component analysis and particle swarm optimization. Plastics recycling is the competitive method which can deal with the shortage of natural resource. To recycle and reuse the waste plastics, this study is given as the key issue to identify and classify waste plastics by resin type such as polyethylene terephthalate, polypropylene, polystyrene, etc. To complement the weak points of recognition and classification of the near-infrared radiation equipment, Raman spectroscopy is used to obtain qualitative as well as quantitative analysis of black plastics. To improve the identification performance of black plastics, an intelligent computing algorithm such as fuzzy radial basis function neural networks classifier and preprocessing algorithm as principal component analysis are applied to analyze and classify the obtained spectrum of black plastics. Finally, to optimize the structure as well as parameters of fuzzy radial basis function neural networks, particle swarm optimization technique is used. The obtained experimental results show that the proposed network architecture exhibits high classification capabilities in practical applications.     

Managing stormwater for urban sustainability: an evaluation of local comprehensive plans in the Chesapeake Bay watershed region

This study uses a developed plan coding protocol in evaluating the quality of 76 comprehensive plans to examine whether local comprehensive plans have adequately integrated the concepts of sustainable stormwater management. The Chesapeake Bay watershed was chosen for the investigation because degraded stormwater runoff from nearby urban and suburban jurisdictions have critically polluted the watershed. The findings indicate that the majority of local governments have not sufficiently incorporated the sustainable stormwater management principles into their comprehensive plans. Five plan components (factual basis, goals and objectives, inter-organizational cooperation, policies, tools and strategies, and implementation) appear weak in realizing the concepts. The current study concludes by providing policy implications and recommendations to increase awareness and understanding of sustainable stormwater management concepts and to produce better implementation plans that integrate stormwater, ecosystem, and environmental planning comprehensively.     

Assessment of Wastewater Reuse Effects on Nutrient Loads from Paddy Field Using Field-Scale Water Quality Model

CREAMS-PADDY, a modified version of the field-scale CREAMS model, simulates the hydrologic, sediment, and nutrient cycles in paddy fields. The CREAMS-PADDY model was applied to estimate the effects of using wastewater for irrigation on nutrient loads from paddy fields in Republic of Korea. The model was calibrated and validated using data from two rice paddy fields. The coefficient of determination between observed and simulated total nitrogen and total phosphorus were 0.92 and 0.57, respectively, for the calibration period and 0.84 and 0.73 for the validation period. Simulations showed that when using wastewater for irrigation, the total nitrogen loads increased by 210% and total phosphorus by 1,270% when compared with conventional water irrigation. The total nitrogen and total phosphorus concentration in the ponded water increased by 254 and 534%, respectively, when compared with conventional water irrigation. The effect of reducing N and P fertilizer application rates by 10, 30, and 50% on nutrient loads exiting a paddy field were also simulated using the validated CREAMS-PADDY model. These simulations indicated that total phosphorus loads from the paddy were reduced only slightly by reducing the fertilizer, while total nitrogen loads were reduced by as much as 8.8, 16.6, and 24.4% when N ferlitizer rates were reduced by 10, 30, and 50%, respectively. An erratum to this article can be found at     

Modeling of road traffic noise and estimated human exposure in Fulton County, Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN?. After analyzing noise levels with raster, vector and fa?ade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N=870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.