基于区间入流预报的右江河道洪水演进

广西右江如果发生大洪水,将对郁江和南宁市的防洪产生严重威胁,因此右江洪水演进分析对南宁市的防洪具有重要意义。选出百色水文站洪峰流量依次增大的5场洪水,用右江百色-田东河段区间内的小流域作为代表性流域率定新安江模型参数,对区间入流洪水进行了预报。根据预报结果采用经参数试错法率定后的马斯京根模型对5场洪水进行了演进,计算了田东水文站断面的流量。结果表明:计算结果与实测流量相对误差较小,相关性系数较大,说明试错法对于马斯京根模型参数求解精度较高。     

粒子群算法在河道水动力模型参数校正中的应用

参数估计一直是河道水动力模型研究的难点之一,在传统的模型参数人为经验率定方法的基础上,提出了基于粒子群算法的模型参数优化校正方法,构建了参数校正优化模型,并将参数优化校正算法与河道水动力模型进行耦合,针对淮河干流和史灌河支流组成的研究区域,采用一维河道洪水演进模型,比较了糙率系数校正方法和传统经验估算法,校正方法得到的河段糙率系数值比人为经验估计值平均大0.01,淮河干流河段糙率略大于史灌河支流河段糙率,采用校正河段糙率系数得到的河道水位过程与实测值拟合更优,特别在主峰段洪水过程模拟精度显著改善,验证了本文所提出的参数优化校正算法的有效性,为复杂河道水动力模型参数的确定提供了一种有效方法。     

基于XAJ-DCH模型的五强溪库区洪水预报研究

由于沅水水系五强溪水库流域面积大，流量控制站少，且洪水进入库区后，洪水波的传播方式变化较大，因此五强溪水库近坝区的洪水预报难度大。为提高五强溪库区洪水预报精度，采用XAJ-DCH模型(Xin′anjiang Digital Channel Model)对近坝区2016～2020年间13场洪水进行模拟，模型河道汇流分别采用了非线性水库法和马斯京根法，根据两种汇流方法的特点制定了两种不同的洪水预报方案。模拟结果表明：XAJ-DCH模型中两种河道演算方法均表现良好且简单实用，13场洪水的确定性系数基本位于0.7以上。非线性水库方法相比于马斯京根法考虑了河段断面情况以及水力特性，能够体现洪水运动的时空变化，且只需要率定河道糙率，其他参数如河道坡降、河宽以及河段长均可根据数字高程模型进行估计；马斯京根法需要率定4个河道参数，但马斯京根法模拟结果相比于非线性水库方法稍好。研究成果可为科学有效开展库区洪水预报、提高预报精度提供参考。     

基于MIKE软件的海城河洪水风险分析研究

为探清河流发生超标准洪水时的淹没范围,基于MIKE软件构建了海城河干流及其洪水可能影响区域的水流数值模型,对模型参数进行合理设置,利用2012年典型实测洪水过程进行模型参数率定。选择2个堤防溃口进行超标准洪水演进计算分析,得出不同方案下的洪水淹没水深、淹没范围。研究结果表明,该软件模拟精度高,拟合效果好,洪水淹没空间分布合理,可为河流洪水风险分析提供科学计算工具。     

基于元胞自动机和大伙房模型的洪水演进研究

为了快速、准确地模拟洪水演进过程,将元胞自动机和二维圣维南方程相结合,构建了基于元胞自动机的洪水演进模型,实现了元胞间的局部水量交换,以及全流域洪水模拟过程的全局转换。接着,创新性地构建了基于DEM的单元栅格大伙房产流模型并将其作为元胞产流输入,将直接径流、地面壤中流和邻域元胞入流共同作为水深增量,充分考虑到了降雨对河道滩地洪水演进模拟带来的影响。以浑河沈阳城区河段物理模型试验数据为基础,选取了不同设计频率洪水进行实例验证与分析。分析结果表明:水深的模拟具有较高的精度;流速总体上满足模拟需求;淹没范围具有相同的变化趋势,具有合理性和有效性。研究结果可为洪水演进模拟提供一种新方法,同时对其他相似地区洪水演进模拟工作也具有借鉴意义。     

平原区河段洪水演进模拟系统研究与应用

基于数字流域平台和水力学模型软件HEC-RAS,研究了河道和行蓄洪区地形数据的处理、分洪口门和水利工程的模拟等技术难题,提出了上下游边界条件、初始条件的自动生成方法,模拟河道和行蓄洪区的洪水演进,研制了平原区河段洪水演进模拟系统,模拟河道洪水波在行蓄洪区各种工况条件下的运动过程。该模拟系统应用于流域洪水实时预报调度,评价行蓄洪区启用对洪水过程的影响,为流域防洪调度决策提供定量技术支持。在淮河流域王家坝至临淮岗区间,利用2007年7月份流域性大洪水期间的报汛数据系列,对本文提出的模拟系统进行了率定和验证,并评价了6种洪水调度方案的效果。结果表明系统中非恒定流模型的数值解稳定,模拟的洪水过程与实测系列吻合,客观地反映了研究区域洪水运动过程和行蓄洪区启用对该过程的影响,准确地评价了流域洪水调度方案的效果。     

黄河宁蒙河段冰期洪水波运动过程中的变形分析

河道中冰盖的存在会影响到洪水波的演进变形。以黄河宁蒙河段为研究对象,将马斯京根法尝试应用于冰期洪水计算,分析了马斯京根法参数与糙率的关系,比较了冰盖冻结增厚和融化减薄过程对洪水波变形的影响差异。研究结果表明,将马斯京根法应用于冰期洪水计算是可行的;断面的糙率越大,洪水波传播时间越久,变形越大;冰盖冻结增厚过程中,洪水波的变形存在先增加再减少而后又增加的现象;冰盖融化减薄过程中,洪水波随冰厚的减薄而变形增大。相同冰厚下,两种过程的变形程度存在交点。交点之前的冰厚范围,冰盖融化减薄时的洪水波变形更大;交点之后的冰厚范围,冰盖冻结增厚时的洪水波变形更大。     

基于马斯京根法的嫩江江桥-大赉段洪水演算

针对嫩江江桥-大赉河段洪水演进不平衡问题,首先分析了1998年前后江桥和大赉两个水文站的径流变化规律;然后引入河道洪水演进损失系数,建立了基于分段马斯京根方法的江桥-大赉河段的洪水演算模型;最后利用1998年后洪水资料,采用粒子群优化算法率定了河道洪水演进参数和洪水演进损失系数,并分析了参数和损失系数的合理性。结果表明,由于受1998年大洪水的冲刷以及河道两岸冲毁的影响,嫩江江桥-大赉段河道洪水传播速度加快,同时在演进过程中洪水向河道外满溢,导致上下游水量不平衡。     

嫩江下游洪水演进及对洪泛区植被影响分析

为揭示嫩江下游洪水演进规律及对洪泛区植被的影响,利用MIKE FLOOD建立了嫩江江桥—大赉河段的一、二维水动力耦合模型,选取1998年与2013年汛期实测资料对河段糙率进行了率定与验证,并模拟了典型河段4种不同重现期洪水的演进过程。在此基础上基于2000—2019年MODIS卫星的MOD13Q1数据集,获取了不同洪水频率淹没范围内的植被指数(NDVI、EVI),评估了嫩江下游不同重现期洪水扰动对植被的影响。结果表明:模型在率定期与验证期的模拟效果符合甲级预报精度,模型模拟精度较高;不同重现期内的植被指数具有较强的季节变化规律,且洪水对植被具有明显的破坏作用,但这种破坏作用在嫩江流域周期性相对较短,表明该地区植被的可恢复性较强;同时受洪水频繁淹没程度影响,不同重现期的植被指数符合中度干扰假说。     

多沙河流洪水演进的计算方法

本文研究了符合于多沙河流洪水演进的计算方法.黄河流域干支流上汛期最大含沙量高达1000kg/m~3以上.汛期洪水在河道里既有水量调蓄作用,也有沙量调蓄作用.河床泥沙的大量淤积或冲刷,直接影响到河段的出流量.因此马斯京干洪水演进计算方法只能适用于清水河流.本文通过水沙量平衡方程式推导得修正流量的含沙率,并修正了马斯京干洪水演进公式.     

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.

     

基于EnKF的无实测资料区间支流反分析

区间入流误差是河道洪水演算不确定性来源之一。为此,一部分研究基于水动力模型和数据同化方法对区间总入流误差进行动态修正,但无法推算出某条支流的单独入流过程;另一部分研究通过从下游往上游反算水流的方式推算区间支流入流,但反算结果稳定性差,对边界条件误差敏感,推算的入流过程误差较大。针对上述问题,本文提出了基于集合卡尔曼滤波(EnKF)的区间支流反分析方法。方法由一维河道水动力模型正、反向水流演算初步估算支流入流,并构建监测断面滞时矩阵,计算水流扰动传播时间,从而确定用于支流入流校正的流量监测值。当EnKF校正的结果仍然存在较大误差时,可再次运用EnKF对首次校正结果进一步校正。将该方法应用于理想案例和西江实例,推算的支流入流过程与实测过程十分接近,入流结果 R2和NSE皆在0.99以上,相对RMSE也小于0.05。结果表明,本文提出方法可准确计算出无实测资料的区间支流入流过程,研究结果对于提高河道洪水演算精度具有重要意义。     

Entropy-Based Flow and Sediment Routing in Data Deficit River Networks

The reliable estimate of the sediment load and streamflow is essential for water resources and flood management. In this study, the entropy-based technique and HEC-RAS are used for flow routing followed by sediment routing in HEC-RAS. The paper’s novelty is its application to data-deficit river networks, where observed sediment load and flow on tributaries are absent. The proposed method accommodates the flow and sediment contribution from the tributaries to the downstream station on a reach, despite unavailable observed data on it. The adopted flow routing techniques are applied to predict downstream flow on three different reaches (on the Mahanadi and the Godavari River). The prediction accuracy is evaluated using three statistical indices ? Nash–Sutcliffe efficiency (NSE), relative error (RE), and Coefficient of determination (R²). Both flow routing techniques showed good performance for all three reaches (with or without tributaries), having NSE, R²?>?0.8, and RE?<?13%. Despite the comparable performance, the entropy-based routing is suggested for natural rivers with or without tributary as it avoids the iterative calibration process to determine the roughness coefficient. Further, the sediment routing is performed on the data-deficit reach of the Mahanadi River to obtain the best-suited sediment transport function. The simulated sediment load using the Yang transport function matched satisfactorily with the observed data with NSE, R²?>?0.85, and RE?<?–27%. Subsequently, the Yang transport function and entropy-based flow routing are utilized for the sediment and flow estimation at an ungauged station on the Mahanadi river.

     

HYPE模型在成屏一级水库的适用性研究

水文模型是模拟水库入库流量的重要工具之一。以浙江省遂昌县成屏一级水库为研究对象,基于LHOAT方法、DE方法和HYPE模型,通过参数敏感性分析、参数率定和误差分析,评估了HYPE模型对成屏一级水库入库流量模拟的适用性。结果表明:HYPE模型中极敏感的参数为cevp,较敏感的参数为pcluse、cevpcorr、rrcscorr、rrcs1; HYPE模型在率定期的纳什效率系数(NSE)为0. 87,在验证期的纳什效率系数(NSE)为0. 83,这表明HYPE模型具备在长序列日尺度水文模拟的能力; HYPE模型在洪峰模拟上模拟值低于实测值,原因可能是输入数据的精确性不足以及率定的模型参数并不能较好地反映出暴雨过程中的流域特征;对暴雨情况采用新的参数进行流域特征刻画,模型模拟效果更好。     

2000年以来黄河宁蒙河段开河期冰凌洪水特点分析

黄河宁蒙河段开河期冰凌洪水主要集中在3月中下旬,一般由融冰洪水与冰坝洪水组成,其特点主要表现在:凌峰、洪量年际变化大,沿程增加明显,头道拐站易形成多峰,峰型系数较夏汛小,洪水历时较夏汛短,水位表现较夏汛同流量水位高,流速在涨水段慢于落水段。这些特点主要与宁蒙河道形态、水利工程、封河期上游来水及开河期气温、开河形势、封冻期形成的槽蓄水增量大小、沿程分布及其释放程度有关。     

河道洪水流量预测方法研究

及时准确地预报某区域内河道指定区段洪水流量及发生时间,对合理实施该区域的防洪预案、落实抗洪抢险措施、组织调度人员及防汛物资具有重要意义。目前河道洪水预报普遍采用马斯京根流量演算法及加里宁—米尔加科夫洪水演进法,两种方法的参数率定存在局限性,对应支流的河道分段处理也存在问题。本文依据最小二乘法,建立含有预测河段上游干流、支流水文站（或水位站）流量或水位预测模型,该模型不受其他水文参数的率定精度影响,直接利用以往洪水及当次洪水上游、下游站的观测资料建立回归预测模型,并通过递推方式完成当次洪水预测,表达形式简单直观、便于实际应用。利用该模型完成了嫩江干流齐齐哈尔水文站2013年洪水流量预测,经与实测成果比较,洪峰流量最大拟合误差小于5.2%,具有较好的计算精度。     

An automatic parameter calibration method for the SWAT model in runoff simulation

Runoff simulation is highly significant for hydrological monitoring, flood peak simulation, water resource management, and basin protection. Runoff simulation by distributed hydrological models, such as the soil and water assessment tool (SWAT) model which is the most widely used, is becoming a hotspot for hydrological forecasting research. However, parameter calibration is inefficient and inaccurate for the SWAT model. An automatic parameter calibration (APC) method of the SWAT model was developed by hybrid of the genetic algorithm (GA) and particle swarm optimization (PSO). Multi‐station and multi‐period runoff simulation and accuracy analysis were conducted in the basin of the Zhangjiang River on the basis of this hybrid algorithm. For example, in the Yaoxiaba Station, the calibration results produced an R² of 0.87 and Nash Sutcliffe efficiency (NSE) index of 0.85, while verification results revealed an R² of 0.83 and NSE of 0.83. Results of this study show that the proposed method can effectively improve the efficiency and simulation accuracy of the model parameters. It can be concluded that the feasibility and applicability of GA‐PSO as an APC method for the SWAT model were confirmed via case studies. The proposed method can provide theoretical guidance for many hydrological research fields, such as hydrological simulation, flood prevention, and forecasting.     

Application of a Simple Raster-Based Hydrological Model for Streamflow Prediction in a Humid Catchment with Polder Systems

The hydrological processes are controlled by many factors such as topography, soil, climate and land management practices. These factors have been included in most hydrological models. This study develops a raster-based distributed hydrological model for catchment runoff simulation integrating flood polders regulation. The overland flow and channel flow are calculated by kinematic wave equations. A simple bucket method is used for outflow estimation of polders. The model was applied to Xitiaoxi catchment of Taihu Lake Basin. The accuracy of the model was satisfactory with Nash–Sutcliffe efficiencies of 0.82 during calibration period and 0.85 for validation at Hengtangcun station. The results at Fanjiacun station are slightly worse due to the tidal influence of Taihu Lake with high values of root mean square errors. A model sensitivity analysis has shown that the ratio of potential evapotranspiration to pan evaporation (K), the outflow coefficients of the freewater storage to groundwater (KG) and interflow (KSS) and the areal mean tension water capacity (WM) were the most sensitive parameters. The simulation results indicate that the polder systems could reduce the flood peaks. Additionally, it was confirmed that the proposed polders operation method improved the accuracy of discharge simulation slightly.     

耦合渗漏项的季节性河道洪水演进模型研究

针对北方干旱或半干旱区季节性河道渗漏现象严重问题,为提高流域洪水演进模拟精度,在传统水动力学洪水演进模型基础上耦合河道渗漏项,构建季节性河流洪水演进数学模型。采用霍顿入渗模型描述季节性河道渗漏过程,解决河道渗漏量计算及与基于圣维南方程组洪水演进模型耦合问题;并利用Preissmann四点偏心隐格式与追赶法对模型离散和计算,开发FORTRAN计算程序;最后以大沽河流域实测资料进行验证。结果表明,沙湾庄和南村断面水位与流量过程的模拟值与实测值吻合且变化趋势一致,洪水峰面到达断面模拟时间和实际时间基本一致,研究区各河段来水量、渗漏量的实测值与模拟值相对误差范围分别为-1.66%~0.36%、-3.09%~3.72%,所建模型可满足在现状条件下进行洪水模拟预报的需要。     

Optimal Operation of Multi-reservoir Systems Considering Time-lags of Flood Routing

Operations of multi-reservoir systems are nonlinear and high-dimensional problems, which are difficult to find the optimal or near-optimal solution owing to the heavy computation burden. This study focuses on flood control operation of multi-reservoir systems considering time-lags caused by Muskingum flood routing of river channels. An optimal model is established to jointly minimize the flood peak on the downstream flood control station for the multi-reservoir systems. A hybrid algorithm, Progressive Optimality Algorithm and Successive Approximation (POA-SA), is improved to solve the multi-reservoir operation model by modifying the POA. The POA-SA uses the DPSA to reduce the spatial dimensionality due to the multiple reservoirs, and adopts an improved POA to alleviate the temporal dimensionality caused by the time-lags of the Muskingum flood routing. Linear programming is then implemented to verify the solution of the POA-SA method with a linear approximation of the discharge capacity curve. The multi-reservoir systems of China’s Xijiang River is selected for a case study. Results show that the flood peak of Wuzhou station can be averagely decreased by 6730 m³/s (12.8 %) for the 100-year return period floods, indicating that the proposed method is efficient to operate the multi-reservoir systems and resolve the time-lags issues.