MVC模式下非点源污染模拟模型的中间件实现

非点源污染模拟预测模型是描述流域非点源污染物迁移转化规律的主要工具,在水环境保护、水污染防治等领域得到了广泛的应用。按照J2EE标准,在提高软件的可扩展性、可维护性和代码复用率指导思想下,以中间件技术的应用框架为基础,采用MVC软件设计模式,实现了非点源污染模拟预测中间件,建立了面向Web的非点源污染模拟预测系统。与传统的开发方式相比,所提出的方法可以缩短模型建模周期,提高模型的使用效率。     

Multi-objective modelling and decision support using a Bayesian network approximation to a non-point source pollution model

This paper illustrates a methodology to create a multi-objective modelling system using Bayesian probability networks to emulate the behaviour of an environmental model that was originally intended for the purpose of analyzing a problem – non-point source pollution in our example. Modelling systems frequently pertain to a single domain (physical or chemical process modelling, hydrology or combinations) to simulate a process in nature such as pollution transport or the production of food or manufactured goods. Economic or other effects are treated separately, or handled in a non-interactive manner. Side-effects of agro-industrial processes, or gains/losses from production enterprises, are generally modelled separately without the ability to examine trade-offs or alternatives. Multi-objective modelling attempts to work in more than one problem domain through decision theoretical principles. Such treatments are designed to couple production and waste systems, to quantify the economic cost of remediation. This model will demonstrate such an application, from the data acquisition, model calibration to the hypothesis testing, for a non-point source pollution model. This will be combined with a simplified net revenue model based on crop rotations typically found in Southern Ontario, Canada, using realistic economic data obtained from agricultural operations similar to those found in this region. We will demonstrate that multi-year analyses are possible with such a system.     

Modelling of point and non-point nutrient loadings from a watershed

An integrated model was developed to estimate the loadings of nutrients and organic matter from point and non-point sources in a watershed by use of the software Pamolare. The model accounted for the loadings from industrial and municipal wastewaters, atmospheric deposition and runoff from the drainage area. We tested the model using data from Lake Glumsø, Denmark, with a drainage area of about 1054.9 ha and with known annual loadings into the lake in 1978, 1982 and 2000. The model was first calibrated against one year's record, followed by one year's validation, and finally a prognosis scenario was performed. The predictions by the model were consistent with the observations. Thus, the model may be applicable for estimating nutrient loadings from drainage areas, when observations in general are not available. It can also be used to examine the current conditions and test the effects of management and planning scenarios within a watershed.     

Integration of a nonpoint source pollution model with a decision support system

This paper is a progress report of an ongoing research project from which the expected final product will be an integral system to model nonpoint source pollution in surface waters. Diffuse pollution models will be included in a decision support system with a unique platform, common interfaces and GIS capabilities. This system will accommodate pre- and post-processing tools, model control and sensitivity analysis for the parameters in the models. Particularly, the construction of the interface for the AGNPS model and its link with the decision support system RAISON is presented. The model is described, including the input requirements, the development of tools and the procedures created to extract the necessary data from digital elevation model, soil type and landcover vectorized files.     

NDVI time series for monitoring RUSLE cover management factor in a tropical watershed

Land cover, an important factor for monitoring changes in land use and erosion risk, has been widely monitored and evaluated by vegetation indices. However, a study that associates normalized difference vegetation index (NDVI) time series to climate parameters to determine soil cover has yet to be conducted in the Atlantic Rainforest of Brazil, where anthropogenic activities have been carried out for centuries. The objective of this paper is to evaluate soil cover in a Brazilian Atlantic rainforest watershed using NDVI time series from Thematic Mapper (TM) Landsat 5 imagery from 1986 to 2009, and to introduce a new method for calculating the cover management factor (C-factor) of the Revised Universal Soil Loss Equation (RUSLE) model. Twenty-two TM Landsat 5 images were corrected for atmospheric effects using the 6S model, georeferenced using control points collected in the field and imported to a GIS database. Contour lines and elevation points were extracted from a 1:50,000-scale topographic map and used to construct a digital elevation model that defined watershed boundaries. NDVI and RUSLE C-factor values derived from this model were calculated within watershed limits with 1 km buffers. Rainfall data from a local weather station were used to verify NDVI and C-factor patterns in response to seasonal rainfall variations. Our proposed method produced realistic values for RUSLE C-factor using rescaled NDVIs, which highly correlated with other methods, and were applicable to tropical areas exhibiting high rainfall intensity. C-factor values were used to classify soil cover into different classes, which varied throughout the time-series period, and indicated that values attributed to each land cover cannot be fixed. Depending on seasonal rainfall distribution, low precipitation rates in the rainy season significantly affect the C-factor in the following year. In conclusion, NDVI time series obtained from satellite images, such as from Landsat 5, are useful for estimating the cover management factor and monitoring watershed erosion. These estimates may replace table values developed for specific land covers, thereby avoiding the cumbersome field measurements of these factors. The method proposed is recommended for estimating the RUSLE C-factor in tropical areas with high rainfall intensity.     

Assessing a fuzzy model and HSPF to supplement rainfall data for nonpoint source water quality in the Feitsui reservoir watershed

The objective of this study was to improve the use of a fuzzy model to supplement rainfall data when the watershed's meteorological station is either far away or suffers a loss of rainfall data. The fuzzy model can also supplement rainfall data when the station is nearby. The accuracy of rainfall data in the EPA's (Environmental Protection Agency) BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. This study also assessed the improvement in stream flow prediction with the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS, using the hourly precipitation estimates for the Feitsui reservoir watershed. This study demonstrates that using a fuzzy model to supplement rainfall data has the potential to improve stream flow predictions, thus aiding water quality assessment in the nonpoint water quality assessment decision tool.     

An integrated media, integrated processes watershed model

The motivation of this work is to carry out parallel simulations of incompressible flows on block-structured meshes. A new partitioning method is proposed. The quality of rectangular partitions is checked and compared with other methods, as regards load balance, edge-cut and block numbers. The partitioner is coupled with the massively parallel Hypre solver library and efficiency of the coupling is measured. Finally, the code is applied to study laminar flows (steady and unsteady) on three non-rectangular geometries. Very fine grids are used to compute reference solutions of a Z-shaped channel flow and the L-shaped and double lid driven cavities.     

AGNPS-UM: applying the USLE-M within the agricultural non point source pollution model

In the Agricultural Non Source Pollution model (AGNPS), grid-cell erosion is predicted for individual rainfall events using the Universal Soil Loss Equation (USLE) even though the USLE is not well suited for this purpose. A new modification of the USLE, the USLE-M, is better suited to predicting event erosion and also provides a mechanism for accounting for the impact of upslope runoff on erosion that is not available with the USLE. A software system that replaces the USLE by the USLE-M in AGNPS is described and its impact illustrated by an example based on a 1-in-10 year event on a 2300 ha catchment near Nundle, New South Wales, Australia.     

城市空气污染脆弱性评价模型及实证研究

利用中国74个样本城市的微观监测数据,通过构建概率模型和分解模型,以三阶段可行广义最小二乘法估计的参数测度城市空气污染脆弱性.研究发现:超过80%的样本城市具有空气污染脆弱性,且呈地域性特征;脆弱性不仅在相邻两级之间转移,还存在跨级间突变.空气污染的差异性表现为近20%的样本城市中度及以上空气污染可能性较高, 46%的城市发生空气轻度污染是大概率事件,仅有12%的城市无污染脆弱性;而由于"污染避难所"效应的存在,空气污染"热点"城市趋向于欠发达地区.根据实证结果,对城市空气污染程度分类并提出了差异化的应对措施,以期为有关部门空气治理政策的制定提供科学依据,从而达到突出重点、分类指导、多管齐下、科学施策的目的.     

Parameter estimation and uncertainty analysis for a watershed model

Where numerical models are employed as an aid to environmental management, the uncertainty associated with predictions made by such models must be assessed. A number of different methods are available to make such an assessment. This paper explores the use of three such methods, and compares their performance when used in conjunction with a lumped parameter model for surface water flow (HSPF) in a large watershed.Linear (or first-order) uncertainty analysis has the advantage that it can be implemented with virtually no computational burden. While the results of such an analysis can be extremely useful for assessing parameter uncertainty in a relative sense, and ascertaining the degree of correlation between model parameters, its use in analyzing predictive uncertainty is often limited. Markov Chain Monte Carlo (MCMC) methods are far more robust, and can produce reliable estimates of parameter and predictive uncertainty. As well as this, they can provide the modeler with valuable qualitative information on the shape of parameter and predictive probability distributions; these shapes can be quite complex, especially where local objective function optima lie within those parts of parameter space that are considered probable after calibration has been undertaken. Nonlinear calibration-constrained optimization can also provide good estimates of parameter and predictive uncertainty, even in situations where the objective function surface is complex. Furthermore, they can achieve these estimates using far fewer model runs than MCMC methods. However, they do not provide the same amount of qualitative information on the probability structure of parameter space as do MCMC methods, a situation that can be partially rectified by combining their use with an efficient gradient-based search method that is specifically designed to locate different local optima.All methods of parameter and predictive uncertainty analysis discussed herein are implemented using freely-available software. Hence similar studies, or extensions of the present study, can be easily undertaken in other modeling contexts by other modelers.     

Modelling nutrient transport in Currency Creek,NSW with AnnAGNPS and PEST

The modelling package Annualized Agricultural Nonpoint Source Model (AnnAGNPS) was applied to the prediction of export of nitrogen and phosphorus from Currency Creek, a small experimental catchment within the Hawkesbury–Nepean drainage basin of the Sydney Region. The catchment is 255 ha in area and has experienced extensive soil erosion and losses of nutrients from intensive vegetable cultivation, irrigated dairy pasture and poultry farms. Simulations of nitrogen and phosphorus loads in the Currency Creek catchment were performed at various temporal scales and the degree of calibration was quantified by comparing the simulated data with the monitoring results. In addition, the model independent, nonlinear parameter estimation code PEST, was applied for sensitivity testing to determine and assess the relative importance of the key parameters of the model. Event flows were simulated satisfactorily with AnnAGNPS but only moderate accuracy was achieved for prediction of event-based nitrogen and phosphorus exports. The biggest deviations from the measured data were observed for daily simulations but trends in the generated nutrients matched observed data. Despite achieving good resemblance between measured and predicted phosphorus loads the model showed high level of sensitivity to assigned pH values for topsoil. Increase in pH by one unit resulted in up to 34% increase in model generated particulate phosphorus load.     

Accurate decision-making for timely washing of substation insulators, based on a pollution model

Substation insulators near coastal areas rapidly become polluted due to the salty wind blowing in from the sea. Hazardous levels of pollution deposit cause higher leakage currents under damp conditions, resulting in system blackouts and damage to substations due to flash-overs. This research is aimed at developing a method of reliable decision-making to determine the time at which to wash polluted insulators to avert detrimental conditions. The proposed method consists of modelling the pollution deposits, and deciding on the best time to wash the insulators by using the actual data related to pollution deposits and weather information. The effectiveness of the proposed method is demonstrated by applying it to actual data taken at the Karatsu substation in Japan.     

Jet acceleration in a variety of mass source model options

An MHD model of the formation of astrophysical jet outflow from the vicinity of a compact object surrounded by a thin accretion disk and immersed into the nebula of a galactic plasma is considered. The numerical algorithm is based on division by physical processes and includes a difference scheme for the MHD system of equations in the two-dimensional (2D) axisymmetrical case. Triangular unstructured staggered grids are used. The modeling results show the formation of the accelerating channel in the shape of a Laval nozzle and comply with the available observation data. Computations are performed on a KIAM K-100 cluster.     

Kad网络的联合污染模型

将Kad网络中的关键词污染和文件源污染结合起来，使用状态转移分析的方法构造了一种联合污染模型。模型中综合考虑了污染程度、退出率、等待率等因素。对模型的仿真实验数据显示，受到联合污染时，Kad网络中查询失败的用户数远大于查询成功的用户数，并随着时间的增加而趋于稳定。在影响联合污染效果的若干因素中，污染程度对联合污染的效果有决定性的影响，退出率的影响次之，等待率的影响最小。     

Development of an integrated model for assessing the impact of diffuse and point source pollution on coastal waters

Pollution loads from land sources and their impact on the receiving waters can be predicted by using land-use and surface water quality models, respectively. In this paper details are given of the development of an integrated modelling system for managing water quality in coastal basins. The system includes a model linking the pollution input loads to land-use and a model for simulating surface flow and chemical and biological processes. The land-use model consists of two main components: a database and a model base. It uses a GIS system, namely ArcGIS, as the model platform. The database, built in the Geo-database format, includes six data sets containing information on social, economical, bathymetrical and hydrological aspects of a study area. The model base includes a series of transfer functions that link the pollution loads to key sources, including those from: industrial, domestic and agricultural inputs, and fish and animal farming. The water quality model is a numerical model which solves the governing equations representing the physical, chemical and biological processes in coastal waters. The modelling system was set up for Bohai Bay in China, with the land-use model being used to provide nutrient loadings from individual inputs and the water quality model used to predict the impact of these inputs on the receiving waters. Model simulations were also undertaken to predict the water quality conditions for various development and management scenarios.     

Non-point source critical area analysis in the Gisselö watershed using GIS

In the southeast in Norrköping, Sweden, is a small fjord-like bay called Slätbaken. The water quality in Slätbaken—with its narrow outlet to the Baltic Sea—depends highly on the water quality of the streams that flow in it. While point pollution sources can be identified easily in general, the non-point sources are harder to find. The most important sources for non-point pollution are agricultural areas, and the pollutants are mostly nutrients like phosphorus, which come from the fertilisation of the fields. One important catchment area for Slätbaken is the 57.7 km² Gisselö river basin (part of the topographic map 8GNO), which contains large agricultural areas.The transport of water pollutants is based on the same hydrological processes as erosion and sediment transport. The implementation of such a model in a GIS allows the analysis of a large area with a high resolution. When choosing the model, special attention was paid to the possibility of using a verified model that is easy to implement in a commercial GIS without the need of too much expert knowledge. This may allow its widespread use in many administrative applications that need non-point source information. A feasibility test for an enhanced GIS USLE model was done in the Gisselö drainage basin before it was implemented for all river basins in the whole administrative area of Norrköpings kommun.It is possible to use the suggested simplified USLE model to estimate the load of both pollutants and sediments, and it is able to show the areas that are critical for the water quality at the outlet of the water basin. The model has been evaluated in three studies [Int. J. Geogr. Inf. Syst. 2 (4) (1988) 365; A GIS to target critical areas for non point source management, in: Proceedings of the International Non Point Source Management Symposium, Austin, TX, November 7, 1989; Vatten 48 (1992) 117]. Then, implemented in a very simple GIS that allowed only rough estimates of terrain models and distances, the model was able to estimate the total suspended solids (TSS) and total phosphorus (TP) loads in the Svartå river basin of 1539 km² in the same region as Gisselö and the Bornsjö river basin outside Stockholm. Besides an estimated R² of 0.91–0.98 (verified by a more than one year measurement from manual and automated sampling stations in the whole river basin), the benefit with the GIS implemented USLE was the possibility to identify the risk areas with high spatial accuracy. During the last decade, both available databases and software have changed the possibilities to identify areas at risk of nutrient leakage. Schein [GIS Methods for Monitoring Sustainable Development by Analysis of Land-use and Land Cover Changes in the Surroundings of Linköping (Sweden), Institut für Photogrammetrie und Fernerkundung, Technische Universität Dresden, Germany] and Schein and Sivertun [Method and models for sustainable development monitoring and analyses in GIS, in: Proceedings of the International Workshop on Geo-Spatial Knowledge Processing for Natural Resource Management, University of Insubria, Varese, Italy, June 28–29, 2001] show that the enhanced land use data available through the European Union agricultural support program can be used together with remote sensing data to fine tune the modified GIS USLE model. The problems with the new 50×50 m digital elevation data now available are also pointed out here. Obvious errors in the data and possibilities to enhance the model by introducing a better terrain model were two important suggestions in these works. In this article, two modifications to the original model are suggested. One is enhancement of the digital terrain model by using height curves from the digital 1:50 000 scale topographic map, and the other is a smooth distance function that better reflects the impact of nutrients on water bodies.Because of its easy implementation on standard low cost systems, the GIS USLE model is suitable for analysing huge areas for critical places. The results can lead to more detailed studies in the risk areas thus identified or to investigations on the effect of land use changes, or can be used simply for taking care in the use of fertilisers and other chemicals in the critical agricultural areas.     

Open source movements as a model for organising

Open source software such as the operating system Linux has in a few years created much attention as an alternative way to develop and distribute software. Open source is to let anyone have access to the source code, so that they can modify it. Open source can be seen as a movement, where communities of highly skilled programmers collectively develop software, often of a quality that outperforms commercial proprietary software. These movements are based on virtual networking on the Internet and the web. They are loosely coupled communities kept together by strong common values related to hacker culture. Work seems to be totally distributed, delegated and loosely coupled. The highly skilled members contribute to the collective effort of free software development. In this paper the open source phenomenon is investigated from different perspectives. It is claimed that the open source movement is one key to the understanding of future forms of organizations, information work and business.     

环境污染源管理系统的设计与实现

基于WebGIS的污染源信息管理系统利用Internet/Intranet技术、GIS技术、数据库技术和环境保护技术,建立了完善的污染源监测与管理网络体系,实现了污染源空间信息、属性信息的综合管理和网上发布.本文首先介绍了此系统的需求目标,在此基础上阐述了系统的体系结构、系统功能和开发方案.     

环境污染源管理系统的设计与实现

基于WebGIS的污染源信息管理系统利用Internet/In-tranet技术、GIS技术、数据库技术和环境保护技术,建立了完善的污染源监测与管理网络体系,实现了污染源空间信息、属性信息的综合管理和网上发布。本文首先介绍了此系统的需求目标,在此基础上阐述了系统的体系结构、系统功能和开发方案。     

Nash model of water reservoir pollution

The paper describes some concept of water quality control in a reservoir.Two factors assessing the water pollution is considered, viz: dissolved oxygen and biochemical oxygen demand.Several polluters can be adjacent to the reservoir. Each polluter minimizes his own costs of treatment of discharged waste . Each polluter is treated as a player. The Nash feedback solution concept is proposed. A numerical example illustrates the paper.