江西柘林河段洪水的反演推求

马斯京根法是我国现行的河道流量演算方法中最常用的一种,在线性运动波演算中具有较高精度.马斯京根法反演主要用于河道断面资料缺乏的地区,通过下断面的洪水流量过程来反推求上断面的洪水过程.当坝址洪水资料缺失时,可以通过马斯京根法反演,分析建立入库洪水与坝址洪水的关系,使建库前后资料满足一致性.     

马斯京根法在锦屏二级水电站减水河段洪水演算中的应用研究

不同场次洪水演算所采用的马斯京根模型的演算参数不同,演算参数的取值对洪水演算的结果有很大影响。传统的演算参数确定方法是试算法,本文提出了一种根据参数的含义运用河道相关数据直接推求马斯京根法演算参数,使参数自适应分段马斯京根模型的方法,本方法具有演算精度高、计算速度快、适应性强等特点,解决了演算参数求解复杂、精度差等问题,该实例验证了本方法的可行性和准确性,可应用于具备类似条件河段的洪水验算。     

基于动力系统反演理论的马斯京根流量演算误差校正

运用马斯京根法进行河道洪水演算时,通常存在上断面及区间入流的预报误差及马斯京根法本身的误差。这些误差都会降低河道下断面洪水的预报精度。为此,基于系统反演理论,构建三种误差的反演方程并进行误差校正,以提高河道下断面洪水预报精度。淮河王家坝—润河集河段初步应用的实例表明,该方法可以提高马斯京根法的预报精度。     

变参数非线性马斯京根分段演算模型研究与应用

为了更好地模拟天然河道中洪水演进的时空非线性特征,通过构建连续型可变参数的槽蓄方程,在前人研究基础上进一步改进了非线性马斯京根模型结构,并与河道分段演算方法相耦合,提出了一种变参数非线性马斯京根分段演算模型(CVPCS-NMM),并应用于实际案例中。结果表明:CVPCS-NMM取得了比分段马斯京根模型和变指数非线性马斯京根模型(CVEP-NMM)更好的效果,反映出了天然河道洪水过程在时空上的非线性变化特点,表明该模型是一种行之有效的河道演算方法,也为进一步探讨如何将河道分段演算方法与非线性马斯京根模型相结合提供了一种研究思路。     

马斯京干法在韩庄运河洪水演算中的应用

韩庄运河是南四湖韩庄闸以下的泄洪通道,本次采用马斯京根法对韩庄运河河段进行河道洪水演算,将其洪水演算方案运用到实际工作中以提高预报时效和精度要求。     

多单元集总式的河道流量演算模型

为解决因上游来水组合多样及计算环节复杂而导致的洪水预报精度差和效率低问题,大河控制站的洪水预报可采用先分单元汇流演算再进行成果合成的方式;用上游干、支流水文站实测流量过程作为单元输入项,便于参数分析和预报因子获取。利用马斯京根法分段连续演算模拟河道汇流,实现模型程序化;根据河道水力特性确定计算时段长及单元河段长,以提高洪水错峰计算精度,由实测洪水资料分析适配汇流参数曲线,增强模型的实用性。结果表明,基于马斯京根法的多单元集总式流量演算模型适合湿润地区河道洪水演算预报。     

入库洪水计算的马斯京根法探讨

本文对马斯京根法推求入库洪水的求解产生的误差进行了系统的研究,其中包括马斯京根法的顺时序顺演算、逆时序逆演算、逆时序顺演算和顺时序逆演算公式。同时对大藤峡水库入库洪水作了条件数的分析。     

河道洪水反向演算问题的研究

河道洪水反向演算在河库联合调度中具有重要意义。为此，利用运动波方程的差分解证明了马斯京根法在求解河道洪水反向演算中的不稳定性；基于河道汇流单位线原理，提出了解决河道洪水反向演算的断面流量相关法。实例研究中采用多场洪水联立求解率定参数，利用镜像影射法求解矛盾方程组，取得了满意的模拟和验证计算成果；在此基础上，提出了基于断面流量相关法的进一步研究课题。     

马斯京根法模型在受闸门影响的预报断面中存在的问题分析——以北运河土门楼站为例

中国洪水预报系统内置的马斯京根法河道洪水演算模型,功能强大且明显简化了运算量,是北运河土门楼站作业洪水预报的重要工具.但在实际预报工作中发现该模型存在一些问题,为提高预报精度延长预见期,阐述了在实际应用中国洪水预报系统马斯京根法模型进行洪水预报工作时发现该模型存在的缺陷,并提出了解决建议,以期促进模型优化,提高洪水预报精度.     

哈里斯鹰算法在广义非线性马斯京根参数优化中的应用——以洛河为例

马斯京根模型在河道洪水演算中发挥着重要作用,其演算精度在于参数的优选。针对目前马斯京根参数率定中存在的求解复杂、精度不高等问题,提出利用哈里斯鹰算法对其参数进行优化,这种方法具有广泛的全局搜索能力,且需要调节的参数较少。以黄河支流洛河为研究对象,利用广义非线性马斯京根模型对宜阳—白马寺段的河道进行洪水演算,且分别用哈里斯鹰算法、粒子群算法和蚁群算法对其参数进行优化。结果表明,基于哈里斯鹰算法的广义非线性马斯京根模型在洛河宜阳—白马寺段的演算精度较高,其Min.SSD为1 237,洪峰误差DPO仅为5,均优于粒子群算法和蚁群算法优化后的结果,其成果适合应用于洛河宜阳—白马寺段的洪水预报工作。     

Rating Curve Development at Ungauged River Sites using Variable Parameter Muskingum Discharge Routing Method

A physically based simplified discharge routing method, namely, the variable parameter Muskingum discharge-hydrograph (VPMD) routing method, having the capability of estimating the stage hydrographs simultaneously in channels with floodplains is presented herein. The upstream discharge hydrograph is routed using this VPMD method in different two-stage symmetrical trapezoidal compound cross section channel reaches. The performance of the VPMD method is evaluated by numerical experiments using the benchmark MIKE11 hydrodynamic model and the field data of the Tiber River in central Italy. The proposed method is capable of accurately routing the discharge hydrographs, corresponding stage hydrographs and synthesizing the normal rating curves at any downstream ungauged river site which is not affected by any downstream effects. This study can be helpful for various planning and management of river water resources in both the diagnostic and prognostic modes.     

马斯京根模型改进新思路

马斯京根模型基于水量平衡原理和线性槽蓄假定而建立,模型自提出以来不断得到改进。归纳起来,模型改进思路主要体现在水量平衡微分方程、槽蓄方程以及参数取值三方面。在已有模型改进思路基础上,通过引入组合流量系数,尝试构建新的马斯京根演进模型。模型以同一断面历史多时刻流量线性组合代替槽蓄方程中当前单时刻流量,并采用微分进化算法进行模型参数率定。以滦河大黑汀水库以下至滦县河段为例,分别选取不同量级的10次代表性水流过程进行模拟。结果表明,模型模拟精度较未改进得到了提高。     

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 dam-breach erosion model: I. Formulation

This paper, Part I in a series of two, develops a mathematical model for earthern dam breach erosion. This model constitutes an extension of the Breach Erosion of Earthfill Dams (BEED) model developed by Singh and Scarlatos (1987). Two aspects are emphasized: the evolution of the dam breach, and the subsequent flood and sediment routing. Simulation of dam breach evolution is based on hydrologic, geometric and geotechnic considerations. Einstein-Brown and Bagnold equations are utilized to compute the rate of erosion in the breached section. A water routing scheme, based on a modified version of the Muskingum method to simulate flow exchange between channel and floodplains, is used to route the resulting breach hydrograph. A sediment routing scheme based on the Muskingum method, modified to simulate deposition in floodplains, and deposition and scouring in the channel, is utilized to route the breach sediment graph. In Part II, the model is tested against historical dam failures, and an analysis is made to determine its sensitivity to various parameters.     

A Modified Muskingum Flow Routing Model for Flood Wave Propagation during River Ice Thawing-Breakup Period

During the period of river ice thawing and breakup process (termed as “ice cover thawing-breakup”), vast amount of water stored in ice-covered river reach will be released comparing to that under open flow condition. The flow routing process during river ice thawing-breakup period will be different from that under open flow condition, since water stored in and channel from ice thawing-breakup process and flow routing process are very complicated. If the flow routing process during river ice thawing-breakup period can be predicted, it will very important for flood protection in the downstream river reach. In present study, water released from ice cover thawing process is considered as the lateral inflow to the channel flow during propagation process of flood wave from upstream to downstream. A model for the flood routing process during river ice thawing-breakup period has been developed based on the Muskingum hydrologic method. Using the modified Muskingum model, the routed outflow hydrograph has been determined along the Baotou Reach of the Yellow River during river ice thawing-breakup period. Results showed that the simulated hydrographs using developed model agree well with those of field measurements.

     

Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)

Flood routing is a technique to determine the flood hydrograph at a point of downstream where is of great importance and flood-induced risks can cause irreparable damages. Routing methods can be classified into two categories: hydraulic routing and hydrologic routing. Hydrologic methods are less accurate than hydraulic methods but they are widely used for engineering of rivers due to simplicity and being acceptable. Muskingum is a simple, widely used hydrologic method in the flood routing. In present study, accuracy of the linear Muskingum method has been evaluated using the Particle Swarm Optimization (PSO) algorithm in a Karun River reach bounded to the Mollasani hydrometric station and Ahwaz station upstream and downstream of the river, respectively. The results suggest that if three distinct values rather than constant values are used for X, K, ?? parameters in the Muskingum method, the accuracy of computed outflow will be increased particularly in the peak section of hydrograph so that the Mean Relative Error (MRE) of the peak hydrograph section was 2.44% when constants were. However, in the case of using three different values for these parameters, the error value reached 0.89%.     

滩地加宽及主槽变化对复式断面过流能力的影响

为了分析不同断面形态对复式断面过流能力的影响,针对概化的复式断面顺直型河道,应用数学模型分别计算并分析了滩地加宽和主槽位置变化河道滩槽流量分配比、沿程水位、河道水力坡降的影响。结果表明：当滩地过水面积小于4~6倍的主槽过水面积时,增大滩地的宽度可以明显降低河道的沿程水位;改变主槽的位置几乎不会影响河道的过流能力。     

Application of New Hybrid Optimization Technique for Parameter Estimation of New Improved Version of Muskingum Model

The Muskingum method is one of the most utilized lumped flood routing model in which calibration of its parameters provides an active area of research in water resources engineering. Although various techniques and versions of Muskingum model have been presented to estimate the parameters of different versions of Muskingum model, more rigorous approaches and models are still required to improve the computational precision of calibration process. In this study, a new hybrid technique was proposed for Muskingum parameter estimation which combines the Modified Honey Bee Mating Optimization (MHBMO) and Generalized Reduced Gradient (GRG) algorithms. According to the conducted literature-review on the improvement of Muskingum flood routing models, a new six-parameter Muskingum model was proposed. The hybrid technique was successfully applied for parameter estimation of this new version of Muskingum model for three case studies selected from literature. The obtained results were compared with those of other methods using several common performance evaluation criteria. The new hybrid method with the new proposed Muskingum model perform the best among all the considered approaches based on most of utilized criteria. The new Muskingum model significantly reduces the SSQ value for the double-peak case study. Finally, the achieved results demonstrate that not only the hybrid MHBMO-GRG algorithm overcomes the shortcomings of both phenomenon-mimicking and mathematical optimization techniques, but also the presented Muskingum model is appeared to be the most reliable version of Muskingum model comparing with other considered models in this research.     

Rainfall-Runoff Modeling: Comparison of Two Approaches with Different Data Requirements

Among several hydrological models developed over the years, the most widely used technique for estimating direct runoff depth from storm rainfall i.e., the United States Department of Agriculture (USDA) Soil Conservation Service’s (SCS) Curve Number (CN) method was adopted in the present study. In addition, the Muskingum method, which continues to be popular for routing of runoff in river network, was used in the developed model to route surface runoffs from different subbasin outlet points up to the outlet point of the catchment. SCS CN method in combination with Muskingum routing technique, however, required a detailed knowledge of several important properties of the watershed, namely, soil type, land use, antecedent soil water conditions, and channel information, which may not be readily available. Due to this complexity of semi-distributed conceptual approach (SCS CN method) and non-linearity involved in rainfall-runoff modeling, researchers also attempted another less data requiring approach for runoff prediction, i.e., the neural network approach, which is inherently suited to problems that are mathematically difficult to describe. The purpose of this study was to compare the rainfall-runoff modeling performance of semi-distributed conceptual SCS CN method (in combination with Muskingum routing technique) with that of empirical ANN technique. The models were coded in C language and to make them user friendly, a Graphical User Interface (GUI) was also developed in Visual Basic 6.0. The developed models were tested for Kangsabati catchment, situated in the western part of West Bengal, India. Monsoon data of 1996 to 1999 were used for calibration of the models whereas they were validated for another four years (1987, 1989, 1990, and 1993) monsoon data. Modeling efficiency (ME) and coefficient of residual mass (CRM) were used as performance indicators. Results indicated that for Kangsabati catchment, the empirical runoff prediction approach (ANN technique), in spite of requiring much less data, predicted daily runoff values more accurately than semi-distributed conceptual runoff prediction approach (SCS CN method).     

复杂河道实时洪水预报的半自适应模型研究

具有行蓄洪区的复杂河道的洪水演算是洪水预报中的一难点。对于复杂河道如何在水文学方法中考虑分洪、蓄洪并提高实时洪水预报的精度是一个重要的问题。为解决这一难题，在提出基于马斯京根流量演算河道洪水实时预报的半自适应滤波模型的基础上，对该模型在具有行蓄洪区的复杂河道中的应用问题进行了深入的研究，提出了蓄洪区的计算与预报方法，使得半适应滤模型可以用于复杂河道行蓄洪的调度和实时洪水预报。