Large-scale constructed wetlands for nutrient removal from stormwater runoff: An everglades restoration project

The South Florida Water Management District (SFWMD) constructed a wetland south of Lake Okeechobee to begin the process of removing nutrients (especially phosphorus) from agricultural stormwater runoff entering the Everglades. The project, called the Everglades Nutrient Removal (ENR) project, is a prototype for larger, similarly constructed wetlands that the SFWMD will build as part of the Everglades restoration program. This innovative project is believed to be one of the largest agricultural stormwater cleanup projects in the United States, if not in the world. This publication describes the ENR project's design, construction, and proposed operation, as well as the proposed research program to be implemented over the next few years.     

Software tools to support incident reporting in safety-critical systems

Incident reporting systems are playing an increasingly important role in the development and maintenance of safety-critical applications. The perceived success of the FAA's Aviation Safety Reporting System (ASRS) and the FDA's MedWatch has led to the establishment of similar national and international schemes. These enable individuals and groups to report their safety concerns in a confidential or anonymous manner. Unfortunately, many of these systems are becoming victims of their own success. The ASRS and MedWatch have both now received over 500,000 submissions. In consequence, the administrators of incident reporting systems increasingly rely upon software tools to support the administration of their systems. In the past, these systems have relied upon ad hoc applications of conventional database technology. However, there are several reasons why this technology is inadequate for many large-scale reporting schemes. In particular, the problems of query formation often result in poor precision and recall. This, in turn, has profound implications for safety-critical applications. Users may fail to identify similar incidents within national or international collections. These ad hoc approaches also neglect the opportunities provided by recent developments in computer assisted interviewing and in the monitoring of retrieval activities to build models of user behavior. These techniques offer a number of potential benefits. For instance, it is possible to automatically detect potential biases in the way that investigators analyze particular incidents.     

计算机局域网络保密措施

随着计算机的普及 ,局域网络越来越广为利用 ,但也出现了相应的失密问题。本文从信息及实体两个方面 ,论述了局域网络的保密措施。     

基于神经网络的温度预测

室内温度与诸多影响因素之间的非线性、复杂性等关系 ,给建模、预测带来了难度 ,引入了人工神经网络 ;利用人工神经网络的非线性、并行计算和自学习特性进行建模 ,实现了对温度模拟     

煤体注水湿润半径预测的神经网络模型

合理的注水半径一直是煤体注水防尘技术中难以确定的参数。笔者基于对影响煤体注水半径因素的分析和神经网络理论的原理之上 ,设计网络模型为 3层 ,输入层为 7个节点 ,应用BP网络算法 ,建立了煤体注水湿润半径的预测模型 ,并对其参数进行了讨论。然后 ,用平顶山矿务局和水城矿务局 13个矿 19个回采工作面的统计资料对BP网络进行自适应学习 ,并取η =0 .9,α =0 .82 ,控制网络总误差E≤ 10 6。经过 2 12 34次迭代后 ,网络趋于稳定。用训练好的网络对平顶山矿务局的某矿的 3层煤的注水湿润半径进行预测 ,预测结果与实测值很接近。其误差分别为 0 .5 %,0 .6 %和 0 .7%。     

关于重大隐患监控GIS模式的研究

系统地分析了重大危险源、事故隐患的地域监管体系以及隐患监控的新技术应用基础 ;提出了职业安全卫生监管体系中的危险源和隐患监控 ,应该分为过程安全监控和安全目标监控两个层次。隐患监管功能的有效实现 :隐患监控的技术载体则越来越依托信息网络的发展 ;重大隐患监管体系特别适合采用地理信息系统     

滨海平原咸水入侵动态监测网构建研究——以潍河下游地区为例

作为进行咸水入侵动态监测的基础性工作，对潍河下游地区的供需水平衡及地下水位、水质和地层电阻率在咸淡水界面上变化规律进行了研究分析；同时，探索了监测工作的地理工程技术途径，并据此构建了3个层次的监测体系：（1）宏观区域供需水平衡分析与地下水位负值区变化监测，（2）中观咸水入侵发展变化的物探监测，（3）微观地下水位、水质变化监测；最后，为了对日益增多的咸水入侵动态数据资料进行有效的管理，设计了一个基于GIS的、以数据库管理应用为核心的信息系统。     

MULTISCALE RIVER ENVIRONMENT CLASSIFICATION FOR WATER RESOURCES MANAGEMENT1

ABSTRACT: River Environment Classification (REC) is a new system for classifying river environments that is based on climate, topography, geology, and land cover factors that control spatial patterns in river ecosystems. REC builds on existing principles for environmental regionalization and introduces three specific additions to the “ecoregion” approach. First, the REC assumes that ecological patterns are dependent on a range of factors and associated landscape scale processes, some of which may show significant variation within an ecoregion. REC arranges the controlling factors in a hierarchy with each level defining the cause of ecological variation at a given characteristic scale. Second, REC assumes that ecological characteristics of rivers are responses to fluvial (i.e., hydrological and hydraulic) processes. Thus, REC uses a network of channels and associated watersheds to classify specific sections of river. When mapped, REC has the form of a linear mosaic in which classes change in the downstream direction as the integrated characteristics of the watershed change, producing longitudinal spatial patterns that are typical of river ecosystems. Third, REC assigns individual river sections to a class independently and objectively according to criteria that result in a geographically independent framework in which classes may show wide geographic dispersion rather than the geographically dependent schemes that result from the ecoregion approach. REC has been developed to provide a multiscale spatial framework for river management and has been used to map the rivers of New Zealand at a 1:50,000 mapping scale.     

ESTIMATING MARYLAND CRITICAL AREA ACVS IMPACT ON FUTURE NONPOINT POLLUTION ALONG THE RHODE RWER ESTUARY1

ABSTRACT: This paper presents the results of an investigation of the effects of the Maryland Critical Area Act on generation of non-point source loads of phosphorus, nitrogen, and sediment to the Rhode River estuary. The Simple Method model, the Marcus and Kearney regression model, and the CREAMS model were used to estimate annual loads under: (1) present conditions, (2) maximum land use development allowable under the Act, and (3) two sets of future land use conditions that might occur if the Act were not in place. Results indicate that the Critical Area Act can reduce the present generation of nonpoint nutrient and sediment loadings 20–30 percent from the regulated area. These reductions can occur while preserving agricultural lands and allowing limited residential and urban development. The decrease in nutrient loadings is primarily dependent upon implementation and enforcement of agricultural best management practices (BMPs). The BMPs could reduce present agricultural nutrient loadings by 90 percent to a level comparable to loadings from residential areas. The estimated effectiveness of the Critical Area Act is even greater when compared to potential future nutrient loadings if development in the area remains unregulated. Unrestricted residential and urban development could increase nutrient loadings by 200 percent to 1000 percent as compared to controlled development under Critical Area Act guidelines. The Critical Area Act primarily prevents these future increases by severely limiting woodland cutting, with lesser results obtained by requiring urban BMPs.     

NETWORK AND SUBWATERSHED PARAMETERS EXTRACTED FROM DIGITAL ELEVATION MODELS: THE BILLS CREEK EXPERIENCE1

ABSTRACT: An automated extraction of channel network and sub-watershed characteristics from digital elevation models (DEM) is performed by model DEDNM. This model can process DEM data of limited vertical resolution representing low relief terrain. Such representations often include ill-defined drainage boundaries and indeterminate flow paths. The application watershed is an 84 km² low relief watershed in southwestern Oklahoma. The standard for validation is the network and subwatershed parameters defined by the blue line method on USGS 7.5–minute topographic maps. Evaluation of the generated and validation networks by visual comparisons shows a high degree of correlation. Comparison of selected network parameters (channel length, slope, drainage density, etc.) and of drainage network composition (bifurcation, length, slope, and area ratios) shows that, on the average, the generated parameters are within 5 percent of those derived from the validation network. The largest discrepancies were found for the channel slope values. The results of this application demonstrate that DEDNM effectively addresses network definition problems often encountered in low relief terrain and that it can generate accurate network and subwatershed parameters under those conditions.