Estimation of Design Flood Hydrograph for an Ungauged Watershed

Based on the physiographical features of the studied watershed of 102.5 km² in northern Ontario and the meteorological data of one nearby climatic station, through the combination of the regionalization of flood and the HEC-1 modeling, this article presents an approach that may be used to determine the desired peak flows for the ungauged watershed. The empirical equations used to determine the desired peak flows were developed by the Cumming Cockburn Ltd. (CCL) who has carried out the studies on flood regionalization by using flow data at 380 gauging stations in Ontario. CCL has proposed four methods to estimate peak flows, namely 1) regression method describing multiple linear relationships between flood flow and related parameters; 2) index flood frequency curve; 3) regional flood frequency curve and 4) isoline map for unit peak flow. The desired peak flows for studied watershed determined by CCL methods were used to calibrate the HEC-1 model for the rainfall-runoff simulation for this watershed which consists of 15 subwatersheds. Through slight adjustment in the CN number used in the HEC-1 model, the calibrated HEC-1 model could be used for rainfall-runoff simulation for this ungauged watershed. This approach could be recommended for hydrological design and watershed management for ungauged watersheds provided the analyses of flood regionalization could be conducted. In addition, comparing to the Bavaria forest region, Germany, some questions have been discussed in this article.     

Comparison of Artificial Neural Network Methods with L-moments for Estimating Flood Flow at Ungauged Sites: the Case of East Mediterranean River Basin, Turkey

A regional flood frequency analysis based on the index flood method is applied using probability distributions commonly utilized for this purpose. The distribution parameters are calculated by the method of L-moments with the data of the annual flood peaks series recorded at gauging sections of 13 unregulated natural streams in the East Mediterranean River Basin in Turkey. The artificial neural networks (ANNs) models of (1) the multi-layer perceptrons (MLP) neural networks, (2) radial basis function based neural networks (RBNN), and (3) generalized regression neural networks (GRNN) are developed as alternatives to the L-moments method. Multiple-linear and multiple-nonlinear regression models (MLR and MNLR) are also used in the study. The L-moments analysis on these 13 annual flood peaks series indicates that the East Mediterranean River Basin is hydrologically homogeneous as a whole. Among the tried distributions which are the Generalized Logistic, Generalized Extreme Vaules, Generalized Normal, Pearson Type III, Wakeby, and Generalized Pareto, the Generalized Logistic and Generalized Extreme Values distributions pass the Z statistic goodness-of-fit test of the L-moments method for the East Mediterranean River Basin, the former performing yet better than the latter. Hence, as the outcome of the L-moments method applied by the Generalized Logistic distribution, two equations are developed to estimate flood peaks of any return periods for any un-gauged site in the study region. The ANNs, MLR and MNLR models are trained and tested using the data of these 13 gauged sites. The results show that the predicting performance of the MLP model is superior to the others. The application of the MLP model is performed by a special Matlab code, which yields logarithm of the flood peak, Ln(Q_T), versus a desired return period, T.     

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.     

Regional Models for the Estimation of Streamflow Series in Ungauged Basins

The assessment of water resources in a region usually must cope with a general lack of data, both in time (short observed series) as well as in space (ungauged basins). Such a lack of data is generally overcome by combining rainfall–runoff models with regionalization techniques in order to transfer information to sites without or with short available observed series. The present paper aims to analyze applicability and limitations of two regionalization procedures for estimating the parameters of simple rainfall–runoff models respectively based on a “two-step” and on a “one-step” approach, for the estimation of monthly streamflow series in ungauged basins. In particular, an application to a Sicilian river basin of multiple regression equations according to a “two-step” and a “one-step” approaches and of a “one-step” approach based on neural networks is reported. For the investigated region, results indicate that models based on the “one-step” approach appear to be robust and adequate for estimating the streamflows in ungauged basins.     

Estimation of Parameters of a Conceptual Water Balance Model for Ungauged Catchments

The problem of parameter estimation constitutes the largest obstacle to successful application of conceptual catchment models in ungauged catchments. This paper investigates the usefulness of a conceptual water balance model for simulating river flow from catchments covering a wide variety of climatic and physiographic areas. The model is a 6-parameter water balance model which was applied to 26 seasonally snow covered catchments in central Sweden. The model was calibrated on a group of catchments and the calibrated parameter values related to physical catchment indices. The relationships were tested by comparing observed and simulated runoff records from 4 catchments that were not contained in the regression analysis. The results show that the model can be satisfactorily applied to ungauged basins in the study region. In order to test the physical relevance of the model to a wider set of conditions, the model was modified by excluding the snow routine part. The resulting model and the same technique were tested on 24 catchments taken from northern Belgium. The verification results were found to be satisfactory.     

西江天河站洪水特性分析与洪峰预报方案研究

通过西江干流、珠江三角洲河口区的天河水文站的洪水特性分析，根据上游的高要站洪峰水位及石角、天河站同时水位，对天河站的峰水位及出现时间进行预报。对受潮汐顶托及网河交汇影响，不便用合成流量法来进行实时水文预报的站点，用相应水位法进行预报，也能取得较好的预报精度，且简单快捷，适用性强。     

Spatial Information-Based Back-Propagation Neural Network Modeling for Outflow Estimation of Ungauged Catchment

Rainfall–Runoff Models (RRMs) are standard tools for hydrologists to organize water resource planning and management. With the development of space-information technology and computing science in recent years, RRMs have improved to better simulate the rainfall–runoff process along with the spatial variation of simulated catchment, with the aim of precisely articulating the underlying relationship between input and output information. The Artificial Neural Network (ANN) model is suitable because it has various mathematical compositions capable of simulating a nonlinear structural system to establish the flow discharge in a catchment. For this reason, it has been successfully applied in RRMs modeling. In this study, the rainfall–runoff behavior of the gauge stations will be replicated in an ANN model. A Back-Propagation Neural network (BPN) was adopted to estimate an ungauged region’s outflow considering the temporal distribution of rainfall–runoff and the spatial distribution of the watershed environment. The nonlinear relationship among the physiographic factors, precipitation and outflow of the specific catchment was established to estimate the outflow of the sub-catchment where no flow gauge had been provided. The hazard preventive hourly model was mainly considered in this paper, and the model was also compared with the Instantaneous Unit Hydrograph (IUH) and Area Ratio Method (ARM) approaches. In validation tests in the middle and large catchments in Taiwan, the model performed well in providing forecast results. From the research work, it is revealed that the relevant spatial information can be obtained easily and precisely, which will help future studies on more related dimensions.     

Development of Design Hyetographs for Ungauged Sites Using an Approach Combining PCA,SOM and Kriging Methods

A design hyetograph represents the temporal distribution of rainfall intensity associated with a return period. The choice of the design hyetograph will have a significant influence on the shape and peak value of the hydrograph. Hence, the determination of design hyetographs is an important task in the hydrologic designs. In this paper, an approach is proposed to develop design hyetographs for ungauged sites. The proposed approach is composed of four steps: principal component analysis (PCA), self-organizing map (SOM)-based clustering, region delineation, and kriging-based construction. Firstly, PCA is applied to obtain the principal components of the design hyetographs. Then the transformed data resulting from PCA and the three geographic characters of the gauges are used as input data to the SOM, which is applied to group the rain gauges into specific clusters. Thirdly, the regions for these clusters are delineated and then the regions map is made. Finally, the design hyetographs for ungauged sites is constructed by using the kriging method. The proposed approach is applied to estimate the design hyetographs of ungauged sites in Taiwan. For comparison with the proposed approach, three other approaches are executed. Four gauges are treated as ungauged and the three approaches are used to construct the design hyetographs. The results show that accurate estimated design hyetographs can be obtained by the proposed approach. Cross-validation tests further have been performed to examine the stability and the accuracy of these approaches. Again, the results indicate that the proposed approach is more accurate and stable than the other approaches. Overall, the results demonstrate that the proposed approach is useful to develop design hyetographs for ungauged sites.     

黄河中游府谷站"03·7"洪峰流量合理性分析

从府谷水文站洪水过程测验控制情况、天桥电厂下泄流量推算和天桥电厂-府谷区间洪水加入等3个方面,对府谷站2003年7月30日洪峰测报是否偏大的问题进行了分析.结果表明,天桥电厂下泄洪峰估算定性偏小,府谷站洪峰测验过程控制良好,天桥-府谷区间产生了1800m3/s的洪峰直接加在天桥电厂下泄的洪峰上,使府谷站8时出现12800m3/s的洪峰是可信的;府谷水文站出现低水位大流量的现象主要是断面冲刷造成的.     

近期黄河洪峰增值现象研究综述

对小浪底水库运用之前黄河干流洪峰增值现象的研究进行了回顾,对小浪底水库运用后洪峰增值的洪水场次进行了系统整理,并对近期黄河洪峰增值现象的研究成果进行了综述,指出了已有的河槽形态变化观点、"孤立波"和"水跃"观点、减阻观点、密度差观点、沙坝观点、扰动说等研究成果存在的问题,认为小浪底水库运用前后小浪底—花园口区间洪水洪峰增值机理是相同的,与洪水是否漫滩无关。另外,建议加测足够的野外资料,然后从理论上分析洪峰增值的机理。     

Identification of Critical Flood Prone Areas in Data-Scarce and Ungauged Regions: A Comparison of Three Data Mining Models

Flood is one of the most devastating natural disasters with socio-economic consequences. Thus, preparation of the flood prone areas (FPA) map is essential for flood disaster management, and for planning further development activities. The main goal of this study is to investigate new applications of the evidential belief function (EBF), random forest (RF), and boosted regression trees (BRT) models for identifying the FPA in the Galikesh region, Iran. This research was conducted in three main stages such as data preparation, flood susceptibility mapping using EBF, RF, and BRT models and validation of constructed models using receiver operating characteristic (ROC) curve. At first, a flood inventory map was prepared using documentary sources of Iranian Water Resources Department (IWRD) and extensive field surveys. In total, 63 flood locations were identified in the study area. Of these, 47 (75%) floods were randomly selected as training/model building and the remaining 16 (25%) cases were used for the validation purposes. The flood conditioning factors considered in the study area are altitude, slope aspect, slope angle, topographic wetness index, plan curvature, geology, landuse, distance from rivers, drainage density, and soil texture. Subsequently, the FPA maps were prepared using EBF, RF, and BRT models in a GIS environment. Finally, the results were validated using ROC curve and area under the curve (AUC) analysis. From the analysis, it was seen that the EBF (AUC?=?78.67%) and BRT models (AUC?=?78.22%) performed better than RF model (AUC?=?73.33%). Therefore, the resultant FPA maps can be useful for researchers and planner in flood mitigation strategies.     

2010年黄河调水调沙期间花园口洪峰增大的成因

对2010年黄河调水调沙期间花园口站出现的洪峰增值现象进行了分析,结果表明:洪峰增大的主要原因是洪水运行过程中,铁谢-逯村间展宽河段内粗颗粒泥沙发生沉积,产生了一个临时的潜水沙坝,造成其上游的蓄水量增加,在水流的持续作用下,沙坝被冲开从而造成了逯村站流量的加大;在洪水波向下游运行的过程中,又产生了沿程河槽的冲刷,流速递增,从而造成了流量进一步加大.     

Estimation of Peak Flow Rates for Small Drainage Areas

Runoff plots are important for soil loss measurements, and increasing numbers of plots use automatic equipment. To choose equipment with appropriate capacities, the peak flow rate must be known. The peak flow rate is also an important parameter in the modified universal soil loss equation (MUSLE) which calculate the soil loss from upland slope. The available peak flow rate equations are primarily for the watershed scale, not for small drainage areas like runoff plot. This study’s purpose was to derive an equation suitable for the small drainage areas. A total of 149 runoff events on 5 runoff plots were used to develop a peak flow rate equation for the hillslope scale. All plots are located in the Tuanshangou catchment, Zizhou county, Shaanxi province, China. Dimensionless analyses were used to determine the equation form of linear regression analyses. The results revealed that the peak flow rate was significantly correlated with plot area, slope steepness, runoff depth, rainfall depth and the maximum 30-min rainfall intensity. Two equations were developed to estimate peak flow. The model efficiencies of both equations exceeded 0.9. The equations developed in this study represent an important complement to existing peak flow rate equations. These new equations will facilitate the design of soil conservation practices and/or the selection of flow-observation equipment for small drainage areas.     

贵州暴雨洪水计算综述

简要阐述设计洪水的主要计算方法。对建国后贵州主要应用的《贵州省水文实用手册》、《中小流域雨洪计算综合法》、《贵州省暴雨洪水计算实用手册》及其修订本和其他一些有关成果 ,以暴雨资料计算设计洪水的方法进行了概述。文中系统介绍推介的贵州现阶段主要应用的暴雨洪水计算方法 ,以及在使用中解决几个具体问题的意见 ,对岩溶地区小流域和特小流域 ,及不透水复盖面积较大的流域等异常情况的暴雨洪水计算问题提出一些具体处理方法 ,可供进行设计洪水计算时参考。     

郁江南宁至西津段洪峰流量衰减规律研究

利用洪水扩散波运动原理,分析在西津电站调蓄和区间来水影响下,郁江南宁至西津段洪峰流量的衰减规律,认为郁江发生不同量级的洪水时,洪水从南宁至西津的传播过程中,洪水量级越小,衰减越明显,反之,衰减不明显。     

汾河水库以洪峰推算洪量法预估入库洪水量

用水库上游水文测站报汛实测洪峰，通过实测洪峰值计算入库洪水量，在汛期水库调度中简单实用，易于被水库基层管理人员掌握。     

利用简测法施测分析山区河流最大洪峰流量方法探讨

河流突发最大洪峰流量时,利用施测断面岸边1～3条测速垂线平均流速与断面平均流违的相关关系,分析其相关系数与误差,可较为精确地求得断面洪峰流量.     

Combined Effects of Parallel and Series Detention Basins for Flood Peak Reduction

A simple analytical method is proposed that allows a preliminary evaluation of the overall efficiency of a detention basin system for flood risk reduction in a specific target section. Solutions are provided both for parallel and series systems, under some simplifying assumptions concerning the linearity of detention basin, river network and watershed responses. Further, for the series configuration a regressive model is proposed for the computation of the overall efficiency, because of the complexity of analytical solution. A case study is also presented, where the overall efficiency of a system of nine detention basins is computed by means of both the analytical and the regressive model. Results are discussed to assess the different influence of detention basins in parallel or in a series system.     

Estimation of Monthly Mean Reference Evapotranspiration in Turkey

Monthly mean reference evapotranspiration (ET ₀ ) is estimated using adaptive network based fuzzy inference system (ANFIS) and artificial neural network (ANN) models. Various combinations of long-term average monthly climatic data of wind speed, air temperature, relative humidity, and solar radiation, recorded at stations in Turkey, are used as inputs to the ANFIS and ANN models so as to calculate ET ₀ given by the FAO-56 PM (Penman-Monteith) equation. First, a comparison is made among the estimates provided by the ANFIS and ANN models and those by the empirical methods of Hargreaves and Ritchie. Next, the empirical models are calibrated using the ET ₀ values given by FAO-56 PM, and the estimates by the ANFIS and ANN techniques are compared with those of the calibrated models. Mean square error, mean absolute error, and determination coefficient statistics are used as comparison criteria for evaluation of performances of all the models considered. Based on these evaluations, it is found that the ANFIS and ANN schemes can be employed successfully in modeling the monthly mean ET ₀ , because both approaches yield better estimates than the classical methods, and yet ANFIS being slightly more successful than ANN.