Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results.The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

Distributed process modeling for regional assessment of coastal vulnerability to sea-level rise

Sea-level rise involves increases in the coastal processes of inundation and erosion which are affected by a complex interplay of physical environmental parameters at the coast. Many assessments of coastal vulnerability to sea-level rise have been detailed and localised in extent. There is a need for regional assessment techniques which identify areas vulnerable to sea-level rise. Four physical environmental parameters – elevation, exposure, aspect and slope, are modeled on a regional scale for the Northern Spencer Gulf (NSG) study area using commonly available low-resolution elevation data of 10 m contour interval and GIS-based spatial modeling techniques. For comparison, the same parameters are modeled on a fine-scale for the False Bay area within the NSG using high-resolution elevation data. Physical environmental parameters on the two scales are statistically compared to coastal vulnerability classes as identified by Harvey et al. [1] using the Spearman rank-correlation test and stepwise linear regression. Coastal vulnerability is strongly correlated with elevation and exposure at both scales and this relationship is only slightly stronger for the high resolution False Bay data. The results of this study suggest that regional scale distributed coastal process modeling may be suitable as a first cut in assessing coastal vulnerability to sea-level rise in tide-dominated, sedimentary coastal regions. Distributed coastal process modeling provides a suitable basis for the assessment of coastal vulnerability to sea-level rise of sufficient accuracy for on-ground management and priority-setting on a regional scale.     

Environmental Exposure Assessment for Emergency Response in a Nuclear Power Plant Using an Integrated Source Term and 3D Numerical Model

Nuclear power plants are normally assumed to be safe when their radiation impact in all operational states is kept at a reasonably low level. However, accidentally released radioactive substances and ionizing radiation may lead to a situation that cannot maintain the regulatory prescribed dose limits for internal and external exposure of the personnel and population. Nuclear emergency preparedness and response in nuclear or radiological events have been of concern recently in international communities. Nuclear power plants may need to provide essential information regarding possible scenarios of accidental releases that might have short-term detrimental effects and long-term risks in nearby populated regions. This paper presents a synergistic integration of a source term model and a three-dimensional, time-dependent, numerical model (i.e., HOTMAC/RAPTAD), which was applied to simulate a specific scenario in which a vapor cloud was accidentally released from Maanshan (i.e., the third nuclear power plant) in South Taiwan. It aims at dealing with middle-range risk assessment for nuclear emergency preparedness and response. The solutions of such an integrated modeling platform can be found with numerical analyses that describe the processes of radionuclide generation, transport, decay, and deposition, giving the final risk assessment in a neighboring coastal city—Kaohsiung, South Taiwan. In addition, sensitivity analyses were performed to evaluate the internal consistency of model parameters, which further support the application potentials. Such a modeling technique is valuable because it can characterize the fate and transport of radioactive nuclides over the long term. The case study in South Taiwan uniquely demonstrates the feasibility and significance of such model integration.     

Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated k-means clustering and gravity model

This study presents an integrated k-means clustering and gravity model (IKCGM) for investigating the spatiotemporal patterns of nutrient and associated dissolved oxygen levels in Tampa Bay, Florida. By using a k-means clustering analysis to first partition the nutrient data into a user-specified number of subsets, it is possible to discover the spatiotemporal patterns of nutrient distribution in the bay and capture the inherent linkages of hydrodynamic and biogeochemical features. Such patterns may then be combined with a gravity model to link the nutrient source contribution from each coastal watershed to the generated clusters in the bay to aid in the source proportion analysis for environmental management. The clustering analysis was carried out based on 1 year (2008) water quality data composed of 55 sample stations throughout Tampa Bay collected by the Environmental Protection Commission of Hillsborough County. In addition, hydrological and river water quality data of the same year were acquired from the United States Geological Survey's National Water Information System to support the gravity modeling analysis. The results show that the k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. The datasets indicate that Lower Tampa Bay is an area with limited nutrient input throughout the year. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high values of colored dissolved organic matter are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. With this new integration, improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a critical coastal bay, the Gulf of Mexico.     

Mercury contamination in the estuaries and coastal sediments of the Strait of Malacca

Fishers’ local ecological knowledge (LEK) is an additional tool to obtain information about cetaceans, regarding their local particularities, fishing interactions, and behavior. However, this knowledge could vary in depth of detail according to the level of interaction that fishers have with a specific species. This study investigated differences in small-scale fishers’ LEK regarding the estuarine dolphin (Sotalia guianensis) in three Brazilian northeast coastal communities where fishing is practiced in estuarine lagoons and/or coastal waters and where dolphin-watching tourism varies from incipient to important. The fishers (N?=?116) were asked about general characteristics of S. guianensis and their interactions with this dolphin during fishing activities. Compared to lagoon fishers, coastal fishers showed greater knowledge about the species but had more negative interactions with the dolphin during fishing activities. Coastal fishing not only offered the opportunity for fishers to observe a wider variety of the dolphin’s behavior, but also implied direct contact with the dolphins, as they are bycaught in coastal gillnets. Besides complementing information that could be used for the management of cetaceans, this study shows that the type of environment most used by fishers also affects the accuracy of the information they provide. When designing studies to gather information on species and/or populations with the support of fishers, special consideration should be given to local particularities such as gear and habitats used within the fishing community.     

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.     

Assessment and Prediction of Contaminant Transport and Migration at a Florida Superfund Site

An important issue in the application of mathematical models to describe or predict the fate of solutes in soil and groundwater systems is providing the necessary data to support the spatial, temporal, and hydrogeologic model parameter requirements. The larger, more complex the model and scope of application, the more likely that significant amounts of data of several types are required. A management tool is required that allows the model and the modeler to interact with various needed databases, cope with numerous database management issues, efficiently achieve model parameterization and provide visualization of model output. The three-dimensional Groundwater Modeling System (GMS) that contains a state-of-the-art flow and solute transport model and a graphical user interface for data manipulation and analysis was applied to a Superfund site in Florida to demonstrate its capabilities for predicting solute migration.     

决策树模型在水环境监测网络中选取代表性样点的应用

地表水体中的硝酸盐污染已经成为全球关注的热点环境问题之一。现今,国内外均建立了相关的监测网络对地表水体的水质实施长期监测,但是却导致大量的监测数据累积,给后续的科学研究工作带来了不便,尤其是在庞大的监测网络中如何选取有代表性样点的研究点则成为急需解决的问题之一。以比利时弗拉芒地区地表水的长期监测物理化学指标为例,利用决策树模型评估地表水样点的硝酸盐污染来源专家分类的有效性,为点位优化提供理论依据。原有监测点位的污染源专家分类和模型输出的可匹配率为80%,优化后监测点位从原有47个点降低到30个点,提高了监测工作效率。     

Towards generalised reference condition models for environmental assessment: a case study on rivers in Atlantic Canada

Evaluation of the ecological status of river sites in Canada is supported by building models using the reference condition approach. However, geography, data scarcity and inter-operability constraints have frustrated attempts to monitor national-scale status and trends. This issue is particularly true in Atlantic Canada, where no ecological assessment system is currently available. Here, we present a reference condition model based on the River Invertebrate Prediction and Classification System approach with regional-scale applicability. To achieve this, we used biological monitoring data collected from wadeable streams across Atlantic Canada together with freely available, nationally consistent geographic information system (GIS) environmental data layers. For the first time, we demonstrated that it is possible to use data generated from different studies, even when collected using different sampling methods, to generate a robust predictive model. This model was successfully generated and tested using GIS-based rather than local habitat variables and showed improved performance when compared to a null model. In addition, ecological quality ratio data derived from the model responded to observed stressors in a test dataset. Implications for future large-scale implementation of river biomonitoring using a standardised approach with global application are presented.     

Transport of NO<Subscript>X</Subscript> Emissions from Sugarcane Fertilisation into the Great Barrier Reef Lagoon

The Great Barrier Reef World Heritage Area contains highly sensitive ecosystems that are threatened by the effects of anthropogenic activity including eutrophication. The nearby sugarcane plantations of tropical north Queensland are fertilised annually and there has been ongoing concern about the magnitude of the loss of applied nitrogen to the environment. Previous studies have considered the potential of rainwater run-off to deposit reactive nitrogen species into rivers and ultimately into the Great Barrier Reef Lagoon, but have neglected the possibility of transport via the atmosphere. This paper reports the results of a modelling study commissioned by Australia’s National Heritage Trust aimed at assessing whether or not atmospheric deposition of reactive nitrogen from Queensland’s sugarcane plantations posed a potential threat to the Great Barrier Reef Lagoon. Atmospheric dispersion modelling was undertaken using The Air Pollution Model, developed by Australia’s Commonwealth Scientific and Industrial Research Organisation. Despite the predominance of onshore southeasterly winds, the dispersion model results indicate that 9% of the time during the sugarcane fertilization season (in the modeled years 2001–2006) the meteorological conditions resulted in emissions from the coastal regions of north Queensland being transported out over the ocean around the Great Barrier Reef. The results suggest that there may be a greater efficiency for transport out over the reef during October than for November and December. For the 2 months that exhibited the greatest potential for transport of coastal pollution to the Great Barrier Reef, the modeled deposition of nitrogen oxides (NO_X) into the Great Barrier Reef lagoon was less than 1% of the total emissions from the sugarcane plantations, but was not zero. Our model has a simple chemical scheme that does not cover the full chemistry of all reactive nitrogen compounds and so the results are only indicative of the potential levels of deposition. Nevertheless, our study shows that small amounts of NO_X that originate from sugarcane fertilization may be transported and dry deposited into the Great Barrier Reef lagoon. Other pathways not included in the modeling scheme may provide a more efficient transport mechanism. Whilst modern practices for the application of fertilizer to sugarcane plantations have drastically reduced emissions, the potential efficiency of transport of pollutants via the atmosphere may be of concern for other more highly polluting agricultural industries.     

空气质量数值模型的构建及应用研究进展

综述了近年来国内外空气质量模型的发展历程、空气质量数值模型构建的关键技术以及应用研究。指出了目前空气质量数值预报及应用主要面临气象条件,尤其是大气边界层模拟、大气污染物排放源和大气物理化学过程等问题。提出,应当通过规范化制作和完善排放源清单数据,建立统一的排放源分析标准,提高排放源数据的准确性;多向发展观测手段,加大监测密度和频率,并进行实验室化学分析,提出适合我国的大气物理化学机制。就空气质量模式而言,对模式方案进行优化,以及使用气象、卫星资料同化等技术手段,将其与观测相结合,构建监测与预报系统相结合的统一体系,应用于多平台。     

Coastal dynamic and shoreline mapping: multi-sources spatial data analysis in Semarang Indonesia

Semarang coastal area has geomorphologically complex processes, such as erosion-sedimentation, land subsidence, and tidal inundation hazard. Multi-years shoreline mapping is considered a valuable task for coastal monitoring and assessment. This paper presents maps illustrating the shoreline dynamic in a coastal area of Semarang-Indonesia using multi-sources spatial data. The segment data has been obtained by visual delineation of the topographic maps Year 1908, 1937, 1992 and Ikonos image Year 2003 as well as digital number (DN) value analysis and masking operation of Landsat MSS Year 1972 and Landsat ETM Year 2001. For the long period of almost 100 year, the shoreline dynamic in Semarang coastal area is dominated by sedimentation process. Shoreline extended to the sea as a result of man-made infrastructure and natural processes. The research's result was satisfactory and the method has proven to be effective considering lack of homogeneous data-series. However, some further improvement regarding geo-processing can be made and the accuracy can be tested in future version.     

Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area

Densely populated coastal urban areas are often exposed to multiple hazards, in particular floods and storms. Flood defenses and other engineering measures contribute to the mitigation of flood hazards, but a holistic approach to flood risk management should consider other interventions from the human side, including warning information, adaptive behavior, people/property evacuation, and the multilateral relief in local communities. There are few simulation approaches to consider these factors, and these typically focus on collective human actions. This paper presents an agent-based model that simulates flood response preferences and actions taken within individual households to reduce flood losses. The model implements a human response framework in which agents assess different flood scenarios according to warning information and decide whether and how much they invest in response measures to reduce potential inundation damages. A case study has been carried out in the Ng Tung River basin, an urbanized watershed in northern Hong Kong. Adopting a digital elevation model (DEM) as the modeling environment and a building map of household locations in the case area, the model considers the characteristics of households and the flood response behavior of their occupants. We found that property value, warning information, and storm conditions all influence household losses, with downstream and high density areas being particularly vulnerable. Results further indicate (i) that a flood warning system, which provides timely, accurate, and broad coverage rainstorm warning, can reduce flood losses by 30–40%; and (ii) to reduce losses, it is more effective and cheaper to invest early in response measures than late actions. This dynamic agent-based modeling approach is an innovative attempt to quantify and model the role of human responses in flood loss assessments. The model is demonstrated being useful for analyzing household scale flood losses and responses and it has the potential to contribute to flood emergency planning resource allocation in pluvial flood incidents.     

Atrazine Transport Within a Coastal Zone in Southeastern Puerto Rico: a Sensitivity Analysis of an Agricultural Field Model and Riparian Zone Management Model

Agrichemical runoff from farmland may adversely impact coastal water quality. Two models, the Agricultural Policy/Environmental eXtender (APEX) and the Riparian Ecosystem Management Model (REMM), were used to evaluate the movement of the herbicide atrazine to the Jobos Bay National Estuarine Research Reserve from adjacent fields. The reserve is located on Puerto Rico’s southeast coast. Edge-of-field atrazine outputs simulated with the APEX were routed through a grass-forest buffer using the REMM. Atrazine DT₅₀ (half-life) values measured in both field and buffer soils indicated that accelerated degradation conditions had developed in the field soil due to repeated atrazine application. APEX simulations examined both the measured field and buffer soil atrazine DT₅₀ and the model’s default value. The use of the measured field soil atrazine degradation rate in the APEX resulted in 33 % lower atrazine transport from the field. REMM simulations indicated that the buffer system had the potential to reduce dissolved atrazine transport in surface runoff by 77 % during non-tropical storm events by increasing infiltration, slowing transport, and increasing time for pesticide degradation. During a large runoff event due to a tropical storm that occurred close to the time of an atrazine application, the REMM simulated only a 37 % reduction in atrazine transport. The results indicate that large storm events soon after herbicide application likely dominate herbicide transport to coastal waters in the region. These results agree with water quality measurements in the reserve. This study demonstrated the sensitivity of these models to variations in DT₅₀ values in evaluating atrazine fate and transport in the region and emphasizes that the use of measured DT₅₀ values can improve model accuracy.     

Application of fuzzy sets and cognitive maps to incorporate social science scenarios in integrated assessment modelsA case study of urbanization in Ujung Pandang, Indonesia

Decision–support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the coastal city of Ujung Pandang, Indonesia. The results indicate that both techniques are useful tools for the design of integrated models based on a combination of concepts from the natural and social sciences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

Development of a landfill model to prioritize design and operating objectives

The application of scientifically based decision making tools to help address solid waste management issues dates back to the early 1960s. Researchers continue to use operations research tools to help optimize landfill design and operating parameters. This paper discusses the application of another type of decision making tool, the analytical hierarchy process (AHP), to address priority ranking for a number of landfill engineering design and operating objectives in developing and developed countries. In this application, the AHP is used to rank, and prioritize, economic, environmental, health and safety, legislative and public perception objectives for landfill design and operations specific to landfill distance from a community, and precipitation levels. Results from a global survey using the Delphi process are included, with a discussion on the survey’s impact on the objective rankings relative to community proximity and precipitation. The Delphi process worked extremely well, and was an excellent tool to use in this application. The initial results from the objective rankings show promise in the development of an integrated model for landfill design and operation.     

MOSESS: A New Emission Model for the Compilation of Model-Ready Emission Inventories—Application in a Coal Mining Area in Northern Greece

Over the last years, the capabilities of chemical transport models have been greatly improved and the need for more accurate emission data has increased as well. In the past, a number of emission models have been developed and present different functionalities and applications. The majority of these though cover very specific needs. This paper describes the development of a new emission model namely computer model for the construction of model-ready emission inventories (MOSESS) which is used to compile high-resolution emission inventories or improve existing ones, utilizing complex GIS techniques. The model aims in helping chemical modelers to obtain a better overview of their modeling application by having a comprehensive understanding of the emission input. MOSESS incorporates more than 70 different emission calculation methodologies, and it is capable of handling external emission databases (such as EMEP and EPER) from which emissions can be extracted. The temporal variation (annual/daily and diurnal processing), chemical speciation of NMVOCs and particles, vertical distribution and point source treatment, as well as the spatial disaggregation of emissions (utilizing numerous spatial proxies including high-resolution landuses) can help create model-ready emission inventories which can be used for contemporary modeling applications.     

A case study on the historical peninsula of Istanbul based on three-dimensional modeling by using photogrammetry and terrestrial laser scanning

Terrestrial laser scanning is a popular methodology that is used frequently in the process of documenting historical buildings and cultural heritage. The historical peninsula region sprawls over an area of approximately 1,500 ha and is one of the main aggregate areas of the historical buildings in Istanbul. In this study, terrestrial laser scanning and close range photogrammetry techniques are integrated into each other to create a 3D city model of this part of Istanbul, including some of the buildings that represent the most brilliant areas of Byzantine and Ottoman Empires. Several terrestrial laser scanners with their different specifications were used to solve various geometric scanning problems for distinct areas of the subject city. Photogrammetric method was used for the documentation of the facades of these historical buildings for architectural purposes. This study differentiates itself from the similar ones by its application process that focuses on the geometry, the building texture, and density of the study area. Nowadays, the largest-scale studies among 3D modeling studies, in terms of the methodology of measurement, are urban modeling studies. Because of this large scale, the application of 3D urban modeling studies is executed in a gradual way. In this study, a modeling method based on the facades of the streets was used. In addition, the complimentary elements for the process of modeling were combined in several ways. A street model was presented as a sample, as being the subject of the applied study. In our application of 3D modeling, the modeling based on close range photogrammetry and the data of combined calibration with the data of terrestrial laser scanner were used in a compatible way. The final work was formed with the pedestal data for 3D visualization.     

基于深度学习的人工智能空气质量预报系统构建

针对现有空气质量预报系统存在预报精度低、人工经验辅助、适用范围单一等问题,利用深度学习方法在分析数据内在特征方面表现出的优异性能,结合多源数据融合技术,设计了基于深度学习的空气质量预报系统实现方案.通过对多源数据集的实时制作更新、分析空气质量演变的时空特性、定义和拟合深度学习模型并部署于服务器等关键技术的研究,最终实现...