APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

WEST AFRICA: VOLTA DISCHARGE DATA QUALITY ASSESSMENT AND USE1

ABSTRACT: Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets.     

韶钢新石灰窑烟气除尘技术的应用

韶钢新石灰窑烟气除尘系统要用旋风除尘器、金属管式换热器、高效陶瓷多管除尘器的组合方式。介绍了该系统的设计参数、工艺流程、主要设备及其功能。     

基于传热分析的林火蔓延特性研究

计算了水平流动的热烟气与大乔木、小乔木、灌木主干及大乔木树叶间的强制对流传热；垂直上升流动的热烟气与各类林木的纵向自然对流、纵向强制对流传热；以及烟气对各类林木的辐射传热。分别比较了它们的热流密度和总换热量。讨论了烟气流速、温度、林木尺寸等因素对换热的影响。在此基础上，对不同林木的火险特性进行了预测。     

烟气扩散的CFD数值模拟

运用商业CFD软件Fluent模拟计算小尺寸下的简单烟气扩散规律.将结果用正态分布假设下的高斯烟羽模型验证.证明该软件模拟烟气扩散问题的可行性.     

国内外大城市防灾减灾管理模式的比较研究

城市综合防灾减灾管理是城市管理的一个重要组成部分。上海综合减灾体系目前尚不够完善，城市抗灾能力仍较薄弱。本文通过对国外大城市减灾管理模式的比较和研究，分析了目前上海市减灾管理模式的现状和问题，提出了改进目前上海市灾害管理模式的措施建议。     

江苏省城市防汛决策支持系统研究

在分析江苏省城市防汛问题的基础上，设计了其防汛决策支持系统；根据江苏省城市洪涝灾情特点研建和选用了适宜的数学模型，该模型可以迅速、可靠和正确地模拟城市雨情、水情、灾情的发展过程和可能后果，为城市防汛决策提供多层次的信息服务和多种支持手段。     

天津市城区暴雨沥涝仿真模拟系统的研究

天津市位于黄河水系尾闾，是我国北方重要的工业和港口城市。该市历史上一直遭受洪涝灾害的威胁，加之近几年市区范围不断扩大，不透水面积增加，排水能力远远不能适应城市的发展要求，城市沥涝问题日趋严重。为了掌握天津市暴雨沥涝的规律，减轻洪涝灾害对该市的影响，作者利用二维不恒定流水动力学模型和计算机信息管理及图形技术，采用Power Station Fortran 4.0和Visual Basic5.0编程语言，在Widows98环境下开发了天津市暴雨沥涝仿真模拟系统。该系统首次实现了从城市暴雨预报、监测到城市暴雨沥涝仿真模拟的研究， 不仅能够处理实时的不均匀的降雨信息，还能处理数值预报模型的预报降雨信息。系统的信息前后处理模块用图形方式管理仿真模型的各类信息，方便用户显示、查询和修改，使系统更加完整、实用。     

GRAPHICALLY MODELING STAKEHOLDER VALUES1

ABSTRACT: This study was designed to give insight into the values considered in environmental policy and illustrate the respondents' personal constructions related to creating policy through the development of a graphic tool. Using both qualitative and quantitative methods, this study anonymously captured the intensity of values currently held by decision makers and tracked changes in values over time. Data were acquired through observations of and interviews with stakeholders in a five‐year wetland mitigation bank permitting process at the Galveston District of the U.S. Army Corps of Engineers. The study included public and private sector respondents in both governmental and nongovernmental roles. The resulting representations of professional and personal stakeholders' values can be used as a tool for improving information exchange in policy negotiation and provides insight into the complexity of individual and corporate perceptions of a policy issue.     

ACCURACY AND RELIABILITY OF NUMERICAL RIVER MODELS1

ABSTRACT: Over the last 20 years, our possibilities to model river flows numerically have increased enormously. In this paper, the question is addressed whether a more sophisticated model is always better than a simpler one. Increased detail, both in finer resolution and in physical processes taken into account, has its price in more computer time, higher data need, and perhaps more unknown coefficients to be calibrated. Moreover, uncertainty in actual physical conditions (e.g., bottom roughness), inflow and parameters remains, which may dominate the uncertainty of the results. Also, the questions asked by a decision maker may not always be very precise. For a schematic but relevant example, we show that a better model does not necessarily give more reliable results because some of the basic uncertainties remain. It is concluded that we should use the simplest model that will answer the question as to the accuracy needed, taking into account uncertainties in the data