Science.gov

Sample records for naive bayes models

  1. A Naive-Bayes model observer for detection and localization of perfusion defects in cardiac SPECT-MPI

    NASA Astrophysics Data System (ADS)

    Parages, Felipe M.; O'Connor, J. Michael; Pretorius, P. Hendrik; Brankov, Jovan G.

    2014-03-01

    Model observers (MO) are widely used in medical imaging to act as surrogates of human observers in task-based image quality evaluation, frequently towards optimization of reconstruction algorithms. In SPECT myocardial perfusion imaging (MPI), a realistic task-based approach involves detection and localization of perfusion defects, as well as a subsequent assessment of defect severity. In this paper we explore a machine-learning MO based on Naive- Bayes classification (NB-MO). NB-MO uses a set of polar-map image features to predict lesion detection, localization and severity scores given by five human readers for a set of simulated 3D SPECT-MPI patients. The simulated dataset included lesions with different sizes, perfusion-reduction ratios, and locations. Simulated projections were reconstructed using two readily used methods namely: FBP and OSEM. For validation, a multireader multi-case (MRMC) analysis of alternative free-response ROC (AFROC) curve was performed for NB-MO and human observers. For comparison, we also report performances of a statistical Hotelling Observer applied on polar-map images. Results show excellent agreement between NB-MO and humans, as well as model's good generalization between different reconstruction treatments.

  2. Improving Naive Bayes with Online Feature Selection for Quick Adaptation to Evolving Feature Usefulness

    SciTech Connect

    Pon, R K; Cardenas, A F; Buttler, D J

    2007-09-19

    The definition of what makes an article interesting varies from user to user and continually evolves even for a single user. As a result, for news recommendation systems, useless document features can not be determined a priori and all features are usually considered for interestingness classification. Consequently, the presence of currently useless features degrades classification performance [1], particularly over the initial set of news articles being classified. The initial set of document is critical for a user when considering which particular news recommendation system to adopt. To address these problems, we introduce an improved version of the naive Bayes classifier with online feature selection. We use correlation to determine the utility of each feature and take advantage of the conditional independence assumption used by naive Bayes for online feature selection and classification. The augmented naive Bayes classifier performs 28% better than the traditional naive Bayes classifier in recommending news articles from the Yahoo! RSS feeds.

  3. Prediction of Protein-Protein Interaction Sites Based on Naive Bayes Classifier

    PubMed Central

    Geng, Haijiang; Lu, Tao; Lin, Xiao; Liu, Yu; Yan, Fangrong

    2015-01-01

    Protein functions through interactions with other proteins and biomolecules and these interactions occur on the so-called interface residues of the protein sequences. Identifying interface residues makes us better understand the biological mechanism of protein interaction. Meanwhile, information about the interface residues contributes to the understanding of metabolic, signal transduction networks and indicates directions in drug designing. In recent years, researchers have focused on developing new computational methods for predicting protein interface residues. Here we creatively used a 181-dimension protein sequence feature vector as input to the Naive Bayes Classifier- (NBC-) based method to predict interaction sites in protein-protein complexes interaction. The prediction of interaction sites in protein interactions is regarded as an amino acid residue binary classification problem by applying NBC with protein sequence features. Independent test results suggested that Naive Bayes Classifier-based method with the protein sequence features as input vectors performed well. PMID:26697220

  4. Joint decision and Naive Bayes learning for detection of space multi-target

    NASA Astrophysics Data System (ADS)

    Huang, Tao; Li, Zhulian; Zhou, Yu; Xiong, Yaoheng; Zhang, Haitao

    2014-07-01

    In the photoelectric tracking system, the detection of space multi-target is crucial for target localization and tracking. The difficulties include the interferences from CCD smear and strong noise, the few characteristics of spot-like targets and the challenge of multiple targets. In this paper, we propose a hybrid algorithm of joint decision and Naive Bayes (JD-NB) learning, and present the duty ratio feature to discriminate the target and smear blocks. Firstly, we extract the proper features and train the parameters of the Naive Bayes classifier. Secondly, target blocks are preliminarily estimated with the Naive Bayes. Lastly, the 4-adjacent blocks of the candidate target blocks are jointed to analyze the distribution pattern and the true target blocks are secondarily extracted by the method of pattern matching. Experimental results indicate that the proposed JD-NB algorithm not only possesses a high recognition rate of better than 90% for the target block, but also effectively overcomes the disturbance of the smear block. Moreover, it performs well in the detection of small and faint targets when the SNR of the block is higher than about 0.014.

  5. Using an Integrated Naive Bayes Calssifier for Crawling Relevent Data on the Web

    NASA Astrophysics Data System (ADS)

    Mihsra, A.

    2015-12-01

    In our experiments (at JPL, NASA) for DARPA Memex project, we wanted to crawl a large amount of data for various domains. A big challenge was data relevancy in the crawled data. More than 50% of the data was irrelevant to the domain at hand. One immediate solution was to use good seeds (seeds are the initial urls from where the program starts to crawl) and make sure that the crawl remains into the original host urls. This although a very efficient technique, fails under two conditions. One when you aim to reach deeper into the web; into new hosts (not in the seed list) and two when the website hosts myriad content types eg. a News website.The relevancy calculation used to be a post processing step i.e. once we had finished crawling, we trained a NaiveBayes Classifier and used it to find a rough relevancy of the web pages that we had. Integrating the relevancy into the crawling rather than after it was very important because crawling takes resources and time. To save both we needed to get an idea of relevancy of the whole crawl during run time and be able to steer its course accordingly. We use Apache Nutch as the crawler, which uses a plugin system to incorporate any new implementations and hence we built a plugin for Nutch.The Naive Bayes Parse Plugin works in the following way. It parses every page and decides, using a trained model (which is built in situ only once using the positive and negative examples given by the user in a very simple format), if it is relevant; If true, then it allows all the outlinks from that page to go to the next round of crawling; If not, then it gives the urls a second chance to prove themselves by checking some commonly expected words in the url relevant to that domain. This two tier system is very intuitive and efficient in focusing the crawl. In our initial test experiments over 100 seed urls, the results were astonishingly good with a recall of 98%.The same technique can be applied to geo-informatics. This will help scientists

  6. A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

    PubMed

    Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

    2015-09-20

    Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system. PMID:25980520

  7. Using naive Bayes classifier for classification of convective rainfall intensities based on spectral characteristics retrieved from SEVIRI

    NASA Astrophysics Data System (ADS)

    Hameg, Slimane; Lazri, Mourad; Ameur, Soltane

    2016-07-01

    This paper presents a new algorithm to classify convective clouds and determine their intensity, based on cloud physical properties retrieved from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The convective rainfall events at 15 min, 4 × 5 km spatial resolution from 2006 to 2012 are analysed over northern Algeria. The convective rain classification methodology makes use of the relationship between cloud spectral characteristics and cloud physical properties such as cloud water path (CWP), cloud phase (CP) and cloud top height (CTH). For this classification, a statistical method based on `naive Bayes classifier' is applied. This is a simple probabilistic classifier based on applying `Bayes' theorem with strong (naive) independent assumptions. For a 9-month period, the ability of SEVIRI to classify the rainfall intensity in the convective clouds is evaluated using weather radar over the northern Algeria. The results indicate an encouraging performance of the new algorithm for intensity differentiation of convective clouds using SEVIRI data.

  8. Detection of Cardiovascular Disease Risk's Level for Adults Using Naive Bayes Classifier

    PubMed Central

    Miranda, Eka; Amelga, Alowisius Y.; Maribondang, Marco M.; Salim, Mulyadi

    2016-01-01

    Objectives The number of deaths caused by cardiovascular disease and stroke is predicted to reach 23.3 million in 2030. As a contribution to support prevention of this phenomenon, this paper proposes a mining model using a naïve Bayes classifier that could detect cardiovascular disease and identify its risk level for adults. Methods The process of designing the method began by identifying the knowledge related to the cardiovascular disease profile and the level of cardiovascular disease risk factors for adults based on the medical record, and designing a mining technique model using a naïve Bayes classifier. Evaluation of this research employed two methods: accuracy, sensitivity, and specificity calculation as well as an evaluation session with cardiologists and internists. The characteristics of cardiovascular disease are identified by its primary risk factors. Those factors are diabetes mellitus, the level of lipids in the blood, coronary artery function, and kidney function. Class labels were assigned according to the values of these factors: risk level 1, risk level 2 and risk level 3. Results The evaluation of the classifier performance (accuracy, sensitivity, and specificity) in this research showed that the proposed model predicted the class label of tuples correctly (above 80%). More than eighty percent of respondents (including cardiologists and internists) who participated in the evaluation session agree till strongly agreed that this research followed medical procedures and that the result can support medical analysis related to cardiovascular disease. Conclusions The research showed that the proposed model achieves good performance for risk level detection of cardiovascular disease. PMID:27525161

  9. Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

    NASA Astrophysics Data System (ADS)

    Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

    2015-12-01

    Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

  10. Naive Probability: Model-Based Estimates of Unique Events.

    PubMed

    Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N

    2015-08-01

    We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. PMID:25363706

  11. Tsunami Inundation modeling for Tolaga Bay, Tokomaru Bay, Hicks Bay and Te Araroa communities

    NASA Astrophysics Data System (ADS)

    Barberopoulou, A.; Wang, X.; Power, W. L.

    2012-12-01

    We assess the tsunami hazard to four communities in Raukumara Peninsula (Northeastern region of North Island of New Zealand): Tokomaru Bay, Tolaga Bay, Hicks Bay and Te Araroa. Representative severe but realistic scenarios that could affect the Raukumara peninsula are earthquakes that rupture the interface between the Australian and Pacific plates, earthquakes that rupture faults within the overlying Australian plate or the subducting Pacific plate (location is not always well constrained). Earthquakes that rupture both the plate interface and simultaneously faults within the crust of the Australian plate are also a possibility. Tsunamis may also be caused by submarine landslides that occur near the edge of the continental shelf, but these are not considered here. For this study four scenario events were constructed, including a distant event from South America (offshore Peru), outer rise events and a thrust event in the Hikurangi region off the east coast of New Zealand. The sources are not exhaustive but representative of the types of significant events that could occur in the region and were either improved from earlier sources or derived from recent studies. Available high resolution LiDAR and RTK data were combined with topographic and LINZ data for the development of bathymetric/topographic grids. Our modelling results show that Tolaga Bay appears most vulnerable to tsunami inundation although Hicks Bay and Te Araroa are also significantly inundated in several of the scenarios. Tokomaru Bay is naturally well protected because the rapid change in elevation limits the range of inundation. The worst scenario for Tokomaru Bay was an earthquake in the Hikurangi subduction zone resulting in large flow depths, whereas for Tolaga Bay inundation is severe from most scenarios. Hicks Bay and Te Araroa get the most severe flooding from earthquakes in South America and on the Hikurangi subduction zone. Inundation extent is similar for Tolaga Bay during the Outer Rise and

  12. Chesapeake Bay sediment flux model. Final report

    SciTech Connect

    Di Toro, D.M.; Fitzpatrick, J.J.

    1993-06-01

    Formulation and application of a predictive diagenetic sediment model are described in this report. The model considers two benthic sediment layers: a thin aerobic layer in contact with the water column and a thicker anaerobic layer. Processes represented include diagenesis, diffusion, particle mixing, and burial. Deposition of organic matter, water column concentrations, and temperature are treated as independent variables that influence sediment-water fluxes. Sediment oxygen demand and sediment-water fluxes of sulfide, ammonium, nitrate, phosphate, and silica are predicted. The model was calibrated using sediment-water flux observations collected in Chesapeake Bay 1985-1988. When independent variables were specified based on observations, the model correctly represented the time series of sediment-water fluxes observed at eight stations in the Bay and tributaries.... Chesapeake Bay, Models, Sediments, Dissolved oxygen, Nitrogen Eutrophication, Phosphorus.

  13. Modeling the seasonal circulation in Massachusetts Bay

    USGS Publications Warehouse

    Signell, Richard P.; Jenter, Harry L.; Blumberg, Alan F.

    1994-01-01

    An 18 month simulation of circulation was conducted in Massachusetts Bay, a roughly 35 m deep, 100??50 km embayment on the northeastern shelf of the United States. Using a variant of the Blumberg-Mellor (1987) model, it was found that a continuous 18 month run was only possible if the velocity field was Shapiro filtered to remove two grid length energy that developed along the open boundary due to mismatch in locally generated and climatologically forced water properties. The seasonal development of temperature and salinity stratification was well-represented by the model once ??-coordinate errors were reduced by subtracting domain averaged vertical profiles of temperature, salinity and density before horizontal differencing was performed. Comparison of modeled and observed subtidal currents at fixed locations revealed that the model performance varies strongly with season and distance from the open boundaries. The model performs best during unstratified conditions, and in the interior of the bay. The model performs poorest during stratified conditions and in the regions where the bay is driven predominantly by remote fluctuations from the Gulf of Maine.

  14. Hydraulic model of the Chesapeake Bay

    NASA Technical Reports Server (NTRS)

    Robinson, A. E., Jr.

    1978-01-01

    Preliminary planning for the formulation of the first year of hydraulic studies on the Chesapeake Bay model was recently completed. The primary purpose of this initial effort was to develop a study program that is both responsive to problems of immediate importance and at the same time ensure that from the very beginning of operation maximum economical use is made of the model. The formulation of this preliminary study plan involved an extensive analysis of the environmental, economic, and social aspects of a series of current problems in order to establish a priority listing of their importance. The study program that evolved is oriented towards the analysis of the effects of some of the works of man on the Chesapeake Bay estuarine environment.

  15. Withdrawal-like effects of pentylenetetrazol and valproate in the naive organism: a model of motivation produced by opiate withdrawal?

    PubMed

    Mucha, R F; Fassos, F F; Perl, F M

    1995-07-01

    Pentylenetetrazol (PTZ) and sodium valproate (VPA) produce acutely in the naive rat various behavioural effects resembling signs of opiate withdrawal in the morphine-treated subject. Suggestions in the literature that these substances may activate directly some of the neural consequences of opiate and drug withdrawal prompted us to look for and examine possible aversive effects of these substances at non-toxic doses. With a sensitive two-flavour, three-trial taste aversion procedure, relatively low doses of PTZ and VPA (5 and 160 mg/kg, respectively) do indeed have aversive effects. The maximum aversions were produced by 10 and 20 mg/kg PTZ and 320 mg/kg VPA and were equivalent to those of morphine withdrawal precipitated by 0.01-0.03 mg/kg naloxone in a morphine pellet-implanted animal. Moreover, the maximum aversions with PTZ and VPA were significantly higher than the maximum aversions seen with naloxone in the drug-naive animal under the same training conditions. Thus, the data from the present study confirmed the notion that low doses of PTZ and VPA in the naive animal may activate processes activated by drug withdrawal, including those important for the motivational effect of withdrawal. However, it was also pointed out that the lowest dose VPA producing aversion was higher than that found here to produce writhes and ataxia (80 mg/kg) but the same as that required for shaking (160 mg/kg), while the PTZ aversion was at a dose lower than that known to produce a PTZ cue. Implications were discussed for using withdrawal-like phenomena as a model in the non-treated organism of clinically-relevant withdrawal effects. PMID:7587968

  16. MOBILE BAY AND WATERSHED WATER QUALITY MODELING

    EPA Science Inventory

    Two major products will come out of this project. The first is a compilation of 2001 water quality data for the Mobile bay area. The second is to develop and run a water quality moded for the bay to assist with development of TMDLs for the Bay

  17. MODELING STUDIES FOR PLANNING: THE GREEN BAY PROJECT

    EPA Science Inventory

    A major contaminant monitoring and modeling study is underway for Green Bay, Lake Michigan. onitoring programs in support of contaminant modeling of large waterbodies, such as for Green Bay, are expensive and their extent is often limited by budget limitations, laboratory capacit...

  18. Default Bayes Factors for Model Selection in Regression

    ERIC Educational Resources Information Center

    Rouder, Jeffrey N.; Morey, Richard D.

    2012-01-01

    In this article, we present a Bayes factor solution for inference in multiple regression. Bayes factors are principled measures of the relative evidence from data for various models or positions, including models that embed null hypotheses. In this regard, they may be used to state positive evidence for a lack of an effect, which is not possible…

  19. Modeling nitrogen cycling in forested watersheds of Chesapeake Bay

    SciTech Connect

    Hunsaker, C.T.; Garten, C.T.; Mulholland, P.J.

    1995-03-01

    The Chesapeake Bay Agreement calls for a 40% reduction of controllable phosphorus and nitrogen to the tidal Bay by the year 2000. To accomplish this goal the Chesapeake Bay Program needs accurate estimates of nutrient loadings, including atmospheric deposition, from various land uses. The literature was reviewed on forest nitrogen pools and fluxes, and nitrogen data from research catchments in the Chesapeake Basin were identified. The structure of a nitrogen module for forests is recommended for the Chesapeake Bay Watershed Model along with the possible functional forms for fluxes.

  20. Modeling studies for planning: The Green Bay project

    SciTech Connect

    Martin, J.L.; Richardson, W.L.; McCutcheon, S.C.

    1991-06-01

    A major contaminant monitoring and modeling study is underway for Green Bay, Lake Michigan. Monitoring programs in support of contaminant modeling of large waterbodies, such as for Green Bay, are expensive and their extent is often limited by budget limitations, laboratory capacity, and logistic constraints. Physical/chemical and food chain models were applied using historical data to aid in project planning by identifying processes having the greatest impact on the predictive capability of mass balance models. Studies were also conducted to estimate errors in computed tributary loadings and in-Bay concentrations and contaminant mass associated with different sampling strategies.

  1. An Amorphous Model for Morphological Processing in Visual Comprehension Based on Naive Discriminative Learning

    ERIC Educational Resources Information Center

    Baayen, R. Harald; Milin, Petar; Durdevic, Dusica Filipovic; Hendrix, Peter; Marelli, Marco

    2011-01-01

    A 2-layer symbolic network model based on the equilibrium equations of the Rescorla-Wagner model (Danks, 2003) is proposed. The study first presents 2 experiments in Serbian, which reveal for sentential reading the inflectional paradigmatic effects previously observed by Milin, Filipovic Durdevic, and Moscoso del Prado Martin (2009) for unprimed…

  2. Tampa Bay Water Clarity Model (TBWCM): As a Predictive Tool

    EPA Science Inventory

    The Tampa Bay Water Clarity Model was developed as a predictive tool for estimating the impact of changing nutrient loads on water clarity as measured by secchi depth. The model combines a physical mixing model with an irradiance model and nutrient cycling model. A 10 segment bi...

  3. Model for carbonate deposition in an Epicontinental Bay

    SciTech Connect

    Carney, C.; Smosna, R.

    1986-05-01

    By mapping the distribution of correlative sediments across the north-central region of the Appalachian basin, a paleogeographic model has been generated for part of the Mississippian period. During the Chesterian, the upper Greenbrier Limestone was deposited in an embayment that extended northward into parts of West Virginia, Ohio, Pennsylvanian, and Maryland. The bay, only a few hundred kilometers wide, was surrounded by lowlands to the west and north, and deltaic sediments shed from nearby highlands diluted the easternmost facies. In the bay, several different shallow-water carbonate environments are distinguished. Muddy skeletal sand was deposited in the central part, which was characterized by normal marine circulation and salinity. This open-bay facies supported a moderately diverse fauna of forams, brachiopods, and mollusks. From the central facies to the bay margins, water depth decreased, circulation became more restricted, and salinity was slightly higher. A restricted-bay facies developed closer to shore, with sediment consisting of pelletal mud and scattered skeletal grains. Diversity was lower, and the fauna was composed primarily of forams and ostracodes. A tidal mud flat surrounded the embayment on all three sides where partly to totally dolomitized mud containing cryptalgal structures formed. Oolite shoals, present on the eastern side of the bay near its mouth, mark areas where tidal currents were concentrated. Eventually, the epicontinental sea flooded the small enclosed bay, replacing the shallow-water facies with an open-marine facies. The new environment supported a highly diverse fauna including crinoids, brachiopods, mollusks, forams, and ostracods.

  4. Nomogram of Naive Bayesian Model for Recurrence Prediction of Breast Cancer

    PubMed Central

    Kim, Woojae; Kim, Ku Sang

    2016-01-01

    Objectives Breast cancer has a high rate of recurrence, resulting in the need for aggressive treatment and close follow-up. However, previously established classification guidelines, based on expert panels or regression models, are controversial. Prediction models based on machine learning show excellent performance, but they are not widely used because they cannot explain their decisions and cannot be presented on paper in the way that knowledge is customarily represented in the clinical world. The principal objective of this study was to develop a nomogram based on a naïve Bayesian model for the prediction of breast cancer recurrence within 5 years after breast cancer surgery. Methods The nomogram can provide a visual explanation of the predicted probabilities on a sheet of paper. We used a data set from a Korean tertiary teaching hospital of 679 patients who had undergone breast cancer surgery between 1994 and 2002. Seven prognostic factors were selected as independent variables for the model. Results The accuracy was 80%, and the area under the receiver operating characteristics curve (AUC) of the model was 0.81. Conclusions The nomogram can be easily used in daily practice to aid physicians and patients in making appropriate treatment decisions after breast cancer surgery. PMID:27200218

  5. Dynamic modeling of Tampa Bay urban development using parallel computing

    USGS Publications Warehouse

    Xian, G.; Crane, M.; Steinwand, D.

    2005-01-01

    Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively. ?? 2005 Elsevier Ltd. All rights reserved.

  6. Modelling Wind Effects on Subtidal Salinity in Apalachicola Bay, Florida

    NASA Astrophysics Data System (ADS)

    Huang, W.; Jones, W. K.; Wu, T. S.

    2002-07-01

    Salinity is an important factor for oyster and estuarine productivity in Apalachicola Bay. Observations of salinity at oyster reefs have indicated a high correlation between subtidal salinity variations and the surface winds along the bay axis in an approximately east-west direction. In this paper, we applied a calibrated hydrodynamic model to examine the surface wind effects on the volume fluxes in the tidal inlets and the subtidal salinity variations in the bay. Model simulations show that, due to the large size of inlets located at the east and west ends of this long estuary, surface winds have significant effects on the volume fluxes in the estuary inlets for the water exchanges between the estuary and ocean. In general, eastward winds cause the inflow from the inlets at the western end and the outflow from inlets at the eastern end of the bay. Winds at 15 mph speed in the east-west direction can induce a 2000 m3 s-1 inflow of saline seawater into the bay from the inlets, a rate which is about 2·6 times that of the annual average freshwater inflow from the river. Due to the varied wind-induced volume fluxes in the inlets and the circulation in the bay, the time series of subtidal salinity at oyster reefs considerably increases during strong east-west wind conditions in comparison to salinity during windless conditions. In order to have a better understanding of the characteristics of the wind-induced subtidal circulation and salinity variations, the researchers also connected model simulations under constant east-west wind conditions. Results show that the volume fluxes are linearly proportional to the east-west wind stresses. Spatial distributions of daily average salinity and currents clearly show the significant effects of winds on the bay.

  7. Hydrodynamic characterization of Corpus Christi Bay through modeling and observation.

    PubMed

    Islam, Mohammad S; Bonner, James S; Edge, Billy L; Page, Cheryl A

    2014-11-01

    Christi Bay is a relatively flat, shallow, wind-driven system with an average depth of 3-4 m and a mean tidal range of 0.3 m. It is completely mixed most of the time, and as a result, depth-averaged models have, historically, been applied for hydrodynamic characterization supporting regulatory decisions on Texas coastal management. The bay is highly stratified during transitory periods of the summer with low wind conditions. This has important implications on sediment transport, nutrient cycling, and water quality-related issues, including hypoxia which is a key water quality concern for the bay. Detailed hydrodynamic characterization of the bay during the summer months included analysis of simulation results of 2-D hydrodynamic model and high-frequency (HF) in situ observations. The HF radar system resolved surface currents, whereas an acoustic Doppler current profiler (ADCP) measured current at different depths of the water column. The developed model successfully captured water surface elevation variation at the mouth of the bay (i.e., onshore boundary of the Gulf of Mexico) and at times within the bay. However, large discrepancies exist between model-computed depth-averaged water currents and observed surface currents. These discrepancies suggested the presence of a vertical gradient in the current structure which was further substantiated by the observed bi-directional current movement within the water column. In addition, observed vertical density gradients proved that the water column was stratified. Under this condition, the bottom layer became hypoxic due to inadequate mixing with the aerated surface water. Understanding the disparities between observations and model predictions provides critical insights about hydrodynamics and physical processes controlling water quality. PMID:25096643

  8. Modeling tidal hydrodynamics of San Diego Bay, California

    USGS Publications Warehouse

    Wang, P.-F.; Cheng, R.T.; Richter, K.; Gross, E.S.; Sutton, D.; Gartner, J.W.

    1998-01-01

    In 1983, current data were collected by the National Oceanic and Atmospheric Administration using mechanical current meters. During 1992 through 1996, acoustic Doppler current profilers as well as mechanical current meters and tide gauges were used. These measurements not only document tides and tidal currents in San Diego Bay, but also provide independent data sets for model calibration and verification. A high resolution (100-m grid), depth-averaged, numerical hydrodynamic model has been implemented for San Diego Bay to describe essential tidal hydrodynamic processes in the bay. The model is calibrated using the 1983 data set and verified using the more recent 1992-1996 data. Discrepancies between model predictions and field data in beth model calibration and verification are on the order of the magnitude of uncertainties in the field data. The calibrated and verified numerical model has been used to quantify residence time and dilution and flushing of contaminant effluent into San Diego Bay. Furthermore, the numerical model has become an important research tool in ongoing hydrodynamic and water quality studies and in guiding future field data collection programs.

  9. Naive time-reversal odd phenomena in semi-inclusive deep-inelastic scattering from light-cone constituent quark models

    SciTech Connect

    Barbara Pasquini, Peter Schweitzer

    2011-06-01

    We present results for leading-twist azimuthal asymmetries in semi-inclusive lepton-nucleon deep-inelastic scattering due to naively time-reversal odd transverse-momentum dependent parton distribution functions from the light-cone constituent quark model. We carefully discuss the range of applicability of the model, especially with regard to positivity constraints and evolution effects. We find good agreement with available experimental data from COMPASS and HERMES, and present predictions to be tested in forthcoming experiments at Jefferson Lab.

  10. Modeling Fecal Indicator Bacteria Like Salt in Newport Bay

    NASA Astrophysics Data System (ADS)

    Ciglar, A. M.; Rippy, M.; Grant, S. B.

    2015-12-01

    Newport Bay is a harbor and estuary located in Orange County, CA that provides many water sports and recreational activities for millions of southern California residents and tourists. The aim of this study is to quickly assess exceedances of FIB in the Newport Bay which pose a health risk to recreational users. The ability to quickly assess water quality is made possible with an advection-diffusion mass transport model that uses easily measurable parameters such as volumetric flow rate from tributaries. Current FIB assessment methods for Newport Bay take a minimum of 24 hours to evaluate health risk by either culturing for FIB or running a more complex fluid dynamics model. By this time the FIB may have already reached the ocean outlet thus no longer posing a risk in the bay or recreationists may have already come in close contact with contaminated waters. The advection-diffusion model can process and disseminate health risk information within a few hours of flow rate measurements, minimizing time between an FIB exceedance and public awareness about the event. Data used to calibrate and validate the model was collected from January 2006 through February 2007. Salinity data was used for calibration and FIB data was used for validation. Both steady-state and transient conditions were assessed to determine if dry weather patterns can be simplified to the steady-state condition.

  11. Modeling of M2 Tidal Circulation in Kyounggi Bay, Korea

    NASA Astrophysics Data System (ADS)

    Park, S.; Park, Y.; Kim, Y.; Jung, K.; Woo, S.

    2008-12-01

    Kyounggi Bay located along the western coast of Korea is a macrotidal zone of 7.9 m tidal range during the spring tide and tidal flats very well developed. Within the bay there are several islands, and the coast lines are crooked significantly so that the geometry of the bay is very complex. To study the tidal circulation of this area, we conducted numerical modeling using a finite volume coastal ocean model, FVCOM, which could represent the complex topography properly. The model domain is about 40 km × 53 km, and the smallest grid is about 72 m. Therefore, the narrowest waterway, Yeomha, is well resolved. Only M2 tidal forcing is considered at the open boundary. There are three rivers in the bay and experiments were conducted with or without the fresh water discharge from the three rivers. Some of the previous modeling studies showed that the fresh water discharge could reverse the direction of the residual flows in Yeomha Waterways, but in the present experiment the river discharge could not reverse the residual flow. Other aspects of the tidal flow in this area were examined.

  12. Formal versus heuristic modeling for multitarget Bayes filtering

    NASA Astrophysics Data System (ADS)

    Mahler, Ronald P. S.

    2004-08-01

    The multisensor-multitarget Bayes filter is the foundation for multi-sensor-multitarget detection, tracking, and identification. This paper addresses the question of principled implementation of this filter. Algorithms can always be cobbled together using catch-as-catch-can heuristic techniques. In formal Bayes modeling one instead derives statistically precise, implementation-independent equations from which principle approximations can then be derived. Indeed, this has become the accepted methodology for single-sensor, single-target tracking R&D. In the case of the multitarget filter, however, partisans of a so-called "plain-vanilla Bayesian approach" have disparaged formal Bayes modelling, and have protrayed specific, ad hoc implementations as completely general, "powerful and robust computational methods." In this and a companion paper I expose the speciousness of such claims. This paper reviews the elements of formal Bayes modeling and approximation, describes what they must look like in the multitarget case, and contrasts them with the "plain-vanilla Bayesian approach."

  13. Using simple models to describe the kinetics of growth, glucose consumption, and monoclonal antibody formation in naive and infliximab producer CHO cells.

    PubMed

    López-Meza, Julián; Araíz-Hernández, Diana; Carrillo-Cocom, Leydi Maribel; López-Pacheco, Felipe; Rocha-Pizaña, María Del Refugio; Alvarez, Mario Moisés

    2016-08-01

    Despite their practical and commercial relevance, there are few reports on the kinetics of growth and production of Chinese hamster ovary (CHO) cells-the most frequently used host for the industrial production of therapeutic proteins. We characterize the kinetics of cell growth, substrate consumption, and product formation in naive and monoclonal antibody (mAb) producing recombinant CHO cells. Culture experiments were performed in 125 mL shake flasks on commercial culture medium (CD Opti CHO™ Invitrogen, Carlsbad, CA, USA) diluted to different glucose concentrations (1.2-4.8 g/L). The time evolution of cell, glucose, lactic acid concentration and monoclonal antibody concentrations was monitored on a daily basis for mAb-producing cultures and their naive counterparts. The time series were differentiated to calculate the corresponding kinetic rates (rx = d[X]/dt; rs = d[S]/dt; rp = d[mAb]/dt). Results showed that these cell lines could be modeled by Monod-like kinetics if a threshold substrate concentration value of [S]t = 0.58 g/L (for recombinant cells) and [S]t = 0.96 g/L (for naïve cells), below which growth is not observed, was considered. A set of values for μmax, and Ks was determined for naive and recombinant cell cultures cultured at 33 and 37 °C. The yield coefficient (Yx/s) was observed to be a function of substrate concentration, with values in the range of 0.27-1.08 × 10(7) cell/mL and 0.72-2.79 × 10(6) cells/mL for naive and recombinant cultures, respectively. The kinetics of mAb production can be described by a Luedeking-Piret model (d[mAb]/dt = αd[X]/dt + β[X]) with values of α = 7.65 × 10(-7) µg/cell and β = 7.68 × 10(-8) µg/cell/h for cultures conducted in batch-agitated flasks and batch and instrumented bioreactors operated in batch and fed-batch mode. PMID:26091615

  14. A Coupled Wave-Current-Sediment model for Skagit Bay

    NASA Astrophysics Data System (ADS)

    Cowles, G. W.; Holmes, E. M.; Ralston, D. K.

    2010-12-01

    Along with tidal currents, waves provide a dominant forcing mechanism for sediment transport on many tidal flats. In semi-enclosed regions such as Skagit Bay, Washington, the wave action is due mainly to local wind forcing that occurs over seasonal and event scales. Due to the limited fetch, variations in along-flat wave characteristics can drive gradients in the wave-induced bottom stress and resulting sediment transport. In this work, we use an unstructured grid, coupled wave-current-sediment model to study the influence of wave-induced near bottom stresses in the presence of tidal currents on the sediment transport within the Skagit River delta and Skagit Bay. The coupled model consists of three primary components: the Finite Volume Coastal Ocean Model (FVCOM) for hydrodynamics, the unstructured grid model SWAN to compute the phase-averaged wave field, and the Community Sediment Transport Modeling System. Model sensitivities to the choice of coupling and bottom boundary layer formulations are examined. Results from process oriented simulations will be presented. The process studies use a realistic domain with controlled forcing conditions to quantify the influence of wave-induced bed stresses on the sediment dynamics in Skagit Bay.

  15. Modeling the tides of Massachusetts and Cape Cod bays

    USGS Publications Warehouse

    Jenter, H.L.; Signell, R.P.; Blumberg, A.F.

    1993-01-01

    A time-dependent, three-dimensional numerical modeling study of the tides of Massachusetts and Cape Code Bays, motivated by construction of a new sewage treatment plant and ocean outfall for the city of Boston, has been undertaken by the authors. The numerical model being used is a hybrid version of the Blumberg and Mellor ECOM3D model, modified to include a semi-implicit time-stepping scheme and transport of a non-reactive dissolved constituent. Tides in the bays are dominated by the semi-diurnal frequencies, in particular by the M2 tide, due to the resonance of these frequencies in the Gulf of Maine. The numerical model reproduces, well, measured tidal ellipses in unstratified wintertime conditions. Stratified conditions present more of a problem because tidal-frequency internal wave generation and propagation significantly complicates the structure of the resulting tidal field. Nonetheless, the numerical model reproduces qualitative aspects of the stratified tidal flow that are consistent with observations in the bays.

  16. An educational interactive numerical model of the Chesapeake Bay

    NASA Astrophysics Data System (ADS)

    Crouch, Jessica R.; Shen, Yuzhong; Austin, Jay A.; Dinniman, Michael S.

    2008-03-01

    Scientists use sophisticated numerical models to study ocean circulation and other physical systems, but the complex nature of such simulation software generally make them inaccessible to non-expert users. In principle, however, numerical models represent an ideal teaching tool, allowing users to model the response of a complex system to changing conditions. We have designed an interactive simulation program that allows a casual user to control the forcing conditions applied to a numerical ocean circulation model using a graphical user interface, and to observe the results in real-time. This program is implemented using the Regional Ocean Modeling System (ROMS) applied to the Chesapeake Bay. Portions of ROMS were modified to facilitate user interaction, and the user interface and visualization capabilities represent new software development. The result is an interactive simulation of the Chesapeake Bay environment that allows a user to control wind speed and direction along with the rate of flow from the rivers that feed the bay. The simulation provides a variety of visualizations of the response of the system, including water height, velocity, and salinity across horizontal and vertical planes.

  17. Consistent safety and infectivity in sporozoite challenge model of Plasmodium vivax in malaria-naive human volunteers.

    PubMed

    Herrera, Sócrates; Solarte, Yezid; Jordán-Villegas, Alejandro; Echavarría, Juan Fernando; Rocha, Leonardo; Palacios, Ricardo; Ramírez, Oscar; Vélez, Juan D; Epstein, Judith E; Richie, Thomas L; Arévalo-Herrera, Myriam

    2011-02-01

    A safe and reproducible Plasmodium vivax infectious challenge method is required to evaluate the efficacy of malaria vaccine candidates. Seventeen healthy Duffy (+) and five Duffy (-) subjects were randomly allocated into three (A-C) groups and were exposed to the bites of 2-4 Anopheles albimanus mosquitoes infected with Plasmodium vivax derived from three donors. Duffy (-) subjects were included as controls for each group. Clinical manifestations of malaria and parasitemia were monitored beginning 7 days post-challenge. All Duffy (+) volunteers developed patent malaria infection within 16 days after challenge. Prepatent period determined by thick smear, was longer for Group A (median 14.5 d) than for Groups B and C (median 10 d/each). Infected volunteers recovered rapidly after treatment with no serious adverse events. The bite of as low as two P. vivax-infected mosquitoes provides safe and reliable infections in malaria-naive volunteers, suitable for assessing antimalarial and vaccine efficacy trials. PMID:21292872

  18. Consistent Safety and Infectivity in Sporozoite Challenge Model of Plasmodium vivax in Malaria-Naive Human Volunteers

    PubMed Central

    Herrera, Sócrates; Solarte, Yezid; Jordán-Villegas, Alejandro; Echavarría, Juan Fernando; Rocha, Leonardo; Palacios, Ricardo; Ramírez, Óscar; Vélez, Juan D.; Epstein, Judith E.; Richie, Thomas L.; Arévalo-Herrera, Myriam

    2011-01-01

    A safe and reproducible Plasmodium vivax infectious challenge method is required to evaluate the efficacy of malaria vaccine candidates. Seventeen healthy Duffy (+) and five Duffy (−) subjects were randomly allocated into three (A–C) groups and were exposed to the bites of 2–4 Anopheles albimanus mosquitoes infected with Plasmodium vivax derived from three donors. Duffy (−) subjects were included as controls for each group. Clinical manifestations of malaria and parasitemia were monitored beginning 7 days post-challenge. All Duffy (+) volunteers developed patent malaria infection within 16 days after challenge. Prepatent period determined by thick smear, was longer for Group A (median 14.5 d) than for Groups B and C (median 10 d/each). Infected volunteers recovered rapidly after treatment with no serious adverse events. The bite of as low as two P. vivax-infected mosquitoes provides safe and reliable infections in malaria-naive volunteers, suitable for assessing antimalarial and vaccine efficacy trials. PMID:21292872

  19. RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.

    PubMed

    Höhna, Sebastian; Landis, Michael J; Heath, Tracy A; Boussau, Bastien; Lartillot, Nicolas; Moore, Brian R; Huelsenbeck, John P; Ronquist, Fredrik

    2016-07-01

    Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.]. PMID:27235697

  20. RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language

    PubMed Central

    Höhna, Sebastian; Landis, Michael J.

    2016-01-01

    Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite of models. Consequently, users of these software packages are simultaneously forced to use a number of programs for a given study, while also lacking the freedom to explore models that have not been implemented by the developers of those programs. We developed a new open-source software package, RevBayes, to address these problems. RevBayes is entirely based on probabilistic graphical models, a powerful generic framework for specifying and analyzing statistical models. Phylogenetic-graphical models can be specified interactively in RevBayes, piece by piece, using a new succinct and intuitive language called Rev. Rev is similar to the R language and the BUGS model-specification language, and should be easy to learn for most users. The strength of RevBayes is the simplicity with which one can design, specify, and implement new and complex models. Fortunately, this tremendous flexibility does not come at the cost of slower computation; as we demonstrate, RevBayes outperforms competing software for several standard analyses. Compared with other programs, RevBayes has fewer black-box elements. Users need to explicitly specify each part of the model and analysis. Although this explicitness may initially be unfamiliar, we are convinced that this transparency will improve understanding of phylogenetic models in our field. Moreover, it will motivate the search for improvements to existing methods by brazenly exposing the model choices that we make to critical scrutiny. RevBayes is freely available at http://www.RevBayes.com. [Bayesian inference; Graphical models; MCMC; statistical phylogenetics.] PMID:27235697

  1. TAMPA BAY MODEL EVALUATION AND ASSESSMENT

    EPA Science Inventory

    A long term goal of multimedia environmental management is to achieve sustainable ecological resources. Progress towards this goal rests on a foundation of science-based methods and data integrated into predictive multimedia, multi-stressor open architecture modeling systems. The...

  2. Modelling a storm surge event in Liverpool Bay with FVCOM.

    NASA Astrophysics Data System (ADS)

    Hall, P.

    2012-04-01

    A model of the Irish Sea/Liverpool Bay area has been developed using the finite volume, unstructured mesh code FVCOM. The model has been run with meteorological forcing to simulate the storm surge event of January 2007. This event has previously been modelled with the POLCOMS code, the results of which were used for a comparison of accuracy and computational efficiency of the two approaches. The wind speed (and hence wind stress) together with atmospheric pressure have been applied to the model as surface boundary conditions for a period of a few days to allow the model to settle down, and then the results for the peak of the storm on January 18th 2007 have been analysed to give metrics for the accuracy of the sea surface elevation that is predicted against measurements taken at Hilbre Island, near the mouth of the River Dee in Liverpool Bay. It was found that by changing the wind stress formulation within the FVCOM code a significant improvement in the accuracy of the model results could be obtained for the period of this surge event.

  3. Forewarning model for water pollution risk based on Bayes theory.

    PubMed

    Zhao, Jun; Jin, Juliang; Guo, Qizhong; Chen, Yaqian; Lu, Mengxiong; Tinoco, Luis

    2014-02-01

    In order to reduce the losses by water pollution, forewarning model for water pollution risk based on Bayes theory was studied. This model is built upon risk indexes in complex systems, proceeding from the whole structure and its components. In this study, the principal components analysis is used to screen out index systems. Hydrological model is employed to simulate index value according to the prediction principle. Bayes theory is adopted to obtain posterior distribution by prior distribution with sample information which can make samples' features preferably reflect and represent the totals to some extent. Forewarning level is judged on the maximum probability rule, and then local conditions for proposing management strategies that will have the effect of transforming heavy warnings to a lesser degree. This study takes Taihu Basin as an example. After forewarning model application and vertification for water pollution risk from 2000 to 2009 between the actual and simulated data, forewarning level in 2010 is given as a severe warning, which is well coincide with logistic curve. It is shown that the model is rigorous in theory with flexible method, reasonable in result with simple structure, and it has strong logic superiority and regional adaptability, providing a new way for warning water pollution risk. PMID:24194413

  4. Prognostic Value of HIV-1 RNA on CD4 Trajectories and Disease Progression Among Antiretroviral-Naive HIV-Infected Adults in Botswana: A Joint Modeling Analysis.

    PubMed

    Farahani, Mansour; Novitsky, Vladimir; Wang, Rui; Bussmann, Hermann; Moyo, Sikhulile; Musonda, Rosemary M; Moeti, Themba; Makhema, Joseph M; Essex, Max; Marlink, Richard

    2016-06-01

    Although HIV-1 RNA levels are measured at the time of initial diagnosis, the results are not used for the clinical follow-up of the patients. This study evaluates the prognostic value of the baseline HIV-1 RNA levels (above or below 10,000 copies/ml) on rate of disease progression, among antiretroviral therapy (ART)-naive patients in Botswana. A prospective cohort of 436 HIV-infected ART-naive adults with baseline CD4 > 400 cells/mm(3) were followed quarterly for 5 years in an urban clinic in Botswana. Baseline HIV-1 RNA levels and longitudinal CD4(+) T-cell count data were analyzed, using mixed-effects regression jointly modeled with the times to a composite endpoint defined by AIDS-defining clinical conditions or death. During 1,547 person-years (PYs) follow-up time, 106 individuals became eligible for ART initiation (incidence rate: 0.07 PYs) and 6 participants died of AIDS-related illness. There were 203 (47%) individuals with baseline HIV-1 RNA <10,000 copies/ml and 233 (53%) individuals with baseline RNA >10,000 copies/ml. The slope of the predicted CD4 trajectory for individuals with baseline HIV-1 RNA >10,000 copies/ml is 30% steeper than that for those with baseline RNA <10,000. The hazard of reaching the composite endpoint for the individuals with baseline HIV-1 RNA >10,000 copies/ml was 2.3 (95% confidence interval: 1.5-3.0) times higher than that for those with baseline HIV-1 RNA <10,000 copies/ml. CD4 decline in individuals with HIV-1 RNA >10,000 copies/ml is much faster than that in those with RNA <10,000. The elevated HIV-1 RNA can be used as a marker to identify individuals at risk of faster disease progression. PMID:26830351

  5. Restoration Lessons Learned from Bay Scallop Habitat Models

    EPA Science Inventory

    Habitat quality and quantity are important factors to consider when restoring bay scallop (Argopecten irradians) populations; however, data linking habitat attributes to bay scallop populations are lacking. This information is essential to guide restoration efforts to reverse sc...

  6. Reinforcing Behavior of "Naive" Trainers

    ERIC Educational Resources Information Center

    Lanzetta, John T.; Hannah, T. E.

    1969-01-01

    Presents an experiment showing that naive trainers tend to allow factors such as task difficulty and competence of the trainee to affect the kind of reinforcement administered. Bibliography, tables, and graphs. (JB)

  7. A variational Bayes spatiotemporal model for electromagnetic brain mapping.

    PubMed

    Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

    2014-03-01

    In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. PMID:24354514

  8. Bayesian model reduction and empirical Bayes for group (DCM) studies.

    PubMed

    Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter

    2016-03-01

    This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570

  9. Bayesian model reduction and empirical Bayes for group (DCM) studies

    PubMed Central

    Friston, Karl J.; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E.; van Wijk, Bernadette C.M.; Ziegler, Gabriel; Zeidman, Peter

    2016-01-01

    This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level – e.g., dynamic causal models – and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570

  10. Simulating Sediment Transport Processes in San Francisco Bay Using Coupled Hydrodynamic, Wave, and Sediment Transport Models

    NASA Astrophysics Data System (ADS)

    Bever, A. J.; MacWilliams, M.

    2012-12-01

    Under the conceptual model of sediment transport in San Pablo Bay, a sub-embayment of San Francisco Bay, proposed by Krone (1979), sediment typically enters San Pablo Bay during large winter and spring flows and is redistributed during summer conditions through wind wave resuspension and transport by tidal currents. A detailed understanding of how the waves and tides redistribute sediment within San Francisco Bay is critical for predicting how future sea level rise and a reduction in the sediment supply to the Bay will impact existing marsh and mudflat habitat, tidal marsh restoration projects, and ongoing maintenance dredging of the navigation channels. The three-dimensional UnTRIM San Francisco Bay-Delta Model was coupled with the Simulating WAves Nearshore (SWAN) wave model and the SediMorph morphological model, to develop a three-dimensional hydrodynamic, wind wave, and sediment transport model of the San Francisco Bay and the Sacramento-San Joaquin Delta. Numerical simulations of sediment resuspension due to tidal currents and wind waves and the subsequent transport of this sediment by tidal currents are used to quantify the spatial and temporal variability of sediment fluxes on the extensive shoals in San Pablo Bay under a range of tidal and wind conditions. The results demonstrate that suspended sediment concentration and sediment fluxes within San Pablo Bay are a complex product of tides and waves interacting spatially throughout the Bay, with concentrations responding to local resuspension and sediment advection. Sediment fluxes between the San Pablo Bay shoals and the deeper channel are highest during spring tides, and are elevated for up to a week following wave events, even though the greatest influence of the wave event occurs abruptly.

  11. Spatial estimation from remotely sensed data via empirical Bayes models

    NASA Technical Reports Server (NTRS)

    Hill, J. R.; Hinkley, D. V.; Kostal, H.; Morris, C. N.

    1984-01-01

    Multichannel satellite image data, available as LANDSAT imagery, are recorded as a multivariate time series (four channels, multiple passovers) in two spatial dimensions. The application of parametric empirical Bayes theory to classification of, and estimating the probability of, each crop type at each of a large number of pixels is considered. This theory involves both the probability distribution of imagery data, conditional on crop types, and the prior spatial distribution of crop types. For the latter Markov models indexed by estimable parameters are used. A broad outline of the general theory reveals several questions for further research. Some detailed results are given for the special case of two crop types when only a line transect is analyzed. Finally, the estimation of an underlying continuous process on the lattice is discussed which would be applicable to such quantities as crop yield.

  12. Spatially and Temporally Detailed Modeling of Water Quality in Narragansett Bay

    EPA Science Inventory

    Nutrient loading to Narragansett Bay has led to eutrophication, resulting in hypoxia and anoxia, finfish and shellfish kills, loss of seagrass, and reductions in the recreational and economic value of the Bay. We are developing a model that simulates the effects of external nutri...

  13. Spatially and Temporally Detailed Modeling of Water Quality in Narragansett Bay (AGU)

    EPA Science Inventory

    Nutrient loading to Narragansett Bay has led to eutrophication, resulting in hypoxia and anoxia, finfish and shellfish kills, loss of seagrass, and reductions in the recreational and economic value of the Bay. We are developing a model that simulates the effects of external nutri...

  14. Naive CD8 T-Cells Initiate Spontaneous Autoimmunity to a Sequestered Model Antigen of the Central Nervous System

    ERIC Educational Resources Information Center

    Na, Shin-Young; Cao, Yi; Toben, Catherine; Nitschke, Lars; Stadelmann, Christine; Gold, Ralf; Schimpl, Anneliese; Hunig, Thomas

    2008-01-01

    In multiple sclerosis, CD8 T-cells are thought play a key pathogenetic role, but mechanistic evidence from rodent models is limited. Here, we have tested the encephalitogenic potential of CD8 T-cells specific for the model antigen ovalbumin (OVA) sequestered in oligodendrocytes as a cytosolic molecule. We show that in these "ODC-OVA" mice, the…

  15. A Variational Bayes Approach to the Analysis of Occupancy Models.

    PubMed

    Clark, Allan E; Altwegg, Res; Ormerod, John T

    2016-01-01

    Detection-nondetection data are often used to investigate species range dynamics using Bayesian occupancy models which rely on the use of Markov chain Monte Carlo (MCMC) methods to sample from the posterior distribution of the parameters of the model. In this article we develop two Variational Bayes (VB) approximations to the posterior distribution of the parameters of a single-season site occupancy model which uses logistic link functions to model the probability of species occurrence at sites and of species detection probabilities. This task is accomplished through the development of iterative algorithms that do not use MCMC methods. Simulations and small practical examples demonstrate the effectiveness of the proposed technique. We specifically show that (under certain circumstances) the variational distributions can provide accurate approximations to the true posterior distributions of the parameters of the model when the number of visits per site (K) are as low as three and that the accuracy of the approximations improves as K increases. We also show that the methodology can be used to obtain the posterior distribution of the predictive distribution of the proportion of sites occupied (PAO). PMID:26928878

  16. Modeling Land Use Change in the Chesapeake Bay Watershed

    NASA Astrophysics Data System (ADS)

    Claire, J. A.; Goetz, S. J.; Bockstael, N.

    2003-12-01

    Low density, decentralized residential and commercial development is increasingly the dominant pattern of exurban land use in many developed countries, particularly the United States. The term "sprawl" is now commonly used to describe this form of development, the environmental and quality-of-life impacts of which are becoming central to debates over land use in urban and suburban areas. Continued poor health of the Chesapeake Bay, located in the Mid-Atlantic region of the United States, is due in part to disruptions in the hydrological system caused by urban and suburban development throughout the 167,000 square kilometer watershed. We present results of a spatial predictive model of land use change based on cellular automata (SLEUTH), which was calibrated using high resolution (30m cell size) maps of the built environment derived from Landsat ETM+ imagery for the period 1986-2000. The model was applied to a 23,740 square kilometer area centered on Washington DC - Baltimore MD, and predictions were made out to 2030 assuming three different policy scenarios (current trends, managed growth, and "sustainable"). Accuracy of the model was assessed at three scales (pixel, watershed and county) and overall strengths and weaknesses of the model are presented, particularly in comparison to other econometric modeling approaches.

  17. A Variational Bayes Approach to the Analysis of Occupancy Models

    PubMed Central

    Clark, Allan E.; Altwegg, Res; Ormerod, John T.

    2016-01-01

    Detection-nondetection data are often used to investigate species range dynamics using Bayesian occupancy models which rely on the use of Markov chain Monte Carlo (MCMC) methods to sample from the posterior distribution of the parameters of the model. In this article we develop two Variational Bayes (VB) approximations to the posterior distribution of the parameters of a single-season site occupancy model which uses logistic link functions to model the probability of species occurrence at sites and of species detection probabilities. This task is accomplished through the development of iterative algorithms that do not use MCMC methods. Simulations and small practical examples demonstrate the effectiveness of the proposed technique. We specifically show that (under certain circumstances) the variational distributions can provide accurate approximations to the true posterior distributions of the parameters of the model when the number of visits per site (K) are as low as three and that the accuracy of the approximations improves as K increases. We also show that the methodology can be used to obtain the posterior distribution of the predictive distribution of the proportion of sites occupied (PAO). PMID:26928878

  18. HABITAT ASSESSMENT MODELS FOR BAY SCALLOP, ARGOPECTEN IRRADIANS

    EPA Science Inventory

    Bay scallops (Argopecten irradians) inhabit shallow subtidal habitats along the Atlantic coast of the United States and require settlement substrates, such as submerged aquatic vegetation (SAV), for their early juvenile stages. The short lifespan of bay scallops (1-2 yr) coupled...

  19. Development of a Hydrodynamic and Transport model of Bellingham Bay in Support of Nearshore Habitat Restoration

    SciTech Connect

    Wang, Taiping; Yang, Zhaoqing; Khangaonkar, Tarang

    2010-04-22

    In this study, a hydrodynamic model based on the unstructured-grid finite volume coastal ocean model (FVCOM) was developed for Bellingham Bay, Washington. The model simulates water surface elevation, velocity, temperature, and salinity in a three-dimensional domain that covers the entire Bellingham Bay and adjacent water bodies, including Lummi Bay, Samish Bay, Padilla Bay, and Rosario Strait. The model was developed using Pacific Northwest National Laboratory’s high-resolution Puget Sound and Northwest Straits circulation and transport model. A sub-model grid for Bellingham Bay and adjacent coastal waters was extracted from the Puget Sound model and refined in Bellingham Bay using bathymetric light detection and ranging (LIDAR) and river channel cross-section data. The model uses tides, river inflows, and meteorological inputs to predict water surface elevations, currents, salinity, and temperature. A tidal open boundary condition was specified using standard National Oceanic and Atmospheric Administration (NOAA) predictions. Temperature and salinity open boundary conditions were specified based on observed data. Meteorological forcing (wind, solar radiation, and net surface heat flux) was obtained from NOAA real observations and National Center for Environmental Prediction North American Regional Analysis outputs. The model was run in parallel with 48 cores using a time step of 2.5 seconds. It took 18 hours of cpu time to complete 26 days of simulation. The model was calibrated with oceanographic field data for the period of 6/1/2009 to 6/26/2009. These data were collected specifically for the purpose of model development and calibration. They include time series of water-surface elevation, currents, temperature, and salinity as well as temperature and salinity profiles during instrument deployment and retrieval. Comparisons between model predictions and field observations show an overall reasonable agreement in both temporal and spatial scales. Comparisons of

  20. Spatially and Temporally Detailed Modeling of Water Quality in Narragansett Bay

    NASA Astrophysics Data System (ADS)

    Charlestra, L.; Dettmann, E. H.; Abdelrhman, M.

    2014-12-01

    Nutrient loading to Narragansett Bay has led to eutrophication, resulting in hypoxia and anoxia, finfish and shellfish kills, loss of seagrass, and reductions in the recreational and economic value of the Bay. We are developing a model that simulates the effects of external nutrient and hydrologic loading on water quality in Narragansett Bay. Extensive field monitoring programs and process studies by the Narragansett Bay Commission, Federal and State agencies, municipalities, and university groups have been measuring physical parameters, nutrient concentrations and other water quality parameters in the Bay and its tributaries, nutrient inputs from wastewater treatment facilities, and process kinetic parameters. We are using data for existing nutrient concentrations, river flow and wastewater treatment facility effluent flow to estimate nutrient loading for non-sampled days using the U.S. Geological Survey's Load Estimator (LOADEST) software. The time-variable data so generated will be used as input to the U.S. Environmental Protection Agency's WASPEUTRO model linked with a calibrated three-dimensional hydrodynamic model, the Environmental Fluid Dynamics Code (EFDC). The primary objectives of the modeling effort are to simulate the effects of nutrient loading on dissolved oxygen concentrations and chlorophyll-a, an important parameter for water clarity and seagrass viability, to estimate the sensitivity of the Bay to changes in nutrient loading and freshwater inflow, and to explore the potential effects of management actions and other factors such as climate change on these water quality parameters in the Bay.

  1. Chesapeake Bay ecosystem modeling program. Technical synthesis report 1993-94

    SciTech Connect

    Brandt, S.B.; Boynton, W.R.; Kemp, W.M.; Wetzel, R.; Bartleson, R.

    1995-03-01

    ;Contents: Ecosystem models for management; Ecosystem regession models; Patuxent River Sav-Littoral Ecosystem Process Model; Lower Chesapeake Bay Polyhaline Sav Model; Emergent Intertidal Marsh Process Model; Plankton-Benthos Ecosystem Process Model; Fish Bioenergetics Models; Linking Water Quality with Fish Habitat; Data Visualization; Publications and Scientific Presentations Resulting From This Research.

  2. Naive Theories of Social Groups

    ERIC Educational Resources Information Center

    Rhodes, Marjorie

    2012-01-01

    Four studies examined children's (ages 3-10, Total N = 235) naive theories of social groups, in particular, their expectations about how group memberships constrain social interactions. After introduction to novel groups of people, preschoolers (ages 3-5) reliably expected agents from one group to harm members of the other group (rather than…

  3. Using Bayes Model Averaging for Wind Power Forecasts

    NASA Astrophysics Data System (ADS)

    Preede Revheim, Pål; Beyer, Hans Georg

    2014-05-01

    For operational purposes predictions of the forecasts of the lumped output of groups of wind farms spread over larger geographic areas will often be of interest. A naive approach is to make forecasts for each individual site and sum them up to get the group forecast. It is however well documented that a better choice is to use a model that also takes advantage of spatial smoothing effects. It might however be the case that some sites tends to more accurately reflect the total output of the region, either in general or for certain wind directions. It will then be of interest giving these a greater influence over the group forecast. Bayesian model averaging (BMA) is a statistical post-processing method for producing probabilistic forecasts from ensembles. Raftery et al. [1] show how BMA can be used for statistical post processing of forecast ensembles, producing PDFs of future weather quantities. The BMA predictive PDF of a future weather quantity is a weighted average of the ensemble members' PDFs, where the weights can be interpreted as posterior probabilities and reflect the ensemble members' contribution to overall forecasting skill over a training period. In Revheim and Beyer [2] the BMA procedure used in Sloughter, Gneiting and Raftery [3] were found to produce fairly accurate PDFs for the future mean wind speed of a group of sites from the single sites wind speeds. However, when the procedure was attempted applied to wind power it resulted in either problems with the estimation of the parameters (mainly caused by longer consecutive periods of no power production) or severe underestimation (mainly caused by problems with reflecting the power curve). In this paper the problems that arose when applying BMA to wind power forecasting is met through two strategies. First, the BMA procedure is run with a combination of single site wind speeds and single site wind power production as input. This solves the problem with longer consecutive periods where the input data

  4. Circulation and effluent dilution modeling in Massachusetts Bay : model implementation, verification and results

    USGS Publications Warehouse

    Signell, Richard P.; Jenter, Harry L.; Blumberg, Alan F.

    1996-01-01

    A three-dimensional hydrodynamic model was developed as part of a cooperative U.S. Geological Survey/Massachusetts Water Resources Authority program to study contaminated sediment accumulation and transport in Massachusetts Bay. This report details the development of the model and assesses how well the model represents observed currents and water properties in the bay. It also summarizes circulation and comparative effluent dilution simulations from existing and future Boston sewage outfalls over a three-year period from October 1, 1989 to December 31, 1992. The ECOM-si model, a semi-implicit version of the Blumberg and Mellor (1987) Estuarine, Coastal and Ocean Model, is shown to reproduce many of the important hydrodynamical features of Massachusetts Bay: the seasonal evolution of the pycnocline, the mean flow pattern, and the strength of sub-tidal current fluctuations. Throughout the simulation period, during both vertically well-mixed and stratified conditions, the seasonal statistics of observed currents are well-represented by the model. The model is therefore appropriate for studying the average dilution of sewage effluent and other continuously discharged substances over seasonal time scales. The ability of the model to reproduce individual flow events varies with season and location within the bay. Flow events during unstratified conditions in western Massachusetts Bay are particularly well-represented, indicating that the model is appropriate for studying processes such as the transport of suspended material from the future outfall site due to winter storms. Individual flow events during stratified conditions and in the offshore Stellwagen Bank region, however, are less well-represented due to small length scales (caused by upwelling and river discharge events) coupled with insufficient data to specify open boundary forcing from the Gulf of Maine. Thus while the model might be used to answer issues such as the frequency with which Gulf of Maine river

  5. Study on the Calculation Models of Bus Delay at Bays Using Queueing Theory and Markov Chain

    PubMed Central

    Sun, Li; Sun, Shao-wei; Wang, Dian-hai

    2015-01-01

    Traffic congestion at bus bays has decreased the service efficiency of public transit seriously in China, so it is crucial to systematically study its theory and methods. However, the existing studies lack theoretical model on computing efficiency. Therefore, the calculation models of bus delay at bays are studied. Firstly, the process that buses are delayed at bays is analyzed, and it was found that the delay can be divided into entering delay and exiting delay. Secondly, the queueing models of bus bays are formed, and the equilibrium distribution functions are proposed by applying the embedded Markov chain to the traditional model of queuing theory in the steady state; then the calculation models of entering delay are derived at bays. Thirdly, the exiting delay is studied by using the queueing theory and the gap acceptance theory. Finally, the proposed models are validated using field-measured data, and then the influencing factors are discussed. With these models the delay is easily assessed knowing the characteristics of the dwell time distribution and traffic volume at the curb lane in different locations and different periods. It can provide basis for the efficiency evaluation of bus bays. PMID:25759720

  6. Study on the calculation models of bus delay at bays using queueing theory and Markov chain.

    PubMed

    Sun, Feng; Sun, Li; Sun, Shao-Wei; Wang, Dian-Hai

    2015-01-01

    Traffic congestion at bus bays has decreased the service efficiency of public transit seriously in China, so it is crucial to systematically study its theory and methods. However, the existing studies lack theoretical model on computing efficiency. Therefore, the calculation models of bus delay at bays are studied. Firstly, the process that buses are delayed at bays is analyzed, and it was found that the delay can be divided into entering delay and exiting delay. Secondly, the queueing models of bus bays are formed, and the equilibrium distribution functions are proposed by applying the embedded Markov chain to the traditional model of queuing theory in the steady state; then the calculation models of entering delay are derived at bays. Thirdly, the exiting delay is studied by using the queueing theory and the gap acceptance theory. Finally, the proposed models are validated using field-measured data, and then the influencing factors are discussed. With these models the delay is easily assessed knowing the characteristics of the dwell time distribution and traffic volume at the curb lane in different locations and different periods. It can provide basis for the efficiency evaluation of bus bays. PMID:25759720

  7. Flexible Modeling of Epidemics with an Empirical Bayes Framework

    PubMed Central

    Brooks, Logan C.; Farrow, David C.; Hyun, Sangwon; Tibshirani, Ryan J.; Rosenfeld, Roni

    2015-01-01

    Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic’s behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the “Predict the Influenza Season Challenge”, with the task of predicting key epidemiological measures for the 2013–2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013–2014 U.S. influenza season, and compare the framework’s cross-validated prediction error on historical data to

  8. Modelling residence-time response to freshwater input in Apalachicola Bay, Florida, USA

    NASA Astrophysics Data System (ADS)

    Huang, Wenrui; Spaulding, M.

    2002-10-01

    Residence time of an estuary can be used to estimate the rate of removal of freshwater and pollutants from river inflow. In this study, a calibrated three-dimensional hydrodynamic model was used to determine residence time in response to the change of freshwater input in Apalachicola Bay. The bay is about 40 km long and 7 km wide, with an average 3 m water depth. Through hydrodynamic model simulations, the spatial and temporal salinity and the total freshwater volume in the bay were calculated. Then the freshwater fraction method was used to estimate the residence time. Results indicate that the residence time in Apalachicola Bay typically ranges between 3 and 10 days for the daily freshwater input ranging from 177 m3/s to 4561 m3/s. Regression analysis of model results shows that an exponential regression equation can be used to correlate the estuarine residence time to changes of freshwater input.

  9. Regional Air Toxics Modeling in California's San Francisco Bay Area

    NASA Astrophysics Data System (ADS)

    Martien, P. T.; Tanrikulu, S.; Tran, C.; Fairley, D.; Jia, Y.; Fanai, A.; Reid, S.; Yarwood, G.; Emery, C.

    2011-12-01

    Regional toxics modeling conducted for California's San Francisco Bay Area (SFBA) estimated potential cancer risk from diesel particulate matter (DPM) and four key reactive toxic gaseous pollutants (1,3-butadiene, benzene, formaldehyde, and acetaldehyde). Concentrations of other non-cancerous gaseous toxic air contaminants, including acrolein, were also generated. In this study, meteorological fields generated from July and December periods in 2000 and emissions from 2005 provided inputs to a three-dimensional air quality model at high spatial resolution (1x1 km^2 grid), from which a baseline set of annual risk values was estimated. Simulated risk maps show highest annual average DPM concentrations and cancer risks were located near and downwind of major freeways and near the Port of Oakland, a major container port in the area. Population weighted risks, using 2000 census data, were found to be highest in highly urbanized areas adjacent to significant DPM sources. For summer, the ratio of mean measured elemental carbon to mean modeled DPM was 0.78, conforming roughly to expectations. But for winter the ratio is 1.13, suggesting other sources of elemental carbon, such as wood smoke, are important. Simulated annual estimates for benzene and 1-3, butadiene compared well to measured annual estimates. Simulated acrolein and formaldehyde significantly under-predicted observed values. Simulations repeated using projected 2015 toxic emissions predicted that potential cancer risk dropped significantly in all areas throughout the SFBA. Emissions estimates for 2015 included the State of California's recently adopted on-road truck rule. Emission estimates of DPM are projected to drop about 70% between 2005 and 2015 in the SFBA, with a commensurate reduction in potential cancer risks. However, due to projected shifts in population during this period, with urban densification close to DPM sources outpacing emission reductions, there are some areas where population-weighted risks

  10. Storm tide simulation in the Chesapeake Bay using an unstructured grid model

    NASA Astrophysics Data System (ADS)

    Shen, Jian; Wang, Harry; Sisson, Mac; Gong, Wenping

    2006-06-01

    Hurricane Isabel made landfall near Drum Inlet, North Carolina on September 18, 2003 (UTC 17:00). Although it was classified as only a Category 2 storm (Saffir-Simpson scale), Hurricane Isabel had a significant impact on the Chesapeake Bay with a 1.5-2.0 m storm surge (above mean sea level), and was dubbed the "100-year storm". A high-resolution unstructured grid model (UnTRIM) was applied to simulate storm tide in the Chesapeake Bay. The application of an unstructured grid in the Bay offers the greatest flexibilities in representing complex estuarine geometry near the coast and encompassing a large modeling domain necessary for storm surge simulation. The resulting mesh has a total of 239,541 surface elements. The model was forced by 9 tidal harmonic constituents at the open boundary and a wind field generated by a parametric wind model. A hindcast simulation of Hurricane Isabel captures both peak storm tide and surge evolution in various sites of the Bay. Model diagnostic studies indicate that the high surge occurring in the upper Bay regions was mainly caused by the forced southerly wind, whereas the offshore surge and both the northeasterly and southeasterly winds influenced the lower Bay region more significantly.

  11. The outflow of radionuclides from Novaya Zemlya bays--modeling and monitoring strategies.

    PubMed

    Harms, I H; Povinec, P P

    1999-09-30

    Hydrodynamic model results are used to evaluate possible monitoring strategies for a continuous survey of underwater dump sites. The Hamburg Shelf Ocean Model (HAMSOM) is applied to Abrosimov Bay and forced with realistic, transient wind fields and air temperatures. The three-dimensional circulation model is coupled to a dynamic-thermodynamic ice model that accounts for surface heat fluxes, fractional ice cover and ice thickness. Model results show significant variations in the bay circulation due to a pronounced seasonality in the wind forcing and the ice cover. The circulation is weakest in early summer when wind speeds are low and the ice still covers most parts of the bay. In autumn, circulation and flushing of the bay is most enhanced, due to increasing wind speeds and the absence of an ice cover. Dispersion scenarios were carried out assuming a leakage at dumped objects. During most of the year the obtained tracer concentrations in the bay are higher in the upper layers than close to the bottom, indicating an outflow at the surface and a compensatory inflow below. This general pattern is only reversed during spring and early summer, when the wind directions change. Since ice problems make it almost impossible to monitor surface waters or even the whole water column in a shallow bay, the only way to install a monitoring system, is at the bottom of the bay, as close as possible to dumped objects. Data transmission via satellite or radio could be realized from a small station located on the bay's edge. PMID:10568276

  12. A modeling study on the response of Chesapeake Bay to hurricane events of Floyd and Isabel

    NASA Astrophysics Data System (ADS)

    Cho, Kyoung-Ho; Wang, Harry V.; Shen, Jian; Valle-Levinson, Arnoldo; Teng, Yi-cheng

    2012-06-01

    The response of Chesapeake Bay to forcing from two hurricanes is investigated using an unstructured-grid three-dimensional hydrodynamic model SELFE. The model domain includes Chesapeake Bay, its tributaries, and the extended continental shelf in the mid-Atlantic Bight. The hurricanes chosen for the study are Hurricane Floyd (1999) and Hurricane Isabel (2003), both of which made landfall within 100 km of the mouth of the Bay. The model results agree reasonably well with field observations of water level, velocity, and salinity. From the Bay's water level response to the hurricanes, it was found that the storm surge in the Bay has two distinct stages: an initial stage set up by the remote winds and the second stage - a primary surge induced by the local winds. For the initial stage, the rising of the coastal sea level was setup by the remote wind of both hurricanes similarly, but for the second stage, the responses to the two hurricanes' local winds are significantly different. Hurricane Floyd was followed by down-Bay winds that canceled the initial setup and caused a set-down from the upper Bay. Hurricane Isabel, on the other hand, was followed by up-Bay winds, which reinforced the initial setup and continued to rise up against the head of the Bay. From the perspective of volume and salt fluxes, it is evident that an oceanic saltwater influx is pushed into the Bay from the continental shelf by the remote wind fields in the initial stages of the storm surge for both Floyd and Isabel. In the second stage after the hurricane made landfall, the Bay's local wind plays a key role in modulating the salinity and velocity fields through vertical mixing and longitudinal salt transport. Controlled numerical experiments are conducted in order to identify and differentiate the roles played by the local wind in stratified and destratified conditions. Down-estuary local wind stress (of Hurricane Floyd-type) tends to enhance stratification under moderate winds, but exhibits an

  13. Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

    NASA Astrophysics Data System (ADS)

    Irby, Isaac D.; Friedrichs, Marjorie A. M.; Friedrichs, Carl T.; Bever, Aaron J.; Hood, Raleigh R.; Lanerolle, Lyon W. J.; Li, Ming; Linker, Lewis; Scully, Malcolm E.; Sellner, Kevin; Shen, Jian; Testa, Jeremy; Wang, Hao; Wang, Ping; Xia, Meng

    2016-04-01

    As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient.

  14. Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

    NASA Astrophysics Data System (ADS)

    Irby, I. D.; Friedrichs, M. A. M.; Friedrichs, C. T.; Bever, A. J.; Hood, R. R.; Lanerolle, L. W. J.; Scully, M. E.; Sellner, K.; Shen, J.; Testa, J.; Li, M.; Wang, H.; Wang, P.; Linker, L.; Xia, M.

    2015-12-01

    As three-dimensional (3-D) aquatic ecosystem models are becoming used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, two-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density

  15. Exploring the sensitivities of crenulate bay shorelines to wave climates using a new vector-based one-line model

    NASA Astrophysics Data System (ADS)

    Hurst, Martin D.; Barkwith, Andrew; Ellis, Michael A.; Thomas, Chris W.; Murray, A. Brad

    2015-12-01

    We use a new exploratory model that simulates the evolution of sandy coastlines over decadal to centennial timescales to examine the behavior of crenulate-shaped bays forced by differing directional wave climates. The model represents the coastline as a vector in a Cartesian reference frame, and the shoreface evolves relative to its local orientation, allowing simulation of coasts with high planform-curvature. Shoreline change is driven by gradients in alongshore transport following newly developed algorithms that facilitate dealing with high planform-curvature coastlines. We simulated the evolution of bays from a straight coast between two fixed headlands with no external sediment inputs to an equilibrium condition (zero net alongshore sediment flux) under an ensemble of directional wave climate conditions. We find that planform bay relief increases with obliquity of the mean wave direction, and decreases with the spread of wave directions. Varying bay size over 2 orders of magnitude (0.1-16 km), the model predicts bay shape to be independent of bay size. The time taken for modeled bays to attain equilibrium was found to scale with the square of the distance between headlands, so that, all else being equal, small bays are likely to respond to and recover from perturbations more rapidly (over just a few years) compared to large bays (hundreds of years). Empirical expressions predicting bay shape may be misleading if used to predict their behavior over planning timescales.

  16. Modeling spatial and temporal variation of suitable nursery habitats for Atlantic sturgeon in the Chesapeake Bay

    NASA Astrophysics Data System (ADS)

    Niklitschek, Edwin J.; Secor, David H.

    2005-07-01

    For rare and endangered species, bioenergetics modeling can represent a valuable approach for understanding issues of habitat value and connectivity among potential habitats within nurseries in restoration programs. We used multivariable bioenergetics and survival models for Atlantic sturgeon to generate spatially explicit maps of potential production in the Chesapeake Bay. For the period 1993-2002, spatial and temporal patterns in water quality effects (temperature, dissolved oxygen [DO] and salinity) on potential production were evaluated. In addition, two forecasted scenarios were modeled: one implementing newly revised U.S. Environmental Protection Agency (EPA) DO-criteria for the Chesapeake Bay, and the other assuming a bay-wide increase of 1 °C due to an underlying trend in regional climate. Atlantic sturgeon's low (survival/growth) tolerance to temperatures >28 °C was a critical constraint during their first 1-2 summers of life. Hatched in freshwater (spring to mid-summer), young-of-the-year were predicted to occupy cooler (deeper) areas as temperature approached sub-lethal levels. While most thermal refuges were located down-estuary, a large fraction of potential refuges were unsuitable due to persistent hypoxia and/or salinity levels beyond the limited osmoregulatory capabilities of early juvenile Atlantic sturgeon. As a result, suitable summer habitats for juvenile Atlantic sturgeons in the Chesapeake Bay were predicted to be spatially restricted and variable between years, ranging from 0 to 35% of the modeled bay surface area. In critical (drought) years, almost no summer habitat was predicted to be available for juvenile Atlantic sturgeon. Value and size of nursery habitat was highly sensitive to climatic oscillations and anthropogenic interventions affecting freshwater inflow, water temperature and/or DO. Achieving EPA DO-criteria for the Chesapeake Bay was predicted to increase total suitable habitat by 13% for an average year, while increasing

  17. Estimation of freshwater runoff into Glacier Bay, Alaska and incorporation into a tidal circulation model

    NASA Astrophysics Data System (ADS)

    Hill, D. F.; Ciavola, S. J.; Etherington, L.; Klaar, M. J.

    2009-03-01

    Freshwater discharge is one of the most critical parameters driving water properties within fjord estuarine environments. To date, however, little attention has been paid to the issue of freshwater runoff into Glacier Bay, a recently deglaciated fjord in southeastern Alaska. Estimates of discharge into Glacier Bay and the outlying waters of Icy Strait and Cross Sound are therefore presented. Existing regression equations for southcentral and southeastern coastal Alaska are applied to Glacier Bay to arrive at the estimates. A limited set of acoustic Doppler current profiler (ADCP) measurements generally support the predictions of the regression equations. The results suggest that discharge into the bay ranges from a few hundred to a few thousand m 3 s -1 during a typical year. Peak discharges can be much higher, approximately 10,000 m 3 s -1 for the 10-year flow event. Estimates of the seasonal variation of discharge are also obtained and reveal a broad peak during the summer months. The hydrologic estimates are then coupled with a barotropic tidal circulation model (ADCIRC - ADvanced CIRCulation model) of Glacier Bay waters. This coupling is achieved by treating the entire coastline boundary as a non-zero normal-flux boundary. Numerical simulations with the inclusion of runoff allow for the estimation of parameters such as the estuarine Richardson number, which is an indicator of estuary mixing. Simulations also allow for the comparison of Lagrangian trajectories in the presence and absence of runoff. The results of the present paper are intended to complement a comprehensive and recently-published dataset on the oceanographic conditions of Glacier Bay. The results will also guide continuing efforts to model three-dimensional circulations in the bay.

  18. Wind-forced circulation model and water exchanges through the channel in the Bay of Toulon

    NASA Astrophysics Data System (ADS)

    Dufresne, Christiane; Duffa, Céline; Rey, Vincent

    2014-01-01

    A hydrodynamic model of the Bay of Toulon has been developed for use as a post-accident radionuclide dispersion simulation tool. Located in a Mediterranean urban area, the Bay of Toulon is separated into two basins by a 1.4-km long seawall. The Little Bay is semi-enclosed and connected to the Large Bay by a fairway channel. This channel is the site of significant water mass exchange as a result of both wind-driven currents and bathymetry. It is therefore a focal point for marine contamination. As part of the model calibration and validation process, the first step consisted of studying the water mass exchange between the two basins. An Acoustic Doppler Current Profiler was moored in the channel for 1 year. The present study analyses in situ data to determine the current intensity and direction, and also to better understand the vertical current profile, which is highly correlated with meteorological forcing. Comparisons of model-generated and measured data are presented, and various atmospheric forcing datasets are used to enhance computed results. It appears that accurate meteorological forcing data is needed to enhance the accuracy of the hydrodynamic model. This channel is an important location for water mass renewal in the Bay of Toulon, and model results are used to quantify these exchanges. The mean calculated annual water exchange time is approximately 3.4 days. However, this duration is strongly wind dependent and shortens during windy winter months. It ranges from 1.5 days during strong wind periods to 7.5 days during calm weather. Residence time values calculated through tracer dispersion modelling after release at the back of the Little Bay are found to be comparable to the mean exchange time values, especially for windy conditions.

  19. MASS BALANCE MODELLING OF PCBS IN THE FOX RIVER/GREEN BAY COMPLEX

    EPA Science Inventory

    The USEPA Office of Research and Development developed and applies a multimedia, mass balance modeling approach to the Fox River/Green Bay complex to aid managers with remedial decision-making. The suite of models were applied to PCBs due to the long history of contamination and ...

  20. MATHEMATICAL MODELS OF WATER QUALITY IN LARGE LAKES. PART 1: LAKE HURON AND SAGINAW BAY

    EPA Science Inventory

    This research was undertaken to develop and apply a mathematical model of the water quality in large lakes, particularly Lake Huron and Saginaw Bay and Lake Erie. A mathematical model of phytoplankton biomass was developed which incorporates both phytoplankton and zooplankton as ...

  1. Nowcast model for hazardous material spill prevention and response, San Francisco Bay, California

    USGS Publications Warehouse

    Cheng, Ralph T.; Wilmot, Wayne L.; Galt, Jerry A.

    1997-01-01

    The National Oceanic and Atmospheric Administration (NOAA) installed the Physical Oceanographic Real-time System (PORTS) in San Francisco Bay, California, to provide real-time observations of tides, tidal currents, and meteorological conditions to, among other purposes, guide hazardous material spill prevention and response. Integrated with nowcast modeling techniques and dissemination of real-time data and the nowcasting results through the Internet on the World Wide Web, emerging technologies used in PORTS for real-time data collection forms a nowcast modeling system. Users can download tides and tidal current distribution in San Francisco Bay for their specific applications and/or for further analysis.

  2. A nowcast model for tides and tidal currents in San Francisco Bay, California

    USGS Publications Warehouse

    Cheng, Ralph T.; Smith, Richard E.

    1998-01-01

    National Oceanographic and Atmospheric Administration (NOAA) installed Physical Oceanographic Real-Time System (PORTS) in San Francisco Bay, California to provide observations of tides, tidal currents, and meteorological conditions. PORTS data are used for optimizing vessel operations, increasing margin of safety for navigation, and guiding hazardous material spill prevention and response. Because tides and tidal currents in San Francisco Bay are extremely complex, limited real-time observations are insufficient to provide spatial resolution for variations of tides and tidal currents. To fill the information gaps, a highresolution, robust, semi-implicit, finite-difference nowcast numerical model has been implemented for San Francisco Bay. The model grid and water depths are defined on coordinates based on Mercator projection so the model outputs can be directly superimposed on navigation charts. A data assimilation algorithm has been established to derive the boundary conditions for model simulations. The nowcast model is executed every hour continuously for tides and tidal currents starting from 24 hours before the present time (now) covering a total of 48 hours simulation. Forty-eight hours of nowcast model results are available to the public at all times through the World Wide Web (WWW). Users can view and download the nowcast model results for tides and tidal current distributions in San Francisco Bay for their specific applications and for further analysis.

  3. Modelling larval dispersal of the king scallop ( Pecten maximus) in the English Channel: examples from the bay of Saint-Brieuc and the bay of Seine

    NASA Astrophysics Data System (ADS)

    Nicolle, Amandine; Dumas, Franck; Foveau, Aurélie; Foucher, Eric; Thiébaut, Eric

    2013-06-01

    The king scallop ( Pecten maximus) is one of the most important benthic species of the English Channel as it constitutes the first fishery in terms of landings in this area. To support strategies of spatial fishery management, we develop a high-resolution biophysical model to study scallop dispersal in two bays along the French coasts of the English Channel (i.e. the bay of Saint-Brieuc and the bay of Seine) and to quantify the relative roles of local hydrodynamic processes, temperature-dependent planktonic larval duration (PLD) and active swimming behaviour (SB). The two bays are chosen for three reasons: (1) the distribution of the scallop stocks in these areas is well known from annual scallop stock surveys, (2) these two bays harbour important fisheries and (3) scallops in these two areas present some differences in terms of reproductive cycle and spawning duration. The English Channel currents and temperature are simulated for 10 years (2000-2010) with the MARS-3D code and then used by the Lagrangian module of MARS-3D to model the transport. Results were analysed in terms of larval distribution at settlement and connectivity rates. While larval transport in the two bays depended both on the tidal residual circulation and the wind-induced currents, the relative role of these two hydrodynamic processes varied among bays. In the bay of Saint-Brieuc, the main patterns of larval dispersal were due to tides, the wind being only a source of variability in the extent of larval patch and the local retention rate. Conversely, in the bay of Seine, wind-induced currents altered both the direction and the extent of larval transport. The main effect of a variable PLD in relation to the thermal history of each larva was to reduce the spread of dispersal and consequently increase the local retention by about 10 % on average. Although swimming behaviour could influence larval dispersal during the first days of the PLD when larvae are mainly located in surface waters, it has a

  4. Reconciling Longitudinal Naive T-Cell and TREC Dynamics during HIV-1 Infection

    PubMed Central

    Mugwagwa, Tendai; de Boer, Anne Bregje; Otto, Sigrid A.; Hazenberg, Mette D.; Tesselaar, Kiki; de Boer, Rob J.; Borghans, José A. M.

    2016-01-01

    Naive T cells in untreated HIV-1 infected individuals have a reduced T-cell receptor excision circle (TREC) content. Previous mathematical models have suggested that this is due to increased naive T-cell division. It remains unclear, however, how reduced naive TREC contents can be reconciled with a gradual loss of naive T cells in HIV-1 infection. We performed longitudinal analyses in humans before and after HIV-1 seroconversion, and used a mathematical model to investigate which processes could explain the observed changes in naive T-cell numbers and TRECs during untreated HIV-1 disease progression. Both CD4+ and CD8+ naive T-cell TREC contents declined biphasically, with a rapid loss during the first year and a much slower loss during the chronic phase of infection. While naive CD8+ T-cell numbers hardly changed during follow-up, naive CD4+ T-cell counts continually declined. We show that a fine balance between increased T-cell division and loss in the peripheral naive T-cell pool can explain the observed short- and long-term changes in TRECs and naive T-cell numbers, especially if T-cell turnover during the acute phase is more increased than during the chronic phase of infection. Loss of thymic output, on the other hand, does not help to explain the biphasic loss of TRECs in HIV infection. The observed longitudinal changes in TRECs and naive T-cell numbers in HIV-infected individuals are most likely explained by a tight balance between increased T-cell division and death, suggesting that these changes are intrinsically linked in HIV infection. PMID:27010200

  5. Sediment deposition from Tropical Storm Lee in the upper Chesapeake Bay: field observations and model predictions

    NASA Astrophysics Data System (ADS)

    Palinkas, C. M.; Halka, J. P.; Li, M.; Sanford, L. P.; Cheng, P.

    2012-12-01

    Episodic flood and storm events are important drivers of sediment dynamics in estuarine and marine environments. Event-driven sedimentation has been well-documented by field and modeling studies. Yet, few studies have integrated field observations and modeling results to overcome the limitations inherent in both techniques. A unique opportunity to integrate field observations and model results was provided in late August/early September 2011 with the passage of Hurricane Irene and the remnants of Tropical Storm Lee in the Chesapeake Bay region. These storms differed in their timing, track, and impact on the Bay region - Hurricane Irene was primarily a wind/resuspension event, whereas TS Lee was a hydrological/deposition event, with the second largest discharge of the Susquehanna River on record. Because these two storms occurred within a relatively short period of time, both are potentially represented in the sediment record obtained during rapid-response cruises in September and October 2011. The resulting sediment deposit was recognized in cores using classic flood-sediment signatures (fine grain size, uniform 7Be activity, physical stratification in x-radiographs) and was found to be <4 cm, thickest in the upper Bay. Model runs conducted for TS Lee generally agreed with these estimates. One exception with physical stratification but no 7Be activity appears to be due to extreme wave activity during Hurricane Irene. Integration of observations and modeling in this case greatly improved understanding of the transport and fate of flood sediments in the Chesapeake Bay.

  6. Baroclinic dynamics of wind-driven circulation in a stratified bay: A numerical study using models of varying complexity

    NASA Astrophysics Data System (ADS)

    Zhai, Li; Sheng, Jinyu; Greatbatch, Richard J.

    2008-10-01

    The baroclinic response of a stratified coastal embayment (Lunenburg Bay of Nova Scotia) to the observed wind forcing is examined using two numerical models. A linear baroclinic model based on the normal mode approach shows skill at reproducing the observed isotherm movements and sub-surface currents during a time of strong stratification in the bay. The linear model also shows that the isotherm movement in Lunenburg Bay is influenced by the wind forcing and propagation of baroclinic Kelvin waves from neighbouring Mahone Bay. The effects of nonlinearity and topography are investigated using a three-dimensional nonlinear coastal circulation model. The nonlinear model results demonstrate that the nonlinear advection terms generate a gyre circulation at the entrance of Lunenburg Bay, and the slope bottom topography at the mouth of the bay strengthens the sub-surface time-mean inflow on the southern side of the bay. A comparison of model-calculated currents in different numerical experiments clearly shows that baroclinicity plays a dominant role in the dynamics of wind-driven circulation in Lunenburg Bay.

  7. Hydrodynamic properties of San Quintin Bay, Baja California: Merging models and observations.

    PubMed

    Melaku Canu, Donata; Aveytua-Alcázar, Leslie; Camacho-Ibar, Victor F; Querin, Stefano; Solidoro, Cosimo

    2016-07-15

    We investigated the physical dynamics of San Quintin Bay, a coastal lagoon located on the Pacific coast of northern Baja California, Mexico. We implemented, validated and used a finite element 2-D hydrodynamic model to characterize the spatial and temporal variability of the hydrodynamic of the bay in response to variability in the tidal regime and in meteorological forcing patterns. Our analysis of general circulation, residual currents, residence times, and tidal propagation delays allowed us to characterize spatial variability in the hydrodynamic basin features. The eulerian water residence time is -on average and under reference conditions- approximately 7days, although this can change significantly by region and season and under different tidal and meteorological conditions. Ocean upwelling events that bring colder waters into the bay mouth affect hydrodynamic properties in all areas of the lagoon and may affect ecological dynamics. A return to pre-upwelling conditions would take approximately 10days. PMID:27140393

  8. MODELING FISH AND SHELLFISH DISTRIBUTIONS IN THE MOBILE BAY ESTUARY, USA

    EPA Science Inventory

    Estuaries in the Gulf of Mexico provide rich habitat for many fish and shellfish, including those that have been identified as economically and ecologically important. For the Mobile Bay estuary, we developed statistical models to relate distributions of individual species and sp...

  9. A Tidally Averaged Sediment-Transport Model for San Francisco Bay, California

    USGS Publications Warehouse

    Lionberger, Megan A.; Schoellhamer, David H.

    2009-01-01

    A tidally averaged sediment-transport model of San Francisco Bay was incorporated into a tidally averaged salinity box model previously developed and calibrated using salinity, a conservative tracer (Uncles and Peterson, 1995; Knowles, 1996). The Bay is represented in the model by 50 segments composed of two layers: one representing the channel (>5-meter depth) and the other the shallows (0- to 5-meter depth). Calculations are made using a daily time step and simulations can be made on the decadal time scale. The sediment-transport model includes an erosion-deposition algorithm, a bed-sediment algorithm, and sediment boundary conditions. Erosion and deposition of bed sediments are calculated explicitly, and suspended sediment is transported by implicitly solving the advection-dispersion equation. The bed-sediment model simulates the increase in bed strength with depth, owing to consolidation of fine sediments that make up San Francisco Bay mud. The model is calibrated to either net sedimentation calculated from bathymetric-change data or measured suspended-sediment concentration. Specified boundary conditions are the tributary fluxes of suspended sediment and suspended-sediment concentration in the Pacific Ocean. Results of model calibration and validation show that the model simulates the trends in suspended-sediment concentration associated with tidal fluctuations, residual velocity, and wind stress well, although the spring neap tidal suspended-sediment concentration variability was consistently underestimated. Model validation also showed poor simulation of seasonal sediment pulses from the Sacramento-San Joaquin River Delta at Point San Pablo because the pulses enter the Bay over only a few days and the fate of the pulses is determined by intra-tidal deposition and resuspension that are not included in this tidally averaged model. The model was calibrated to net-basin sedimentation to calculate budgets of sediment and sediment-associated contaminants. While

  10. 78 FR 14007 - Special Conditions: Embraer S.A., Model EMB-550 Airplanes; Electrical/Electronic Equipment Bay...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-04

    ...These special conditions are issued for the Embraer S.A. Model EMB-550 airplane. This airplane will have novel or unusual design features, specifically distributed electrical and electronic equipment bays in pressurized areas of the airplane. Older transport category airplane electrical/electronic equipment bay installations are located in the lower lobe where the flight crew could determine......

  11. A Combined Modeling Approach to Evaluate Water Quality Benefits of Riparian Buffers in the Jobos Bay Watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Jobos Bay Watershed, located in south-central Puerto Rico, is a tropical Conservation Effects Assessment Project (CEAP) Special Emphasis Watershed. The purpose of CEAP is to quantify environmental benefits of conservation practices and includes field and watershed modeling. In Jobos Bay, the goa...

  12. Empirical Bayes Point Estimates of True Score Using a Compound Binomial Error Model. Research Memorandum 74-11.

    ERIC Educational Resources Information Center

    Kearns, Jack

    Empirical Bayes point estimates of true score may be obtained if the distribution of observed score for a fixed examinee is approximated in one of several ways by a well-known compound binomial model. The Bayes estimates of true score may be expressed in terms of the observed score distribution and the distribution of a hypothetical binomial test.…

  13. Development of a high-resolution coastal circulation model for the ocean observatory in lunenburg bay

    NASA Astrophysics Data System (ADS)

    Wang, Liang; Sheng, Jinyu

    2005-10-01

    An advanced ocean observatory has been established in Lunenburg Bay of Nova Scotia, Canada as part of an interdisciplinary research project of marine environmental prediction. The development of a high-resolution coastal circulation model is one of important components of the observatory. The model horizontal resolution is 60 m and the vertical resolution is about lm. The coastal circulation model is used to simulate the semi-diurnal tidal circulation and associated nonlinear dynamics with the M2 forcing specified at the model open boundaries. The model is also used to simulate the storm-induced circulation in the bay during Hurricane Juan in September 2003, with the model forcing to be the combination of tides and remotely generated waves specified at the model open boundaries and wind stress applied at the sea surface. The model results demonstrate strong interactions between the local wind stress, tidal forcing, and remotely generated waves during this period. Comparison of model results with the surface elevation and current observations demonstrates that the coastal circulation model has reasonable skills in simulating the tidal and storm-induced circulation in the bay.

  14. Finite-difference model for 3-D flow in bays and estuaries

    USGS Publications Warehouse

    Smith, Peter E.; Larock, Bruce E.

    1993-01-01

    This paper describes a semi-implicit finite-difference model for the numerical solution of three-dimensional flow in bays and estuaries. The model treats the gravity wave and vertical diffusion terms in the governing equations implicitly, and other terms explicitly. The model achieves essentially second-order accurate and stable solutions in strongly nonlinear problems by using a three-time-level leapfrog-trapezoidal scheme for the time integration.

  15. Workplan for tributary refinements to Chesapeake Bay eutrophication model package. Final report

    SciTech Connect

    Cerco, C.F.

    1994-05-01

    The Corps of Engineers, in partnership with the U.S. Environmental Protection Agency Chesapeake Bay Program Office, recently completed a three-dimensional model study of eutrophication in Chesapeake Bay and tributaries. The model package applied included an intratidal hydrodynamic model, an intertidal water-quality model, and a benthic sediment diagenesis model. This report comprises a workplan to improve model representation of Chesapeake Bay tributaries and to incorporate living resources directly into the model framework. Four tributaries have been selected for emphasis under this tributary refinements program. They are the James, York, and Rappahannock rivers, and Baltimore Harbor. The James, York, and Rappahannock were specified because tributary-specific models are required to address water-quality and living-resource benefits to be derived from nutrient reductions. Baltimore Harbor was specified because it presents unique management problems, coupled with long-term toxic impacts, which cannot be addressed in the current model framework. The time scale for the project is 4 years from initiation to completion. Anticipated commencement is April 1, 1994.

  16. Predicting tidal currents in San Francisco Bay using a spectral model

    USGS Publications Warehouse

    Burau, Jon R.; Cheng, Ralph T.

    1988-01-01

    This paper describes the formulation of a spectral (or frequency based) model which solves the linearized shallow water equations. To account for highly variable basin bathymetry, spectral solutions are obtained using the finite element method which allows the strategic placement of the computation points in the specific areas of interest or in areas where the gradients of the dependent variables are expected to be large. Model results are compared with data using simple statistics to judge overall model performance in the San Francisco Bay estuary. Once the model is calibrated and verified, prediction of the tides and tidal currents in San Francisco Bay is accomplished by applying astronomical tides (harmonic constants deduced from field data) at the prediction time along the model boundaries.

  17. Mapping tidal residual circulations in the outer Xiangshan Bay using a numerical model

    NASA Astrophysics Data System (ADS)

    Xu, Peng; Mao, Xinyan; Jiang, Wensheng

    2016-02-01

    Xiangshan Bay, which is elongated and semi-enclosed, is characterized by strong tides. The original understanding of the tidal residual circulation in the bay was based on the Eulerian time-mean method. However, it has been theoretically proved that the Lagrangian time-mean method rather than the Eulerian one should be employed to detide. This knowledge motivated us to remap the tidal residual circulation in the bay. A three-dimensional numerical model with a Lagrangian particle-tracking module was used to simulate tides, from which the Lagrangian and Eulerian tidal residual circulations were produced. The Lagrangian residual circulation exhibited a two-branch pattern that connected the southern and northern outer seas of Xiangshan Bay, whereas the Eulerian residual circulation was characterized by eddies that are not favorable for water exchange. Through comparing to the observed salinity distribution, the Lagrangian residual current presented a reasonable spatial pattern which could explain the inter-tidal mass transport. Furthermore, the Lagrangian residual current performed better in sustaining the mass conservation as predicted by theory. A series of sensitivity experiments were conducted to investigate the effect of nonlinear mechanisms on the Lagrangian residual circulation. The results showed that nonlinear advection is dominant while the time-varying width and depth play a minor role, and the quadratic bottom friction has no influence with only M2 tide driving the model.

  18. Evaluation of CALPUFF nitrogen deposition modeling in the Chesapeake Bay Watershed Area using NADP data

    SciTech Connect

    Garrison, M.; Mayes, P.; Sherwell, J.

    1998-12-31

    The CALMET/CALPUFF modeling system has been used to estimate nitrogen deposition in an area surrounding Baltimore and the northern portion of the Chesapeake Bay. Comprehensive NO{sub x} emissions inventories and meteorological data bases have been developed to conduct the modeling. This paper discusses the results of an evaluation of predicted nitrogen wet deposition rates compared to measured rates at two NADP/NTN sites in Maryland, Wye and White Rock. Underprediction of wet deposition rates is investigated through the use of sensitivity and diagnostic evaluations of model performance. A suggested change to the calculation of NO{sub x} transformation rates involving an alternative specification of minimum NO{sub x} concentrations was made to CALPUFF and the performance evaluation was re-done. Results of the new evaluation show significantly improved model performance, and therefore the modification is tentatively proposed for use in further applications of CALPUFF to the assessment of nitrogen deposition in the Chesapeake Bay watershed.

  19. Modeling the Effect of Hypoxia on Macrobenthos Production in the Lower Rappahannock River, Chesapeake Bay, USA

    PubMed Central

    Sturdivant, Samuel Kersey; Brush, Mark J.; Diaz, Robert J.

    2013-01-01

    Hypoxia in Chesapeake Bay has substantially increased in recent decades, with detrimental effects on macrobenthic production; the production of these fauna link energy transfer from primary consumers to epibenthic and demersal predators. As such, the development of accurate predictive models that determine the impact of hypoxia on macrobenthic production is important. A continuous-time, biomass-based model was developed for the lower Rappahannock River, a Bay tributary prone to seasonal hypoxia. Phytoplankton, zooplankton, and macrobenthic state variables were modeled, with a focus on quantitatively constraining the effect of hypoxia on macrobenthic biomass. This was accomplished through regression with Z': a sigmoidal function between macrobenthic biomass and dissolved oxygen concentration, derived using macrobenthic data collected from the Rappahannock River during the summers of 2007 and 2008, and applied to compute hypoxia-induced mortality as a rate process. The model was verified using independent monitoring data collected by the Chesapeake Bay Program. Simulations showed that macrobenthic biomass was strongly linked to dissolved oxygen concentrations, with fluctuations in biomass related to the duration and severity of hypoxia. Our model demonstrated that hypoxia negatively affected macrobenthic biomass, as longer durations of hypoxia and greater hypoxic severity resulted in an increasing loss in biomass. This exercise represents an important contribution to modeling anthropogenically impacted coastal ecosystems, by providing an empirically constrained relationship between hypoxia and macrobenthic biomass, and applying that empirical relationship in a mechanistic model to quantify the effect of the severity, duration, and frequency of hypoxia on benthic biomass dynamics. PMID:24391904

  20. Modeling the effect of hypoxia on macrobenthos production in the lower Rappahannock River, Chesapeake Bay, USA.

    PubMed

    Sturdivant, Samuel Kersey; Brush, Mark J; Diaz, Robert J

    2013-01-01

    Hypoxia in Chesapeake Bay has substantially increased in recent decades, with detrimental effects on macrobenthic production; the production of these fauna link energy transfer from primary consumers to epibenthic and demersal predators. As such, the development of accurate predictive models that determine the impact of hypoxia on macrobenthic production is important. A continuous-time, biomass-based model was developed for the lower Rappahannock River, a Bay tributary prone to seasonal hypoxia. Phytoplankton, zooplankton, and macrobenthic state variables were modeled, with a focus on quantitatively constraining the effect of hypoxia on macrobenthic biomass. This was accomplished through regression with Z': a sigmoidal function between macrobenthic biomass and dissolved oxygen concentration, derived using macrobenthic data collected from the Rappahannock River during the summers of 2007 and 2008, and applied to compute hypoxia-induced mortality as a rate process. The model was verified using independent monitoring data collected by the Chesapeake Bay Program. Simulations showed that macrobenthic biomass was strongly linked to dissolved oxygen concentrations, with fluctuations in biomass related to the duration and severity of hypoxia. Our model demonstrated that hypoxia negatively affected macrobenthic biomass, as longer durations of hypoxia and greater hypoxic severity resulted in an increasing loss in biomass. This exercise represents an important contribution to modeling anthropogenically impacted coastal ecosystems, by providing an empirically constrained relationship between hypoxia and macrobenthic biomass, and applying that empirical relationship in a mechanistic model to quantify the effect of the severity, duration, and frequency of hypoxia on benthic biomass dynamics. PMID:24391904

  1. Using a food-web model to assess the trophic structure and energy flows in Daya Bay, China

    NASA Astrophysics Data System (ADS)

    Chen, Zuozhi; Xu, Shannan; Qiu, Yongsong

    2015-12-01

    Daya Bay, is one of the largest and most important semi-closed bays along the southern coast of China. Due to the favorable geomorphological and climatic conditions, this bay has become an important conservation zone of aquatic germplasm resources in South China Sea. To characterize the trophic structure, ecosystem properties and keystone species, a food-web model for Daya Bay has been developed by the means of a mass-balance approach using the Ecopath with Ecosim software. The mean trophic transfer efficiency for the entire ecosystem as a whole is 10.9% while the trophic level II is 5.1%. The primary- and secondary-producers, including phytoplankton, zooplankton and micro-zoobenthos demonstrated the important overall impacts on the rest of the groups based on mixed trophic impact (MIT) analysis and are classified as the keystone groups. The analysis of ecosystem attributes indicated that ecosystem of Daya Bay can be categorized as an immature one and/or is in the degraded stage. A comparison of this model with other coastal ecosystems, including Kuosheng Bay, Tongoy Bay, Beibu Gulf and Cadiz Gulf, underpinned that the ecosystem of Daye Bay is an obviously stressed system and is more vulnerable to the external disturbance. In general, our study indicates that a holistic approach is needed to minimize the impacts of anthropogenic activities to ensure the sustainability of the ecosystem in the future.

  2. Hydrodynamic modeling and ecohydrological analysis of river inflow effects on Apalachicola Bay, Florida, USA

    NASA Astrophysics Data System (ADS)

    Huang, Wenrui

    2010-02-01

    This paper presents an integrated hydrodynamic modeling and probability analysis approach to assess the long-term effects of changing river inflows on the estuarine ecosystem. The probability analysis method, which is popularly used in advanced hydrological frequency analysis of river flows and rainfalls, has been applied to analyze the effects of changing inflow on salinity and thus on oyster ecology in Apalachicola Bay. Long-term salinity data were predicted through the application of a calibrated 3D hydrodynamic model under two river inflow conditions over a 10-year period. The first flow represents the historic flow. The 2nd flow condition, called Scenario-1, represents a regulated flow scenario to account for the potential increasing upstream water demands. Two stations, Mid Bay and Dry Bar, in the bay were selected to examine the estuarine responses. Under the historic flow condition, the maximum probability salinity at Dry Bar in the rich oyster reef is near 24 ppt, within the optimal salinity range for oyster growth of 16-26 ppt (Harned et al., 1996); the maximum probability salinity at Mid Bay station is 27 ppt, beyond the optimal salinity for oyster growth in mid-bay area where there is no oyster reef around. While it is difficult to examine the difference between two scenarios by conventional time series analysis of river flows and salinity, probability analysis reasonably characterizes and quantifies the changes of river flow and salinity patterns over the 10-year period. The Scenario-1 has caused the increase of the probability in low flows. Higher probability of low flows for the regulated flow scenario shortens the period of optimal salinity in the oyster reef, and cause substantial increase of exceedance probability of higher salinity in the oyster reef to the level beyond the optimal salinity range for oyster growth. The probability analysis approach has demonstrated its advantage for the risk assessments of the long-term estuarine ecohydrological

  3. Issues related to modeling the transport of suspended sediments in Northern San Francisco Bay, California

    USGS Publications Warehouse

    McDonald, Ellen Thomas; Cheng, Ralph T.

    1994-01-01

    Measurements of suspended sediment concentrations at several deep-channel stations in San Francisco Bay are reviewed. Sediment concentrations are found to be strongly correlated with delta outflow, tidal, and spring/neap variations. However, little to no correlation is observed between wind speed and sediment concentration in the deep channel. A two-dimensional depth-averaged sediment transport model has been developed which includes the effects of tidal and spring-neap variations and wind-generated resuspension. During a period of low delta outflow, the model successfully reproduces field measurements of suspended sediment concentration at a station in San Pablo Bay. The model is found to be most sensitive to critical shear stresses, settling velocity, and the erosion rate constant.

  4. Simulation model of Skeletonema costatum population dynamics in northern San Francisco Bay, California

    USGS Publications Warehouse

    Cloern, J.E.; Cheng, R.T.

    1981-01-01

    A pseudo-two-dimensional model is developed to simulate population dynamics of one dominant phytoplankton species (Skeletonema costatum) in northern San Francisco Bay. The model is formulated around a conceptualization of this estuary as two distinct but coupled subsystems-a deep (10-20 m) central channel and lateral areas with shallow (<2 m) water and slow circulation. Algal growth rates are governed by solar irradiation, temperature and salinity, while population losses are assumed to result from grazing bycalanoid copepods. Consequences of estuarine gravitational circulation are approximated simply by reducing convective-dispersive transport in that section of the channel (null zone) where residual bottom currents are near zero, and lateral mixing is treated as a bulkexchange process between the channel and the shoals. Model output is consistent with the hypothesis that, because planktonic algae are light-limited, shallow areas are the sites of active population growth. Seasonal variation in the location of the null zone (a response to variable river discharge) is responsible for maintaining the spring bloom of neritic diatoms in the seaward reaches of the estuary (San Pablo Bay) and the summer bloom upstream (Suisun Bay). Model output suggests that these spring and summer blooms result from the same general process-establishment of populations over the shoals, where growth rates are rapid, coupled with reduced particulate transport due to estuarine gravitational circulation. It also suggests, however, that the relative importance of physical and biological processes to phytoplankton dynamics is different in San Pablo and Suisun Bays. Finally, the model has helped us determine those processes having sufficient importance to merit further refinement in the next generation of models, and it has given new direction to field studies. ?? 1981 Academic Press Inc. (London) Ltd.

  5. Multispecies modeling for adaptive management of horseshoe crabs and red knots in the delaware bay

    USGS Publications Warehouse

    McGowan, C.P.; Smith, D.R.; Sweka, J.A.; Martin, J.; Nichols, J.D.; Wong, R.; Lyons, J.E.; Niles, L.J.; Kalasz, K.; Brust, J.; Klopfer, M.; Spear, B.

    2011-01-01

    Adaptive management requires that predictive models be explicit and transparent to improve decisions by comparing management actions, directing further research and monitoring, and facilitating learning. The rufa subspecies of red knots (Calidris canutus rufa), which has recently exhibited steep population declines, relies on horseshoe crab (Limulus polyphemus) eggs as their primary food source during stopover in Delaware Bay during spring migration. We present a model with two different parameterizations for use in the adaptive management of horseshoe crab harvests in the Delaware Bay that links red knot mass gain, annual survival, and fecundity to horseshoe crab dynamics. The models reflect prevailing hypotheses regarding ecological links between these two species. When reported crab harvest from 1998 to 2008 was applied, projections corresponded to the observed red knot population abundances depending on strengths of the demographic relationship between these species. We compared different simulated horseshoe crab harvest strategies to evaluate whether, given this model, horseshoe crab harvest management can affect red knot conservation and found that restricting harvest can benefit red knot populations. Our model is the first to explicitly and quantitatively link these two species and will be used within an adaptive management framework to manage the Delaware Bay system and learn more about the specific nature of the linkage between the two species. ?? 2011 Wiley Periodicals, Inc.

  6. Multispecies modeling for adaptive management of horseshoe crabs and red knots in the Delaware Bay

    USGS Publications Warehouse

    McGowan, Conor P.; Smith, David; Sweka, John A.; Martin, Julien; Nichols, James D.; Wong, Richard; Lyons, J.E.; Niles, Lawrence J.; Kalasz, Kevin S.; Brust, Jeffrey; Klopfer, Michelle; Spear, Braddock

    2011-01-01

    Adaptive management requires that predictive models be explicit and transparent to improve decisions by comparing management actions, directing further research and monitoring, and facilitating learning. The rufa subspecies of red knots (Calidris canutus rufa), which has recently exhibited steep population declines, relies on horseshoe crab (Limulus polyphemus) eggs as their primary food source during stopover in Delaware Bay during spring migration. We present a model with two different parameterizations for use in the adaptive management of horseshoe crab harvests in the Delaware Bay that links red knot mass gain, annual survival, and fecundity to horseshoe crab dynamics. The models reflect prevailing hypotheses regarding ecological links between these two species. When reported crab harvest from 1998 to 2008 was applied, projections corresponded to the observed red knot population abundances depending on strengths of the demographic relationship between these species. We compared different simulated horseshoe crab harvest strategies to evaluate whether, given this model, horseshoe crab harvest management can affect red knot conservation and found that restricting harvest can benefit red knot populations. Our model is the first to explicitly and quantitatively link these two species and will be used within an adaptive management framework to manage the Delaware Bay system and learn more about the specific nature of the linkage between the two species.

  7. Water resources planning for rivers draining into Mobile Bay. Part 2: Non-conservative species transport models

    NASA Technical Reports Server (NTRS)

    April, G. C.; Liu, H. A.

    1975-01-01

    Total coliform group bacteria were selected to expand the mathematical modeling capabilities of the hydrodynamic and salinity models to understand their relationship to commercial fishing ventures within bay waters and to gain a clear insight into the effect that rivers draining into the bay have on water quality conditions. Parametric observations revealed that temperature factors and river flow rate have a pronounced effect on the concentration profiles, while wind conditions showed only slight effects. An examination of coliform group loading concentrations at constant river flow rates and temperature shows these loading changes have an appreciable influence on total coliform distribution within Mobile Bay.

  8. Sediment deposition from tropical storms in the upper Chesapeake Bay: Field observations and model simulations

    NASA Astrophysics Data System (ADS)

    Palinkas, Cindy M.; Halka, Jeffrey P.; Li, Ming; Sanford, Lawrence P.; Cheng, Peng

    2014-09-01

    Episodic flood and storm events are important drivers of sediment dynamics in estuarine and marine environments. Event-driven sedimentation has been well-documented by field and modeling studies, though both techniques have inherent limitations. A unique opportunity to integrate field observations and model results was provided in late August/early September 2011 with the passage of Hurricane Irene and Tropical Storm Lee in the Chesapeake Bay region. Because these two storms occurred within a relatively short period of time, both are potentially represented in the sediment record obtained during rapid-response cruises in September and October 2011. Associated sediment deposits were recognized in cores using classic flood-sediment signatures (fine grain size, uniform 7Be activity, physical stratification in x-radiographs) and were found to be <4 cm, thickest in the upper Bay. A coupled hydrodynamic-sediment transport model is used to simulate the sediment plume and sediment deposition onto the seabed. The predicted deposition thickness for TS Lee is in general agreement with the observational estimates. One exception with physical stratification but no 7Be activity appears to be due to extreme wave activity during Hurricane Irene. Integration of observations and modeling in this case greatly improved understanding of the transport and fate of flood sediments in the Chesapeake Bay.

  9. A Multilayer Naïve Bayes Model for Analyzing User's Retweeting Sentiment Tendency

    PubMed Central

    Wang, Mengmeng; Zuo, Wanli; Wang, Ying

    2015-01-01

    Today microblogging has increasingly become a means of information diffusion via user's retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user's retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to exploit dynamic retweeting sentiment features in retweeting sentiment tendency analysis. On the basis of time series of user's network structure information and published text information, we first model dynamic retweeting sentiment features. Then we build Naïve Bayes models from profile-, relationship-, and emotion-based dimensions, respectively. Finally, we build a multilayer Naïve Bayes model based on multidimensional Naïve Bayes models to analyze user's retweeting sentiment tendency towards a microblog. Experiments on real-world dataset demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of dynamic retweeting sentiment features and temporal information in retweeting sentiment tendency analysis. What is more, we provide a new train of thought for retweeting sentiment tendency analysis in dynamic social networks. PMID:26417367

  10. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  11. A Multilayer Naïve Bayes Model for Analyzing User's Retweeting Sentiment Tendency.

    PubMed

    Wang, Mengmeng; Zuo, Wanli; Wang, Ying

    2015-01-01

    Today microblogging has increasingly become a means of information diffusion via user's retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user's retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to exploit dynamic retweeting sentiment features in retweeting sentiment tendency analysis. On the basis of time series of user's network structure information and published text information, we first model dynamic retweeting sentiment features. Then we build Naïve Bayes models from profile-, relationship-, and emotion-based dimensions, respectively. Finally, we build a multilayer Naïve Bayes model based on multidimensional Naïve Bayes models to analyze user's retweeting sentiment tendency towards a microblog. Experiments on real-world dataset demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of dynamic retweeting sentiment features and temporal information in retweeting sentiment tendency analysis. What is more, we provide a new train of thought for retweeting sentiment tendency analysis in dynamic social networks. PMID:26417367

  12. Hydraulic modeling and scour analysis for the San Francisco - Oakland Bay Bridge

    USGS Publications Warehouse

    Shelden, J.G.; Smith, E.D.; Sheppard, D.M.; Odeh, M.

    2004-01-01

    A study was conducted to determine potential maximum scour depths for the foundations of the replacement east span of the San Francisco-Oakland Bay Bridge, as part of the ongoing structural design. This effort presented unique challenges as strong tidal currents, large depths, and cohesive bottom sediments characterize the site. The authors met these challenges with a multi-faceted approach to the problem. First, design current velocities were determined using a two-dimensional hydrodynamic model of San Francisco Bay in conjunction with ADCP hydrographic surveys. Analytical scour calculations were performed and live-bed flume tests of the proposed foundations were also conducted. Finally, two separate methodologies were used to interpret the physical model tests in order to calculate potential scour depths around the foundations. Copyright ASCE 2004.

  13. Extending radiative transfer models by use of Bayes rule. [in atmospheric science

    NASA Technical Reports Server (NTRS)

    Whitney, C.

    1977-01-01

    This paper presents a procedure that extends some existing radiative transfer modeling techniques to problems in atmospheric science where curvature and layering of the medium and dynamic range and angular resolution of the signal are important. Example problems include twilight and limb scan simulations. Techniques that are extended include successive orders of scattering, matrix operator, doubling, Gauss-Seidel iteration, discrete ordinates and spherical harmonics. The procedure for extending them is based on Bayes' rule from probability theory.

  14. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

    USGS Publications Warehouse

    Clarke, K.C.; Hoppen, S.; Gaydos, L.

    1997-01-01

    In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

  15. Chesapeake Bay nitrogen fluxes derived from a land-estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets

    NASA Astrophysics Data System (ADS)

    Feng, Yang; Friedrichs, Marjorie A. M.; Wilkin, John; Tian, Hanqin; Yang, Qichun; Hofmann, Eileen E.; Wiggert, Jerry D.; Hood, Raleigh R.

    2015-08-01

    The Chesapeake Bay plays an important role in transforming riverine nutrients before they are exported to the adjacent continental shelf. Although the mean nitrogen budget of the Chesapeake Bay has been previously estimated from observations, uncertainties associated with interannually varying hydrological conditions remain. In this study, a land-estuarine-ocean biogeochemical modeling system is developed to quantify Chesapeake riverine nitrogen inputs, within-estuary nitrogen transformation processes and the ultimate export of nitrogen to the coastal ocean. Model skill was evaluated using extensive in situ and satellite-derived data, and a simulation using environmental conditions for 2001-2005 was conducted to quantify the Chesapeake Bay nitrogen budget. The 5 year simulation was characterized by large riverine inputs of nitrogen (154 × 109 g N yr-1) split roughly 60:40 between inorganic:organic components. Much of this was denitrified (34 × 109 g N yr-1) and buried (46 × 109 g N yr-1) within the estuarine system. A positive net annual ecosystem production for the bay further contributed to a large advective export of organic nitrogen to the shelf (91 × 109 g N yr-1) and negligible inorganic nitrogen export. Interannual variability was strong, particularly for the riverine nitrogen fluxes. In years with higher than average riverine nitrogen inputs, most of this excess nitrogen (50-60%) was exported from the bay as organic nitrogen, with the remaining split between burial, denitrification, and inorganic export to the coastal ocean. In comparison to previous simulations using generic shelf biogeochemical model formulations inside the estuary, the estuarine biogeochemical model described here produced more realistic and significantly greater exports of organic nitrogen and lower exports of inorganic nitrogen to the shelf.

  16. Modelled trends in oceanic conditions of Pine Island Bay between 1991 and 2014

    NASA Astrophysics Data System (ADS)

    Kimuras, Satoshi; Holland, Paul; Regan, Heather; Jenkins, Adrian; Van Wessem, Melchior

    2016-04-01

    Two ice shelves in Pine Island Bay, Pine Island Glacier and its neighbour Thwaites Glacier, have been highlighted as major drainage pathways for the West Antarctic Ice Sheet. We quantify the melting of these ice shelves and oceanic conditions between 1991 and 2014 using a general circulation model. Two different atmospheric forcing scenarios (RACMO2.3 and ERA-Interim) are used as a surface boundary. The ocean heat content of the Pine Island Bay from the simulations shows periodic decrease in the late 1990s and 2012-2014, but the magnitude of cooling is different between RACMO2.3 and ERA-Interim forced simulations. The brine rejection of the sea ice production causes enhanced overturning and cools the water north of Pine Island Glacier Ice Shelf. This cold water flows southward along the coastline, resulting in lower melt rate in the late 1990s and 2012-2014.

  17. Uncertainty in Model Predictions of Vibrio vulnificus Response to Climate Variability and Change: A Chesapeake Bay Case Study

    PubMed Central

    Urquhart, Erin A.; Zaitchik, Benjamin F.; Waugh, Darryn W.; Guikema, Seth D.; Del Castillo, Carlos E.

    2014-01-01

    The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3–0.4°C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist. PMID:24874082

  18. Uncertainty in model predictions of Vibrio vulnificus response to climate variability and change: a Chesapeake Bay case study.

    PubMed

    Urquhart, Erin A; Zaitchik, Benjamin F; Waugh, Darryn W; Guikema, Seth D; Del Castillo, Carlos E

    2014-01-01

    The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4°C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist. PMID:24874082

  19. Uncertainty in Model Predictions of Vibrio Vulnificus Response to Climate Variability and Change: A Chesapeake Bay Case Study

    NASA Technical Reports Server (NTRS)

    Urquhart, Erin A.; Zaitchik, Benjamin F.; Waugh, Darryn W.; Guikema, Seth D.; Del Castillo, Carlos E.

    2014-01-01

    The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4 C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.

  20. Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

    PubMed

    Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

    2015-09-15

    The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. PMID:26140748

  1. Three-Dimensional Numerical Modeling of Sediment Suspension in San Francisco Bay

    NASA Astrophysics Data System (ADS)

    Chou, Y.; Holleman, R. C.; Lee, S.; Chang, C.; Fringer, O. B.; Stacey, M. T.; Monismith, S. G.; Koseff, J. R.

    2012-12-01

    Sediment suspension in San Francisco Bay is simulated using the unstructured-grid SUNTANS model. Hydrodynamics is calculated by solving the phase-averaged Navier-Stokes equations that are coupled to the wind waves through the radiation stress. Suspended mud is divided into two size classes, namely, micro and macro flocs. Transport of suspended mud is computed using the advection-diffusion equation with different settling velocities assigned for each class. A multi-layer bed model is developed to calculate time-varying bed sediment erodibility due to erosion and consolidation. In the bed model, suspended mud first forms a fluff layer on the bottom that in turn dissipates surface waves. This is parameterized using a two-layer flow model and is of critical importance in modeling shallow water waves. The field data of bed sediment properties is incorporated into the bed model to account for non-uniform coarse/fine sediment ratio, which limits erodibility of bottom mud in the presence of coarse sediment. The model is calibrated against field observations in South San Francisco Bay, and the relative importance of tidal and wind forcing on mud suspension is assessed. Moreover, we analyze the sensitivity of important sediment parameters to the model results.

  2. Numerical modeling of landslide generated tsunamis in the bay of Biscay

    NASA Astrophysics Data System (ADS)

    Frere, Antoine; Hebert, Helene

    2016-04-01

    Tsunami hazard in metropolitan France is poorly known. The TANDEM (Tsunamis in northern AtlaNtic : Definition of Effects by Modeling) project is a French initiative to draw lessons from the 2011 catastrophic tsunami in Japan on French coastlines, in order to provide guidance for risk assessment on the nuclear facilities in the area. This project is aimed at adapting numerical methods of tsunami hazard assessment against the outstanding observation database of the 2011 tsunami, in order to apply these validated methods to the definition of the tsunami hazard for the French Atlantic and Channel coastlines. Landslide induced tsunami hazard in the Bay of Biscay France (NE Atlantic ocean) is poorly known. Investigation on the continental slope of the Bay show the existence of numerous landslide scars, but no real risk assessment studies were made to determine the potential tsunami hazard from those landslide. This work focuses on tsunami induced by landslides, and aims to assess the threat using numerical simulation. We assumes that the landslide has a fluid-like behaviour and applies shallow water/thin layer approximations to both aspect. The similarity of the resulting equations of momentum and mass conservation enables to use a single Godunov-like numerical scheme for both parts of the model. The model results are then carried into a multigrid dispersive model in order to get better estimation of the water height near the coast. This second model uses the Boussinesq equations for larger scale grids and the Saint-Venant equations near the coast, and is resolved using a Crank-Nicholson scheme. The first study zone is located in the Cap Breton canyon region in the south of the Bay. Investigation is carried out to identify scenarios that could have caused paleo-tsunamis, with a special interest on a large scar off the canyon(~70 km3). 4 scenarios of varying volumes (from 17 to 70 km3) and depth are carried into the model and the result show maximum water heights of up to

  3. 2010 bathymetric survey and digital elevation model of Corte Madera Bay, California

    USGS Publications Warehouse

    Foxgrover, Amy C.; Finlayson, David P.; Jaffe, Bruce E.; Takekawa, John Y.; Thorne, Karen M.; Spragens, Kyle A.

    2011-01-01

    A high-resolution bathymetric survey of Corte Madera Bay, California, was collected in early 2010 in support of a collaborative research project initiated by the San Francisco Bay Conservation and Development Commission and funded by the U.S. Environmental Protection Agency. The primary objective of the Innovative Wetland Adaptation in the Lower Corte Madera Creek Watershed Project is to develop shoreline adaptation strategies to future sea-level rise based upon sound science. Fundamental to this research was the development of an of an up-to-date, high-resolution digital elevation model (DEM) extending from the subtidal environment through the surrounding intertidal marsh. We provide bathymetric data collected by the U.S. Geological Survey and have merged the bathymetry with a 1-m resolution aerial lidar data set that was collected by the National Oceanic and Atmospheric Administration during the same time period to create a seamless, high-resolution DEM of Corte Madera Bay and the surrounding topography. The bathymetric and DEM surfaces are provided at both 1 m and 10 m resolutions formatted as both X, Y, Z text files and ESRI Arc ASCII files, which are accompanied by Federal Geographic Data Committee compliant metadata.

  4. BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations.

    PubMed

    Wang, Junbai; Batmanov, Kirill

    2015-12-01

    Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein-DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein-DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions. PMID:26202972

  5. Antenatal BAY 41-2272 reduces pulmonary hypertension in the rabbit model of congenital diaphragmatic hernia.

    PubMed

    Vuckovic, Aline; Herber-Jonat, Susanne; Flemmer, Andreas W; Strizek, Brigitte; Engels, Alexander C; Jani, Jacques C

    2016-04-01

    Infants with congenital diaphragmatic hernia (CDH) fail to adapt at birth because of persistent pulmonary hypertension (PH), a condition characterized by excessive muscularization and abnormal vasoreactivity of pulmonary vessels. Activation of soluble guanylate cyclase by BAY 41-2272 prevents pulmonary vascular remodeling in neonatal rats with hypoxia-induced PH. By analogy, we hypothesized that prenatal administration of BAY 41-2272 would improve features of PH in the rabbit CDH model. Rabbit fetuses with surgically induced CDH at day 23 of gestation were randomized at day 28 for an intratracheal injection of BAY 41-2272 or vehicle. After term delivery (day 31), lung mechanics, right ventricular pressure, and serum NH2-terminal-pro-brain natriuretic peptide (NT-proBNP) levels were measured. After euthanasia, lungs were processed for biological or histological analyses. Compared with untouched fetuses, the surgical creation of CDH reduced the lung-to-body weight ratio, increased mean terminal bronchial density, and impaired lung mechanics. Typical characteristics of PH were found in the hypoplastic lungs, including increased right ventricular pressure, higher serum NT-proBNP levels, thickened adventitial and medial layers of pulmonary arteries, reduced capillary density, and lower levels of endothelial nitric oxide synthase. A single antenatal instillation of BAY 41-2272 reduced mean right ventricular pressure and medial thickness of small resistive arteries in CDH fetuses. Capillary density, endothelial cell proliferation, and transcripts of endothelial nitric oxide synthase increased, whereas airway morphometry, lung growth, and mechanics remained unchanged. These results suggest that pharmacological activation of soluble guanylate cyclase may provide a new approach to the prenatal treatment of PH associated with CDH. PMID:26873974

  6. Research on Bayes matting algorithm based on Gaussian mixture model

    NASA Astrophysics Data System (ADS)

    Quan, Wei; Jiang, Shan; Han, Cheng; Zhang, Chao; Jiang, Zhengang

    2015-12-01

    The digital matting problem is a classical problem of imaging. It aims at separating non-rectangular foreground objects from a background image, and compositing with a new background image. Accurate matting determines the quality of the compositing image. A Bayesian matting Algorithm Based on Gaussian Mixture Model is proposed to solve this matting problem. Firstly, the traditional Bayesian framework is improved by introducing Gaussian mixture model. Then, a weighting factor is added in order to suppress the noises of the compositing images. Finally, the effect is further improved by regulating the user's input. This algorithm is applied to matting jobs of classical images. The results are compared to the traditional Bayesian method. It is shown that our algorithm has better performance in detail such as hair. Our algorithm eliminates the noise well. And it is very effectively in dealing with the kind of work, such as interested objects with intricate boundaries.

  7. Modeling Trace Element Concentrations in the San Francisco Bay Estuary from Remote Measurement of Suspended Solids

    NASA Astrophysics Data System (ADS)

    Press, J.; Broughton, J.; Kudela, R. M.

    2014-12-01

    Suspended and dissolved trace elements are key determinants of water quality in estuarine and coastal waters. High concentrations of trace element pollutants in the San Francisco Bay estuary necessitate consistent and thorough monitoring to mitigate adverse effects on biological systems and the contamination of water and food resources. Although existing monitoring programs collect annual in situ samples from fixed locations, models proposed by Benoit, Kudela, & Flegal (2010) enable calculation of the water column total concentration (WCT) and the water column dissolved concentration (WCD) of 14 trace elements in the San Francisco Bay from a more frequently sampled metric—suspended solids concentration (SSC). This study tests the application of these models with SSC calculated from remote sensing data, with the aim of validating a tool for continuous synoptic monitoring of trace elements in the San Francisco Bay. Using HICO imagery, semi-analytical and empirical SSC algorithms were tested against a USGS dataset. A single-band method with statistically significant linear fit (p < 0.001) was chosen as the proxy for SSC values. The numerical models for WCT and the distribution ratio D were applied in MATLAB with terms to account for regional and seasonal effects, and results were used to calculate WCD. The modeled results were assessed against in situ data from the San Francisco Estuary Regional Monitoring Program. Quantile regression was used to evaluate model sensitivity to the distribution of regions, and outliers displaying regional aberrations were removed before robust regression was applied. Statistically significant and highly correlated results for WCT were found for 10 elements, with goodness of fit greater than or equal to that of the original models of seven elements. WCD was successfully modeled for six elements, with goodness of fit for each exceeding that of the original models. Concentrations of Arsenic, Iron, and Lead in the southern region of the

  8. Development of a data-driven numerical model for San Francisco Bay marsh habitat sustainability

    NASA Astrophysics Data System (ADS)

    Swanson, K.; Drexler, J. Z.; Schoellhamer, D. H.; Thorne, K.; Spragens, K.; Takekawa, J.

    2011-12-01

    Marsh species have specific requirements for marsh elevation relative to sea level. As sea level rises and sediment and organic matter accumulate within a marsh, the effect of changes in relative elevation on habitat for specific species will differ. The Wetland Accretion Rate Model for Ecosystem Resilience, WARMER, is a 1-D model of elevation that incorporates both biological and physical processes of vertical marsh accretion at a point representative of wetland habitat. It is currently being developed in order to better understand the threat of rising sea level on marsh sustainability and habitat quality. WARMER incorporates dynamic processes of relative sea-level rise, inorganic sediment deposition and organic matter production, decomposition, and compaction to evaluate changes in marsh surface elevation and the impact of these elevation changes on marsh habitat for specific species of concern. WARMER builds upon existing wetland vertical accretion models by improving upon the sediment input relationship as well as including a more realistic biomass production routine. Sediment input is determined from elevation-dependent marsh inundation and temporal suspended sediment concentration variability and is calibrated to accumulation rates in sediment cores determined from 210Pb dating. Organic matter accumulation is also an elevation-dependent parabolic function defined by the tidal range of San Francisco Bay marsh vegetation and calibrated to measured organic matter accumulation. Both above ground and below ground organic matter accumulation are accounted for within the model. The cohort-based model is also parametrized with measurements of elevation, porosity, tidal inundation patterns measured in San Francisco Bay marshes and a single scenario of modeled sea level within the Bay from Cayan et al. (2008) and Cayan et al. (2009) based on the IPCC A2 emissions scenario. Model results are compared to elevation-based habitat evaluation criteria developed for marsh

  9. Storm and fair-weather driven sediment-transport within Poverty Bay, New Zealand, evaluated using coupled numerical models

    NASA Astrophysics Data System (ADS)

    Bever, Aaron J.; Harris, Courtney K.

    2014-09-01

    The Waipaoa River Sedimentary System in New Zealand, a focus site of the MARGINS Source-to-Sink program, contains both a terrestrial and marine component. Poverty Bay serves as the interface between the fluvial and oceanic portions of this dispersal system. This study used a three-dimensional hydrodynamic and sediment-transport numerical model, the Regional Ocean Modeling System (ROMS), coupled to the Simulated WAves Nearshore (SWAN) wave model to investigate sediment-transport dynamics within Poverty Bay and the mechanisms by which sediment travels from the Waipaoa River to the continental shelf. Two sets of model calculations were analyzed; the first represented a winter storm season, January-September, 2006; and the second an approximately 40 year recurrence interval storm that occurred on 21-23 October 2005. Model results indicated that hydrodynamics and sediment-transport pathways within Poverty Bay differed during wet storms that included river runoff and locally generated waves, compared to dry storms driven by oceanic swell. During wet storms the model estimated significant deposition within Poverty Bay, although much of the discharged sediment was exported from the Bay during the discharge pulse. Later resuspension events generated by Southern Ocean swell reworked and modified the initial deposit, providing subsequent pulses of sediment from the Bay to the continental shelf. In this manner, transit through Poverty Bay modified the input fluvial signal, so that the sediment characteristics and timing of export to the continental shelf differed from the Waipaoa River discharge. Sensitivity studies showed that feedback mechanisms between sediment-transport, currents, and waves were important within the model calculations.

  10. Agents, Bayes, and Climatic Risks - a modular modelling approach

    NASA Astrophysics Data System (ADS)

    Haas, A.; Jaeger, C.

    2005-08-01

    When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.

  11. CALMET/CALPUFF modeling of nitrogen deposition to Sarasota Bay, Florida

    SciTech Connect

    Weaver, R.; Poor, N.; Iranipour, G.; Kalch, R.; Shell, P.

    1999-07-01

    The dispersion, transport, chemical transformation and deposition of southern Florida nitrogen oxide emissions were modeled using CALMET/CALPUFF to estimate nitrogen deposition to Sarasota Bay. The domain modeled was 390 km x 400 km with a 10-km grid size, and included emissions from the metropolitan areas of Tampa Bay, Orlando, Miami, and Ft. Myers. Utility emissions were modeled as 67 point sources (150,000 metric tons/year), industrial emissions as 90 point sources (18,000 metric tons/year), and combined mobile and area sources as 13 volume and 20 line sources (320,000 metric tons/year). CALMET/CALPUFF modeling was done month-by-month, and each source category was modeled separately. Annually averaged ambient air concentrations predicted over Sarasota Bay for NO{sub x}, HNO{sub 3} and NO{sub 3} were 9 {micro}g m{sup {minus}3}, 1 {micro}g m{sup {minus}3}, and 0.7 {micro}g m{sup {minus}3}, respectively. Mobile plus area sources contributed 86%, 69% and 78% to the average annual ambient air NO{sub x}, HNO{sub 3} and NO{sub 3} concentrations, respectively. The total predicted nitrogen deposition to Sarasota Bay from these species was 23 metric tons/year, and this represents a deposition rate of 1.8 kg-N/ha/year. Of this total predicted nitrogen deposition, 11% was from wet deposition and 89% from dry deposition. Mobile and area sources accounted for 80%, utility sources 16% and industrial sources 4%, of the total nitrogen deposition. By species, NO{sub x} contributed 69%, HNO{sub 3} 29%, and NO{sub 3} 2%, to the total nitrogen deposited. The modeled wet deposition rate of 0.2 kg-N/ha/year is well below the 1.9 kg-N/ha/year NO{sub 3} wet deposition rate measured in 1990 at a National Atmospheric Deposition Program site in Sarasota County.

  12. Final report for sea-level rise response modeling for San Francisco Bay estuary tidal marshes

    USGS Publications Warehouse

    Takekawa, John Y.; Thorne, Karen M.; Buffington, Kevin J.; Spragens, Kyle A.; Swanson, Kathleen M.; Drexler, Judith Z.; Schoellhamer, David H.; Overton, Cory T.; Casazza, Michael L.

    2013-01-01

    The International Panel on Climate Change has identified coastal ecosystems as areas that will be disproportionally affected by climate change. Current sea-level rise projections range widely with 0.57 to 1.9 meters increase in mea sea level by 2100. The expected accelerated rate of sea-level rise through the 21st century will put many coastal ecosystems at risk, especially those in topographically low-gradient areas. We assessed marsh accretion and plant community state changes through 2100 at 12 tidal salt marshes around San Francisco Bay estuary with a sea-level rise response model. Detailed ground elevation, vegetation, and water level data were collected at all sites between 2008 and 2011 and used as model inputs. Sediment cores (taken by Callaway and others, 2012) at four sites around San Francisco Bay estuary were used to estimate accretion rates. A modification of the Callaway and others (1996) model, the Wetland Accretion Rate Model for Ecosystem Resilience (WARMER), was utilized to run sea-level rise response models for all sites. With a mean sea level rise of 1.24 m by 2100, WARMER projected that the vast majority, 95.8 percent (1,942 hectares), of marsh area in our study will lose marsh plant communities by 2100 and to transition to a relative elevation range consistent with mudflat habitat. Three marshes were projected to maintain marsh vegetation to 2100, but they only composed 4.2 percent (85 hectares) of the total marsh area surveyed.

  13. Estimating the input of submarine groundwater discharge (SGD) and SGD-derived nutrients in Geoje Bay, Korea using (222)Rn-Si mass balance model.

    PubMed

    Hwang, Dong-Woon; Lee, In-Seok; Choi, Minkyu; Kim, Tae-Hoon

    2016-09-15

    In order to evaluate the main source of nutrients for maintaining the high production in shellfish farming bay, we have measured (222)Rn activities and the concentrations of nutrients in stream water, seawater, and coastal groundwater around Geoje Bay, one of the largest cultivation areas of oyster in the southern sea of Korea in April 2013. Using the (222)Rn and Si mass balance model, the residence time of bay seawater was about 5days and the submarine groundwater discharge (SGD) into the bay was estimated to be approximately 1.8×10(6)m(3) d(-1). The SGD-derived nutrient fluxes contributed approximately 54% for DIN, 5% for DIP, and 50% for DSi of total nutrient input entering into the bay. Thus, our results suggest that SGD is the major source of nutrients in Geoje Bay, and SGD-derived nutrients are very important to support the biological production of this shellfish farming bay. PMID:27377001

  14. Modeling the periodic stratification and gravitational circulation in San Francisco Bay, California

    USGS Publications Warehouse

    Cheng, Ralph T.; Casulli, Vincenzo

    1996-01-01

    A high resolution, three-dimensional (3-D) hydrodynamic numerical model is applied to San Francisco Bay, California to simulate the periodic tidal stratification caused by tidal straining and stirring and their long-term effects on gravitational circulation. The numerical model is formulated using fixed levels in the vertical and uniform computational mesh on horizontal planes. The governing conservation equations, the 3-D shallow water equations, are solved by a semi-implicit finite-difference scheme. Numerical simulations for estuarine flows in San Francisco Bay have been performed to reproduce the hydrodynamic properties of tides, tidal and residual currents, and salt transport. All simulations were carried out to cover at least 30 days, so that the spring-neap variance in the model results could be analyzed. High grid resolution used in the model permits the use of a simple turbulence closure scheme which has been shown to be sufficient to reproduce the tidal cyclic stratification and well-mixed conditions in the water column. Low-pass filtered 3-D time-series reveals the classic estuarine gravitational circulation with a surface layer flowing down-estuary and an up-estuary flow near the bottom. The intensity of the gravitational circulation depends upon the amount of freshwater inflow, the degree of stratification, and spring-neap tidal variations.

  15. Empirical model of Skeletonema costatum photosynthetic rate, with applications in the San Francisco Bay estuary

    USGS Publications Warehouse

    Cloern, J.E.

    1978-01-01

    An empirical model of Skeletonema costatum photosynthetic rate is developed and fit to measurements of photosynthesis selected from the literature. Because the model acknowledges existence of: 1) a light-temperature interaction (by allowing optimum irradiance to vary with temperature), 2) light inhibition, 3) temperature inhibition, and 4) a salinity effect, it accurately estimates photosynthetic rates measured over a wide range of temperature, light intensity, and salinity. Integration of predicted instantaneous rate of photosynthesis with time and depth yields daily net carbon assimilation (pg C cell-1 day-1) in a mixed layer of specified depth, when salinity, temperature, daily irradiance and extinction coefficient are known. The assumption of constant carbon quota (pg C cell-1) allows for prediction of mean specific growth rate (day-1), which can be used in numerical models of Skeletonema costatum population dynamics. Application of the model to northern San Francisco Bay clearly demonstrates the limitation of growth by low light availability, and suggests that large population densities of S. costatum observed during summer months are not the result of active growth in the central deep channels (where growth rates are consistently predicted to be negative). But predicted growth rates in the lateral shallows are positive during summer and fall, thus offering a testable hypothesis that shoals are the only sites of active population growth by S. costatum (and perhaps other neritic diatoms) in the northern reach of San Francisco Bay. ?? 1978.

  16. Inference for dynamic and latent variable models via iterated, perturbed Bayes maps

    PubMed Central

    Ionides, Edward L.; Nguyen, Dao; Atchadé, Yves; Stoev, Stilian; King, Aaron A.

    2015-01-01

    Iterated filtering algorithms are stochastic optimization procedures for latent variable models that recursively combine parameter perturbations with latent variable reconstruction. Previously, theoretical support for these algorithms has been based on the use of conditional moments of perturbed parameters to approximate derivatives of the log likelihood function. Here, a theoretical approach is introduced based on the convergence of an iterated Bayes map. An algorithm supported by this theory displays substantial numerical improvement on the computational challenge of inferring parameters of a partially observed Markov process. PMID:25568084

  17. Observations and modelling of fast ice growth in the Tiksi Bay, Laptev Sea

    NASA Astrophysics Data System (ADS)

    Bogorodsky, Petr; Makshtas, Aleksandr; Grubiy, Andrey; Kustov, Vasiliy

    2016-04-01

    Fast ice is one of the main features of sea ice cover in the Laptev Sea. The formation of this immobile ice which occupies up to 30% of the sea area and significantly affects the intensity of air-sea energy exchange in the coastal zones had been investigated during winter 2014-2015 in the Tiksi Bay (Buor-Khaya Gulf). The temperature measurements within sea ice thickness and under-ice sea layer using GeoPrecision thermistor string of 10 sensors together with measurements of snow and ice thicknesses were carried out at the distance of 0.5 km from the shore at the 3.5 m water depth. According to measurements temperature variations qualitatively repeat air temperature variations and, damping with depth, approach to sea water freezing temperature. Vertical temperature distributions allow to recognize snow, ice and water layers by profile inclination in each layer. The temperature profiles within growing ice were quasi-linear, indicating permanence of heat flux inside ice. The linearity of temperature profiles increased during ice growth. For calculations of fast ice evolution one-dimensional thermodynamic model was used. Besides the empirical formulae, based on frost degree-days, developed in 1930th for the Tiksi Bay was applied. Numerical experiments were carried out with constant values of thermal properties of all media and 10 ppt water salinity, as initial condition. The daily average data from Hydrometeorological Observatory Tiksi, located approximately 1 km from the site of ice observations, were used as atmospheric forcing. For the examined area evolutions of ice cover thickness estimated from direct measurements, the thermodynamic model and the empirical formulae were almost identical. The result indicates stability of hydrological and meteorological conditions, determining fast ice growth in the Tiksi Bay during last 75 years. Model simulations showed that in shallow waters the growth of ice thickness is stabilized due to increase of sub-ice water layer

  18. A three-dimensional, time-dependent model of Mobile Bay

    NASA Technical Reports Server (NTRS)

    Pitts, F. H.; Farmer, R. C.

    1976-01-01

    A three-dimensional, time-variant mathematical model for momentum and mass transport in estuaries was developed and its solution implemented on a digital computer. The mathematical model is based on state and conservation equations applied to turbulent flow of a two-component, incompressible fluid having a free surface. Thus, bouyancy effects caused by density differences between the fresh and salt water, inertia from thare river and tidal currents, and differences in hydrostatic head are taken into account. The conservation equations, which are partial differential equations, are solved numerically by an explicit, one-step finite difference scheme and the solutions displayed numerically and graphically. To test the validity of the model, a specific estuary for which scaled model and experimental field data are available, Mobile Bay, was simulated. Comparisons of velocity, salinity and water level data show that the model is valid and a viable means of simulating the hydrodynamics and mass transport in non-idealized estuaries.

  19. Naive Optics: Acting on Mirror Reflections

    ERIC Educational Resources Information Center

    Hecht, Heiko; Bertamini, Marco; Gamer, Matthias

    2005-01-01

    It is known that naive observers have striking misconceptions about mirror reflections. In 5 experiments, this article systematically extends the findings to graphic stimuli, to interactive visual tasks, and finally to tasks involving real mirrors. The results show that the perceptual knowledge of nonexpert adults is far superior to their…

  20. Hydrodynamic and water quality modeling of lower Green Bay, Wisconsin. Volume 1. Main text and appendixes A - E. Final report

    SciTech Connect

    Mark, D.J.; Scheffner, N.W.; Butler, H.L.; Bunch, B.W.; Dortch, M.S.

    1993-09-01

    A confined disposal facility (CDF) for dredged material presently exists in lower Green Bay, Wisconsin. A planned expansion of the CDF was studied to assess its impact on current patterns and subsequent redistribution of dissolved oxygen in the immediate vicinity of the proposed expansion. The redistribution is, in part, dependent on the magnitude and direction of currents generated by storm-induced seiches occurring in Lake Michigan and within the bay itself. Two-dimensional, vertically averaged hydrodynamic and water quality models were applied to make this assessment by investigating the spatial and temporal variations in dissolved oxygen concentrations for existing and proposed configurations. Field data collected over three summers were used for calibrating and validating the hydrodynamic model. The water quality model was calibrated with field data collected over one summer. Results and conclusions of the modeling effort are summarized in this report. Circulation, Green Bay, Dissolved oxygen, Seiche, Great Lakes, Water quality.

  1. Modelling Hydrodynamics, Sediment Transport and Provenance in the South San Francisco Bay Salt Ponds

    NASA Astrophysics Data System (ADS)

    Holleman, R. C.; Gross, E. S.; MacVean, L. J.; Stacey, M. T.; Fringer, O. B.

    2012-12-01

    Restoration of the South San Francisco Bay Salt Ponds is an immense and ongoing project with potentially far-reaching ramifications related to sediment supply, resuspension of contaminants, salt intrusion dynamics, tidal propagation and morphologic change. The rate of accretion in breached ponds depends on many factors, and the source of deposited material may be local or from other embayments. We present a high resolution hydrodynamic model of San Francisco Bay which resolves a broad range of spatial scales ranging from tens of kilometers in the coastal ocean, down to meters in a series of breached levees located in the Island Ponds. Complexities of the hydrodynamic model include both the generation of intertidal bathymetry and the numerical stability of wetting and drying when grid resolution is at the meter scale. Tides and currents show good validation against observed flows near the breaches. Hydrodynamic results are used to drive a particle-tracking based sediment model, allowing for detailed sediment provenance studies. Results demonstrate the viability of pond-deposited sediments sourced from beyond Calaveras Point even over short time periods.

  2. A computer model of long-term salinity in San Francisco Bay: Sensitivity to mixing and inflows

    USGS Publications Warehouse

    Uncles, R.J.; Peterson, D.H.

    1995-01-01

    A two-level model of the residual circulation and tidally-averaged salinity in San Francisco Bay has been developed in order to interpret long-term (days to decades) salinity variability in the Bay. Applications of the model to biogeochemical studies are also envisaged. The model has been used to simulate daily-averaged salinity in the upper and lower levels of a 51-segment discretization of the Bay over the 22-y period 1967–1988. Observed, monthly-averaged surface salinity data and monthly averages of the daily-simulated salinity are in reasonable agreement, both near the Golden Gate and in the upper reaches, close to the delta. Agreement is less satisfactory in the central reaches of North Bay, in the vicinity of Carquinez Strait. Comparison of daily-averaged data at Station 5 (Pittsburg, in the upper North Bay) with modeled data indicates close agreement with a correlation coefficient of 0.97 for the 4110 daily values. The model successfully simulates the marked seasonal variability in salinity as well as the effects of rapidly changing freshwater inflows. Salinity variability is driven primarily by freshwater inflow. The sensitivity of the modeled salinity to variations in the longitudinal mixing coefficients is investigated. The modeled salinity is relatively insensitive to the calibration factor for vertical mixing and relatively sensitive to the calibration factor for longitudinal mixing. The optimum value of the longitudinal calibration factor is 1.1, compared with the physically-based value of 1.0. Linear time-series analysis indicates that the observed and dynamically-modeled salinity-inflow responses are in good agreement in the lower reaches of the Bay.

  3. Dispersal of lobster larvae within and between coastal bays in the eastern Gulf of Maine: Preliminary model studies

    NASA Astrophysics Data System (ADS)

    Brooks, D.

    2003-04-01

    The lobster (Homarus americanus) supports the most important coastal fishery in the Gulf of Maine. Over the last decade, lobster landing rates have roughly doubled, leading to concerns about sustainable levels of the fishery. Informed management requires better understanding of the physical processes responsible for the dispersal of lobster larvae by shelf and coastal currents and the exchange of post-larvae between offshore waters and coastal bays, where settlement and eventual harvest can occur. The issues are international, because the Gulf currents link Canadian and U.S. waters. The eastern Maine coastal current, a seasonal component of the prevailing circulation, is influenced by river run-off, the winds, tidal mixing, and the hydrographic structure of the deeper offshore waters. Circulation models show that increased run-off in wet years produces river plumes with strong thermohaline fronts that deflect the coastal current offshore, which may reduce the probability of larval settlement in bays. Fine-scale models applied to several bays at the eastern end of the Maine coast show that the pathways of neutral particles approximating larvae entering the region are strongly dependent on the vigorous semidiurnal tidal currents and complex topography. Residence times of particles within the bays range from one tidal cycle to greater than a week, and particles may be exchanged between bays. Ejected particles may enter the coastal current and subsequently be carried southwestward to other bays. Ongoing model studies will quantify the bay-shelf larval exchange rates under different climatological conditions. This work is part of a multidisciplinary project entitled "Impact of Transport Processes on Lobster Fishery Patterns," funded by the U.S. NOAA Coastal Ocean Program, grant number NA160P2658.

  4. Chesapeake Bay study

    NASA Technical Reports Server (NTRS)

    Love, W. J.

    1972-01-01

    The objectives and scope of the Chesapeake Bay study are discussed. The physical, chemical, biological, political, and social phenomena of concern to the Chesapeake Bay area are included in the study. The construction of a model of the bay which will provide a means of accurately studying the interaction of the ecological factors is described. The application of the study by management organizations for development, enhancement, conservation, preservation, and restoration of the resources is examined.

  5. Bed composition generation for morphodynamic modeling: Case study of San Pablo Bay in California, USA

    USGS Publications Warehouse

    van der Wegen, M.; Dastgheib, A.; Jaffe, B.E.; Roelvink, D.

    2011-01-01

    Applications of process-based morphodynamic models are often constrained by limited availability of data on bed composition, which may have a considerable impact on the modeled morphodynamic development. One may even distinguish a period of "morphodynamic spin-up" in which the model generates the bed level according to some ill-defined initial bed composition rather than describing the realistic behavior of the system. The present paper proposes a methodology to generate bed composition of multiple sand and/or mud fractions that can act as the initial condition for the process-based numerical model Delft3D. The bed composition generation (BCG) run does not include bed level changes, but does permit the redistribution of multiple sediment fractions over the modeled domain. The model applies the concept of an active layer that may differ in sediment composition above an underlayer with fixed composition. In the case of a BCG run, the bed level is kept constant, whereas the bed composition can change. The approach is applied to San Pablo Bay in California, USA. Model results show that the BCG run reallocates sand and mud fractions over the model domain. Initially, a major sediment reallocation takes place, but development rates decrease in the longer term. Runs that take the outcome of a BCG run as a starting point lead to more gradual morphodynamic development. Sensitivity analysis shows the impact of variations in the morphological factor, the active layer thickness, and wind waves. An important but difficult to characterize criterion for a successful application of a BCG run is that it should not lead to a bed composition that fixes the bed so that it dominates the "natural" morphodynamic development of the system. Future research will focus on a decadal morphodynamic hindcast and comparison with measured bathymetries in San Pablo Bay so that the proposed methodology can be tested and optimized. ?? 2010 The Author(s).

  6. Examination of circulation, dispersion, and connectivity in Lunenburg Bay of Nova Scotia using a nested-grid circulation model

    NASA Astrophysics Data System (ADS)

    Sheng, Jinyu; Zhao, Jun; Zhai, Li

    2009-05-01

    A coastal ocean observatory has been established in Lunenburg Bay, Nova Scotia since summer 2002 as part of a multi-agency research program of marine environmental observation and prediction over Atlantic Canada coastal waters. The observatory was operational when a category-2 hurricane (Juan) made land fall within 50-km of the bay in September 2003. The coastal response of the bay to Hurricane Juan is examined using a nested-grid coastal circulation modelling system. The nested-grid system is forced by the local wind, tides, and remotely generated coastal waves. A comparison of model results with observed surface elevations and currents demonstrates that the nested-grid system has reasonable skills in simulating the three-dimensional (3D) storm-induced circulation in the study region. The 3D model currents are used to examine the transport and dispersion of passive tracers, local flushing time, and retention and connectivity of passive particles in the bay during Hurricane Juan. Numerical results demonstrate that local wind forcing plays a dominant role in generating large dispersion and hydrodynamic connectivity in the bay during the storm.

  7. An investigation into using the CALMET/CALPUFF modeling system for assessing atmospheric nitrogen deposition in the Chesapeake Bay

    SciTech Connect

    Sherwell, J.; Garrison, M.

    1997-12-31

    The Maryland Department of Natural Resources Power Plant Research Program (PPRP) has a long-standing interest in the water quality of the Chesapeake Bay. A plan has been developed for the ten tributary regions in Maryland that feed into the Chesapeake Bay. Possible reductions in NO{sub x} deposition rates achievable from reductions in airborne NO{sub x} due to Clean Air Act mandates for power plants are of interest in helping to meet the nutrient reduction targets. The Regional Acid Deposition Model (RADM) has been used to estimate NO{sub x} deposition quantities and the extent of the airshed for the Chesapeake Bay. The CALMET/CALPUFF modeling system, recently made available to the public via EPA`s Technology Transfer Network (TTN), is a meteorological and concentration/deposition modeling system that offers a great deal of flexibility for modeling airborne NO{sub x} deposition and for possibly complementing the RADM analyses. A study by PPRP is underway to explore different ways in which the CALMET/CALPUFF modeling system can provide insights into magnitudes, sources, and possible reductions of NO{sub x} deposition to the Bay. The Penn State/NCAR Mesoscale Model (MM4) gridded data set for 1990 has been used for meteorological inputs, and EPA`s 1990 National Emissions Inventory for NO{sub x} has been used to derive source inputs. The CALPUFF analysis is being conducted to provide information in three primary areas: first, detailed deposition estimates for the northern part of the Chesapeake Bay around Baltimore; second, source or source group-specific estimates of deposition in the receptor region for both local and distant sources; and third, time series of deposition patterns throughout the receptor region. This paper reports on the experiences gained in preparing and running the CALMET/CALPUFF system, and on the preliminary results of the analysis of NO{sub x} deposition to the Chesapeake Bay.

  8. Bioenergetics modeling to investigate habitat use by the non-indigenous crab, Carcinus maenas, in Willapa Bay, Washington, USA

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A bioenergetics model was developed and applied to questions of habitat use and migration behavior of non-indigenous European green crab (Carcinus maenas) in Willapa Bay, Washington, USA. The model was parameterized using existing data from published studies on the ecology and physiology of C. maena...

  9. USING THE REGIONAL ACID DEPOSITION MODEL TO DETERMINE THE NITROGEN DEPOSITION AIRSHED OF THE CHESAPEAKE BAY WATERSHED

    EPA Science Inventory

    The Regional Acid Deposition Model, RADM, an advanced Eulerian model, is used to develop an estimate of the primary airshed of nitrogen oxide (NOx) emissions that is contributing nitrogen deposition to the Chesapeake Bay watershed. rief description of RADM together with a summary...

  10. Role of wetlands in attenuation of storm surges using coastal circulation model (ADCIRC), Chesapeake Bay region

    NASA Astrophysics Data System (ADS)

    Deb, Mithun; Ferreira, Celso; Lawler, Seth

    2014-05-01

    The Chesapeake Bay, Virginia is subject to storm surge from extreme weather events nearly year-round; from tropical storms and hurricanes during the summer and fall, (e.g., hurricanes Isabel [2003] and Sandy [2012]), and from nor'easters during the winter (e.g., winter storms Nemo and Saturn [2013]). Coastal wetlands can deliver acute fortification against incoming hurricane storm surges. Coastal wetlands and vegetation shape the hydrodynamics of storm surge events by retaining water and slowing the propagation of storm surge, acting as a natural barrier to flooding. Consequently, a precise scheme to quantify the effect of wetlands on coastal surge levels was also prerequisite. Two wetland sites were chosen in the Chesapeake Bay region for detailed cataloging of vegetation characteristics, including: height, stem diameter, and density. A framework was developed combining these wetlands characterizations with numerical simulations. Storms surges were calculated using Coastal circulation model (ADCIRC) coupled to a wave model (SWAN) forced by an asymmetric hurricane vortex model using an unstructured mesh (comprised of 1.8 million nodes) under a High Performance Computing environment. The Hurricane Boundary Layer (HBL) model was used to compute wind and pressure fields for historical tropical storms and for all of the synthetic storms. Wetlands were characterized in the coupled numerical models by bathymetric and frictional resistance. Multiple model simulations were performed using historical hurricane data and hypothetical storms to compare the predicted storm surge inundation resulting from various levels of wetlands expansion or reduction. The results of these simulations demonstrate the efficacy of wetlands in storm surge attenuation and also the outcome will scientifically support planning of wetlands restoration projects with multi-objective benefits for society.

  11. Modeling wetting and drying process in San Francisco Bay using the Princeton Ocean Model

    NASA Astrophysics Data System (ADS)

    Uchiyama, Y.

    2003-12-01

    Wetting and drying scheme (WDS) is developped to incorporate into the Princeton Ocean Model (POM, Blumberg and Mellor, 1987), which is based upon a sigma-coordinate system. Using a length scale D to characterize the bed topography or the roughness height, WDS scans each grid cell every 2DH external mode time step. If the depth at the center of each grid cell becomes less than D, the cell is considered potentially dry. This grid cell is effectively dry if the depths of all four adjacent cells are also less than D, and subsequently removed from the computational domain. The water elevation retained on the grid cell is set to the corresponding value at the end of the time step, and used for next flooding. If at least one water depth around the four sides of the grid cell is still greater than D, the cell is left in the computational domain to be scanned again by WDS at the next time step. Although WDS seems simplistic, it guarantees mass conservation and works well for an idealized estuarine intertidal basin with a uniform bed slope of about 1:4200. It is realistic that the onshore front of water body immediately runs up the slope during flood to inundate the dried cells in response to tide. This phase speed is relatively faster than that for ebb and accordingly it reproduces the tidal asymmetry. The model is next applied to South San Francisco Bay, California, which is often described as "a tidally oscillating lagoon with density-driven exchanges with the northern reach". The simulation does not include density effect, thus corresponds to summer condition when freshwater input is minimal. Sinusoidal semi-diurnal tide with amplitude of 1.2 m induces wetting and drying processes (WDP) effectively. The number of simultaneously dried-up grid cells varies with time, reaching up to 271 cells. The depth-integrated and 3D surface residual current velocities show that there exists intense horizontal mixing between shallower and deeper regions. Further examination such as

  12. Three-dimensional eutrophication model of Chesapeake Bay. Volume 1: Main report. Final report

    SciTech Connect

    Cerco, C.F.; Cole, T.M.

    1994-05-01

    A three-dimensional, time-variable, eutrophication model, CE-QUAL-ICM, was applied to Chesapeake Bay. The model incorporated 22 state variables that included physical properties, multiple forms of algae, carbon, nitrogen, phosphorus, and silica, and dissolved oxygen. The model was part of a larger package that included a three-dimensional hydrodynamic model and a benthic sediment diagenesis model. The model was initially applied to a 3-year period, 1984-1986. The model successfully simulated water-column and sediment processes that affected water quality. Phenomena simulated include formation of the spring algal bloom subsequent to the annual peak in nutrient runoff, onset and breakup of summer anoxia, and coupling of organic particle deposition with sediment-water nutrient and oxygen fluxes. The model was next applied in a 30-year simulation of water quality, 1959-1988. The model indicated longterm trends in water quality and affirmed the role of stratification in determining anoxia. Final application of the model was in a series of nutrient load-reduction sensitivity analyses. The study demonstrated that complex eutrophication problems can be addressed with coupled three-dimensional hydrodynamic and water quality models.

  13. Fecal coliform modeling under two flow scenarios in St. Louis Bay of Mississippi.

    PubMed

    Liu, Zhijun; Hashim, Noor B; Kingery, William L; Huddleston, David H

    2010-01-01

    St. Louis Bay, along with its two major tributaries, Wolf River and Jourdan River, are included in the Mississippi 1998 Section 303(d) List for violation of the designated water use of recreation and shellfish harvesting. Fecal coliform was identified as one of the pollutants that caused the water quality impairment. In order to facilitate the total maximum daily loads (TMDL) development, the fecal coliform dynamics was investigated under 2 flow scenarios with a calibrated and validated modeling framework by integration of Environmental Fluid Dynamic Code (EFDC) and Hydrological Simulation Program Fortran (HSPF). EFDC was used to model the hydrodymics and fecal coliform transportation in the Bay and the tributaries, whereas HSPF was applied to compute the flow and fecal coliform loadings from the watersheds. The total amount of precipitation in the dry year simulation corresponds to a 50-year return period of low flow condition, and a 10-year return period of high flow condition for wet weather simulation. For EFDC modeling, the fecal coliform sources considered were the contributions from the 2 upper watersheds (no tidal influence), the 28 small surrounding watershed, and 12 municipal, industrial, and domestic point sources. When simulating the fecal coliform loadings from the 2 upper watersheds using HSPF, the simulated non-point source loadings of fecal coliform included wildlife, land application of hog and cattle manure, land application of poultry litter, and grazing animals. The EFDC modeling results indicated that the wet weather exerted greater stress on fecal coliform water quality conditions. The number of exceedance of fecal coliform water quality standard in wet year simulation is much higher than that in dry year simulation. The impact of the upper rural watersheds loads on fecal coliform levels in the St. Louis Bay is much less significant than that from the surrounding urban runoff. Fecal coliform TMDL development should be based on high flow

  14. Ecological niche modeling of sympatric krill predators around Marguerite Bay, Western Antarctic Peninsula

    NASA Astrophysics Data System (ADS)

    Friedlaender, Ari S.; Johnston, David W.; Fraser, William R.; Burns, Jennifer; Halpin, Patrick N.; Costa, Daniel P.

    2011-07-01

    Adélie penguins ( Pygoscelis adeliae), carabeater seals ( Lobodon carcinophagus), humpback ( Megaptera novaeangliae), and minke whales ( Balaenoptera bonaernsis) are found in the waters surrounding the Western Antarctic Peninsula. Each species relies primarily on Antarctic krill ( Euphausia superba) and has physiological constraints and foraging behaviors that dictate their ecological niches. Understanding the degree of ecological overlap between sympatric krill predators is critical to understanding and predicting the impacts on climate-driven changes to the Antarctic marine ecosystem. To explore ecological relationships amongst sympatric krill predators, we developed ecological niche models using a maximum entropy modeling approach (Maxent) that allows the integration of data collected by a variety of means (e.g. satellite-based locations and visual observations). We created spatially explicit probability distributions for the four krill predators in fall 2001 and 2002 in conjunction with a suite of environmental variables. We find areas within Marguerite Bay with high krill predator occurrence rates or biological hot spots. We find the modeled ecological niches for Adélie penguins and crabeater seals may be affected by their physiological needs to haul-out on substrate. Thus, their distributions may be less dictated by proximity to prey and more so by physical features that over time provide adequate access to prey. Humpback and minke whales, being fully marine and having greater energetic demands, occupy ecological niches more directly proximate to prey. We also find evidence to suggest that the amount of overlap between modeled niches is relatively low, even for species with similar energetic requirements. In a rapidly changing and variable environment, our modeling work shows little indication that krill predators maintain similar ecological niches across years around Marguerite Bay. Given the amount of variability in the marine environment around the

  15. A comparative study on entrepreneurial attitudes modeled with logistic regression and Bayes nets.

    PubMed

    López Puga, Jorge; García García, Juan

    2012-11-01

    Entrepreneurship research is receiving increasing attention in our context, as entrepreneurs are key social agents involved in economic development. We compare the success of the dichotomic logistic regression model and the Bayes simple classifier to predict entrepreneurship, after manipulating the percentage of missing data and the level of categorization in predictors. A sample of undergraduate university students (N = 1230) completed five scales (motivation, attitude towards business creation, obstacles, deficiencies, and training needs) and we found that each of them predicted different aspects of the tendency to business creation. Additionally, our results show that the receiver operating characteristic (ROC) curve is affected by the rate of missing data in both techniques, but logistic regression seems to be more vulnerable when faced with missing data, whereas Bayes nets underperform slightly when categorization has been manipulated. Our study sheds light on the potential entrepreneur profile and we propose to use Bayesian networks as an additional alternative to overcome the weaknesses of logistic regression when missing data are present in applied research. PMID:23156922

  16. Modeling nutrient dynamics under critical flow conditions in three tributaries of St. Louis Bay.

    PubMed

    Liu, Zhijun; Kingery, William L; Huddleston, David H; Hossain, Faisal; Chen, Wei; Hashim, Noor B; Kieffer, Janna M

    2008-05-01

    Previous research results indicated that dry weather condition has complicated impacts on nitrogen dynamics; monitored and modeling data showed both increased and decreased levels. In order to facilitate the total maximum daily loads (TMDLs) development at three tributaries of St. Louis Bay estuary, the nitrogen dynamics were investigated for two designed critical flow conditions by integrating Hydrological Simulation Program Fortran (HSPF), Environmental Fluid Dynamics Code (EFDC), and Water Quality Analysis Simulation Program (WASP). The total amount of precipitation during the dry year corresponded to a flow condition with return period of 50 years, and 10-year return period for wet year. The dry year contributed more total nitrogen (TN) loads per unit flow volume. At the upstream tributaries, the computed peak reach-averaged TN concentrations were significantly higher for dry weather simulation than wet conditions, whereas at the near-bay tributary, there were no significant differences in the peak TN concentrations. Hence, for the upstream tributaries, the nitrogen TMDL calculation should be based on dry weather condition since the decision-makers are more concerned about the worse scenario. PMID:18393072

  17. The evolution of nonlinear internal waves in Massachusetts Bay: observations and model results.

    NASA Astrophysics Data System (ADS)

    Scotti, A. D.

    2004-05-01

    Nonlinear internal waves are a common feature in many coastal areas. In Massachusetts Bay, trains of high-frequency and short-wavelength internal waves are generated by the semidiurnal barotropic tide flowing over Stellwagen Bank, and propagate shoreward. In this talk, we present observational and modeling results that have been accumulated over the past 6 years. We will consider in particular the strongly nonlinear interaction with the bottom that occurs when the waves propagate along the incline leading to the shallow (25 m) area just off the coast south of Boston. Contrary to what was previously thought, only part of the baroclinic energy is dissipated locally. The remaining energy propagates in the shallow area to the west of the incline, creating highly nonlinear and very steep waves of elevation that we were able to observe in great detail. The evidence accumulated so far suggest that these waves depart strongly from the hydrostatic equilibrium. The consequences for modeling will be discussed.

  18. Modeling selenium bioaccumulation through arthropod food webs in San Francisco Bay, California, USA

    USGS Publications Warehouse

    Schlekat, C.E.; Purkerson, D.G.; Luoma, S.N.

    2004-01-01

    Trophic transfer is the main process by which upper trophic level wildlife are exposed to selenium. Transfers through lower levels of a predator's food web thus can be instrumental in determining the threat of selenium in an ecosystem. Little is known about Se transfer through pelagic, zooplankton-based food webs in San Francisco Bay ([SFB], CA, USA), which serve as an energy source for important predators such as striped bass. A dynamic multipathway bioaccumulation model was used to model Se transfer from phytoplankton to pelagic copepods to carnivorous mysids (Neomysis mercedis). Uptake rates of dissolved Se, depuration rates, and assimilation efficiencies (AE) for the model were determined for copepods and mysids in the laboratory. Small (73-250 ??m) and large (250-500 ??m) herbivorous zooplankton collected from SFB (Oithona/Limnoithona and Acartia sp.) assimilated Se with similar efficiencies (41-52%) from phytoplankton. Mysids assimilated 73% of Se from small herbivorous zooplankton; Se AE was significantly lower (61%) than larger herbivorous zooplankton. Selenium depuration rates were high for both zooplankton and mysids (12-25% d-1), especially compared to bivalves (2-3% d-1). The model predicted steady state Se concentrations in mysids similar to those observed in the field. The predicted concentration range (1.5-5.4 ??g g -1) was lower than concentrations of 4.5 to 24 ??g g-1 observed in bivalves from the bay. Differences in efflux between mysids and bivalves were the best explanation for the differences in uptake. The results suggest that the risk of selenium toxicity to predators feeding on N. mercedis would be less than the risk to predators feeding on bivalves. Management of selenium contamination should include food webs analyses to focus on the most important exposure pathways identified for a given watershed.

  19. Shuttle measured contaminant environment and modeling for payloads. Preliminary assessment of the space telescope environment in the shuttle bay

    NASA Technical Reports Server (NTRS)

    Scialdone, J. J.

    1983-01-01

    A baseline gaseous and particulate environment of the Shuttle bay was developed based on the various measurements which were made during the first four flights of the Shuttle. The environment is described by the time dependent pressure, density, scattered molecular fluxes, the column densities and including the transient effects of water dumps, engine firings and opening and closing of the bay doors. The particulate conditions in the ambient and on surfaces were predicted as a function of the mission time based on the available data. This basic Shuttle environment when combined with the outgassing and the particulate contributions of the payloads, can provide a description of the environment of a payload in the Shuttle bay. As an example of this application, the environment of the Space Telescope in the bay, which may be representative of the environment of several payloads, was derived. Among the many findings obtained in the process of modeling the environment, one is that the payloads environment in the bay is not substantially different or more objectionable than the self-generated environment of a large payload or spacecraft. It is, however, more severe during ground facilities operations, the first 15 to 20 hours of the flight, during and for a short period after ater was dumped overboard, and the reaction control engines are being fired.

  20. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

  1. Validation of ocean-meteorological models in the Southeastern Bay of Biscay

    NASA Astrophysics Data System (ADS)

    Gaztelumendi, S.; Rubio, A.; Egaña, J.; Fontán, A.; Gelpi, I. R.; Gonzalez, M.; Otxoa de Alda, K.; Mader, J.; Alchaarani, N.; Ferrer, L.; Caballero, A.; Larreta, J.

    2009-09-01

    This contribution is focused on the validation of the modelling forecasts provided by the operational ocean-meteorological system established for the Basque Country region (Southeastern Bay of Biscay). The system, implemented and developed within the Framework of ETORTEK Programme (Department of Industry, Trade and Tourism of the Basque Government), brings together climatological, oceanographic and meteorological institutions, in order to improve the way in which these services are working presently and merge the products in a unique operational system. This modelling system, working at several time-scales, includes: (1) the Global Forecast System (GFS), and the PSU/NCAR mesoscale model (MM5) to provide atmospheric information; (2) the Wavewatch-III wind-wave forecast model (WW3); and (3) the Regional Ocean Modeling System (ROMS). Validation of the models is carried out using information from the operational observational system of the Basque Country: 6 coastal stations, 2 deep sea buoys - over ocean floors around 600 m depth - and an HF Radar array, together with satellite images of sea surface temperature (SST). Concerning the meteorological and wind wave models, some validation results for selected scenarios representative on ocean-meteorological situation over the study area are shown. On the other hand some statistical results for a pre-operational evaluation period are also exposed, focusing on relevant ocean-meteorological variables. With respect to the hydrodynamic model, comparisons with SST show that it is able to reproduce correctly the main patterns and variability observed in the Bay of Biscay. RMS errors for the annual SST show that, on average, models tend to overestimate the SST (RMS under 1.5 °C). Moreover, high errors are observed in some locations, related to specific processes, as happens, for instance, in the Northeastern coast of the Iberian Peninsula (RMS errors around 2 °C), where the model is not able to reproduce correctly the upwelling

  2. Atmospheric response to a realistic coastal polynya in Terra Nova Bay (Antarctica) simulated by ETA model.

    NASA Astrophysics Data System (ADS)

    Morelli, S.; Casini, G.; Parmiggiani, F.

    2009-04-01

    Coastal polynyas are areas of open water (and/or very thin ice) which form adjacent to coasts or blocking feature in polar regions during the wintertime, when the sea water is expected to be ice covered. They are thought to be maintained by strong offshore winds blowing over these area and/or by ocean currents. Sea ice is removed as it forms and drifted offshore. In polynya areas a direct contact is established between the relatively warm sea water and the cold, dry atmosphere. As a consequence, the physical characteristics of the atmospheric boundary layer change. The work presented here concerns a real polynya event in the region of Terra Nova Bay (TNB), Antarctica, where a recurring coastal polynya occurs nearby the Italian Antarctic Base. The aim is the study of atmospheric response to the presence of a open water area of realistic size by three-dimensional numerical simulations. Atmospheric numerical modelling is a fundamental tool for the study of air - polynya interactions in the remote polar regions, where observational data are difficult. The numerical model used for the simulations is a recent version of ETA model (Mesinger et al., 2006), with the addition of a piecewise linear advection for the wind field. ECMWF and NCEP data provided the initial and boundary conditions. A previous version of the model had already been successfully used in the Antarctic area (De Carolis et al, 2006, Casini and Morelli, 2007). As a first step to analyze the polynya event, numerical simulation was performed for the period from 12 to 17 July 2006 in order to study the development of the katabatic wind (Morelli and Casini, 2008; Morelli, 2008). Daily satellite images, concerning the period, display that a sea ice free area formed on 15 and 16 July, reaching its maximum extension of about 4000 km2 on 16 July (Morelli et al.,2007). In order to gain insight on the atmospheric response to open water area within a sea ice field, ETA model runs were carried out from 15 to 17 July

  3. Modeling sediment transport processes and residence times in the shallow coastal bay complex of the Virginia Coast Reserve

    NASA Astrophysics Data System (ADS)

    Safak, I.; Wiberg, P. L.

    2011-12-01

    Patterns of sediment transport and particle residence times influence the morphology and ecology of shallow coastal bays in important ways. The Virginia Coast Reserve (VCR), a barrier island-lagoon-marsh system on the Eastern Shore of Virginia, is typical of many shallow coastal bay complexes that lack a significant fluvial source of freshwater and sediment. Sediment redistribution within the bays in response to storms and sea-level rise, together with the dynamics of marsh and lagoon-bottom plants, largely governs the morphological evolution of this system. There are also important feedbacks between sediment and ecosystem dynamics. This is particularly true in the VCR, which is relatively unaffected by human activities. As a step towards evaluating the impact of hydrodynamics on sediment and ecological processes in the VCR, a single unified model that accounts for circulation, surface waves, wave-current interaction, and sediment processes is employed. This three-dimensional unstructured grid finite-volume coastal ocean model (FVCOM) is validated with field observations of wind- and tide-induced water flow (water level and current velocities) in Hog Island Bay, centrally located within the VCR. Here, the resulting patterns of sediment transport and particle residence times over event and seasonal time scales are presented. Water and particle exchange within the VCR and between the VCR and the ocean is examined with the Lagrangian particle-tracking module in FVCOM. We focus on three bays with strongly varying bathymetry and coastline geometry, which are also located along a gradient of nitrogen input to the system. The results indicate that residence time of particles within the system vary greatly depending on the location of particle release, bay morphology, and wind conditions. The implications for morphologic evolution and ecosystem response to climate and land-use changes are evaluated.

  4. Cenozoic thermal history of the Bohai Bay Basin: constraints from heat flow and coupled basin-mountain modeling

    NASA Astrophysics Data System (ADS)

    He, L.; Wang, J.

    2003-04-01

    Bohai Bay Basin is located in the east of North China Craton. Heat flow measurements show a moderate thermal background (~ 61 mW/m2) in the Bohai Bay Basin, which although experienced multi-phase rifting in the Cenozoic era. In contrast, its surrounding mountain areas are characterized by low heat flow. Constraint by heat flow measurements, the thermal evolution of the Bohai Bay Basin during the Cenozoic era was performed by a numerical basin-mountain model. The model incorporates differential lithosphere stretching and shortening by finite-element method in the Lagrangian frame. The predicted heat flow in the center of the three depressions of the Bohai Bay Basin is calculated to have varied between 51 mW/m2 and 63 mW/m2 through the Cenozoic evolution, indicating a rather smooth variation of basin thermal state, and a cooling trend from the Oligocene to present-day. Model results also suggest that the Taihang Mountains probably uplifted in the Quaternary, which resulted in low heat flow in the mountain area. Both heat flow constraints and modeling imply that a new phase of rifting in the Pliocene existed in the Huanghua and Bozhong Depressions, which was suggested by tectonic subsidence analysis.

  5. Modeling the Role of Zebra Mussels in the Proliferation of Blue-green Algae in Saginaw Bay, Lake Huron

    EPA Science Inventory

    Under model assumptions from Saginaw Bay 1991, selective rejection of blue-green algae by zebra mussels appears to be a necessary factor in the enhancement of blue-green algae production in the presence of zebra mussels. Enhancement also appears to depend on the increased sedime...

  6. A numerical model of sediment transport applied to San Francisco Bay, California

    USGS Publications Warehouse

    Mcdonald, E.T.; Cheng, R.T.

    1997-01-01

    A two dimensional depth-averaged sediment transport model is used to simulate field measurements of suspended sediment concentrations in northern San Francisco Bay. The model uses a semi-implicit finite difference method to solve the shallow water equations and incorporates standard empirical expressions for erosion and deposition of sediments into the transport equation as source/sink terms. The field measurements indicate that tidal scale variations (both diurnal and spring-neap) dominate the variations in suspended sediment concentration (SSC). Increases in SSC also correlated highly with large delta outflows following a storm in late winter. The sediment transport model reproduces the field measurements quite well during periods when the water column is relatively well-mixed vertically. However, the present model only includes one size class of sediment and does not perform well when spatial variability of sediment properties and multiple size classes are significant factors. Comparison of erosion and accretion patterns generated by the model with those obtained from historical bathymetric surveys indicate that the model captures several of the general features observed historically. A sensitivity analysis demonstrates that the model is very sensitive to the critical shear stress for erosion and moderately sensitive to the erosion rate constant, critical shear stress for deposition, and settling velocity.

  7. Application of spatially referenced regression modeling for the evaluation of total nitrogen loading in the Chesapeake Bay watershed

    USGS Publications Warehouse

    Preston, Stephen D.; Brakebill, John W.

    1999-01-01

    The reduction of stream nutrient loads is an important part of current efforts to improve water quality in the Chesapeake Bay. To design programs that will effectively reduce stream nutrient loading, resource managers need spatially detailed information that describes the location of nutrient sources and the watershed factors that affect delivery of nutrients to the Bay. To address this need, the U.S. Geological Survey has developed a set of spatially referenced regression models for the evaluation of nutrient loading in the watershed. The technique applied for this purpose is referred to as ?SPARROW? (SPAtially Referenced Regressions On Watershed attributes), which is a statistical modeling approach that retains spatial referencing for illustrating predictions, and for relating upstream nutrient sources to downstream nutrient loads. SPARROW is based on a digital stream-network data set that is composed of stream segments (reaches) that are attributed with traveltime and connectivity information. Drainage-basin boundaries are defined for each stream reach in the network data set through the use of a digital elevation model. For the Chesapeake Bay watershed, the spatial network was developed using the U.S. Environmental Protection Agency?s River Reach File 1 digital stream network, and is composed of 1,408 stream reaches and watershed segments. To develop a SPARROW model for total nitrogen in the Chesapeake Bay watershed, data sets for sources and basin characteristics were incorporated into the spatial network and related to stream-loading information by using a nonlinear regression model approach. Total nitrogen source variables that were statistically significant in the model include point sources, urban area, fertilizer application, manure generation and atmospheric deposition. Total nitrogen loss variables that were significant in the model include soil permeability and instream-loss rates for four stream-reach classes. Applications of SPARROW for evaluating

  8. A parametric multiclass Bayes error estimator for the multispectral scanner spatial model performance evaluation

    NASA Technical Reports Server (NTRS)

    Mobasseri, B. G.; Mcgillem, C. D.; Anuta, P. E. (Principal Investigator)

    1978-01-01

    The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.

  9. Development of a seamless multisource topographic/bathymetric elevation model of Tampa Bay

    USGS Publications Warehouse

    Gesch, D.; Wilson, R.

    2001-01-01

    Many applications of geospatial data in coastal environments require knowledge of the nearshore topography and bathymetry. However, because existing topographic and bathymetric data have been collected independently for different purposes, it has been difficult to use them together at the land/water interface owing to differences in format, projection, resolution, accuracy, and datums. As a first step toward solving the problems of integrating diverse coastal datasets, the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA) are collaborating on a joint demonstration project to merge their data for the Tampa Bay region of Florida. The best available topographic and bathymetric data were extracted from the USGS National Elevation Dataset and the NOAA hydrographic survey database, respectively. Before being merged, the topographic and bathymetric datasets were processed with standard geographic information system tools to place them in a common horizontal reference frame. Also, a key part of the preprocessing was transformation to a common vertical reference through the use of VDatum, a new tool created by NOAA's National Geodetic Survey for vertical datum conversions. The final merged product is a seamless topographic/bathymetric model covering the Tampa Bay region at a grid spacing of 1 arc-second. Topographic LIDAR data were processed and merged with the bathymetry to demonstrate the incorporation of recent third party data sources for several test areas. A primary application of a merged topographic/bathymetric elevation model is for user-defined shoreline delineation, in which the user decides on the tidal condition (for example, low or high water) to be superimposed on the elevation data to determine the spatial position of the water line. Such a use of merged topographic/bathymetric data could lead to the development of a shoreline zone, which could reduce redundant mapping efforts by federal, state, and local agencies

  10. Numerical model on the material circulation for coastal sediment in Ago Bay, Japan

    NASA Astrophysics Data System (ADS)

    Anggara Kasih, G. A.; Chiba, Satoshi; Yamagata, Youichi; Shimizu, Yasuhiro; Haraguchi, Koichi

    2009-04-01

    In this paper, we study the sediment in Ago Bay from the aspects of the biogeochemical cycle and the mass transport by means of a numerical model. We developed the model by adopting the basic idea of Berg et al. (Berg, P., Rysgaard, S., Thamdrup, B., 2003. Dynamic modeling of early diagenesis and nutrient cycling: A case study in Artic marine sediment. Am. J. Sci. 303, 905-955.), Fossing et al. [Fossing, H., Berg, P., Thamdrup, B., Rysgaard, S., Sorensen, H.M., Nielsen, K.A., 2004. Model set-up for an oxygen and nutrient flux for Aarhus Bay (Denmark). National Environmental Research Institute (NERI) Technical Report No. 483. Ministry of the Environment, Denmark, 65 pp.] and Sayama [Sayama, M., 2000. Analytical technique for the nitrogen circulation in the boundary layer of the coastal sediment. Isao Koike edited, Japan Environmental Management Association for Industry, Tokyo, pp. 51-103. (in Japanese)]. In the model, the biogeochemical processes involve five primary reactions and sixteen secondary reactions. The primary reactions describe the degradation of organic matters, and the secondary reactions describe the miscellaneous reactions such as re-oxidation of reduced species formed as a product from primary reactions, and the crystallizing process of oxidized particles. The transports process includes molecular diffusion, advection, bioturbation and bioirrigation. The model performance is verified by comparing the model predicted data to the observed data. The comparison involves data of vertical distribution of material concentrations and the material fluxes at the sediment-water interface. The comparison shows that the model can reproduce the observed vertical profile and the observed material fluxes at the sediment-water interface. The material circulation result shows that about 42% of dissolved organic matter (DOM) is mineralized by sulfate reduction, around 41% by oxygen respiration, and the remaining is mineralized by denitrification, manganese and iron

  11. A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

    USGS Publications Warehouse

    Brakebill, J.W.; Preston, S.D.

    2003-01-01

    The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived

  12. Extreme Crustal Thinning in a Transtensional Setting (Bay of Biscay - Western Pyrenees): from Observations to Modelling

    NASA Astrophysics Data System (ADS)

    Jammes, S.; Manatschal, G.; Lavier, L.; Tiberi, C.

    2008-12-01

    What are the processes controlling extreme crustal thinning observed in front of a propagating ocean? Young V-shaped basins such as the Gulf of California, the Woodlark basin, the Red Sea, or the ancient Bay of Biscay-Western Pyrenees are natural laboratories where such processes can be studied. In the case of the Bay of Biscay, previous studies suggested late Cretaceous rifting associated with at least 400 km of left lateral movements between Iberia and Europe. However using the latest plate reconstructions from the Iberian/Newfoundland margins, we propose that oblique rifting initiated in latest Jurassic-Early Cretaceous time and predated the anticlockwise rotation of Iberia during Late Aptian to Early Albian time. This reinterpretation of the kinematics has major implications for the formation of the Parentis and Mauléon basins located at the termination of the Bay of Biscay, both presenting evidence for extreme crustal thinning. In this study we develop a model for the evolution of the Bay of Biscay based on seismic and field evidence for extreme thinning and exhumation of the crust and mantle. In the Parentis basin, geophysical surveys (reflection, refraction and gravity) and well data show evidence for extreme crustal thinning, an important asymmetry of the basin and only little evidence for normal faulting. A major E-W trending fault, named the Ibis fault, separates a sag basin to the north from a more complex basin geometry that is strongly affected by salt tectonics to the south. The Mauléon basin, in contrast, is exposed onshore in the western Pyrenees and affected by a mild reactivation during the Pyrenean compression. Our field investigations show that the base of this basin was formed by mantle peridotites and lower crustal rocks that were exhumed, reworked and overlain either by extensional allochthons, today preserved in "chaînons Béarnais", or upper Aptian to Albian sediments. Structures that document the exhumation are exposed in the Labourd

  13. The Hayflick Limit May Determine the Effective Clonal Diversity of Naive T Cells.

    PubMed

    Ndifon, Wilfred; Dushoff, Jonathan

    2016-06-15

    Having a large number of sufficiently abundant T cell clones is important for adequate protection against diseases. However, as shown in this paper and elsewhere, between young adulthood and >70 y of age the effective clonal diversity of naive CD4/CD8 T cells found in human blood declines by a factor of >10. (Effective clonal diversity accounts for both the number and the abundance of T cell clones.) The causes of this observation are incompletely understood. A previous study proposed that it might result from the emergence of certain rare, replication-enhancing mutations in T cells. In this paper, we propose an even simpler explanation: that it results from the loss of T cells that have attained replicative senescence (i.e., the Hayflick limit). Stochastic numerical simulations of naive T cell population dynamics, based on experimental parameters, show that the rate of homeostatic T cell proliferation increases after the age of ∼60 y because naive T cells collectively approach replicative senescence. This leads to a sharp decline of effective clonal diversity after ∼70 y, in agreement with empirical data. A mathematical analysis predicts that, without an increase in the naive T cell proliferation rate, this decline will occur >50 yr later than empirically observed. These results are consistent with a model in which exhaustion of the proliferative capacity of naive T cells causes a sharp decline of their effective clonal diversity and imply that therapeutic potentiation of thymopoiesis might either prevent or reverse this outcome. PMID:27183600

  14. Modeling hydrodynamics, water quality, and benthic processes to predict ecological effects in Narragansett Bay

    EPA Science Inventory

    The environmental fluid dynamics code (EFDC) was used to study the three dimensional (3D) circulation, water quality, and ecology in Narragansett Bay, RI. Predictions of the Bay hydrodynamics included the behavior of the water surface elevation, currents, salinity, and temperatur...

  15. Model for the incorporation of plant detritus within clastic accumulating interdistributary bays

    SciTech Connect

    Gastaldo, R.A.; McCarroll, S.M.; Douglass, D.P.

    1985-01-01

    Plant-bearing clastic lithologies interpreted as interdistributary bay deposits are reported from rocks Devonian to Holocene in age. Often, these strata preserve accumulations of discrete, laterally continuous leaf beds or coaly horizons. Investigations within two modern inter-distributary bays in the lower delta plain of the Mobile Delta, Alabama have provided insight into the phytotaphonomic processes responsible for the generation of carbonaceous lithologies, coaly horizons and laterally continuous leaf beds. Delvan and Chacalooche Bays lie adjacent to the Tensaw River distributary channel and differ in the mode of clastic and plant detrital accumulation. Delvan Bay, lying west of the distributary channel, is accumulating detritus solely by overbank deposition. Chacaloochee Bay, lying east of the channel, presently is accumulating detritus by active crevasse-splay activity. Plant detritus is accumulating as transported assemblages in both bays, but the mode of preservation differs. In Delvan Bay, the organic component is highly degraded and incorporated within the clastic component resulting in a carbonaceous silt. Little identifiable plant detritus can be recovered. On the other hand, the organic component in Chacaloochee Bay is accumulating in locally restricted allochthonous peat deposits up to 2 m in thickness, and discrete leaf beds generated by flooding events. In addition, autochthonous plant accumulations occur on subaerially and aerially exposed portions of the crevasse. The resultant distribution of plant remains is a complicated array of transported and non-transported organics.

  16. ECOSYSTEM MODELING IN COBSCOOK BAY, MAINE:A SUMMARY, PERSPECTIVE, AND LOOK FORWARD

    EPA Science Inventory

    In the mid-1990s, an interdisciplinary, multi-institutional team of scientists was assembled to address basic issues concerning biological productivity and the unique co-occurrence of many unusual ecological features in Cobscook Bay, Maine. Cobscook Bay is a geologically complex,...

  17. Modeling Diel Oxygen Dynamics and Ecosystem Metabolism in Weeks Bay, Alabama.

    EPA Science Inventory

    Weeks Bay is a shallow eutrophic estuary that exhibits frequent summertime diel-cycling hypoxia and periods of dissolved oxygen (DO) oversaturation during the day. Diel DO dynamics in shallow estuaries like Weeks Bay are complex, and may be influenced by wind forcing, vertical an...

  18. BaySTDetect: detecting unusual temporal patterns in small area data via Bayesian model choice.

    PubMed

    Li, Guangquan; Best, Nicky; Hansell, Anna L; Ahmed, Ismaïl; Richardson, Sylvia

    2012-09-01

    Space-time modeling of small area data is often used in epidemiology for mapping chronic disease rates and by government statistical agencies for producing local estimates of, for example, unemployment or crime rates. Although there is typically a general temporal trend, which affects all areas similarly, abrupt changes may occur in a particular area, e.g. due to emergence of localized predictors/risk factor(s) or impact of a new policy. Detection of areas with "unusual" temporal patterns is therefore important as a screening tool for further investigations. In this paper, we propose BaySTDetect, a novel detection method for short-time series of small area data using Bayesian model choice between two competing space-time models. The first model is a multiplicative decomposition of the area effect and the temporal effect, assuming one common temporal pattern across the whole study region. The second model estimates the time trends independently for each area. For each area, the posterior probability of belonging to the common trend model is calculated, which is then used to classify the local time trend as unusual or not. Crucial to any detection method, we provide a Bayesian estimate of the false discovery rate (FDR). A comprehensive simulation study has demonstrated the consistent good performance of BaySTDetect in detecting various realistic departure patterns in addition to estimating well the FDR. The proposed method is applied retrospectively to mortality data on chronic obstructive pulmonary disease (COPD) in England and Wales between 1990 and 1997 (a) to test a hypothesis that a government policy increased the diagnosis of COPD and (b) to perform surveillance. While results showed no evidence supporting the hypothesis regarding the policy, an identified unusual district (Tower Hamlets in inner London) was later recognized to have higher than national rates of hospital readmission and mortality due to COPD by the National Health Service, which initiated

  19. Estimation of regional hydrogeological properties for use in a hydrologic model of the Chesapeake Bay watershed

    NASA Astrophysics Data System (ADS)

    Seck, A.; Welty, C.

    2012-12-01

    Characterization of subsurface hydrogeologic properties in three dimensions and at large scales for use in groundwater flow models can remain a challenge owing to the lack of regional data sets and scatter in coverage, type, and format of existing small-scale data sets. This is the case for the Chesapeake Bay watershed, where numerous studies have been carried out to quantify groundwater processes at small scales but limited information is available on subsurface characteristics and groundwater fluxes at regional scales. One goal of this work is to synthesize disparate information on subsurface properties for the Chesapeake Bay watershed for use in a 3D integrated ParFlow model over an area of 400,000 km2 with a horizontal resolution of 1 km and a vertical resolution of 5 m. We combined different types of data at various scales to characterize hydrostratigraphy and hydrogeological properties. The conceptual hydrogeologic model of the study area is composed of two major regions. One region extends from the Valley and Ridge physiographic province south of New York to the Piedmont physiographic province in Maryland and Virginia. This region is generally characterized by fractured rock overlain by a mantle of regolith. Soil thickness and hydraulic conductivity values were obtained from the U.S. General Soil Map (STATSGO2). Saprolite thickness was evaluated using casing depth information from well completion reports from four state agencies. Geostatistical methods were used to generalize point data to the model extent and resolution. A three-dimensional hydraulic conductivity field for fractured bedrock was estimated using a published national map of permeability and depth- varying functions from literature. The Coastal Plain of Maryland, Virginia, Delaware and New Jersey constitutes the second region and is characterized by layered sediments. In this region, the geometry of 20 aquifers and confining units was constructed using interpolation of published contour maps of

  20. Analyses of phosphorus and nitrogen cyclings in the estuarine ecosystem of Hiroshima Bay by a pelagic and benthic coupled model

    NASA Astrophysics Data System (ADS)

    Kittiwanich, J.; Yamamoto, T.; Kawaguchi, O.; Hashimoto, T.

    2007-10-01

    A pelagic and benthic coupled model expressing both phosphorus and nitrogen cyclings in the ecosystem of Hiroshima Bay, Japan was developed to investigate the fate and transportation of these elements and their annual budgets. The Bay was divided into eight (8) boxes, wherein two (2) areas ran horizontally and four (4) layers vertically. The model consists of equations representing all the concerned physical and biological processes. The results revealed that internal regeneration of materials is an important source of bio-available nutrients for phytoplankton growth. The study indicated that Hiroshima Bay's sediment functions as source of dissolved phosphorus and nitrogen for phytoplankton in the pelagic system, which is supported by calculated results indicating that the releasing rates of dissolved phosphorus and nitrogen from the sediment exceeded 100% of TP and TN loadings in the southern area. As for the northern area which is known to have significant loading via the river, the releasing rates were found to be up to 56% of TP and TN loadings. With regards to the denitrification process, the results revealed that 48% and 37% of NO 3- produced by nitrification was denitrified in the northern and southern areas, respectively. More than 10% of the total nitrogen loaded to the northern area of Hiroshima Bay was estimated to be denitrified. A similar trend was also found in the southern area where the figure was more than 14%. Such findings suggested that the process taking place in the sediment is an important natural purification mechanism that helps remove nitrogen from land. Whereas, almost all phosphorus in the sediment is remineralized, it subsequently goes back to the pelagic system and is repeatedly utilized for the growth of phytoplankton. The model used, therefore, provides a basis and tool to describe the dynamics of phosphorus and nitrogen cyclings in Hiroshima Bay.

  1. Do the Naive Know Best? The Predictive Power of Naive Ratings of Couple Interactions

    ERIC Educational Resources Information Center

    Baucom, Katherine J. W.; Baucom, Brian R.; Christensen, Andrew

    2012-01-01

    We examined the utility of naive ratings of communication patterns and relationship quality in a large sample of distressed couples. Untrained raters assessed 10-min videotaped interactions from 134 distressed couples who participated in both problem-solving and social support discussions at each of 3 time points (pre-therapy, post-therapy, and…

  2. The Preference for Symmetry in Flower-Naive and Not-so-Naive Bumblebees

    ERIC Educational Resources Information Center

    Plowright, C. M. S.; Evans, S. A.; Leung, J. Chew; Collin, C. A.

    2011-01-01

    Truly flower-naive bumblebees, with no prior rewarded experience for visits on any visual patterns outside the colony, were tested for their choice of bilaterally symmetric over asymmetric patterns in a radial-arm maze. No preference for symmetry was found. Prior training with rewarded black and white disks did, however, lead to a significant…

  3. Use of linked models to describe transport and distribution of trace metals in Boston Harbor and Massachusetts Bay

    NASA Astrophysics Data System (ADS)

    Li, L.; Pala, F.; Jiang, M.; Wallace, G. T.

    2008-12-01

    Transport of Cu and Pb in Boston Harbor and Massachusetts Bay was simulated using a previously developed three dimensional hydrodynamic model. The model has been used and refined over a period of 10 years and has proven to be a useful tool to simulate physical parameters in the Bay. In this study, trace elements are integrated into the hydrodynamic model to predict annual or monthly mean trace metal distributions in the water column. We verify model predicted results using historical and recent observational data in Boston Harbor and Massachusetts Bay, exploring the influence of key sources and sinks affecting trace metal distribution, and then link observed water column distributions to surface sediment concentrations of Cu using a dynamic sediment-water equilibrium model. Results of initial model runs for Cu compared well with observed surface sediment data. The linked models show promise as a powerful tool to better understand system responses to varying source strengths and biogeochemical processes controlling trace element transport, distribution and fate in coastal marine environments.

  4. Solar Radiation Measurements at the Chesapeake Bay COVE Site and Comparison With Model

    NASA Astrophysics Data System (ADS)

    Jin, Z.; Charlock, T.; Rutledge, K.

    2001-05-01

    To validate retrievals of flux and albedo in the CERES satellite program, broad-band upwelling and downwelling solar irradiances are measured routinely at the CERES Ocean Validation Experiment (COVE) site 25 km east of the coast of Virginia, near the mouth of the Chesapeake Bay. A full year of observations are compared with simulations from a coupled radiative transfer model. The coupled model treats absorption and scattering by layers of both the atmosphere and the ocean explicitly and consistently, in terms of the inherent optical properties of the air and the sea. Key input parameters for the model include aerosol optical depth, wind speed, and total precipitable water; these are measured at COVE. The modeled total downwelling irradiances, which depend mainly on the atmospheric optical properties, agree well with observations. But the modeled upwelling irradiances (and hence ocean surface albedo), which depend heavily on the the ocean optical properties, are generally less than the observations. The measured upwelling irradiances are strongly influenced by sea state and surface wind, resulting in a seasonal variation of the ocean surface albedo. Candidates to explain the discrepancy of observed and modeled albedo are (1) in-ocean scattering that was not included in the model (i.e., sediments or air bubbles), (2) possible inadequacy of the classical Cox-Munk distribution for the wind speed dependence of sea slopes, and (3) uncertainties in aerosol optical properties. We are presently testing SeaWiFS data as a source for the concentrations of chlorophyl and dissolved organic matter (DOM); and plan to compare the model with available upwelling spectral irradiances and radiances, in addition to the broadband fluxes as described above.

  5. Integrated geostatistics for modeling fluid contacts and shales in Prudhoe Bay

    SciTech Connect

    Perez, G.; Chopra, A.K.; Severson, C.D.

    1997-12-01

    Geostatistics techniques are being used increasingly to model reservoir heterogeneity at a wide range of scales. A variety of techniques is now available with differing underlying assumptions, complexity, and applications. This paper introduces a novel method of geostatistics to model dynamic gas-oil contacts and shales in the Prudhoe Bay reservoir. The method integrates reservoir description and surveillance data within the same geostatistical framework. Surveillance logs and shale data are transformed to indicator variables. These variables are used to evaluate vertical and horizontal spatial correlation and cross-correlation of gas and shale at different times and to develop variogram models. Conditional simulation techniques are used to generate multiple three-dimensional (3D) descriptions of gas and shales that provide a measure of uncertainty. These techniques capture the complex 3D distribution of gas-oil contacts through time. The authors compare results of the geostatistical method with conventional techniques as well as with infill wells drilled after the study. Predicted gas-oil contacts and shale distributions are in close agreement with gas-oil contacts observed at infill wells.

  6. Development of baseline water quality stormwater detention pond model for Chesapeake Bay catchments

    SciTech Connect

    Musico, W.J.; Yoon, J.

    1999-07-01

    An environmental impact assessment is required for every proposed development in the Commonwealth of Virginia to help identify areas of potential concerns. The purpose of the Chesapeake Bay Local Assistance Department (CBLAD), Guidance Calculation Procedures is to ensure that development of previously constructed areas do not further exacerbate current problems of stormwater-induced eutrophication and downstream flooding. The methodology is based on the post development conditions that will not generate greater peak flows and will result in a 10% overall reduction of total phosphorus. Currently, several well-known models can develop hydrographs and pollutographs that accurately model the real response of a given watershed to any given rainfall event. However, conventional method of achieving the desired peak flow reduction and pollutant removal is not a deterministic procedure, and is inherently a trail and error process. A method of quickly and accurately determining the required size of stormwater easements was developed to evaluate the effectiveness of alternative stormwater collection and treatment systems. In this method, predevelopment conditions were modeled first to estimate the peak flows and subsequent pollutants generation that can be used as a baseline for post development plan. Resulting stormwater easement estimates facilitate decision-making processes during the planning and development phase of a project. The design can be optimized for the minimum cost or the smallest-possible pond size required for peak flow reduction and detention time given the most basic data such as: inflow hydrograph and maximum allowable pond depth.

  7. spBayes: An R Package for Univariate and Multivariate Hierarchical Point-referenced Spatial Models

    PubMed Central

    Finley, Andrew O.; Banerjee, Sudipto; Carlin, Bradley P.

    2010-01-01

    Scientists and investigators in such diverse fields as geological and environmental sciences, ecology, forestry, disease mapping, and economics often encounter spatially referenced data collected over a fixed set of locations with coordinates (latitude–longitude, Easting–Northing etc.) in a region of study. Such point-referenced or geostatistical data are often best analyzed with Bayesian hierarchical models. Unfortunately, fitting such models involves computationally intensive Markov chain Monte Carlo (MCMC) methods whose efficiency depends upon the specific problem at hand. This requires extensive coding on the part of the user and the situation is not helped by the lack of available software for such algorithms. Here, we introduce a statistical software package, spBayes, built upon the R statistical computing platform that implements a generalized template encompassing a wide variety of Gaussian spatial process models for univariate as well as multivariate point-referenced data. We discuss the algorithms behind our package and illustrate its use with a synthetic and real data example. PMID:21494410

  8. Investigation of Spatial Variation of Sea States Offshore of Humboldt Bay CA Using a Hindcast Model.

    SciTech Connect

    Dallman, Ann Renee; Neary, Vincent Sinclair

    2014-10-01

    Spatial variability of sea states is an important consideration when performing wave resource assessments and wave resource characterization studies for wave energy converter (WEC) test sites and commercial WEC deployments. This report examines the spatial variation of sea states offshore of Humboldt Bay, CA, using the wave model SWAN . The effect of depth and shoaling on bulk wave parameters is well resolved using the model SWAN with a 200 m grid. At this site, the degree of spatial variation of these bulk wave parameters, with shoaling generally perpendicular to the depth contours, is found to depend on the season. The variation in wave height , for example, was higher in the summer due to the wind and wave sheltering from the protruding land on the coastline north of the model domain. Ho wever, the spatial variation within an area of a potential Tier 1 WEC test site at 45 m depth and 1 square nautical mile is almost negligible; at most about 0.1 m in both winter and summer. The six wave characterization parameters recommended by the IEC 6 2600 - 101 TS were compared at several points along a line perpendicular to shore from the WEC test site . As expected, these parameters varied based on depth , but showed very similar seasonal trends.

  9. Determination of PAH sources in dated sediments from Green Bay, Wisconsin, by a chemical mass balance model.

    PubMed

    Su, M C; Christensen, E R; Karls, J F

    1998-01-01

    Six sediment cores were collected from Green Bay, Wisconsin, in order to identify possible sources of polycyclic aromatic hydrocarbons (PAHs) by a chemical mass balance (CMB) model. The cores which were obtained in 1995 had total PAH concentrations between 8.04 and 0.460 ppm. 210Pb and 137Cs dating was used to determine historical trends of PAH inputs, and elemental carbon particle analysis was done to characterize particles from combustion of coal, wood and petroleum. The results show that coke burning, highway dust, and wood burning are likely sources of PAHs to Green Bay. The contribution of coke oven emissions (CB) for the Green Bay cores is in the range of 5 to 90%. The overall highway dust (HWY) contribution is between 5 and 70%. There is a maximum (approximately 67%) contribution of HWY around 1988 which is in agreement with the historical US petroleum consumption. The wood burning (WB) contribution is between 1 to 30%, except in core GB-A where a maximum (approximately 50%) is found around 1994. The average relative errors of measurement for x2 equal to the number of degrees of freedom, are 52.5, 56.2, 36.2, 52.3, and 42.8 (df = 3) for the Green Bay cores A, B, C, E, and F, respectively. The sums of the contribution factors are less than one, indicating gain of inert biological or other bulk material between source and receptor. The results of carbon particles for Green Bay core D show that coal, oil, and wood burning are consistent with the CMB modeling results. PMID:15093306

  10. The use of computer models to predict temperature and smoke movement in high bay spaces

    NASA Technical Reports Server (NTRS)

    Notarianni, Kathy A.; Davis, William D.

    1993-01-01

    The Building and Fire Research Laboratory (BFRL) was given the opportunity to make measurements during fire calibration tests of the heat detection system in an aircraft hangar with a nominal 30.4 (100 ft) ceiling height near Dallas, TX. Fire gas temperatures resulting from an approximately 8250 kW isopropyl alcohol pool fire were measured above the fire and along the ceiling. The results of the experiments were then compared to predictions from the computer fire models DETACT-QS, FPETOOL, and LAVENT. In section A of the analysis conducted, DETACT-QS AND FPETOOL significantly underpredicted the gas temperature. LAVENT at the position below the ceiling corresponding to maximum temperature and velocity provided better agreement with the data. For large spaces, hot gas transport time and an improved fire plume dynamics model should be incorporated into the computer fire model activation routines. A computational fluid dynamics (CFD) model, HARWELL FLOW3D, was then used to model the hot gas movement in the space. Reasonable agreement was found between the temperatures predicted from the CFD calculations and the temperatures measured in the aircraft hangar. In section B, an existing NASA high bay space was modeled using the CFD model. The NASA space was a clean room, 27.4 m (90 ft) high with forced horizontal laminar flow. The purpose of this analysis is to determine how the existing fire detection devices would respond to various size fires in the space. The analysis was conducted for 32 MW, 400 kW, and 40 kW fires.

  11. Forward Bay Cover Separation Modeling and Testing for the Orion Multi-Purpose Crew Vehicle

    NASA Technical Reports Server (NTRS)

    Ali, Yasmin; Radke, Tara; Chuhta, Jesse; Hughes, Michael

    2014-01-01

    Spacecraft multi-body separation events during atmospheric descent require complex testing and analysis to validate the flight separation dynamics model and to verify no recontact. NASA Orion Multi-Purpose Crew Vehicle (MPCV) teams examined key model parameters and risk areas to develop a robust but affordable test campaign in order to validate and verify the Forward Bay Cover (FBC) separation event for Exploration Flight Test-1 (EFT-1). The FBC jettison simulation model is highly complex, consisting of dozens of parameters varied simultaneously, with numerous multi-parameter interactions (coupling and feedback) among the various model elements, and encompassing distinct near-field, mid-field, and far-field regimes. The test campaign was composed of component-level testing (for example gas-piston thrusters and parachute mortars), ground FBC jettison tests, and FBC jettison air-drop tests that were accomplished by a highly multi-disciplinary team. Three ground jettison tests isolated the testing of mechanisms and structures to anchor the simulation models excluding aerodynamic effects. Subsequently, two air-drop tests added aerodynamic and parachute parameters, and served as integrated system demonstrations, which had been preliminarily explored during the Orion Pad Abort-1 (PA-1) flight test in May 2010. Both ground and drop tests provided extensive data to validate analytical models and to verify the FBC jettison event for EFT-1, but more testing is required to support human certification, for which NASA and Lockheed Martin are applying knowledge from Apollo and EFT-1 testing and modeling to develop a robust but affordable human spacecraft capability.

  12. Forward Bay Cover Separation Modeling and Testing for the Orion Multi-Purpose Crew Vehicle

    NASA Technical Reports Server (NTRS)

    Ali, Yasmin; Chuhta, Jesse D.; Hughes, Michael P.; Radke, Tara S.

    2015-01-01

    Spacecraft multi-body separation events during atmospheric descent require complex testing and analysis to validate the flight separation dynamics models used to verify no re-contact. The NASA Orion Multi-Purpose Crew Vehicle (MPCV) architecture includes a highly-integrated Forward Bay Cover (FBC) jettison assembly design that combines parachutes and piston thrusters to separate the FBC from the Crew Module (CM) and avoid re-contact. A multi-disciplinary team across numerous organizations examined key model parameters and risk areas to develop a robust but affordable test campaign in order to validate and verify the FBC separation event for Exploration Flight Test-1 (EFT-1). The FBC jettison simulation model is highly complex, consisting of dozens of parameters varied simultaneously, with numerous multi-parameter interactions (coupling and feedback) among the various model elements, and encompassing distinct near-field, mid-field, and far-field regimes. The test campaign was composed of component-level testing (for example gas-piston thrusters and parachute mortars), ground FBC jettison tests, and FBC jettison air-drop tests that were accomplished by a highly multi-disciplinary team. Three ground jettison tests isolated the testing of mechanisms and structures to anchor the simulation models excluding aerodynamic effects. Subsequently, two air-drop tests added aerodynamic and parachute elements, and served as integrated system demonstrations, which had been preliminarily explored during the Orion Pad Abort-1 (PA-1) flight test in May 2010. Both ground and drop tests provided extensive data to validate analytical models and to verify the FBC jettison event for EFT-1. Additional testing will be required to support human certification of this separation event, for which NASA and Lockheed Martin are applying knowledge from Apollo and EFT-1 testing and modeling to develop a robust human-rated FBC separation event.

  13. Informing Marine Spatial Planning (MSP) with numerical modelling: A case-study on shellfish aquaculture in Malpeque Bay (Eastern Canada).

    PubMed

    Filgueira, Ramón; Guyondet, Thomas; Bacher, Cédric; Comeau, Luc A

    2015-11-15

    A moratorium on further bivalve leasing was established in 1999-2000 in Prince Edward Island (Canada). Recently, a marine spatial planning process was initiated explore potential mussel culture expansion in Malpeque Bay. This study focuses on the effects of a projected expansion scenario on productivity of existing leases and available suspended food resources. The aim is to provide a robust scientific assessment using available datasets and three modelling approaches ranging in complexity: (1) a connectivity analysis among culture areas; (2) a scenario analysis of organic seston dynamics based on a simplified biogeochemical model; and (3) a scenario analysis of phytoplankton dynamics based on an ecosystem model. These complementary approaches suggest (1) new leases can affect existing culture both through direct connectivity and through bay-scale effects driven by the overall increase in mussel biomass, and (2) a net reduction of phytoplankton within the bounds of its natural variation in the area. PMID:26371845

  14. Modelling river discharge and precipitation from estuarine salinity in the northern Chesapeake Bay: Application to Holocene palaeoclimate

    USGS Publications Warehouse

    Saenger, C.; Cronin, T.; Thunell, R.; Vann, C.

    2006-01-01

    Long-term chronologies of precipitation can provide a baseline against which twentieth-century trends in rainfall can be evaluated in terms of natural variability and anthropogenic influence. However, there are relatively few methods to quantitatively reconstruct palaeoprecipitation and river discharge compared with proxies of other climatic factors, such as temperature. We developed autoregressive and least squares statistical models relating Chesapeake Bay salinity to river discharge and regional precipitation records. Salinity in northern and central parts of the modern Chesapeake Bay is influenced largely by seasonal, interannual and decadal variations in Susquehanna River discharge, which in turn are controlled by regional precipitation patterns. A power regressive discharge model and linear precipitation model exhibit well-defined decadal variations in peak discharge and precipitation. The utility of the models was tested by estimating Holocene palaeoprecipitation and Susquehanna River palaeodischarge, as indicated by isotopically derived palaeosalinity reconstructions from Chesapeake Bay sediment cores. Model results indicate that the early-mid Holocene (7055-5900 yr BP) was drier than the late Holocene (1500 yr BP - present), the 'Mediaeval Warm Period' (MWP) (1200-600 yr BP) was drier than the 'Little Ice Age' (LIA) (500-100 yr BP), and the twentieth century experienced extremes in precipitation possibly associated with changes in ocean-atmosphere teleconnections. ?? 2006 Edward Arnold (Publishers) Ltd.

  15. A physical model for strain accumulation in the San Francisco Bay region: Stress evolution since 1838

    USGS Publications Warehouse

    Pollitz, F.; Bakun, W.H.; Nyst, M.

    2004-01-01

    Understanding of the behavior of plate boundary zones has progressed to the point where reasonably comprehensive physical models can predict their evolution. The San Andreas fault system in the San Francisco Bay region (SFBR) is dominated by a few major faults whose behavior over about one earthquake cycle is fairly well understood. By combining the past history of large ruptures on SFBR faults with a recently proposed physical model of strain accumulation in the SFBR, we derive the evolution of regional stress from 1838 until the present. This effort depends on (1) an existing compilation of the source properties of historic and contemporary SFBR earthquakes based on documented shaking, geodetic data, and seismic data (Bakun, 1999) and (2) a few key parameters of a simple regional viscoelastic coupling model constrained by recent GPS data (Pollitz and Nyst, 2004). Although uncertainties abound in the location, magnitude, and fault geometries of historic ruptures and the physical model relies on gross simplifications, the resulting stress evolution model is sufficiently detailed to provide a useful window into the past stress history. In the framework of Coulomb failure stress, we find that virtually all M ??? 5.8 earthquakes prior to 1906 and M ??? 5.5 earthquakes after 1906 are consistent with stress triggering from previous earthquakes. These events systematically lie in zones of predicted stress concentration elevated 5-10 bars above the regional average. The SFBR is predicted to have emerged from the 1906 "shadow" in about 1980, consistent with the acceleration in regional seismicity at that time. The stress evolution model may be a reliable indicator of the most likely areas to experience M ??? 5.5 shocks in the future.

  16. Time Series Models of Silver and Lead Contamination in San Francisco Bay

    NASA Astrophysics Data System (ADS)

    Squire, S.; Scelfo, G. H.; Revenaugh, J.; Flegal, A. R.

    2001-12-01

    Measurements of silver and lead concentrations in San Francisco Bay waters from 1989 to 1998, along with associated water quality parameters, provide new insights into their biogeochemical cycling within the estuary. Both elements have similar biogeochemical properties and both have been relatively enriched in the estuary by anthropogenic inputs (dissolved trace metal decadal mean: Ag ~ 5.7 ng kg-1 and Pb ~ 31 ng kg-1 in the southern reach). Time series models confirm that dissolved lead concentrations have remained essentially constant over the past decade, as previously indicated by stable lead isotopic composition measurements and mass balance calculations. Conversely, the models show statistically significant decreases in dissolved silver concentrations over the same time period. This disparity is consistent with the differences in contemporary anthropogenic inputs of those metals to the estuary, where there has been a 3-fold decrease in industrial silver inputs over the last decade, but where industrial lead inputs have remained relatively high due to the persistent discharge of historic industrial lead deposits in its drainage basin.

  17. Modeling the fate of p,p'-DDT in water and sediment of two typical estuarine bays in South China: Importance of fishing vessels' inputs.

    PubMed

    Fang, Shu-Ming; Zhang, Xianming; Bao, Lian-Jun; Zeng, Eddy Y

    2016-05-01

    Antifouling paint applied to fishing vessels is the primary source of dichloro-diphenyl-trichloroethane (DDT) to the coastal marine environments of China. With the aim to provide science-based support of potential regulations on DDT use in antifouling paint, we utilized a fugacity-based model to evaluate the fate and impact of p,p'-DDT, the dominant component of DDT mixture, in Daya Bay and Hailing Bay, two typical estuarine bays in South China. The emissions of p,p'-DDT from fishing vessels to the aquatic environments of Hailing Bay and Daya Bay were estimated as 9.3 and 7.7 kg yr(-1), respectively. Uncertainty analysis indicated that the temporal variability of p,p'-DDT was well described by the model if fishing vessels were considered as the only direct source, i.e., fishing vessels should be the dominant source of p,p'-DDT in coastal bay areas of China. Estimated hazard quotients indicated that sediment in Hailing Bay posed high risk to the aquatic system, and it would take at least 21 years to reduce the hazards to a safe level. Moreover, p,p'-DDT tends to migrate from water to sediment in the entire Hailing Bay and Daya Bay. On the other hand, our previous research indicated that p,p'-DDT was more likely to migrate from sediment to water in the maricultured zones located in shallow waters of these two bays, where fishing vessels frequently remain. These findings suggest that relocating mariculture zones to deeper waters would reduce the likelihood of farmed fish contamination by p,p'-DDT. PMID:27016888

  18. Development, calibration, and analysis of a hydrologic and water-quality model of the Delaware Inland Bays watershed

    USGS Publications Warehouse

    Gutierrez-Magness, Angelica L.; Raffensperger, Jeffrey Peter

    2003-01-01

    Excessive nutrients and sediment are among the most significant environmental stressors in the Delaware Inland Bays (Rehoboth, Indian River, and Little Assawoman Bays). Sources of nutrients, sediment, and other contaminants within the Inland Bays watershed include point-source discharges from industries and wastewater-treatment plants, runoff and infiltration to ground water from agricultural fields and poultry operations, effluent from on-site wastewater disposal systems, and atmospheric deposition. To determine the most effective restoration methods for the Inland Bays, it is necessary to understand the relative distribution and contribution of each of the possible sources of nutrients, sediment, and other contaminants. A cooperative study involving the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was initiated in 2000 to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed that can be used as a water-resources planning and management tool. The model code Hydrological Simulation Program - FORTRAN (HSPF) was used. The 719-square-kilometer watershed was divided into 45 model segments, and the model was calibrated using streamflow and water-quality data for January 1999 through April 2000 from six U.S. Geological Survey stream-gaging stations within the watershed. Calibration for some parameters was accomplished using PEST, a model-independent parameter estimator. Model parameters were adjusted systematically so that the discrepancies between the simulated values and the corresponding observations were minimized. Modeling results indicate that soil and aquifer permeability, ditching, dominant land-use class, and land-use practices affect the amount of runoff, the mechanism or flow path (surface flow, interflow, or base flow), and the loads of sediment and nutrients. In general, the edge-of-stream total suspended solids yields in the Inland Bays

  19. Quantitative Models for the Narragansett Bay Estuary, Rhode Island/Massachusetts, USA

    EPA Science Inventory

    Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem in Rhode Island/Massachusetts, USA. Managers are interested in understanding the timing and magnitude of these effects, and ecosystem responses to restoration actions. To provid...

  20. Quantitative Models for Ecosystem Assessment in Narragansett Bay: Response to Nutrient Loading and Other Stressors

    EPA Science Inventory

    Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem. Managers are interested in understanding the timing and magnitude of these effects, as well as ecosystem responses to restoration actions, such as the capacity and potential fo...

  1. Evaluation of effects of changes in canal management and precipitation patterns on salinity in Biscayne Bay, Florida, using an integrated surface-water/groundwater model

    USGS Publications Warehouse

    Lohmann, Melinda A.; Swain, Eric D.; Wang, John D.; Dixon, Joann

    2012-01-01

    Biscayne National Park, located in Biscayne Bay in southeast Florida, is one of the largest marine parks in the country and sustains a large natural marine fishery where numerous threatened and endangered species reproduce. In recent years, the bay has experienced hypersaline conditions (salinity greater than 35 practical salinity units) of increasing magnitude and duration. Hypersalinity events were particularly pronounced during April to August 2004 in nearshore areas along the southern and middle parts of the bay. Prolonged hypersaline conditions can cause degradation of water quality and permanent damage to, or loss of, brackish nursery habitats for multiple species of fish and crustaceans as well as damage to certain types of seagrasses that are not tolerant of extreme changes in salinity. To evaluate the factors that contribute to hypersalinity events and to test the effects of possible changes in precipitation patterns and canal flows into Biscayne Bay on salinity in the bay, the U.S. Geological Survey constructed a coupled surface-water/groundwater numerical flow model. The model is designed to account for freshwater flows into Biscayne Bay through the canal system, leakage of salty bay water into the underlying Biscayne aquifer, discharge of fresh and salty groundwater from the Biscayne aquifer into the bay, direct effects of precipitation on bay salinity, indirect effects of precipitation on recharge to the Biscayne aquifer, direct effects of evapotranspiration (ET) on bay salinity, indirect effects of ET on recharge to the Biscayne aquifer, and maintenance of mass balance of both water and solute. The model was constructed using the Flow and Transport in a Linked Overland/Aquifer Density Dependent System (FTLOADDS) simulator, version 3.3, which couples the two-dimensional, surface-water flow and solute-transport simulator SWIFT2D with the density-dependent, groundwater flow an solute-transport simulator SEAWAT. The model was calibrated by a trial

  2. Cenozoic thermal history of the Bohai Bay Basin: constraints from heat flow and coupled basin?mountain modeling

    NASA Astrophysics Data System (ADS)

    He, Lijuan; Wang, Jiyang

    Heat flow measurements show a moderate thermal background (∼61 mW/m 2) in the Bohai Bay Basin, which although experienced multi-phase rifting in the Cenozoic era. In contrast, its surrounding mountain areas are characterized by low heat flow. Constraint by heat flow measurements, the thermal evolution of the Bohai Bay Basin during the Cenozoic era was performed by a numerical basin-mountain model. The model incorporates differential lithosphere stretching and shortening by finite-element method in the Lagrangian frame. The predicted heat flow in the center of the three depressions of the Bohai Bay Basin is calculated to have varied between 51 and 63 mW/m 2 through the Cenozoic evolution, indicating a rather smooth variation of basin thermal state, and a cooling trend from the Oligocene to present-day. Model results also suggest that the Taihang Mountains probably uplifted in the Quaternary, which resulted in low heat flow in the mountain area. Both heat flow constraints and modeling imply that a new phase of rifting in the Pliocene existed in the Huanghua and Bozhong Depressions, which was suggested by tectonic subsidence analysis.

  3. A landscape based, systems dynamic model for assessing impacts of urban development on water quality for sustainable seagrass growth in Tampa Bay, Florida

    EPA Science Inventory

    We present an integrated assessment model to predict potential unintended consequences of urban development on the sustainability of seagrasses and preservation of ecosystem services, such as catchable fish, in Tampa Bay. Ecosystem services are those ecological functions and pro...

  4. Applications of 3D hydrodynamic and particle tracking models in the San Francisco bay-delta estuary

    USGS Publications Warehouse

    Smith, P.E.; Donovan, J.M.; Wong, H.F.N.

    2005-01-01

    Three applications of three-dimensional hydrodynamic and particle-tracking models are currently underway by the United States Geological Survey in the San Francisco Bay-Delta Estuary. The first application is to the San Francisco Bay and a portion of the coastal ocean. The second application is to an important, gated control channel called the Delta Cross Channel, located within the northern portion of the Sacramento-San Joaquin River Delta. The third application is to a reach of the San Joaquin River near Stockton, California where a significant dissolved oxygen problem exists due, in part, to conditions associated with the deep-water ship channel for the Port of Stockton, California. This paper briefly discusses the hydrodynamic and particle tracking models being used and the three applications. Copyright ASCE 2005.

  5. An empirical model for earthquake probabilities in the San Francisco Bay region, California, 2002-2031

    USGS Publications Warehouse

    Reasenberg, P.A.; Hanks, T.C.; Bakun, W.H.

    2003-01-01

    The moment magnitude M 7.8 earthquake in 1906 profoundly changed the rate of seismic activity over much of northern California. The low rate of seismic activity in the San Francisco Bay region (SFBR) since 1906, relative to that of the preceding 55 yr, is often explained as a stress-shadow effect of the 1906 earthquake. However, existing elastic and visco-elastic models of stress change fail to fully account for the duration of the lowered rate of earthquake activity. We use variations in the rate of earthquakes as a basis for a simple empirical model for estimating the probability of M ???6.7 earthquakes in the SFBR. The model preserves the relative magnitude distribution of sources predicted by the Working Group on California Earthquake Probabilities' (WGCEP, 1999; WGCEP, 2002) model of characterized ruptures on SFBR faults and is consistent with the occurrence of the four M ???6.7 earthquakes in the region since 1838. When the empirical model is extrapolated 30 yr forward from 2002, it gives a probability of 0.42 for one or more M ???6.7 in the SFBR. This result is lower than the probability of 0.5 estimated by WGCEP (1988), lower than the 30-yr Poisson probability of 0.60 obtained by WGCEP (1999) and WGCEP (2002), and lower than the 30-yr time-dependent probabilities of 0.67, 0.70, and 0.63 obtained by WGCEP (1990), WGCEP (1999), and WGCEP (2002), respectively, for the occurrence of one or more large earthquakes. This lower probability is consistent with the lack of adequate accounting for the 1906 stress-shadow in these earlier reports. The empirical model represents one possible approach toward accounting for the stress-shadow effect of the 1906 earthquake. However, the discrepancy between our result and those obtained with other modeling methods underscores the fact that the physics controlling the timing of earthquakes is not well understood. Hence, we advise against using the empirical model alone (or any other single probability model) for estimating the

  6. Spectral aerosol optical depths over Bay of Bengal and Chennai: II—sources, anthropogenic influence and model estimates

    NASA Astrophysics Data System (ADS)

    Ramachandran, S.; Jayaraman, A.

    A cruise experiment was conducted in February-March 2001 to study the aerosol optical characteristics over Bay of Bengal, identify the source regions of aerosols and to estimate the anthropogenic contribution to the measured aerosol optical depths. The aerosol optical depths (AODs) exhibit significant spatial differences. The observed variations are explained by 7-days back trajectory analyses performed at different heights. The higher AODs obtained on 21 February are found influenced by the air mass at different heights originating either from Bangladesh or mainland India, indicating the anthropogenic influence. The anthropogenic influence on AOD are estimated by comparing the AODs obtained over Bay of Bengal (i) with that measured over a clean oceanic region taking into account the wind speed dependence on sea-salt aerosols and (ii) using maritime clean aerosol. From the two methods the estimated mean contribution by the anthropogenic sources to the AODs measured over Bay of Bengal are found to be in the range of 74-92% at 0.5 μm. Over Chennai, an urban station located on the eastern coastline of India, the anthropogenic contribution is estimated by comparing the measured AOD values with that of clean continental aerosol model and is found to be about 89%. This percentage contribution is higher than the contributions measured over Kaashidhoo and the northern Indian Ocean during INDOEX. INDOEX expeditions were conducted over the Arabian Sea and Indian Ocean on the western side of the Indian subcontinent, while the Bay of Bengal experiment was conducted on the eastern side. The differences in percentage contributions could possibly be due to the differences in anthropogenic activities, changes in the meteorological conditions, wind patterns, production and subsequently the transport of aerosols. The measured AOD spectra are reconstructed using OPAC to find out the possible chemical species which make up the aerosols over Bay of Bengal and Chennai. The AODs are

  7. Assessing past and present P Retention in Sediments in Lake Ontario (Bay of Quinte) by Reaction-Transport Diagenetic Modeling

    NASA Astrophysics Data System (ADS)

    Doan, Phuong; Berry, Sandra; Markovic, Stefan; Watson, Sue; Mugalingam, Shan; Dittrich, Maria

    2016-04-01

    Phosphorus (P) is an important macronutrient that can limit aquatic primary production and the risk of harmful algal blooms. Although there is considerable evidence that P release from sediments can represent a significant source of P and burial in sediments returns P to the geological sink; these processes have been poorly characterised. In this study, we applied a non-steady state reactive transport diagenetic model to gain insights into the dynamics of phosphorus binding forms in sediments and the phosphorus cycling of the Bay of Quinte, an embayment of Lake Ontario, Canada. The three basins of the bay (Belleville, Hay Bay and Napanee) that we investigated had differences in their phosphorus binding forms and phosphorus release, reflecting the distinct spatial temporal patterns of land use and urbanization levels in the watershed. Sediment cores from the three stations were collected during summer and under ice cover in 2013-14. Oxygen, pH and redox potential were monitored by microsensors; porewater and sediment solid matter were analyzed for P content, and a sequential extraction was used to analyze P binding forms. In the reaction-transport model, total phosphorus was divided into adsorbed phosphorus, phosphorus bound with aluminium, organic phosphorus, redox sensitive and apatite phosphorus. Using the fluxes of organic and inorganic matter as dynamic boundary conditions, we simulated the depth profiles of solute and solid components. The model closely reproduced the fractionation data of phosphorus binding forms and soluble reactive phosphorus. The past and present P fluxes were calculated and estimated; they related to geochemical conditions, and P binding forms in sediments. Our results show that P release from sediments is dominated by the redox-sentive P fraction accounting for higher percentage at Napanee station. The main P binding form that can be immobilized through diagenesis is apatite P contributing highest P retention at HayBay station. The mass

  8. Vitalistic causality in young children's naive biology.

    PubMed

    Inagaki, Kayoko; Hatano, Giyoo

    2004-08-01

    One of the key issues in conceptual development research concerns what kinds of causal devices young children use to understand the biological world. We review evidence that children predict and interpret biological phenomena, especially human bodily processes, on the basis of 'vitalistic causality'. That is, they assume that vital power or life force taken from food and water makes humans active, prevents them from being taken ill, and enables them to grow. These relationships are also extended readily to other animals and even to plants. Recent experimental results show that a majority of preschoolers tend to choose vitalistic explanations as most plausible. Vitalism, together with other forms of intermediate causality, constitute unique causal devices for naive biology as a core domain of thought. PMID:15335462

  9. Three-dimensional P wave velocity model for the San Francisco Bay region, California

    NASA Astrophysics Data System (ADS)

    Thurber, Clifford H.; Brocher, Thomas M.; Zhang, Haijiang; Langenheim, Victoria E.

    2007-07-01

    A new three-dimensional P wave velocity model for the greater San Francisco Bay region has been derived using the double-difference seismic tomography method, using data from about 5,500 chemical explosions or air gun blasts and approximately 6,000 earthquakes. The model region covers 140 km NE-SW by 240 km NW-SE, extending from 20 km south of Monterey to Santa Rosa and reaching from the Pacific coast to the edge of the Great Valley. Our model provides the first regional view of a number of basement highs that are imaged in the uppermost few kilometers of the model, and images a number of velocity anomaly lows associated with known Mesozoic and Cenozoic basins in the study area. High velocity (Vp > 6.5 km/s) features at ˜15-km depth beneath part of the edge of the Great Valley and along the San Francisco peninsula are interpreted as ophiolite bodies. The relocated earthquakes provide a clear picture of the geometry of the major faults in the region, illuminating fault dips that are generally consistent with previous studies. Ninety-five percent of the earthquakes have depths between 2.3 and 15.2 km, and the corresponding seismic velocities at the hypocenters range from 4.8 km/s (presumably corresponding to Franciscan basement or Mesozoic sedimentary rocks of the Great Valley Sequence) to 6.8 km/s. The top of the seismogenic zone is thus largely controlled by basement depth, but the base of the seismogenic zone is not restricted to seismic velocities of ≤6.3 km/s in this region, as had been previously proposed.

  10. Human Naive Embryonic Stem Cells: How Full Is the Glass?

    PubMed

    Wang, Yixuan; Gao, Shaorong

    2016-03-01

    Human naive embryonic stem cells in the ground state of pluripotency provide a new opportunity to study human developmental biology and potential clinical applications. Two studies now report related work in human naive stem cell derivation and DNA methylation analysis, with one reporting some differences from oocyte and blastocyst profiles. PMID:26942847

  11. Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

    NASA Technical Reports Server (NTRS)

    Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

    2005-01-01

    This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has

  12. Florida Bay salinity and Everglades wetlands hydrology circa 1900 CE: A compilation of paleoecology-based statistical modeling analyses

    USGS Publications Warehouse

    Marshall, F.E.; Wingard, G.L.

    2012-01-01

    The upgraded method of coupled paleosalinity and hydrologic models was applied to the analysis of the circa-1900 CE segments of five estuarine sediment cores collected in Florida Bay. Comparisons of the observed mean stage (water level) data to the paleoecology-based model's averaged output show that the estimated stage in the Everglades wetlands was 0.3 to 1.6 feet higher at different locations. Observed mean flow data compared to the paleoecology-based model output show an estimated flow into Shark River Slough at Tamiami Trail of 401 to 2,539 cubic feet per second (cfs) higher than existing flows, and at Taylor Slough Bridge an estimated flow of 48 to 218 cfs above existing flows. For salinity in Florida Bay, the difference between paleoecology-based and observed mean salinity varies across the bay, from an aggregated average salinity of 14.7 less than existing in the northeastern basin to 1.0 less than existing in the western basin near the transition into the Gulf of Mexico. When the salinity differences are compared by region, the difference between paleoecology-based conditions and existing conditions are spatially consistent.

  13. Modeling bioaccumulation and biotransformation of PAHs and PCBs by benthic macrofauna from lower Chesapeake Bay

    SciTech Connect

    Dickhut, R.M.; Schaffner, L.C.; Lay, P.; Mitra, S.

    1995-12-31

    The bioaccumulation and biotransformation of selected PAHs and PCBs from sediments spiked with radiolabeled compounds were examined in benthic communities from lower chesapeake Bay during summer and winter. Kinetic models were then used to determine the steady-state bioaccumulation factors (BAFs) for the parent compounds in various benthic macrofaunal organisms, as well as the BAFs of aqueous soluble metabolites that tended to accumulate in the animals. BAFs for the parent compounds increased with the octanol-water partition coefficient (K{sub ow}) of the compound up to a log K{sub ow} of approximately 6. However, in contrast to previous studies, the elimination rate constant was the dominant factor controlling the observed nonequilibrium with respect to bioaccumulation of the organic contaminants. Consequently, BAFs for the parent contaminants were related to the physical-chemical factors regulating passive elimination, as well as metabolic transformation of the parent compound. Aqueous soluble metabolite BAFs were directly related to the physical-chemical factors dictating the rate of formation of the conjugated complexes. Overall, body burdens of organic contaminants were higher in the summer relative to winter, as were the aqueous soluble metabolite fractions of contaminants in the animals, possibly indicating that organism activities as well as lipid pools are higher in summer compared to winter. The results indicate that a variety of physical, chemical, and biological factors interact in the ecosystem to dictate bioaccumulation and biotransformation of organic contaminants.

  14. Fuzzy Naive Bayesian for constructing regulated network with weights.

    PubMed

    Zhou, Xi Y; Tian, Xue W; Lim, Joon S

    2015-01-01

    In the data mining field, classification is a very crucial technology, and the Bayesian classifier has been one of the hotspots in classification research area. However, assumptions of Naive Bayesian and Tree Augmented Naive Bayesian (TAN) are unfair to attribute relations. Therefore, this paper proposes a new algorithm named Fuzzy Naive Bayesian (FNB) using neural network with weighted membership function (NEWFM) to extract regulated relations and weights. Then, we can use regulated relations and weights to construct a regulated network. Finally, we will classify the heart and Haberman datasets by the FNB network to compare with experiments of Naive Bayesian and TAN. The experiment results show that the FNB has a higher classification rate than Naive Bayesian and TAN. PMID:26405944

  15. Micropollutant dynamics in Vidy Bay--a coupled hydrodynamic-photolysis model to assess the spatial extent of ecotoxicological risk.

    PubMed

    Bonvin, Florence; Razmi, Amir M; Barry, David A; Kohn, Tamar

    2013-08-20

    The direct discharge of effluent wastewater into Vidy Bay (Lake Geneva) results in the formation of an effluent plume with locally high concentrations of wastewater-derived micropollutants. The micropollutant hotspots above the wastewater outfall present a potential ecotoxicological risk, yet the spatial extent of the plume and the associated ecotoxicological risk zone remain unclear. This work combines the two main processes affecting the spreading of the plume, namely dilution of micropollutants due to mixing and degradation by photolysis, into a coupled hydrodynamic-photolysis model, with which we estimated the spatial extent of the risk zone in Vidy Bay. The concentration of micropollutants around the wastewater outfall was simulated for typical wind scenarios and seasons relevant to Vidy Bay, and the resulting ecotoxicological risk was evaluated. Specifically, we determined the direct and indirect photolysis rate constants for 24 wastewater-derived micropollutants and implemented these in a hydrodynamic particle tracking model, which tracked the movement of water parcels from the wastewater outfall. Simulations showed that owing to thermal stratification, the zone of ecotoxicological risk is largest in summer and extends horizontally over 300 m from the outfall. Photolysis processes contribute to reducing the plume extent mainly under unstratified conditions when the plume surfaces. Moreover, it was shown that only a few compounds, mainly antibiotics, dominate the total ecotoxicological risk. PMID:23919891

  16. James Bay

    Atmospheric Science Data Center

    2013-04-17

    article title:  First Views of James Bay, Canada     ... show the winter landscape of James Bay, Ontario, Canada from three of the instrument's nine cameras. The image at left captures the opening ... down. The image on the right was taken seven minutes after the first image from the most oblique, aftward-viewing camera. "These ...

  17. Memory T cell–driven differentiation of naive cells impairs adoptive immunotherapy

    PubMed Central

    Klebanoff, Christopher A.; Scott, Christopher D.; Leonardi, Anthony J.; Yamamoto, Tori N.; Cruz, Anthony C.; Ouyang, Claudia; Ramaswamy, Madhu; Roychoudhuri, Rahul; Ji, Yun; Eil, Robert L.; Sukumar, Madhusudhanan; Crompton, Joseph G.; Palmer, Douglas C.; Borman, Zachary A.; Clever, David; Thomas, Stacy K.; Patel, Shashankkumar; Yu, Zhiya; Muranski, Pawel; Liu, Hui; Wang, Ena; Marincola, Francesco M.; Gros, Alena; Gattinoni, Luca; Rosenberg, Steven A.; Siegel, Richard M.; Restifo, Nicholas P.

    2015-01-01

    Adoptive cell transfer (ACT) of purified naive, stem cell memory, and central memory T cell subsets results in superior persistence and antitumor immunity compared with ACT of populations containing more-differentiated effector memory and effector T cells. Despite a clear advantage of the less-differentiated populations, the majority of ACT trials utilize unfractionated T cell subsets. Here, we have challenged the notion that the mere presence of less-differentiated T cells in starting populations used to generate therapeutic T cells is sufficient to convey their desirable attributes. Using both mouse and human cells, we identified a T cell–T cell interaction whereby antigen-experienced subsets directly promote the phenotypic, functional, and metabolic differentiation of naive T cells. This process led to the loss of less-differentiated T cell subsets and resulted in impaired cellular persistence and tumor regression in mouse models following ACT. The T memory–induced conversion of naive T cells was mediated by a nonapoptotic Fas signal, resulting in Akt-driven cellular differentiation. Thus, induction of Fas signaling enhanced T cell differentiation and impaired antitumor immunity, while Fas signaling blockade preserved the antitumor efficacy of naive cells within mixed populations. These findings reveal that T cell subsets can synchronize their differentiation state in a process similar to quorum sensing in unicellular organisms and suggest that disruption of this quorum-like behavior among T cells has potential to enhance T cell–based immunotherapies. PMID:26657860

  18. Characterization of the finch embryo supports evolutionary conservation of the naive stage of development in amniotes

    PubMed Central

    Mak, Siu-Shan; Alev, Cantas; Nagai, Hiroki; Wrabel, Anna; Matsuoka, Yoko; Honda, Akira; Sheng, Guojun; Ladher, Raj K

    2015-01-01

    Innate pluripotency of mouse embryos transits from naive to primed state as the inner cell mass differentiates into epiblast. In vitro, their counterparts are embryonic (ESCs) and epiblast stem cells (EpiSCs), respectively. Activation of the FGF signaling cascade results in mouse ESCs differentiating into mEpiSCs, indicative of its requirement in the shift between these states. However, only mouse ESCs correspond to the naive state; ESCs from other mammals and from chick show primed state characteristics. Thus, the significance of the naive state is unclear. In this study, we use zebra finch as a model for comparative ESC studies. The finch blastoderm has mESC-like properties, while chick blastoderm exhibits EpiSC features. In the absence of FGF signaling, finch cells retained expression of pluripotent markers, which were lost in cells from chick or aged finch epiblasts. Our data suggest that the naive state of pluripotency is evolutionarily conserved among amniotes. DOI: http://dx.doi.org/10.7554/eLife.07178.001 PMID:26359635

  19. Shallow-water System Dynamics in Chesapeake Bay, with Physical-Biological Modeling Application

    NASA Astrophysics Data System (ADS)

    Tian, R.; Wang, P.; Linker, L. C.

    2014-12-01

    Chesapeake Bay is the largest estuary in the United States. The total surface area is 9920 square kilometers of which 7540 square kilometers are shallower than 10 m. These shallow systems provide vital habitats and nursery grounds for numerous species of fish, shellfish, and wildlife. In the Chesapeake the shallow water systems have deteriorated in terms of healthy ecosystem levels and submerged aquatic vegetation (SAV). Restoration of the shallow water systems requires an understanding of their dynamics including wave-current interactions, shoreline erosion, sediment suspension, biological and biogeochemical processes, sediment diagenesis, sediment-water exchange, and diel cycles of temperature, salinity, turbidity, alkalinity, chlorophyll, nutrients, and dissolved oxygen (DO). To this end, an extensive shallow water monitoring program has been implemented in the Chesapeake since 2003. The program includes bi-weekly cruises of nutrient sampling, a continuous monitoring network with electronic sensors collecting data at a 15 minute interval, and a unique data flow survey from moving boats that collect underway observations with a datum frequency of seconds. The data reveal large diel cycles, with chlorophyll varying between a few mg/l to hundreds of mg/l, DO between 0 to 20 mg/l (with saturation from 0 to 250%), turbidity between 0 to 1500 NTUs, and pH from 6.0 to 9.5, which demonstrate the highly dynamic nature in physical and biological process of the shallow water systems . In order to better understand the key mechanisms and processes of these shallow-water systems and to explore the monitoring data, we applied a coupled physical and water quality model to the Chester and Corsica tributaries. The physical model is the Unstructured Finite Volume Coastal Ocean Model (FVCOM) and the water quality model is the Integrated Compartment Model (ICM) which has 36 state variables such as phytoplankton, zooplankton, DO, nutrients, and various organic matter and sediment

  20. Wind-Farm Forecasting Using the HARMONIE Weather Forecast Model and Bayes Model Averaging for Bias Removal.

    NASA Astrophysics Data System (ADS)

    O'Brien, Enda; McKinstry, Alastair; Ralph, Adam

    2015-04-01

    Building on previous work presented at EGU 2013 (http://www.sciencedirect.com/science/article/pii/S1876610213016068 ), more results are available now from a different wind-farm in complex terrain in southwest Ireland. The basic approach is to interpolate wind-speed forecasts from an operational weather forecast model (i.e., HARMONIE in the case of Ireland) to the precise location of each wind-turbine, and then use Bayes Model Averaging (BMA; with statistical information collected from a prior training-period of e.g., 25 days) to remove systematic biases. Bias-corrected wind-speed forecasts (and associated power-generation forecasts) are then provided twice daily (at 5am and 5pm) out to 30 hours, with each forecast validation fed back to BMA for future learning. 30-hr forecasts from the operational Met Éireann HARMONIE model at 2.5km resolution have been validated against turbine SCADA observations since Jan. 2014. An extra high-resolution (0.5km grid-spacing) HARMONIE configuration has been run since Nov. 2014 as an extra member of the forecast "ensemble". A new version of HARMONIE with extra filters designed to stabilize high-resolution configurations has been run since Jan. 2015. Measures of forecast skill and forecast errors will be provided, and the contributions made by the various physical and computational enhancements to HARMONIE will be quantified.

  1. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem.

    PubMed

    Taktak, Azzam F G; Fisher, Anthony C; Damato, Bertil E

    2004-01-01

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to > 100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For < 10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate. PMID:14971774

  2. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    NASA Astrophysics Data System (ADS)

    Taktak, Azzam F. G.; Fisher, Anthony C.; Damato, Bertil E.

    2004-01-01

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate.

  3. Results of a modeling workshop concerning economic and environmental trends and concomitant resource management issues in the Mobile Bay area

    USGS Publications Warehouse

    Hamilton, David B.; Andrews, Austin K.; Auble, Gregor T.; Ellison, Richard A.; Johnson, Richard A.; Roelle, James E.; Staley, Michael J.

    1982-01-01

    During the past decade, the southern regions of the U.S. have experienced rapid change which is expected to continue into the foreseeable future. Growth in population, industry, and resource development has been attributed to a variety of advantages such as an abundant and inexpensive labor force, a mild climate, and the availability of energy, water, land, and other natural resources. While this growth has many benefits for the region, it also creates the potential for increased air, water, and solid waste pollution, and modification of natural habitats. A workshop was convened to consider the Mobile Bay area as a site-specific case of growth and its environmental consequences in the southern region. The objectives of the modeling workshop were to: (1) identify major factors of economic development as they relate to growth in the area over the immediate and longer term; (2) identify major environmental and resource management issues associated with this expected growth; and (3) identify and characterize the complex interrelationships among economic and environmental factors. This report summarizes the activities and results of a modeling workshop concerning economic growth and concomitant resource management issues in the Mobile Bay area. The workshop was organized around construction of a simulation model representing the relationships between a series of actions and indicators identified by participants. The workshop model had five major components. An Industry Submodel generated scenarios of growth in several industrial and transportation sectors. A Human Population/Economy Submodel calculated human population and economic variables in response to employment opportunities. A Land Use/Air Quality Submodel tabulated changes in land use, shoreline use, and air quality. A Water Submodel calculated indicators of water quality and quantity for fresh surface water, ground water, and Mobile Bay based on discharge information provided by the Industry and Human

  4. Influence of water allocation and freshwater inflow on oyster production: a hydrodynamic-oyster population model for Galveston Bay, Texas, USA.

    PubMed

    Powell, Eric N; Klinck, John M; Hofmann, Eileen E; McManus, Margaret A

    2003-01-01

    A hydrodynamic-oyster population model was developed to assess the effect of changes in freshwater inflow on oyster populations in Galveston Bay, Texas, USA. The population model includes the effects of environmental conditions, predators, and the oyster parasite, Perkinsus marinus, on oyster populations. The hydrodynamic model includes the effects of wind stress, river runoff, tides, and oceanic exchange on the circulation of the bay. Simulations were run for low, mean, and high freshwater inflow conditions under the present (1993) hydrology and predicted hydrologies for 2024 and 2049 that include both changes in total freshwater inflow and diversions of freshwater from one primary drainage basin to another. Freshwater diversion to supply the Houston metropolitan area is predicted to negatively impact oyster production in Galveston Bay. Fecundity and larval survivorship both decline. Mortality from Perkinsus marinus increases, but to a lesser extent. A larger negative impact in 2049 relative to 2024 originates from the larger drop in fecundity under that hydrology. Changes in recruitment and mortality, resulting in lowered oyster abundance, occur because the bay volume available for mixing freshwater input from the San Jacinto and Buffalo Bayou drainage basins that drain metropolitan Houston is small in comparison to the volume of Trinity Bay that presently receives the bulk of the bay's freshwater inflow. A smaller volume for mixing results in salinities that decline more rapidly and to a greater extent under conditions of high freshwater discharge.Thus, the decline in oyster abundance results from a disequilibrium between geography and salinity brought about by freshwater diversion. Although the bay hydrology shifts, available hard substrate does not. The simulations stress the fact that it is not just the well-appreciated reduction in freshwater inflow that can result in decreased oyster production. Changing the location of freshwater inflow can also

  5. Alternative models of climatic effects on sockeye salmon (Oncorhynchus nerka) productivity in Bristol Bay, Alaska, and the Fraser River, British Columbia

    USGS Publications Warehouse

    Adkison, M.; Peterman, R.; Lapointe, M.; Gillis, D.; Korman, J.

    1996-01-01

    We compare alternative models of sockeye salmon (Oncorhynchus nerka) productivity (returns per spawner) using more than 30 years of catch and escapement data for Bristol Bay, Alaska, and the Fraser River, British Columbia. The models examined include several alternative forms of models that incorporate climatic influences as well as models not based on climate. For most stocks, a stationary stock-recruitment relationship explains very little of the interannual variation in productivity. In Bristol Bay, productivity co-varies among stocks and appears to be strongly related to fluctuations in climate. The best model for Bristol Bay sockeye involved a change in the 1970s in the parameters of the Ricker stock-recruitment curve; the stocks generally became more productive. In contrast, none of the models of Fraser River stocks that we examined explained much of the variability in their productivity.

  6. Sediment characterization in intertidal zone of the Bourgneuf bay using the Automatic Modified Gaussian Model (AMGM)

    NASA Astrophysics Data System (ADS)

    Verpoorter, C.; Carrère, V.; Combe, J.-P.; Le Corre, L.

    2009-04-01

    Understanding of the uppermost layer of cohesive sediment beds provides important clues for predicting future sediment behaviours. Sediment consolidation, grain size, water content and biological slimes (EPS: extracellular polymeric substances) were found to be significant factors influencing erosion resistance. The surface spectral signatures of mudflat sediments reflect such bio-geophysical parameters. The overall shape of the spectrum, also called a continuum, is a function of grain size and moisture content. Composition translates into specific absorption features. Finally, the chlorophyll-a concentration derived from the strength of the absorption at 675 nm, is a good proxy for biofilm biomass. Bourgneuf Bay site, south of the Loire river estuary, France, was chosen to represent a range of physical and biological influences on sediment erodability. Field spectral measurements and samples of sediments were collected during various field campaigns. An ASD Fieldspec 3 spectroradiometer was used to produce sediment reflectance hyperspectra in the wavelength range 350-2500 nm. We have developed an automatic procedure based on the Modified Gaussian Model that uses, as the first step, the Spectroscopic Derivative Analysis (SDA) to extract from spectra the bio-geophysical properties on mudflat sediments (Verpoorter et al., 2007). This AMGM algorithm is a powerfull tool to deconvolve spectra into two components, first gaussian curves for the absorptions bands, and second a straight line in the wavenumber range for the continuum. We are investigating the possibility of including other approaches, as the inverse gaussian band centred on 2800 nm initially developed by Whiting et al., (2006) to estimate water content. Additionally, soils samples were analysed to determine moisture content, grain size (laser grain size analyses), organic matter content, carbonate content (calcimetry) and clay content. X-ray diffraction analysis was performed on selected non

  7. A SIMPLE MODEL FOR FORECASTING THE EFFECTS OF NITROGEN LOADS ON CHESAPEAKE BAY HYPOXIA

    EPA Science Inventory

    The causes and consequences of oxygen depletion in Chesapeake Bay have been the focus of research, assessment, and policy action over the past several decades. An ongoing scientific re-evaluation of what nutrients load reductions are necessary to meet the water quality goals is ...

  8. A physical model for strain accumulation in the San Francisco Bay Region

    USGS Publications Warehouse

    Pollitz, F.F.; Nyst, M.

    2005-01-01

    Strain accumulation in tectonically active regions is generally a superposition of the effects of background tectonic loading, steady-state dislocation processes, such as creep, and transient deformation. In the San Francisco Bay region (SFBR), the most uncertain of these processes is transient deformation, which arises primarily in association with large earthquakes. As such, it depends upon the history of faulting and the rheology of the crust and mantle, which together determine the pattern of longer term (decade-scale) post-seismic response to earthquakes. We utilize a set of 102 GPS velocity vectors in the SFBR in order to characterize the strain rate field and construct a physical model of its present deformation. We first perform an inversion for the continuous velocity gradient field from the discrete GPS velocity field, from which both tensor strain rate and rotation rate may be extracted. The present strain rate pattern is well described as a nearly uniform shear strain rate oriented approximately N34??W (140 nanostrain yr-1) plus a N56??E uniaxial compression rate averaging 20 nanostrain yr-1 across the shear zone. We fit the velocity and strain rate fields to a model of time-dependent deformation within a 135-kin-wide, arcuate shear zone bounded by strong Pacific Plate and Sierra Nevada block lithosphere to the SW and NE, respectively. Driving forces are purely lateral, consisting of shear zone deformation imposed by the relative motions between the thick Pacific Plate and Sierra Nevada block lithospheres. Assuming a depth-dependent viscoelastic structure within the shear zone, we account for the effects of steady creep on faults and viscoelastic relaxation following the 1906 San Francisco and 1989 Loma Prieta earthquakes, subject to constant velocity boundary conditions on the edges of the shear zone. Fault creep is realized by evaluating dislocations on the creeping portions of faults in the fluid limit of the viscoelastic model. A priori plate

  9. Regional downscaling of temporal resolution in near-surface wind from statistically downscaled Global Climate Models (GCMs) for use in San Francisco Bay coastal flood modeling

    NASA Astrophysics Data System (ADS)

    O'Neill, A.; Erikson, L. H.; Barnard, P.

    2013-12-01

    While Global Climate Models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues (MACA) provide daily near-surface winds at an appropriate spatial resolution for wave modeling within San Francisco Bay. Using 30 years (1975-2004) of climatological data from four representative stations around San Francisco Bay, a library of example daily wind conditions for four corresponding over-water sub-regions is constructed. Empirical cumulative distribution functions (ECDFs) of station conditions are compared to MACA GFDL hindcasts to create correction factors, which are then applied to 21st century MACA wind projections. For each projection day, a best match example is identified via least squares error among all stations from the library. The best match's daily variation in velocity components (u/v) is used as an analogue of representative wind variation and is applied at 3-hour increments about the corresponding sub-region's projected u/v values. High temporal resolution reconstructions using this methodology on hindcast MACA fields from 1975-2004 accurately recreate extreme wind values within the San Francisco Bay, and because these extremes in wind forcing are of key importance in wave and subsequent coastal flood modeling, this represents a valuable method of generating near-surface wind vectors for use in coastal flood modeling.

  10. Air-sea interactions over Terra Nova Bay during winter: Simulation with a coupled atmosphere-polynya model

    NASA Astrophysics Data System (ADS)

    Gallée, Hubert

    A preliminary simulation of the Terra Nova Bay polynya has been performed with a coupled atmosphere-polynya model. The atmospheric model is a hydrostatic primitive equations model that has been validated previously by a simulation of the strong katabatic winds observed in that area. The polynya model includes a representation of the free drift of frazil ice and simple sea-ice dynamics and thermodynamics. Two and three-dimensional experiments have been performed under polar night conditions. Two-dimensional experiments show that an open (warm) water area influences significantly the atmospheric circulation in the antarctic coastal zone: an additional ice-breeze effect is simulated and is responsible for the strengthening of the katabatic winds near the coast. Because of the important temperature difference between the continental air and the ice-free ocean (up to 40°C), strong surface heat fluxes are simulated over the polynya. Finally, a three-dimensional experiment has been performed. The integration domain includes Terra Nova Bay. The polynya observed in that region is well simulated. It is found that heat losses from the polynya surface are stronger than previously thought but are probably constrained by the idealized representation of frazil ice, which is assumed to be uniform in each grid box. This stresses the need for having a better knowledge of frazil ice evolution in large polynyas.

  11. Performance of WRF-ARW model in real-time prediction of Bay of Bengal cyclone `Phailin'

    NASA Astrophysics Data System (ADS)

    Mandal, M.; Singh, K. S.; Balaji, M.; Mohapatra, M.

    2016-05-01

    This study examines the performance of the Advanced Research core of Weather Research and Forecasting (ARW-WRF) model in prediction of the Bay of Bengal cyclone `Phailin'. The two-way interactive double-nested model at 27 and 9-km resolutions customized at Indian Institute of Technology Kharagpur (IITKGP) is used to predict the storm on real-time basis and five predictions are made with five different initial conditions. The initial and boundary conditions for the model are derived from the Global Forecasting System (GFS) analysis and forecast respectively. The track of storm is well predicted in all the five forecasts. In particular, the forecast with less initial positional error led to more accurate track and landfall prediction. It is observed that the predicted peak intensity and translation speed of the storm depends strongly on initial intensity error, vertical wind shear and vertical distribution of maximum potential vorticity. The trend of intensification and dissipation of the storm is well predicted by the model in terms of central sea level pressure (CSLP). The intensity in terms of maximum surface wind (MSW) is under-predicted by the model and it is suggested that the MSW estimated from predicted pressure drop may be used as prediction guideline. The storm intensified rapidly during its passage over the high Tropical Cyclone Heat Potential zone and is reasonably well predicted by the model. Though the magnitude of the precipitation is not well predicted, distribution of precipitation is fairly well predicted by the model. The track and intensity of the storm predicted by the customized WRF-ARW is better than that of other NWP models. The landfall (time and position) is also better predicted by the model compared to other NWP models if initialized at cyclonic storm stage. The results indicate that the customized model have good potential for real-time prediction of Bay of Bengal cyclones and encourage further investigation with larger number of cyclones.

  12. Successful gas shutoff with polymer gel using temperature modeling and selective placement in the Prudhoe Bay field

    SciTech Connect

    Sanders, G.S.; Chambers, M.J.; Lane, R.H.

    1995-12-31

    A combination of known crosslinked gel chemistry with careful problem diagnosis, wellbore and formation temperature modeling, and zone isolation techniques yields a high success rate for shutting off unwanted gas influx into production wells in the Prudhoe Bay Field of Alaska. The paper includes candidate selection criteria, methodology of temperature simulation, job design, field operations case histories, and pre- and post-job production data for evaluation of success. This approach has led to a 60% technical success rate, primarily on wells that had cement squeeze failures. Job costs are about 75% those of comparable cement squeezes.

  13. Mapping the route from naive pluripotency to lineage specification.

    PubMed

    Kalkan, Tüzer; Smith, Austin

    2014-12-01

    In the mouse blastocyst, epiblast cells are newly formed shortly before implantation. They possess a unique developmental plasticity, termed naive pluripotency. For development to proceed, this naive state must be subsumed by multi-lineage differentiation within 72 h following implantation. In vitro differentiation of naive embryonic stem cells (ESCs) cultured in controlled conditions provides a tractable system to dissect and understand the process of exit from naive pluripotency and entry into lineage specification. Exploitation of this system in recent large-scale RNAi and mutagenesis screens has uncovered multiple new factors and modules that drive or facilitate progression out of the naive state. Notably, these studies show that the transcription factor network that governs the naive state is rapidly dismantled prior to upregulation of lineage specification markers, creating an intermediate state that we term formative pluripotency. Here, we summarize these findings and propose a road map for state transitions in ESC differentiation that reflects the orderly dynamics of epiblast progression in the embryo. PMID:25349449

  14. Hydrodynamic modeling and analysis of sea-level rise impacts on salinity for oyster growth in Apalachicola Bay, Florida

    NASA Astrophysics Data System (ADS)

    Huang, Wenrui; Hagen, Scott; Bacopoulos, Peter; Wang, Dingbao

    2015-04-01

    In this study, a previously calibrated hydrodynamic model was applied to investigate the impacts of sea level rise on salinity variations and oyster growth in Apalachicola Bay. With available observed data (winds, tides, and river flow), a case study has been conducted for the period of June 10-July 9, 2005. In addition, sea level rise impacts under a range of river flow conditions have also been examined, which include minimum monthly flow, average monthly flow, and maximum monthly flow based on the flow data from 1977 to 2013. Referring to the case study conditions under the existing sea level, model simulations were conducted to examine salinity changes in the bay in response to the sea level rise scenarios of 0.31 m, 0.5 m and 1.0 m. SLR-induced saline water intrusion mainly enters the estuary from the large opening in the east boundary. Based on the optimal salinity range for oyster growth (20-25 at Cat Point and 17-26 at Dry Bar) in Apalachicola Bay, SLR impacts were evaluated based on the model predicted salinity at Dry Bay and Cat Point. Results indicate that sea level rise results in stronger impacts on Cat Point than Dry Bar. Under the flow conditions of average monthly flow and the observed daily flow during June 10-July 9, mean salinity at Dry Bar varies within 21-24 in the optimal salinity range under 0.31 m and 0.5 m SLR conditions; and further increase above 26.0 when SLR is equal to 1.0 m. Under the conditions of average monthly flow and the observed daily flow during June 10-July 9, the mean salinity at Cat Point is within the optimal range under existing sea level, and increases above the maximum optimal salinity of 27 under the SLR scenarios of 0.31 m, 0.5 m, and 1.0 m, respectively. Extreme low and high flow conditions have also been investigated to examine the combined effects of flow and SLR. At the same sea level rise conditions, salinity under minimum flow is much higher than those under average flow, while salinity under maximum flow is

  15. AN "ENVIRO-INFORMATIC" ASSESSMENT OF SAGINAW BAY (LAKE HURON, USA) PHYTOPLANKTON: DATA-DRIVEN CHARACTERIZATION AND MODELING OF MICROCYSTIS (CYANOPHYTA)(1).

    PubMed

    Millie, David F; Fahnenstiel, Gary L; Weckman, Gary R; Klarer, David M; Dyble, Julianne; Vanderploeg, Henry A; Fishman, Daniel B

    2011-08-01

    Phytoplankton and Microcystis aeruginosa (Kütz.) Kütz. biovolumes were characterized and modeled, respectively, with regard to hydrological and meteorological variables during zebra mussel invasion in Saginaw Bay (1990-1996). Total phytoplankton and Microcystis biomass within the inner bay were one and one-half and six times greater, respectively, than those of the outer bay. Following mussel invasion, mean total biomass in the inner bay decreased 84% but then returned to its approximate initial value. Microcystis was not present in the bay during 1990 and 1991 and thereafter occurred at/in 52% of sample sites/dates with the greatest biomass occurring in 1994-1996 and within months having water temperatures >19°C. With an overall relative biomass of 0.03 ± 0.01 (mean + SE), Microcystis had, at best, a marginal impact upon holistic compositional dynamics. Dynamics of the centric diatom Cyclotella ocellata Pant. and large pennate diatoms dominated compositional dissimilarities both inter- and intra-annually. The environmental variables that corresponded with phytoplankton distributions were similar for the inner and outer bays, and together identified physical forcing and biotic utilization of nutrients as determinants of system-level biomass patterns. Nonparametric models explained 70%-85% of the variability in Microcystis biovolumes and identified maximal biomass to occur at total phosphorus (TP) concentrations ranging from 40 to 45 μg · L(-1) . From isometric projections depicting modeled Microcystis/environmental interactions, a TP concentration of <30 μg · L(-1) was identified as a desirable contemporary "target" for management efforts to ameliorate bloom potentials throughout mussel-impacted bay waters. PMID:27020008

  16. A numerical model simulation of the regional air pollution meteorology of the greater Chesapeake Bay area - Summer day case study

    NASA Technical Reports Server (NTRS)

    Segal, M.; Pielke, R. A.; Mcnider, R. T.; Mcdougal, D. S.

    1982-01-01

    The mesoscale numerical model of the University of Virginia (UVMM), has been applied to the greater Chesapeake Bay area in order to provide a detailed description of the air pollution meteorology during a typical summer day. This model provides state of the art simulations for land-sea thermally induced circulations. The model-predicted results agree favorably with available observed data. The effects of synoptic flow and sea breeze coupling on air pollution meteorological characteristics in this region, are demonstrated by a spatial and temporal presentation of various model predicted fields. A transport analysis based on predicted wind velocities indicated possible recirculation of pollutants back onto the Atlantic coast due to the sea breeze circulation.

  17. Environmental consequences of a power plant shut-down: a three-dimensional water quality model of Dublin Bay.

    PubMed

    Bedri, Zeinab; Bruen, Michael; Dowley, Aodh; Masterson, Bartholomew

    2013-06-15

    A hydro-environmental model is used to investigate the effect of cessation of thermal discharges from a power plant on the bathing water quality of Dublin Bay. Before closing down, cooling water from the plant was mixed with sewage effluent prior to its discharge, creating a warmer, less-saline buoyant pollutant plume that adversely affects the water quality of Dublin Bay. The model, calibrated to data from the period prior to the power-plant shut-down (Scenario1), assessed the water quality following its shut-down under two scenarios; (i) Scenario2: continued abstraction of water to dilute sewage effluents before discharge, and (ii) Scnenario3: sewage effluents are discharged directly into the Estuary. Comparison between scenarios was based on distribution of Escherichia coli (E. coli), a main bathing quality indicator. Scenarios1 and 2, showed almost similar E. coli distribution patterns while Scenario3 displayed significantly higher E. coli concentrations due to the increased stratification caused by the lack of prior dilution. PMID:23622835

  18. GALVESTON BAY CCMP

    EPA Science Inventory

    Galveston Bay ranks high among the nation's great bay systems, providing huge economic benefits to the region and state. Remarkably, the bay's natural resources are self-renewing as long as the bay remains healthy and productive. However, Galveston Bay, like many other U.S. bays,...

  19. Investigation of Wave Energy Converter Effects on Near-shore Wave Fields: Model Generation Validation and Evaluation - Kaneohe Bay HI.

    SciTech Connect

    Roberts, Jesse D.; Chang, Grace; Jones, Craig

    2014-09-01

    The numerical model, SWAN (Simulating WAves Nearshore) , was used to simulate wave conditions in Kaneohe Bay, HI in order to determine the effects of wave energy converter ( WEC ) devices on the propagation of waves into shore. A nested SWAN model was validated then used to evaluate a range of initial wave conditions: significant wave heights (H s ) , peak periods (T p ) , and mean wave directions ( MWD) . Differences between wave height s in the presence and absence of WEC device s were assessed at locations in shore of the WEC array. The maximum decrease in wave height due to the WEC s was predicted to be approximately 6% at 5 m and 10 m water depths. Th is occurred for model initiation parameters of H s = 3 m (for 5 m water depth) or 4 m (10 m water depth) , T p = 10 s, and MWD = 330deg . Subsequently, bottom orbital velocities were found to decrease by about 6%.

  20. Post-stratification sampling in small area estimation (SAE) model for unemployment rate estimation by Bayes approach

    NASA Astrophysics Data System (ADS)

    Hanike, Yusrianti; Sadik, Kusman; Kurnia, Anang

    2016-02-01

    This research implemented unemployment rate in Indonesia that based on Poisson distribution. It would be estimated by modified the post-stratification and Small Area Estimation (SAE) model. Post-stratification was one of technique sampling that stratified after collected survey data. It's used when the survey data didn't serve for estimating the interest area. Interest area here was the education of unemployment which separated in seven category. The data was obtained by Labour Employment National survey (Sakernas) that's collected by company survey in Indonesia, BPS, Statistic Indonesia. This company served the national survey that gave too small sample for level district. Model of SAE was one of alternative to solved it. According the problem above, we combined this post-stratification sampling and SAE model. This research gave two main model of post-stratification sampling. Model I defined the category of education was the dummy variable and model II defined the category of education was the area random effect. Two model has problem wasn't complied by Poisson assumption. Using Poisson-Gamma model, model I has over dispersion problem was 1.23 solved to 0.91 chi square/df and model II has under dispersion problem was 0.35 solved to 0.94 chi square/df. Empirical Bayes was applied to estimate the proportion of every category education of unemployment. Using Bayesian Information Criteria (BIC), Model I has smaller mean square error (MSE) than model II.

  1. Higher Surface Ozone Concentrations Over the Chesapeake Bay than Over the Adjacent Land: Observations and Models from the DISCOVER-AQ and CBODAQ Campaigns

    NASA Technical Reports Server (NTRS)

    Goldberg, Daniel L.; Loughner, Christopher P.; Tzortziou, Maria; Stehr, Jeffrey W.; Pickering, Kenneth E.; Marufu, Lackson T.; Dickerson, Russell R.

    2013-01-01

    Air quality models, such as the Community Multiscale Air Quality (CMAQ) model, indicate decidedly higher ozone near the surface of large interior water bodies, such as the Great Lakes and Chesapeake Bay. In order to test the validity of the model output, we performed surface measurements of ozone (O3) and total reactive nitrogen (NOy) on the 26-m Delaware II NOAA Small Research Vessel experimental (SRVx), deployed in the Chesapeake Bay for 10 daytime cruises in July 2011 as part of NASA's GEO-CAPE CBODAQ oceanographic field campaign in conjunction with NASA's DISCOVER-AQ air quality field campaign. During this 10-day period, the EPA O3 regulatory standard of 75 ppbv averaged over an 8-h period was exceeded four times over water while ground stations in the area only exceeded the standard at most twice. This suggests that on days when the Baltimore/Washington region is in compliance with the EPA standard, air quality over the Chesapeake Bay might exceed the EPA standard. Ozone observations over the bay during the afternoon were consistently 10-20% higher than the closest upwind ground sites during the 10-day campaign; this pattern persisted during good and poor air quality days. A lower boundary layer, reduced cloud cover, slower dry deposition rates, and other lesser mechanisms, contribute to the local maximum of ozone over the Chesapeake Bay. Observations from this campaign were compared to a CMAQ simulation at 1.33 km resolution. The model is able to predict the regional maximum of ozone over the Chesapeake Bay accurately, but NOy concentrations are significantly overestimated. Explanations for the overestimation of NOy in the model simulations are also explored

  2. Remote sensing of harmful algal blooms in the Mississippi Sound and Mobile Bay: Modelling and algorithm formation

    NASA Astrophysics Data System (ADS)

    Holiday, Dan Martin

    The incidence and severity of harmful algal blooms have increased in recent decades, as have the economic effects of their occurrence. The diatom Pseudo-nitzschia spp. caused fisheries closures in Mobile Bay during 2005 due to elevated levels of domoic acid. In the previous 4 years Karenia brevis counts of >5,000 cells L-1 have occurred in Mobile Bay and the Mississippi Sound. Population levels of this magnitude had previously been recorded only in 1996. Increases in human populations, urban sprawl, development of shoreline properties, sewage effluent and resultant changes in N-P ratios of discharge waters, and decline in forest and marsh lands, will potentially increase future harmful algal bloom occurrences in the northern Gulf of Mexico. Due to this trend in occurrence of harmful algal populations, there has been an increasing awareness of the need for development of monitoring systems in this region. Traditional methods of sampling have proven costly in terms of time and resources, and increasing attention has been turned toward use of satellite data in phytoplankton monitoring and prediction. This study shows that remote sensing does have utility in monitoring and predicting locations of phytoplankton blooms in this region. It has described the composition and spatial and temporal relationships of these populations, inferring salinity, total nitrogen and total phosphorous as the primary variables driving phytoplankton populations in Mobile Bay and the Mississippi Sound. Diatoms, chlorophytes, cryptophytes, and dinoflagellates were most abundant in collections. Correlations between SeaWiFS, MODIS and in situ data have shown relationships between Rrs reflectance and phytoplankton populations. These data were used in formation of a decision tree model predicting environmental conditions conducive to the formation of phytoplankton blooms that is driven completely by satellite data. Empirical algorithms were developed for prediction of salinity, based on Rrs ratios

  3. Naive T cells proliferate strongly in neonatal mice in response to self-peptide/self-MHC complexes

    PubMed Central

    Le Campion, Armelle; Bourgeois, Christine; Lambolez, Florence; Martin, Bruno; Léaument, Sandrine; Dautigny, Nicole; Tanchot, Corinne; Pénit, Claude; Lucas, Bruno

    2002-01-01

    Adult naive T cells, which are at rest in normal conditions, proliferate strongly when transferred to lymphopenic hosts. In neonates, the first mature thymocytes to migrate to the periphery reach a compartment devoid of preexisting T cells. We have extensively analyzed the proliferation rate and phenotype of peripheral T cells from normal C57BL/6 and T cell antigen receptor transgenic mice as a function of age. We show that, like adult naive T cells transferred to lymphopenic mice, neonatal naive T cells proliferate strongly. By using bone-marrow transfer and thymic-graft models, we demonstrate that the proliferation of the first thymic emigrants reaching the periphery requires T cell antigen receptor-self-peptide/self-MHC interactions and is regulated by the size of the peripheral T cell pool. PMID:11917110

  4. Identifying beach sand sources and pathways in the San Francisco Bay Coastal System through the integration of bed characteristics, geochemical tracers, current measurements, and numerical modeling

    NASA Astrophysics Data System (ADS)

    Barnard, P.; Foxgrover, A. C.; Elias, E.; Erikson, L. H.; Hein, J. R.; McGann, M. L.; Mizell, K.; Rosenbauer, R. J.; Swarzenski, P. W.; Takesue, R. K.; Wong, F. L.; Woodrow, D. L.

    2012-12-01

    A unique, multi-faceted provenance study was performed to definitively establish the primary sources, sinks, and transport pathways of beach sized-sand in the San Francisco Bay Coastal System. This integrative program is based on comprehensive surficial sediment sampling of the San Francisco Bay Coastal System, including the seabed, bay floor, area beaches, adjacent rock units, and major drainages. Analyses of sample morphometrics and biological composition (e.g., foraminifera) were then integrated with a suite of tracers including 87Sr/86Sr and 143Nd/144Nd isotopes, rare earth elements, semi-quantitative X-ray diffraction mineralogy, and heavy minerals, and with process-based numerical modeling, in situ current measurements, and bedform asymmetry, to robustly determine the provenance of beach-sized sand in the region. Cross-validating geochemical analyses, numerical modeling, physical process measurements, and proxy-based techniques (e.g., bedform asymmetry, grain size morphometrics) is proved an effective technique for confidently defining sources, pathways, and sinks of sand in complex coastal-estuarine systems. The consensus results highlight the regional impact of a sharp reduction in the primary sediment source, the Sierras, to the San Francisco Bay Coastal System over the last century in driving erosion of the bay floor, ebb-tidal delta, and the outer coast south of the Golden Gate.A) Calculated transport directions based on the integration of the provenance techniques. B) Number of techniques applied for each grid cell to determine the final transport directions.

  5. Mobile Bay turbidity study

    NASA Technical Reports Server (NTRS)

    Crozier, G. F.; Schroeder, W. W.

    1978-01-01

    The termination of studies carried on for almost three years in the Mobile Bay area and adjacent continental shelf are reported. The initial results concentrating on the shelf and lower bay were presented in the interim report. The continued scope of work was designed to attempt a refinement of the mathematical model, assess the effectiveness of optical measurement of suspended particulate material and disseminate the acquired information. The optical characteristics of particulate solutions are affected by density gradients within the medium, density of the suspended particles, particle size, particle shape, particle quality, albedo, and the angle of refracted light. Several of these are discussed in detail.

  6. Petrologic composition model of the upper crust in Bohai Bay basin, China, based on Lamé impedances

    NASA Astrophysics Data System (ADS)

    Zhang, Xi; Tsang, Louisa L. H.; Wang, Yanghua; Zhao, Bing

    2009-12-01

    Seismic attributes, such as P- and S-wave velocity, Poisson’s ratio, and acoustic impedances, all generally can be used for distinguishing different rock types. The non-uniqueness can be largely reduced using Lamé impedances instead of acoustic impedances as additional constraints. We have followed this method to constitute a petrologic composition model of the upper crust in the Bohai Bay basin, China. We briefly review the seismic parameters used for discrimination of rock types and focus our attention on the sensitivity of different combinations of parameters to determine the composition of materials. Corrections for pressure and temperature are performed in order to compare elastic wave velocities and densities measured at room temperature and surface pressure in laboratory with those for representative rock parameters. In a second step, we find the rock classes in the tested area by contrasting known data to laboratory measurements on a variety of rock samples extracted in the area. The basic field data are P-wave velocity values collected along a seismic profile conducted in the Bozhong Depression. The different rock types belonging to a particular rock class are finally constrained by the seismic velocities, Poisson’s ratio, density, acoustic impedance, and Lamé impedance related to the topmost 10 km of the Bohai Bay crust.

  7. Full Bayes Poisson gamma, Poisson lognormal, and zero inflated random effects models: Comparing the precision of crash frequency estimates.

    PubMed

    Aguero-Valverde, Jonathan

    2013-01-01

    In recent years, complex statistical modeling approaches have being proposed to handle the unobserved heterogeneity and the excess of zeros frequently found in crash data, including random effects and zero inflated models. This research compares random effects, zero inflated, and zero inflated random effects models using a full Bayes hierarchical approach. The models are compared not just in terms of goodness-of-fit measures but also in terms of precision of posterior crash frequency estimates since the precision of these estimates is vital for ranking of sites for engineering improvement. Fixed-over-time random effects models are also compared to independent-over-time random effects models. For the crash dataset being analyzed, it was found that once the random effects are included in the zero inflated models, the probability of being in the zero state is drastically reduced, and the zero inflated models degenerate to their non zero inflated counterparts. Also by fixing the random effects over time the fit of the models and the precision of the crash frequency estimates are significantly increased. It was found that the rankings of the fixed-over-time random effects models are very consistent among them. In addition, the results show that by fixing the random effects over time, the standard errors of the crash frequency estimates are significantly reduced for the majority of the segments on the top of the ranking. PMID:22633143

  8. Modeling Tidal Stream Energy Extraction and its Effects on Transport Processes in a Tidal Channel and Bay System Using a Three-dimensional Coastal Ocean Model

    SciTech Connect

    Yang, Zhaoqing; Wang, Taiping; Copping, Andrea E.

    2013-02-28

    This paper presents a numerical modeling study for simulating in-stream tidal energy extraction and assessing its effects on the hydrodynamics and transport processes in a tidal channel and bay system connecting to coastal ocean. A marine and hydrokinetic (MHK) module was implemented in a three-dimensional (3-D) coastal ocean model using the momentum sink approach. The MHK model was validated with the analytical solutions for tidal channels under one-dimensional (1-D) conditions. Model simulations were further carried out to compare the momentum sink approach with the quadratic bottom friction approach. The effects of 3-D simulations on the vertical velocity profile, maximum extractable energy, and volume flux reduction across the channel were investigated through a series of numerical experiments. 3-D model results indicate that the volume flux reduction at the maximum extractable power predicted by the 1-D analytical model or two-dimensional (2-D) depth-averaged numerical model may be overestimated. Maximum extractable energy strongly depends on the turbine hub height in the water column, and which reaches a maximum when turbine hub height is located at mid-water depth. Far-field effects of tidal turbines on the flushing time of the tidal bay were also investigated. Model results demonstrate that tidal energy extraction has a greater effect on the flushing time than volume flux reduction, which could negatively affect the biogeochemical processes in estuarine and coastal waters that support primary productivity and higher forms of marine life.

  9. Refraction measurements and modeling over the Chesapeake Bay during the NATO (TG-51) SAPPHIRE trials, June 2006

    NASA Astrophysics Data System (ADS)

    de Jong, Arie N.; Fritz, Peter J.

    2007-10-01

    Optical refraction tends to occur frequently in the atmospheric boundary layer. Due to a gradient in the temperature as function of height, rays are bending down towards the earth (super-refraction), or up towards to the sky (sub-refraction). As a consequence, images of targets at long range may be distorted and mirages may occur, while the maximum detection range may be affected. In addition the irradiance, received from a point target at a sensor pupil, may increase or decrease due to atmospheric focusing effects. Sub-refraction tends to occur more frequently over sea-paths, as the air is normally cooler than the water. Currently available propagation models, like IRBLEM [1] and EOSTAR [2] adequately describe the mentioned effects for this condition. However sparse data are available for model validation in super-refractive conditions, when the air is warmer than the water. For this reason, the SAPPHIRE trial, (Ship and Atmospheric Propagation Phenomena Infrared Experiment), was organized in the Chesapeake Bay near Washington DC by NATO Task Group TG51 in June 2006. At this location and in this time of the year, the probability for having positive ASTD (Air to Sea Temperature Difference) conditions is high. In the bay a buoy was positioned, on which a set of precision temperature sensors was mounted. They provided as well ASTD values as temperature gradients at a height of 3.7 m. By means of a geodetic theodolite, absolute AOA's (Angle Of Arrival) were measured for a set of lights at various altitudes, located on the other side of the bay at a distance of 16.2 km. The buoy was located at about mid-path position. Positive ASTD conditions did occur on a number of days allowing validation of the values of the AOA, predicted by the models, based upon the meteorological data, simultaneously collected at the buoy. It was found, that the temperature profile, generated by the bulk model for the marine surface layer [3] is incorrect, resulting in deviations in the AOA

  10. Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling

    USGS Publications Warehouse

    Bernal, Nicholas A.; DeAngelis, Donald L.; Schofield, Pamela J.; Sullivan Sealey, Kathleen

    2014-01-01

    Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.