Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

洪灾风险评价等级模型探讨

采用特尔菲法,选择4个一级因子和14个二级因子,建立洪灾风险评价等级指标体系。利用层次分析法,根据对同一层元素相对重要性比较,决定各指标权重。应用模糊综合评判方法,将福建省67个县(市)分为高风险区、次高风险区、中度风险区、低风险区4个等级。评价结果可为防灾减灾提供科学依据。     

南水北调中线工程渡槽的综合防洪风险分析

远距离输水工程沿途往往要跨越众多河系,交叉建筑物极易受到洪水的冲击,这就需要对其防洪风险给出定量的评估。以可靠度理论为基础,根据渠道所穿越的各条河流的水文、气象、地质、工程结构的随机特征给出了引水工程交叉建筑物的综合防洪风险计算方法;并以南水北调中线工程河北省段3座渡槽为例对该方法进行了验证。结果表明:南水北调中线工程河北省段渡槽的综合防洪风险小于万分之一。     

渭河流域"05.10"洪涝灾害特征分析

利用2005年9~10月渭河流域内各气象站和水文站的资料,对2005年渭河流域致洪暴雨的雨情、水情及灾情进行分析。对洪水的特征,水情、河道的概况,特大洪灾的降水特点进行总结,得出“05.10”洪水具有降水范围广、水位高、洪水倒灌、灾害重等特征,造成的经济损失严重。揭示了洪灾形成的主要原因,从而对减少洪灾的形成和流域的治理提出有关建议,达到防灾减灾的目的。     

2004年主汛期我国强对流天气灾害统计特征

运用全国各省、市、县气象部门直接上报国家气象局的气象灾害数据,对全国各地2004年主汛期(6-8月)对流性天气造成的灾害分布特征和人员死亡情况进行了统计分析,结果表明,主汛期内强对流天气在全国31个省市都有发生,其中黄淮、江淮、江南、西南地区东部为强对流天气灾害死亡人数多发区,且在主汛期内,以7月份强对流天气发生频次最高;在年度所有气象灾害中,除了暴雨洪涝灾害造成人员死亡最多外,雷击事件造成的死亡人数占气象灾害死亡人数的第二位;各大城市均遭遇到强对流天气袭击,造成了严重的交通瘫痪,城市应急响应系统建设亟待加强。     

1998年中国洪灾与减灾对策

分析了 1998年中国洪灾的原因 ,并提出了相应的防灾、减灾对策     

Balancing Endangered Species and Ecosystems: A Case Study of Adaptive Management in Grand Canyon

/ Adaptive ecosystem management seeks to sustain ecosystems while extracting or using natural resources. The goal of endangered species management under the Endangered Species Act is limited to the protection and recovery of designated species, and the act takes precedence over other policies and regulations guiding ecosystem management. We present an example of conflict between endangered species and ecosystem management during the first planned flood on the Colorado River in Grand Canyon in 1996. We discuss the resolution of the conflict and the circumstances that allowed a solution to be reached. We recommend that adaptive management be implemented extensively and early in ecosystem management so that information and working relationships will be available to address conflicts as they arise. Though adaptive management is not a panacea, it offers the best opportunity for balanced solutions to competing management goals.     

流域防洪体系防洪安全评价研究

提出了防洪安全评价的概念，建立了防洪安全评价指标体系；提出利用熵值法确定指标权重，采用多层次模糊优选评价模型对防洪安全进行评价；以辽宁省辽河流域为例，对不同历史时期防洪安全状况进行了比较，结果与实际相符。     

湘江流域洪水灾害综合风险评价

依据灾害系统理论,在综合考虑致灾因子、孕灾环境和承灾体的基础上,从致灾因子、孕灾环境的自然属性和承灾体的社会属性两方面出发,以县级行政单元为基本评价单元,进行了湘江流域洪水灾害的综合风险评价。在综合考虑降雨量、地形以及历史上洪水灾害发生频次等自然因素的条件下,利用地图代数分析得到了湘江流域洪水灾害危险性评价图;在综合考虑人口密度、耕地面积百分比、人均GDP和单位面积水库和塘坝容量等社会经济指标的基础上,利用模糊综合评判法得到了湘江流域洪水灾害脆弱性评价图。在此基础上采取“乘”模型的计算公式,即风险=危险性×脆弱性,将湘江流域洪水灾害风险划分为高风险、较高风险、中等风险、较低风险和低风险5个等级,并借助地理信息系统软件编制了湘江流域洪水灾害综合风险等级评价图。     

MULTITEMPORAL SCALE HYDROGRAPH PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

Abstract: An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydro-logically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks station (RR-GF) in North Dakota. The modeling exercise used 1 year (2002), 5 years (1998–2002), and 27 years (1975–2002) of data for the daily, weekly, and monthly predictions, respectively. The hydrometeorological data (precipitations P_(t), P_(t-1), P_(t-2), P_(t-3), antecedent runoff/lake stage R_(t-1) and air temperature T_(t) were partitioned for training and for testing to predict the current hydro-graph at the selected DL and RR-GF stations. Performance of ANN was evaluated using three combinations of daily datasets (Input I = P_(t)), P_(t-l), P_(t-2), P_(t-3), T_(t) and R_(t-l); Input II = Input-l less P_(t) P_(t-l), P_(t-2), P_(t-3); and Input III = Input-II less T_(t)). Comparison of the model output using Input I data with the observed values showed average testing prediction efficiency (E) of 86 percent for DL basin and 46 percent for RR-GF basin, and higher efficiency for the daily than monthly simulations.