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.     

不同面雨量估算方法对水库入流预测 模型精度的影响

以潘家口水库入库径流预测为研究对象,分别采用分块法、栅格计算法以及DEM法计算区域平均降雨量,并在此基础上建立潘家口水库来流预测模型。结果表明不同的面雨量估算方法对水库入库径流的预测精度具有较大影响。以DEM法计算区域平均雨量值作为预测模型的输入所模拟的效果优于另外两种区域平均雨量计算方法,且预测结果合理。     

适用于分布式水文模拟的空间插值方法改进

降水数据是水文模型重要输入数据之一,雨量空间插值是获得面雨量数据的有效方法。改进现有雨量插值方法,获取较为精确的逐日连续面域降水数据,并以补远江流域为例对改进效果进行验证,将插值后得到的降水数据作为输入条件,基于MIKE SHE水文模型模拟补远江流域径流过程,分析改进后的插值方法所得降水数据对模型精度的提高效果。结果表明:利用改进插值方法(简称IDW-Thiessen插值法)得到的降水数据,在模型模拟径流过程中的效果优于利用Thiessen多边形获得的降水数据;在补远江流域这一研究案例中,利用IDW-Thiessen插值法得到的降水数据模拟补远江日径流,所得结果的纳什系数在率定期和验证期都超过0.7,高于利用Thiessen多边形法得到的降水数据进行径流模拟结果的纳什系数;IDW-Thiessen插值法与Thiessen多边形得到的径流模拟结果相比,年平均误差减少10%,雨季模型模拟精度提高6%,旱季模型模拟精度提高了7%,模拟径流过程线与实测径流过程线更吻合。     

Runoff modelling using radar data and flow measurements in a stochastic state space approach.

In urban drainage the estimation of runoff with the help of models is a complex task. This is in part due to the fact that rainfall, the most important input to urban drainage modelling, is highly uncertain. Added to the uncertainty of rainfall is the complexity of performing accurate flow measurements. In terms of deterministic modelling techniques these are needed for calibration and evaluation of the applied model. Therefore, the uncertainties of rainfall and flow measurements have a severe impact on the model parameters and results. To overcome these problems a new methodology has been developed which is based on simple rain plane and runoff models that are incorporated into a stochastic state space model approach. The state estimation is done by using the extended Kalman filter in combination with a maximum likelihood criterion and an off-line optimization routine. This paper presents the results of this new methodology with respect to the combined consideration of uncertainties in distributed rainfall derived from radar data and uncertainties in measured flows in an urban catchment within the Emscher river basin, Germany.     

雨量站网分布对雨量插值算法及径流响应的影响

为比较雨量站网密度及分布对不同空间插值算法的影响,选取6种雨量站密度的不同分布,采用4种空间插值算法对研究区2006—2014年的日降雨进行插值,并将面均雨量作为新安江模型的输入,分析和比较其降雨径流响应。结果表明:①雨量站网空间分布越均匀,降雨插值误差越小,其径流模拟的精度也越高;②在雨量站网均匀布置的情况下,各空间插值算法的插值结果差异较小;雨量站网布置不均匀时,站点数目越少各空间插值算法插值结果差异越大;③计算点雨量时,考虑空间变量的克里金法能更准确地计算日降雨的结果;计算面雨量时,不同插值算法间差异较小,建议选用计算简便的插值算法,比如泰森多边形、反距离权重法。     

Estimation of the Velocity Parameter of the Geomorphologic Instantaneous Unit Hydrograph

The problem of estimation of the velocity parameter in the exponential distribution geomorphological instantaneous unit hydrograph (ED-GIUH) is investigated in this study. The main difficulty in applying the ED-GIUH model is the estimation of this parameter. In the present study, the ED-GIUH model is applied to six watersheds in Indiana, U.S.A. The relationships between the velocity parameter and climatic as well as basin geomorphologic parameters are investigated. The results of the study indicate that the velocity parameter is related to effective rainfall depth, total basin area and cumulative slope; it does not depend on runoff characteristics. Therefore, the ED-GIUH model can be used for estimating discharge hydrographs from ungauged watersheds.     

Comparison of the Lumped and Quasi-distributed Clark Runoff Models in Simulating Flood Hydrographs on a Semi-arid Watershed

In applied hydrology, predicting peak flow for a stream or river is so complex due to temporal and spatial dependency of hydrological variables such as meteorological parameters, variations in soil type and land use. Either advanced distributed hydrological models or simple Lump models can be used for simulating these situations. This paper compares the performance of the quasi-distributed model ModClark versus lumped parameter model Clark in simulating the process of transformation of rainfall to runoff. The aim of this comparison is to identify whether using a complex model which takes into account spatial and temporal distribution parameters, which are hard to prepare and use, will lead to more precise results or not. For the purpose of this study, historical data of Randan basin situated in semi-arid region of Iran in North West of Tehran was used. The size of the catchment is 67.76 km². Reviewing the results of calibration and accuracy of models revealed that both models are able to simulate the hydrology of the catchment in an acceptable way.     

泰森多边形法在小流域面雨量计算中的应用

为探究泰森多边形法在小流域面雨量计算中的适用性,以地处江淮丘陵区适宜进行产汇流机制等水文基础理论研究的典型闭合小流域花山流域为例,结合流域现状站点分布和地形特点,选取流域多年面雨量、典型场次与典型日面雨量三种不同降雨量级实例,分别采用算术平均法、泰森多边形法和等值线法计算面雨量进行对比。年面雨量和场次面雨量计算中泰森多边法对比等值线法计算值相对误差小于 1.00%,日面雨量计算值相对误差小于 2.00%;算术平均法在典型场次面雨量样本中有 40.0%的计算值相对误差大于 1.00%,最大相对误差为 -2.47%,在典型日面雨量样本中有36.8%的计算值相对误差大于 2.00%,最大相对误差为 9.38%。结果表明：不同降雨量级使用泰森多边形法计算面雨量比算术平均法更接近于等值线法计算值;算术平均法在降雨量较小时受局部降雨影响计算误差较大,在年面雨量计算时可以和泰森多边形法互换使用。     

基于水动力模型的土地利用格局对流域雨洪过程的影响研究

为了定量分析不同土地利用对流域雨洪过程的影响,建立流域雨洪水动力数值模型,模拟了王茂沟流域不同土地利用情景方案的地表径流过程,对比流域洪峰流量削减程度。结果表明：在重现期为2、10、50、100 a一遇降雨条件下,对于不同土地利用情景方案,林地的位置对径流量影响较大;林地位于流域坡面下部时,对洪峰流量的削减作用最大;降雨重现期越长,林地位于流域坡面下部的削峰效果越好。该研究结果在优化流域内土地利用方案规划等方面具有重要意义。     

融雪的水量平衡模型在内蒙古锡林河流域水文模拟中的应用

水量平衡模型是目前水文及环境分析中最常用的工具和手段之一,半干旱地区的水文模拟是目前水文科学研究中的难点.以内蒙古地区的锡林河流域为研究对象,开展了考虑融雪的水量平衡模型(Snowmelt-based Water Balance Model,SWBM模型)的拓展性应用研究.结果表明:锡林河流域气候干旱,产流受降水和融雪驱动,流域降水量及实测径流量均呈现弱减少趋势.SWBM模型对对月径流过程具有较好的模拟效果,率定期和检验期的模型效率系数均可超过60％,相对误差小于8％,说明该模型可以用于研究气候变化对半干旱地区的影响评价.     

Effects of Raingauge Distribution on Estimation Accuracy of Areal Rainfall

Rainfall analysis is important to managing water resources. Mean rainfall is usually used to calculate the spatial rainfall status of a region and is the input into various rainfall-runoff models. However, this method relies on an adequate raingauge network. This study identifies the effects of raingauge distribution based on estimation results of areal rainfall using the Thiessen polygon and block Kriging methods. Twelve rainfall events with complete data from 14 raingauges were selected to complete the goal of this study. The block Kriging method in this study uses a dimensionless semivariogram to obtain hourly semivariograms based on a standardized rainfall depth. The power semivariogram model was used to describe the temporal-spatial variation of rainfall. The analytical process in this study uses raingauge weight and rainfall volume as evaluation criteria. All raingauges were in turn removed from the original raingauge network. The effects of removing each raingauge were compared with computations using all raingauges. Comparison results indicate that (1) the block Kriging method can accurately describe rainfall processes in terms of the spatiotemporal structure of a semivariogram. (2) the block Kriging method is better than the Thiessen polygon method at obtaining exact mean rainfall, and (3) the effects of different raingauge distributions on a mean hyetograph warrant further investigation.     

Prediction of peak runoff from rainfall in a temperate area

The purpose of this study is to investigate some of the factors controlling the rainfall-runoff relationship and, consequently, predicting flood events in a catchment. Primarily, the research is concerned with the study of rainfall and runoff with respect to various hydrometeorological and physical factors. An equation to predict the peak discharge is proposed. The prediction equation illustrates that the maximum peak discharge can be obtained as a function of rainfall intensity, rainfall duration, duration of rainfall up to time of concentration, and the previous discharge. Such analyses are considered vital as the basis for flood warning systems in the area under consideration.     

新安江模型参数变化对流域降雨径流过程的影响分析

水文模型可以模拟自然流域的降雨径流过程,在降雨径流过程模拟中,水文模型参数的选择往往会影响模型对流域径流过程的模拟效果.针对新安江模型,以陕西黑河金盆水库流域为研究流域,分析新安江模型参数变化对模拟流域降雨径流过程的影响,以确定新安江模型参数的敏感程度,从而服务于研究流域的汛期水文预报参数修正.模拟结果表明:在研究流域新安江模型参数中KKSS、KKG、WLM、WDM、kg、k为敏感参数,对模拟流域降雨径流过程的影响较大;参数WUM、IMP、B、c、SM、EX为不敏感参数,对模拟流域降雨径流过程影响较小.     

Sensitivity Analysis of the GIUH based Clark Model for a Catchment

For estimation of runoff response of an ungauged catchment resulting from a rainfall event, geomorphologicalinstantaneous unit hydrograph (GIUH) approach is getting popularbecause of its direct application to an ungauged catchment. Itavoids adoption of tedious methods of regionalization of unithydrograph; wherein, the historical rainfall-runoff data of anumber of gauged catchments are required to be analyzed. In thisstudy, the GIUH derived from geomorphological characteristics ofa catchment has been related to the parameters of Clark IUH modelfor deriving its complete shape. The DSRO hydrographs estimatedby the GIUH based Clark model have been compared with the DSROhydrographs computed by the Clark IUH model option of the HEC-1package and the Nash IUH model by employing some of the commonlyused error functions. Sensitivity analysis of the GIUH basedClark model has been conducted with the objective to identify thegeomorphological and other model parameters which are moresensitive in estimation of peak of unit hydrographs computed bythe GIUH based Clark model. So that these parameters may beevaluated with more precision for accurate estimation of floodhydrographs for the ungauged catchments.     

基于 DEM 的泰森多边形计算

在计算流域的面平均雨量时,泰森多边形法考虑到站点密度及其空间分布影响,计算精度较高。该文介绍了一种采用计算机语言程序来计算泰森多边形的方法,比传统几何制图方法更方便、快捷、可靠,在水文预报、水文分析计算和分布式水文模型中可广泛应用。     

A Modified LAPSUS Model to Enhance the Effective Rainfall Estimation by SCS-CN Method

In this study, LAPSUS model is modified to enhance the effective rainfall estimation by SCS curve number method. The LAPSUS model calculates discharge based on effective rainfall and routs it towards lower neighbouring grid cells following the multiple flow direction principle. Then, the sediment transport capacity and sediment transport rate are calculated in each grid cell. Finally, erosion or sedimentation is calculated by comparing the sediment transport rate with the sediment already in the transport of each grid cell. The amount of rainfall, curve number, convergence factor, discharge exponent, slope exponent, erodibility factor, and sedimentation ability factor are inputted to the application page of the modified model that was created in the C⁺⁺ programming. The outputs of the model are runoff and erosion maps in ASCII format. Evaluating performance of the modified model showed a high accuracy of its results. The value of the coefficient of determination (R²) calculated 0.99 for runoff and 0.97 for erosion. The Nash-Sutcliffe efficiency was 0.96 for runoff and 0.97 for erosion. The value of the precision index calculated 0.81 for both runoff and erosion. Also, the nRMSE calculated 3% for both runoff and erosion. The result showed that the modified model capable to estimate the runoff and erosion on a landscape in a micro sub-catchment scale.     

雨量插值方法对BTOPMC模型及洪水模拟的影响

以BTOPMC为研究对象和平台,用最邻近插值法、算术平均法、引入面积权重的泰森多边形法、引入泰森多边形的距离反比加权法4种不同的降雨空间插值方法,对3个小流域进行了洪水模拟,分析了各插值方法对模型参数、模拟精度、洪水洪峰流量、峰现时间等的影响。结果表明:引入泰森多边形的距离反比加权法在各插值方法中表现较好,对各流域各场洪水洪峰流量的模拟精度较高,模拟洪峰时刻与其他几种方法相比更接近实测洪峰时刻;BTOPMC模型原有的最邻近插值法在对模型参数进行率定时Nash效率较高,但在验证时比另外3种插值方法低;引入面积权重的泰森多边形法在模拟中表现不稳定。     

Modeling of Surface Runoff in Xitiaoxi Catchment,China

Xitiaoxi catchment is one of the most important catchments in the Taihu basin in China. Due to its significant contribution of surface runoff and associated nutrients input to Lake Taihu, understanding of the processes of surface runoff in this catchment is, therefore, of primary importance in quantifying water and nutrient balances for Lake Taihu. The generation of surface runoff in the catchment is mainly controlled by rainfall and land cover, so the variety of surface runoff in Xitiaoxi catchment is seasonal. Moreover, the annual change of surface runoff is distinct. Because of the diversity of land use and variety of hydrological characteristics, numerical simulation of the generation of surface runoff over this catchment is not straightforward. In this paper, attempts were made in applying the Large Scale Catchment Model (LASCAM) to Xitiaoxi catchment. The Xitiaoxi catchment is divided into 47 subcatchments connected via a river network based on topology. The model was first run in an optimization mode to calibrate the parameters against the observed runoff for the period of 1968–1977, and then was run in a prediction mode to try to reproduce the runoff for the next 10 years from 1978 to 1987. The model indicates that saturation excess runoff is probably the dominant process for the catchment. The modeling results indicate that water storage in shallow soils near the stream has a high correlation with daily rainfall, while the water storage changes in deep aquifers demonstrate an annual change trend, showing a rising level for wet seasons and a declining level for dry seasons. The success in modeling surface runoff leads to confidence in modeling nutrients transport as the next step of modeling work.     

Integrated Surface–Subsurface Modeling of Fuxianhu Lake Catchment, Southwest China

This paper describes an integrated surface–subsurface modeling study of the Fuxianhu Lake catchment (southwest China). Pollution threats to this important water resource have led to the need to evaluate transport pathways and the overall water balance of the catchment. Catchment inputs to the lake include river inflows, direct overland flow and groundwater discharge, which are incorporated into a mathematical model of the system. Surface runoff and groundwater recharge are estimated using a parsimonious soil–vegetation modeling approach, while groundwater flow is based on the MODFLOW-2005 code. Overland flow and stream discharge are coupled to the groundwater regime through the soil layer and are routed through the catchment to account for surface water flow pathways. The model is tested using the V-catchment benchmark problem and is compared to existing models to demonstrate accuracy and capability. Application of the model to the Fuxianhu catchment provides for the first-order approximation of the average catchment water balance, which comprises such components as evapotranspiration losses (37% of rainfall), surface runoff to the lake (37% of rainfall), and groundwater discharge to the lake (8% of rainfall), amongst others. The computationally efficient approach to surface–subsurface modeling adopted in this investigation presents as an alternative to more complex methods, and allows for the rapid assessment of flow pathways at the catchment scale. An erratum to this article can be found at     

Deterministic Insight into ANN Model Performance for Storm Runoff Simulation

The artificial neural network (ANN) theory has been widely applied to practical applications in hydrology. Since watershed rainfall–runoff processes are nonlinear and exhibit spatial and temporal variability, the ANN model, which considers watershed nonlinear characteristics, can usually but not always obtain satisfactory simulation results. The training of an ANN network is based completely on the reliability of the available hydrologic records. The objective of this study was to provide deterministic insight into the limitations of storm runoff simulation when using ANN. Hydrologic records of 42 storm events from two watersheds in Taiwan were adopted for analysis. A deterministic runoff model was used to classify the hydrologic records into “usual” and “unusual” storm events. The analytical results show that the ANN model could provide good simulation results for “usual” storm events; however, its performance was poor when it was applied to “unusual” storm events because no consistent hydrologic characteristics could be extracted from the storm event records using ANN. The success of the ANN model in usual storm discharge simulations may be mainly due to the input vectors including the previous observed discharge. Moreover, the number of past periods of rainfall that were set as the input vectors of the ANN model was found to be highly correlated with the watershed time of concentration. It can be used to efficiently determine the ANN network structure instead of using iterative network training.