淮河具有行蓄洪区河系洪水预报水力学模型研究

针对淮河流域河系特点,建立淮河具有行蓄洪区河系洪水预报模型.干流河道洪水演进采用一维水动力学模型,钐岗分流量利用分流曲线法推求,利用虚拟线性水库法解决大洪水时支流洪水受干流顶托作用,临淮岗闸作为水力学模型的内边界条件进行处理,利用分流比法概化行洪过程,行洪区内只有蓄满时,才会有出流,行洪区内的洪水利用Muskingum...     

考虑降雨空间变化的随机产汇流模型

引入两个负指数型差值函数,估计降雨量的概率分布,以此描述流域降雨空间变异性问题.将降雨量空间统计分布与垂向混合产流模型耦合进行产流量计算,即对地表径流,采用超渗产流模式,根据降雨与土壤下渗能力的联合分布推求其空间分布;对地面以下径流,采用蓄满产流模式,以地表渗入量的均值作为输入,进行简化处理以提高其实用性;最终推导出总产流量概率分布函数计算公式.将流域概化成一个线性水库,并根据随机微分方程理论,推导任一计算时段洪水流量的概率分布,从而构建了一个完整的随机产汇流模型.以淮河支流黄泥庄流域为例进行应用研究,结果表明,该模型可提供洪水过程的概率预报,可用于防洪风险分析,若以概率分布的期望值作为确定性预报,亦具有较高精度.     

基于面平均雨量误差修正的实时洪水预报修正方法

空间集总式水文模型的洪水预报精度会受到面平均雨量估计误差的严重影响.点雨量监测值的误差类型、误差大小以及流域的雨量站点密度和站点的空间分布都会影响到面平均雨量的计算.为提高实时洪水预报精度,本文提出了一种基于降雨系统响应曲线洪水预报误差修正方法.通过此方法估计降雨输入项的误差,从而提高洪水预报精度.此方法将水文模型做为输入和输出之间的响应系统,用实测流量和计算流量之间的差值做为信息,通过降雨系统响应曲线,使用最小二乘估计原理,对面平均雨量进行修正,再用修正后的面平均雨量重新计算出流过程.将此修正方法结合新安江模型使用理想案例进行检验,并应用于王家坝流域的16场历史洪水以及此流域不同雨量站密度的情况下,结果证明均有明显修正效果,且在雨量站密度较低时修正效果更加明显.该方法是一种结构简单且不增加模型参数和复杂度的实时洪水修正的新方法.     

基于土壤墒情抗差的降雨径流预报模型——设计与实验流域应用

本文旨在将实时监测得到的土壤墒情转化为流域水文模型可以直接使用的土壤含水量,论证将实时土壤墒情资料用于实时预报的可行性;利用实时监测土壤墒情,改进传统的模型结构,设计基于实测土壤墒情的降雨径流水文预报模型.采用土壤含水量误差抗差估计技术以抵御观测资料粗差的影响,提高系统的稳定性;并在此基础上提出了土壤含水量系统响应修正方法,以提高模型计算精度.将该模型应用于实验流域——宝盖洞流域进行应用检验,洪水模拟合格率达到92.3%,整体模拟精度达到甲级.     

我国东南沿海中小流域洪水模拟研究

我国东南沿海多为独流入海的中小流域,河流短小,流域调节能力弱.该区洪水历时较短,但危害较大,加之近年来区内经济的迅速发展,洪水造成损失日趋加剧,因此开展此区洪水特性和防洪减灾研究意义重大.本文以中国东南沿海曹娥江流域为典型,根据中小流域洪水的特点,在初步分析流域降雨径流的成因和洪水演进规律的基础上,开展了流域洪水模拟研究, 选择建立了流域降雨径流模型以及洪水演进模型,重点探讨了利用遥感信息和GIS相结合确定水文模型参数的方法和途径,经实验流域资料检验分析,其模拟结果计算精度满足要求.该研究将有助于该区流域降雨径流特性及洪水演变规律的深入研究,同时为东南沿海中小流域洪水模拟预测和防洪减灾研究提供了经验和模式.     

强烈下渗条件下天然河道洪水演进模拟方法

河道洪水演进模拟是河道洪水预报与汇流计算的主要内容和关键.对于常年断流、河水与地下水长期处于脱节状态的河道,一旦行洪下渗非常强烈,渗漏量很大.不考虑河道下渗洪水演进模拟模型,无法准确模拟真实的洪水运动行为,不能用于洪水模拟预报.本文采用土壤下渗理论描述河道下渗,推导出了河道下渗流量计算公式,建立了基于霍顿下渗公式的河道下渗模拟方法;并把下渗当做单位区间出流,与基于马斯京根康吉法天然河道洪水演进模型进行耦合,构建了强烈下渗条件下天然河道洪水演进模拟模型.针对天然河道水力特性复杂特点,研究了洪水演进模型参数确定方法和波速计算方法.海河流域漳卫河水系岳城水库-蔡小庄段的典型场次洪水应用结果表明,模型能很好反映强烈下渗条件下洪水演进实际情况,具有很高模拟精度,基于土壤下渗理论的下渗量计算公式和模拟方法可以很好地模拟河道下渗过程.这一模型具有计算简便、参数确定简单、适合于洪水预报等特点,在干旱和半干旱地区河道洪水演进模拟预报与河道汇流计算中也具有一定的推广应用价值.     

新疆阿克苏河流域径流预报方法研究

阿克苏河(中吉国际河流)现已成为塔里木河的主河源,它对塔里木河干流的形成、发展和演变过程起着决定性作用.随着国家西部开发战略--塔里木河流域综合治理的深入开展和实施,阿克苏河流域的水文特征、水文预报等研究成为热点.特别是在干旱区中纬度高海拔流域的河流中,阿克苏河是以冰雪融水补充为主河流的典型代表,对阿克苏河流域径流进行预报研究具有理论和现实意义.鉴于此:(i)结合干旱区无资料或少资料的现状,利用现有的水文气象资料,尝试并构建日尺度水文预报方法;(ii)采用高空气温代替地面实测气温与日径流相关关系法、AR(p)预报模型、气温降雨修正的AR(p)预报模型和NAM降雨径流模型,对阿克苏流域的两大支流进行日径流模拟和预报;(iii)对4种方法模拟结果进行对比分析,表明利用气温和降雨修正后的AR(p)模型所用水文气象资料少、应用简便、预报精度较高、比较适用于资料较缺乏的阿克苏流域的短期径流预报.该研究以日尺度进行水文预报,在该流域尚属首次,不仅为阿克苏河、塔里木河的水文预报、洪水防治和全流域的水量调度等提供基础,也为干旱区其他流域的水文预报提供了参考方法.     

新疆阿克苏河流域径流预报方法研究

阿克苏河(中吉国际河流)现已成为塔里木河的主河源,它对塔里木河干流的形成、发展和演变过程起着决定性作用.随着国家西部开发战略--塔里木河流域综合治理的深入开展和实施,阿克苏河流域的水文特征、水文预报等研究成为热点.特别是在干旱区中纬度高海拔流域的河流中,阿克苏河是以冰雪融水补充为主河流的典型代表,对阿克苏河流域径流进行预报研究具有理论和现实意义.鉴于此(i)结合干旱区无资料或少资料的现状,利用现有的水文气象资料,尝试并构建日尺度水文预报方法;(ii)采用高空气温代替地面实测气温与日径流相关关系法、AR(p)预报模型、气温降雨修正的AR(p)预报模型和NAM降雨径流模型,对阿克苏流域的两大支流进行日径流模拟和预报;(iii)对4种方法模拟结果进行对比分析,表明利用气温和降雨修正后的AR(p)模型所用水文气象资料少、应用简便、预报精度较高、比较适用于资料较缺乏的阿克苏流域的短期径流预报.该研究以日尺度进行水文预报,在该流域尚属首次,不仅为阿克苏河、塔里木河的水文预报、洪水防治和全流域的水量调度等提供基础,也为干旱区其他流域的水文预报提供了参考方法.     

云南洱海桃溪河口净化工程的设计思路及初步净化效果

以太湖上游西苕溪流域为研究对象,通过分布式水文模型HEC-HMS模拟次降雨洪水过程:采用可视化数据存储系统HEC-DSS建立水文气象数据库,利用Geodatabase地理数据库技术集成流域自然属性数据库,通过距离平方倒数法对雨量数据进行空间插值,SCS曲线数法计算水文损失,运动波法计算直接径流与河道洪水演进,选用基流指数退水法模拟流域基流,并对模型中水库模拟部分进行适当修正.经模型校验,模拟结果表明,计算流量与观测流量拟合较好,效率系数大于0.8,洪峰流量误差低于4%,峰现时间误差低于2 h,该模型在土地利用变化对洪水水文要素的影响研究方面有较好的应用前景.     

鄱阳湖湖泊流域系统水文水动力联合模拟

本文以鄱阳湖湖泊流域系统为研究对象,鉴于该湖泊流域系统尺度较大,下垫面自然属性呈现高度空间异质性且具有流域-平原区-湖泊不同机制的水文水动力过程,为了真实描述湖泊流域间的水文水动力联系及反映不同过程间的作用机制,构建了鄱阳湖湖泊流域联合模拟模型.该模型基于自主研发的流域分布式水文模型WATLAC和湖滨平原区产流模型以及水动力模型MIKE 21 3个不同功能子模型的连接来实现该复杂系统的模拟.模型的联合采用输入-输出驱动及子模型的顺序执行进程,即将五大子流域与平原区入湖径流量作为输入条件来驱动湖泊水动力模型,模拟湖泊水位对流域入湖径流量的响应.以2000-2005年鄱阳湖流域6个水文站点的河道径流量、流域基流指数以及湖泊4个站点的水位资料来率定模型,其中各站点日径流量拟合的纳希效率系数E_ns为0.71~0.84,确定性系数R²介于0.70~0.88之间,而湖泊各站点水位拟合的纳希效率系数E_ns变化为0.88~0.98,确定性系数R²为0.96~0.98,均取得令人满意的率定结果.本文提出的鄱阳湖湖泊流域系统水文水动力联合模拟模型能较为理想再现湖泊水位对流域降雨-径流过程的响应.水位模拟结果进一步表明,该联合模型能用来获取重要的水动力空间变化特征.该模型可作为有效工具定量揭示湖泊流域系统水文水动力过程对气候变化和流域人类活动的响应.     

On the prediction of the Toce alpine basin floods with distributed hydrologic models

With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land‐surface sub‐models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant. The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km²). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996–1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations). The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one‐layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long‐term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright © 2006 John Wiley & Sons, Ltd.     

基于误差分布估计的三峡水库入库洪水概率预报方法

准确、及时的入库洪水预报,对三峡水库综合效益的发挥和长江流域水旱灾害防御、水资源利用、流域综合管理等具有重要作用。基于预报误差的最优分布估计和分布函数动态参数假定,提出了一种三峡水库入库洪水概率预报方法,并进行了洪水概率预报业务试验。结果表明:本文所提方法科学可行,计算快捷,使用方便,便于在实时作业预报中应用推广;概率预报结果较确定性预报结果,在水量预报、预警效果等方面均有所改善,1～5 d预见期预报的确定性系数提高0.1%～3.4%,水量误差减少0.1%～4.8%,可为三峡水库实时调度提供更可靠的预报信息;所提出的三峡水库入库洪水概率预报业务化产品,可提供更多风险信息,为三峡水库的科学调度,尤其是洪水资源化利用提供更好的优化决策支撑。     

Simulating streamflow on regulated rivers using characteristic reservoir storage patterns derived from synthetic remote sensing data

This study presents a method to estimate streamflow in rivers regulated by lakes or reservoirs using synthetic satellite remote sensing data. To illustrate the approach, the new reservoir routing method is integrated into the Hillslope River Routing model, and a case study is presented for the highly regulated river in the Cumberland River basin (46,400 km²). The study period is April–May 2000, which contains a significant flood event that occurred in 1–2 May 2000. The model is shown to capture storage/release characterises in eight reservoirs with a mean normalized root mean square error (NRMSE) of 20% for entire simulation period and 27% for the May flood event. These errors are 69 and 75%, respectively, less than the NRMSE if reservoirs are not included in the model. Given the limitations of satellite missions, the impacts of the revisit cycles and operational periods are quantified. We used 26 observation sets of satellite altimetry over Cumberland River basin that are generated by considering both repeat cycles and satellite operation periods. For the revisit cycles, increasing the interval of repeat cycle leads to a corresponding increase of mean NRMSE from 27 to 59% as a result of sampling fewer flood events and smoothing of the change in storage signal as a result of longer intervals between visits. For the operation periods, the impact of data periods is limited because of the strong seasonal pattern of reservoir operations. Overall, the results suggest that the generalized routing model derived from reservoir stage observations can be used to simulate reservoir operating conditions, which can be used in forecasting hydrologic impacts of land cover or climate change. Copyright © 2014 John Wiley & Sons, Ltd.     

Flood hydrograph attenuation induced by a reservoir system: analysis with a distributed rainfall‐runoff model

Spatially distributed hydrologic models can be effectively utilized for flood event simulation over basins where a complex system of reservoirs affecting the natural flow regime is present. Flood peak attenuation through mountain reservoirs can, in fact, mitigate the impact of major floods in flood‐prone areas of the lower river valley. Assessment of this effect for a complex reservoir system is performed with a spatially distributed hydrologic model where the surface runoff formation and the hydraulic routing through each reservoir and the river system are performed at a fine spatial and time resolution. The Toce River basin is presented as a case study, because of the presence of 14 active hydroelectric dams that affect the natural flow regime. A recent extreme flood event is simulated using a multi‐realization kriging method for modelling the spatial distribution of rainfall. A sensitivity analysis of the key elements of the distributed hydrologic model is also performed. The flood hydrograph attenuation is assessed. Several possible reservoir storage conditions are used to characterize the initial condition of each reservoir. The results demonstrate how a distributed hydrologic model can contribute to defining strategies for reservoir management in flood mitigation. Copyright © 2004 John Wiley & Sons, Ltd.     

Updating Real-Time Flood Forecasting Using a Fuzzy Rule-Based Model/Mise à Jour de Prévision de Crue en Temps Réel Grâce à un Modèle à Base de Règles Floues

Abstract

An updating technique is a tool to update the forecasts of mathematical flood forecasting model based on data observed in real time, and is an important element in a flood forecasting model. An error prediction model based on a fuzzy rule-based method was proposed as the updating technique in this work to improve one- to four-hour-ahead flood forecasts by a model that is composed of the grey rainfall model, the grey rainfall—runoff model and the modified Muskingum flow routing model. The coefficient of efficiency with respect to a benchmark is applied to test the applicability of the proposed fuzzy rule-based method. The analysis reveals that the fuzzy rule-based method can improve flood forecasts one to four hours ahead. The proposed updating technique can mitigate the problem of the phase lag in forecast hydrographs, and especially in forecast hydrographs with longer lead times.     

Basinwide flood control system by combining prediction and reservoir operation

Japan has traditionally performed flood prevention through the construction and use of dikes, storage reservoirs, and basins which are costly and time consuming options. Another non-structural option is to operate the flood control system appropriately with a view to reducing flood damage. In this paper, a flood control system combining the runoff prediction model in the whole river basin with the reservoir operation is discussed. Different models of the runoff process are introduced in order to compare their accuracies and the computational time for the flood forecasting system. The reservoir operational rule is formulated in terms of fuzzy inference theory. Historical data are applied in a case study for verification of the proposed theories.     

BMA集合预报在淮河流域应用及参数规律初探

以淮河流域吴家渡水文站作为试验站点,采用基于贝叶斯平均法(BMA)的集合预报模型处理来源于马斯京根法、一维水动力学方法、BPNN(Back Propagation Neural Network)的预报流量序列,通过分析BMA的参数以及其预报结果,对各方法在淮河典型站点流量预报中的适用性进行验证与分析.经2003—2016年19场洪水模拟检验可知,BMA模型能够有效避免模型选择带来的洪水预报误差放大效应,可以提供高精度、鲁棒性强的洪水预报结果.通过进一步比较各模型统计最优的频率与BMA权重值之间的相关性,发现权重值不适用于对单场洪水预报精度评定,而适用于描述多场洪水预报中,模型为最优的统计频率;基于大量先验信息,提前获取BMA的权重等参数,将是指导模型选择、降低洪水预报不确定性、改进洪水预报技术的有效手段.     

Classified real-time flood forecasting by coupling fuzzy clustering and neural network

This paper presented a new classified real-time flood forecasting framework by integrating a fuzzy clustering model and neural network with a conceptual hydrological model. A fuzzy clustering model was used to classify historical floods in terms of flood peak and runoff depth, and the conceptual hydrological model was calibrated for each class of floods. A back-propagation (BP) neural network was trained by using real-time rainfall data and outputs from the fuzzy clustering model. BP neural network provided a rapid on-line classification for real-time flood events. Based on the on-line classification, an appropriate parameter set of hydrological model was automatically chosen to produce real-time flood forecasting. Different parameter sets was continuously used in the flood forecasting process because of the changes of real-time rainfall data and on-line classification results. The proposed methodology was applied to a large catchment in Liaoning province, China. Results show that the classified framework provided a more accurate prediction than the traditional non-classified method. Furthermore, the effects of different index weights in fuzzy clustering were also discussed.     

ANALYTICAL HAYAMI SOLUTION FOR THE DIFFUSIVE WAVE FLOOD ROUTING PROBLEM WITH LATERAL INFLOW

The diffusive wave equation is generally used in flood routing in rivers. The two parameters of the equation, celerity and diffusivity, are usually taken as functions of the discharge. If these two parameters can be assumed to be constant without lateral inflow, the diffusive wave equation may have an analytical solution: the Hayami model. A general analytical method, based on ‘Hayami’s hypothesis, is developed here which resolves the diffusive wave flood routing equation with lateral inflow or outflow uniformly distributed over a channel reach. Flood routing parameters are then identified using observed inflow and outflow and the Hayami model used to simulate outflow. Two examples are discussed. Firstly, the prediction of the hydrograph at a downstream section on the basis of a knowledge of the hydrograph at an upstream section and the lateral inflow. The second example concerns lateral inflow identification between an upstream and a downstream section on the basis of a knowledge of hydrographs at the upstream and downstream sections. The new general Hayami model was applied to flood routing simulation and for lateral inflow identification of the River Allier in France. The major advantages of the method relate to computer simulation, real-time forecasting and control applications in examples where numerical instabilities, in the solution of the partial differential equations must be avoided.