水情自动测报系统的实时联机洪水预报

实时联机洪水预报是指利用水情自动测报系统实时收集的流域水文数据,由人_工随机启动或定时自动启动计算机根据专用流域洪水竟预报数学模型进行作业洪水预报,并预报出流域出口断面的洪水过程。流域洪水预报模型是以流域为研究对象,对流域内发生的降雨径流这一特定的水文过程进行数学模     

数字流域水文模型在柘溪水电站洪水预报中的应用

将数字高程模型（DEM）生成的数字高程流域水系模型（DEDNM）与新安江水文模型相结合构建数字流域水文模型，并将该模型应用于柘溪水电站的6个子流域进行产、汇流计算，所得子流域出口的径流过程与实际洪水过程进行拟合，制作洪水预报方案。结合流域现有遥测信息和实时校正技术编制了实时洪水预报系统。实时预报系统通过近1年的试运行表明该方案得到了成功应用，预报精度达到甲级标准。试运行期间依据该系统预报调度对大洪水进行了有效的错峰削峰，充分显示了水库的巨大防洪效益；洪水后期的拦蓄洪尾也为水库后期的保水抗旱提供了有力保障，增加了发电效益。     

水库洪水实时优化校正预报模型的探究与应用

以经典流域水文模型——新安江模型为基础,耦合SCE-UA全局自动优化算法和AR自回归误差校正模型构建出适用于水库流域的洪水实时优化校正预报模型。根据实测的降雨径流过程对水文模型参数和流域状态变量参数进行全局优化实时校正计算,并依据预报降雨对未来一定时期内水库洪水过程进行高精度预报。选取亭下水库流域为实验对象,对亭下水库流域洪水分别进行初步预报和实时优化校正预报,两种预报结果比较分析显示,实时优化校正预报结果能更好地模拟实测洪水过程,其预报精度更高。     

流域洪水实时预报模型研究及应用

根据广西合浦水库流域的水文特征 ,利用分散型新安江三水源模型对合浦水库流域洪水实时预报进行了研究。对流域产汇流模型以及洪水实时预报校正模型的参数进行了率定 ,并将研制的模型应用于实际洪水预报 ,取得较满意的效果     

基于气象模式的汉江流域洪水预报系统

针对现行洪水预报方法的不足与汉江流域的特点,建立了汉江流域MM5气象预报模式和VIC分布式水文模型,耦合集成3种预报模式并开发了基于气象模式的汉江流域洪水预报系统。应用2005~2007年汛期日水文气象资料进行验证,结果表明所建VIC分布式水文模型具有较高的模拟与预报精度。基于气象模式的汉江流域洪水预报系统可为汉江流域的中长期水文预报和水资源综合管理提供技术支撑和决策参考。     

北江飞来峡～石角河道洪水演算

根据北江飞来峡～石角河道水力特征,分别用线性模型、非线性模型和具有预见期的洪水演算模型对该河道洪水进行了模拟计算.结果表明：三种演算模型的计算精度大体相当,结果令人满意;三种模型与流域水文模型的有机结合,可以应用于该河段洪水预报作业预报、实时洪水预报系统和防汛决策支持系统.     

概念性流域水文模型实时预报校正方法探讨及枫树坝水库应用实例

本文基于概念性流域水文模型洪水预报误差信息，探讨了多种洪水实时预报校正模型与计算方法，经枫树坝水库实际洪水模拟计算，表明针对该水库ＡＲ（２）模型的自适应实时校正方法和卡尔曼滤波方法的预报校正效果较好。     

建立多支流汇入河段洪水预报模型的方法

针对受无流量控制断面支流汇入影响的河段,传统预报方法很难较好预报洪水过程的实际情况,以实例流域数据和实时水情传输系统为基础,将水文预报数学拟合模型进行了尝试性应用.     

三峡水库入库流量短期洪水预报

本文对三峡水库入库流量实时短期洪水预报从预报流域站网布设、预报系统构建、水文预报方法选用、实时预报管理等几个方面进行了分析和阐述.并对三峡水库建成以来及2010年几场洪水实时预报成果进行了总结分析.     

基于Transformer的智能洪水预报模型及其应用研究

万安水库是赣江流域以发电为主的大型控制型水库,其洪水预报准确性将影响赣江流域的防洪以及发电调度决策。基于Transformer网络建立入库洪水预报模型,对万安流域不同区域分区设计三种预报方案,经实际洪水预测结果表明,输入降雨和径流数据越完整,Transformer模型可以较好模拟入库洪水过程,达到较好的水文预报准确度,是大型流域洪水实时预报的有效工具。     

积石峡水电站水文预报方案与站网规划设计

为了最大限度地减少暴雨洪水灾害损失,实现积石峡水电站水情测报自动化,根据公伯峡至积石峡区间流域的实际情况,确定了公伯峡～积石峡区间流域水文预报模型,设计了公伯峡至积石峡区间流域水情测报系统站网规划方案,为积石峡水电站水情自动测报系统的建立提供依据,为防汛调度、决策指挥提供科学依据。     

水情自动测报系统在龙滩水电工程中的应用

工程施工期和运行期的安全度汛，协调发电与防洪的矛盾，进行梯级水库联合调度，提高工程现代化管理水平等，都必须有行之有效的水情测报手段。龙滩水情测报系统由信息采集传输、信息处理、信息发布等子系统组成。系统设备配置合理，性能稳定，运行可靠，在龙滩工程施工防洪度汛工作中发挥了重要作用。     

A coupled rainfall-runoff and runoff-routing model for adaptive real-time flood forecasting

This paper describes an adaptive hydrologic modelling technique for real-time flood forecasting. The modelling approach is based on a linear stochastic time-varying representation of the rainfall-runoff process and on the Muskingum routing method formulated as an optimal linear filtering problem. The most general stochastic rainfall-runoff model used for linear forecasting is known as the transfer function noise model. An on-line identification procedure based on an extension of the recursive Instrumental Variable estimator is discussed. The routing procedure, based on the Muskingum method, is written in a state-space representation. This allows real-time updating of the state and the system parameters by means of Kalman filtering. The described method is used to forecast extreme flood events for the River Ourthe (drainage basin: approx 3626 km²), one of the main tributaries of the River Meuse, Belgium. The method is compared with stationary modelling procedures and its superiority based on objective forecasting criteria is demonstrated.     

马斯京根分段演算与水箱模型组合在区间洪水过程预报中的应用

介绍了马斯京根流量演算方法和水箱模型,提出了将马斯京根分段分步流量演算方法与水箱模型相结合进行区间洪水预报的方法,并将该方法应用于渭河林家村站、汉江安康水库站的洪水预报的研究中,实践证明该方法合理可行,可以推广应用到其它的区间洪水预报中。     

RTU 在小花间暴雨洪水预警预报系统中的应用

小花间暴雨洪水预警预报系统是“数字黄河”工程的首项工程。结合系统中水情信息采集传输系统的设计与建设,介绍了水情测报系统的组成和远程终端设备(RTU)的工作原理与功能,以及水文测报专用数据采集终端YSCADA-1在小花间水情信息采集传输系统中的应用情况,对水文自动测报系统的设计和建设具有较高的参考价值和指导意义。     

基于水文水动力学耦合的洪水预报模型研究及应用

为了提高下垫面变化剧烈流域的洪水预报精度,在传统流域水文模型的基础上耦合水动力学模型,建立水文水动力耦合洪水预报模型。首先利用水文模型获得某一断面的流量过程作为水动力学模型的边界条件;之后利用一维水动力学模型进行河道洪水演进计算,推求流域出口断面的流量过程;最后以烟台市外夹河流域为例进行验证。结果表明,所建水文水动力耦合模型模拟的产流合格率较高,流量过程与实测值吻合,在一定程度上弥补了集总式水文模型不能考虑河道内复杂水流运动的不足,因此对具有复杂水文、水力条件的流域的洪水预报具有重要的指导意义。     

张峰水库工程水文预报模型

水情自动测报可为水库安全渡讯和防洪调度提供可靠的依据。本文以张峰水库工程水情自动测报系统为例,介绍流域水文模型的建立,供相关工程参考。     

基于BP神经网络的贝叶斯概率水文预报模型

本文在贝叶斯概率水文预报系统(BFS)框架之上，研究了双牌水库水文预报的不确定性，建立了流量先验分布及似然函数的BP神经网络模型，并通过Markov链Monte Carlo(MCMC)方法求解得到流量后验分布及其统计参数。通过对双牌水库历史洪水的研究结果表明，基于BP神经网络的BFS不仅显著提高了预报精度，而且为防洪决策提供了更多的信息，使得预报人员在决策中能考虑预报的不确定性，定量的估计各种决策的风险和后果。     

Real-time flood forecasting of Huai River with flood diversion and retarding areas

A combination of the rainfall-runoff module of the Xin’anjiang model, the Muskingum routing method, the water stage simulating hydrologic method, the diffusion wave nonlinear water stage method, and the real-time error correction method is applied to the real-time flood forecasting and regulation of the Huai River with flood diversion and retarding areas. The Xin’anjiang model is used to forecast the flood discharge hydrograph of the upstream and tributary. The flood routing of the main channel and flood diversion areas is based on the Muskingum method. The water stage of the downstream boundary condition is calculated with the water stage simulating hydrologic method and the water stages of each cross section are calculated from downstream to upstream with the diffusion wave nonlinear water stage method. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The faded-memory forgetting factor least square of error series is used as the real-time error correction method for forecasting discharge and water stage. As an example, the combined models were applied to flood forecasting and regulation of the upper reaches of the Huai River above Lutaizi during the 2007 flood season. The forecast achieves a high accuracy and the results show that the combined models provide a scientific way of flood forecasting and regulation for a complex watershed with flood diversion and retarding areas.     

A System Approach to Real-time Hydrologic Forecast in Watersheds

Abstract

In non-structural measurement of flood control, hydrologic forecasting plays a very important role. Owing to time-variance, non-linearity, and uncertainty of hydrological processes, realtime forecasting has become an efficient approach. The paper addresses an important practical problem: improving short-term hydrological forecasting based on real-time updating in the operation model. A simple nonlinear model with a variable gain parameter (VGPM) is developed. A separated calibration approach for updating parameters used in the runoff generation process and the response function in the flow routing is proposed. State space equations associated with updating model parameters in a real time scheme were developed. The VGPM approach is verified for three types of representative watersheds. The performances of different updating schemes in rainfall-runoff modeling and real-time forecasting were tested. The results indicate that significant improvement in the efficiency of hydrological modeling can be obtained from the VGPM approach, relative to simple linear models (SLM). For the watersheds with a time-variant characteristic, moreover, significant improvement in the hydrologic forecasting efficiency can be obtained by adaptive schemes. The efficiency of real-time modeling by the self-adaptive Kalman Filtering algorithm was found to be very close to that of the Recursive Least-Square method.