参数率定过程中目标函数选择的不确定性对径流模拟的影响

在水文模型率定过程中,不同目标函数侧重于径流模拟的不同层面。为了探究目标函数选择的不确定性对模型参数和径流模拟的影响,将HyMod模型应用于黄河源区,选择纳什效率函数f_NS、总水量平衡误差函数f_t、低水量误差函数f_d和高水量误差函数f_g作为目标函数,采用遗传算法(GA)分别率定出不同目标函数下对应的最优参数值,并依次代入水文模型模拟水文过程;通过对比分析年尺度及年内各月实测与模拟径流过程、纳什效率系数NSE、决定系数R²和均方根误差RMSE评价指标来探究参数率定的目标函数不确定性对年尺度水资源演变过程的影响。结果表明:当HyMod模型应用于黄河源区水文模拟的率定期和验证期时,目标函数选择的不确定性对各评价指标的影响差异明显,如f_NS目标函数下NSE值最大,在f_g下次之,在f_d下最小,此外率定期模拟精度优于验证期;同样,目标函数不确定性对不同特征时期径流的影响差异显著,其中,f_NS和f_t目标函数下,非汛期分别高估和低估模拟流量。研究成果可为水文模型参数率定目标函数的选择提供理论参考。     

妫水河流域水文模拟及参数不确定性分析

以北京市延庆区妫水河为例,使用SWAT(Soil and Water Assessment Tool)模型对妫水河流域进行月尺度水文模拟,使用SUFI-2(Sequential Uncertainty Fitting)算法分析参数的敏感性,依据SWAT-CUP自动率定得到P因子和R因子分析模型的不确定性,从而完成本流域分布式水文模型的构建。率定结果显示,率定期确定系数R 2为0.65,效率系数NSE为0.61;验证期确定系数R 2为0.89,效率系数NSE为0.88;不确定性分析结果中P-factor均大于0.5,R-factor均小于0.3。通过以上分析可得该模型对妫水河流域的水文模拟有良好的效果。     

基于不同目标函数GLUE方法参数不确定性研究

水文模型在防洪预报中发挥着重要作用,然而由于模型参数具有不确定性,即使有实测的降雨资料,也可能会产生较大的预报误差。针对参数的不确定性问题,以半湿润的陈河流域为研究区域,基于单目标GLUE方法和多目标GLUE方法,分析不同目标函数GLUE方法对实测径流的模拟能力以及参数的敏感性。研究结果表明,参数可分为敏感性参数(SM,CS)和非敏感性参数(K,KG,KI,CG,CI),不同的似然目标函数对径流具有不同的模拟能力,相对于单目标函数,多目标函数预报的不确定性范围较大,区间覆盖率较大,洪水预报的精度更高。     

基于SWAT模型的北江飞来峡流域径流模拟

为满足北江飞来峡流域非点源污染负荷核算需要,利用SWAT模型对研究区1969-2011年日径流过程进行模拟。基于飞来峡流域水文、气象、地形、土地利用和土壤类型等资料构建SWAT径流模型,并运用SWAT-CUP中的SUFI-2方法对模型中的14个径流参数进行敏感性分析及参数率定,再进行径流模拟效果定量评价。结果表明:对径流过程有显著影响的参数主要为SCS径流曲线系数、主河道曼宁系数、地下水滞后系数以及地表径流滞后时间等;日径流率定期和验证期的效率系数均为0.83,相对误差分别为1.40%和0.58%,且大部分模拟数据落在不确定性区间内,模拟结果的不确定性较小,表明所构建的SWAT径流模型具有较高的精度,在北江飞来峡流域适用性良好。     

图们江流域SWAT模型的构建及其参数敏感性分析

为科学评估与合理优化图们江流域水资源，以图们江流域(中国一侧)1995年～2019实测气象水文数据为基础，应用ArcGIS 10.2建立了SWAT水文模型，对流域2000年～2019年月径流过程进行模拟。基于SWAT-CUP中的SUFI-2算法对模型输入的参数进行敏感性分析和率定校准，并探讨了模型在图们江流域的适用性。结果表明，对所构建模型模拟效果影响最大的参数为CN2、ALPHA＿BF、SLSUBBSN;率定期的确定系数R²=0.88,效率系数NSE=0.74;验证期的确定系数R²=0.83,效率系数NSE=0.66,两个时期的百分比偏差PBIAS<25%,均方根差与标准偏差的比值RSR均小于0.6。     

新安江流域abcd水量平衡模型及参数敏感性分析

abcd水量平衡模型在国外得到了广泛应用,但在国内应用基本处于空白状态。为了探究该模型在我国中小流域应用的适应性及有效性,在介绍abcd模型的原理及结构的基础上,将其应用于新安江流域的径流预报模拟。在国内首次对abcd模型的4个参数进行敏感性分析,采用单变量法和多变量法分别探讨模型的性能指标对参数变化的响应程度。结果表明:校验阶段汛期与非汛期Nash确定性系数(Nash-Sutcliffe efficiency, NSE)分别为0.929和0.863,表明拟合程度较高;参数敏感性分析对于提高abcd模型参数率定的效率和精度具有显著意义;单变量法与多变量法结果相近,NSE对参数c最为敏感。通过对比径流模拟值与实测值,得出该模型模拟精度高、具有较高的适应性,能够广泛应用于我国中小流域。     

基于LH-OAT与变异系数法的汇流模型参数敏感性分析

为分析汇流模型参数对洪水模拟效果的影响,提高模型参数率定的精确性,以山西省洪水预报系统中的纳什瞬时单位线汇流模型为研究对象,运用LH-OAT法对汇流模型参数进行定向改变,分析确定汇流模型参数在不同等级洪水、不同流域、不同目标函数中的敏感性,再基于变异系数法确定汇流模型参数综合敏感性系数。研究表明,纳什瞬时单位线汇流模型参数敏感性会随着洪水等级、流域特征、目标函数的不同而改变,且汇流模型参数的敏感性仅与目标函数洪峰误差PE、洪峰流量Q_(mi)有关,与其他的目标函数无关;C_1与C_2这2个汇流模型参数综合敏感性系数分别为0.58、0.42,均为敏感性参数,且C_2的敏感性大于C_1。     

基于 SWAT 模型的北山水库流域地表径流模拟

为评价北山水库流域地表水资源,选用SWAT软件构建了该流域的分布式水文模型。基于2016-2018年实测水文数据以及高程、土地利用类型、土壤类型等数据,完成了对北山水库流域的SWAT模型构建,利用SWATCUP软件对参数进行率定及敏感性分析,选取决定系数(R~2)、纳什效率系数(NSE)、平均相对误差绝对值(MARE)和均方根误差(RMSE)作为模型评价指标。结果表明:北山水库月蓄水量模拟值与实测值吻合良好,模型率定期和验证期的R~2均达到0.89,NSE分别达到0.88与0.85,MARE分别为5.04%与4.23%,RMSE分别为1.15×10~6 m~3与0.90×10~6 m~3,由此表明该模型能近似反映研究区的径流变化特征,展示了SWAT模型在该流域的适用性。此外,基于验证的水文模型对主要参数进行敏感性分析,表明影响该区径流模拟最为显著的两个参数是浅层地下水回归流阈值和径流曲线数。     

基于统计仿真和数据同化的流域水文过程模拟

针对模型参数率定计算负荷量和优化性能问题,以沙河流域为研究区域,基于分布式时变增益水文模型,通过PSUADE平台提供的响应曲面参数优化方法,结合误差纠偏的集合卡尔曼滤波数据同化算法,实现水文模拟的综合优化。利用流域出口流量观测作为验证数据,以纳西效率系数和水量平衡系数及其综合函数作为评价目标,借鉴响应曲面方法生成水文模型的统计仿真代理模型,对模型参数进行敏感性分析并缩小取值范围,利用全局优化方法实现参数率定。基于遥感蒸散发观测、借助集合卡尔曼滤波算法,进行水文模型的数据同化,实现流域径流过程模拟的有效校正。结果显示:借助统计仿真方法降低了参数率定的计算消耗;利用数据同化调整了模型模拟的轨迹,验证期水量平衡系数、纳西效率系数、综合评价指标分别达到1.102、0.798、0.152,整体径流模拟效果较好,蒸散发模拟结果同样得到改善。     

基于ArcSWAT2009的锦江流域径流模拟分析

基于ArcGis10.0建立了锦江流域数据库,将ArcSWAT2009模型应用于锦江流域的径流模拟。采用LH-OAT灵敏度分析方法进行参数灵敏度分析,得出模型灵敏参数序列,并利用4个水文站(危坊、宜丰、上高、高安)2001~2008年径流观测数据对SWAT模型进行参数率定。模型适用性评价结果表明:校准期和验证期年均值相对误差(Re)小于20%,月相关系数(R2)和月效率系数(NSE)均大于0.7,拟合精度较高,SWAT模型适宜锦江流域的径流模拟。     

系统微分响应参数率定方法在建阳流域SWAT模型中的应用

利用基于系统微分响应理论的参数率定方法率定闽江建阳流域SWAT模型,通过流域1992—2000年日资料验证了该方法的实际应用效果,采用纳什效率系数(NSE)、偏差百分比(PBIAS)和相关系数r作为评价指标对率定后的SWAT模型模拟精度进行评价,并与传统利用SUFI-2方法率定得到的SWAT模型模拟结果进行对比分析。结果表明：系统微分响应方法率定的参数在建阳流域的日径流模拟中表现较好,率定期和检验期NSE均为0.65以上,径流量PBIAS在5%以内,r在0.65以上;利用系统微分响应率定参数方法率定SWAT模型参数在实际应用中可行,且效率与精度均高于传统的SUFI-2方法。     

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.     

Parameters Optimization using Fuzzy Rule Based Multi-Objective Genetic Algorithm for an Event Based Rainfall-Runoff Model

The calibration of an event based rainfall-runoff model for steam flow forecasting is challenging because, it is difficult to measure the parameters physically on the field for each rainfall event. In the present study, Fuzzy rule based Multi-objective Genetic Algorithm (MGA) is developed to optimize the infiltration and roughness parameters of an event based rainfall-runoff model. Nash Sutcliffe Efficiency (NSE), Coefficient of Determination (R²) and transformed volume difference (f(V)) are used as the objective functions of the MGA and all Pareto optimal solutions are identified using Nondominated Sorting method. As three objective functions are included in the calibration, the number of Pareto optimal solutions are also increases and hence, the optimization problem now becomes a decision making problem. Therefore, to select the best solution from all Pareto optimal solutions, a Fuzzy Rule-Based Model (FRBM) is developed to get alternative values of each Pareto optimal solution. First, the Fuzzy rule based MGA is developed by integrating the FRBM with the MGA. Then the Fuzzy rule based MGA is integrated with an event based runoff model. The developed Fuzzy-MGA based runoff model is tested on three different watersheds and the simulation results of Fuzzy-MGA based runoff model are compared with observed data and previous study results. From the simulated events of three watersheds using Fuzzy-MGA based runoff model, it is observed that the mean percentage error in any criteria (i.e. volume of runoff, peak runoff, and time to peak) of the developed model for a watershed is less than 16.33%. It is also noted that the developed Fuzzy-MGA based runoff model is able to produce hydrographs that are much closer to the measured hydrographs.     

基于相似流域法的SWAT模型模拟黄河中游无资料地区径流

选用黄河中游两个小流域,基于相似流域法探求分布式水文模型SWAT在黄河中游小流域无资料地区径流模拟的适用性。通过距离、流域面积相近及属性相似的方法,用已知流域率定参数移植到无资料流域进行径流模拟。选取2009-2013年的日径流与月径流进行模型率定,以效率系数(NS)和决定系数(R2)为评价指标,率定出4个模型敏感系数,并用2014-2016年的日径流与月径流进行模型验证。结果显示:率定期月径流模拟的R2为0. 76,NS为0. 70;日径流模拟的R2为0. 70,NS为0. 64;验证期月径流模拟的R2为0. 82,NS为0. 74;日径流模拟的R2为0. 78,NS为0. 68。说明基于相似流域法的SWAT模型对于无资料的小流域月径流量模拟具有很好的适用性。     

The Influence of Conceptual Flow Simulation Model Parameters on Model Solution

This article investigates the influence of conceptual flow simulation model parameters (i.e coefficients and constants that need to be estimated in calibration) on model solution (surface runoff) to understand the characteristics of the model. A new conceptual watershed yield model (WYM) was employed. There are four physical parameters, two fitting coefficients and two initial estimates of the surface water and groundwater storagesthat control the functioning of the model. The conceptual model was applied on Ling River near Kahuta and detailed sensitivity analysis was performed to explore the most sensitive model parameters. The most sensitive model parameters worked out were C _g (a fitting coefficient, which reflects the rate at whichgroundwater runoff occurs), w _r (watershed retention is the initial rainfall losses before runoff begins), p _gr (inputparameter that reflects the discharge capacity of the groundwateraquifer). The model parameters like i _c (infiltration coefficient), g _wsm (input parameter that depends on the subsurface storage available in the watershed) and e _p (input parameter) have negligible effect on model solution. It was observed that w _r (watershed retention) is the only surface runoff controlling parameter and p _gr and C _g are the groundwater runoff controlling parameters.     

Transferability of Conceptual Hydrological Models Across Temporal Resolutions: Approach and Application

The temporal resolution of observed data is a critical element in determining the parameters, prediction performance, and applicability of hydrological models. In this study, runoff simulations were performed at different temporal resolutions using the Xinanjiang model to evaluate the influence of temporal resolution on the model parameters and performance. Based on the sensitivity analysis of the model parameters, the posterior distribution of the sensitive parameters was derived using the Bayesian method and Differential Evolution Adaptive Metropolis (DREAM) algorithm at different temporal resolutions. The transformation functions of the model parameters were put forward to transform the parameters according to the regulatory between the parameters and time-steps on the basis of the parameters posterior distribution. The model performance and uncertainty for runoff simulation were compared and discussed at each temporal resolution. The results show that (1) the parameters related with the process of the water balance and runoff routing are identified as sensitive to the temporal resolutions, and there exist linear or power function relationships between parameter values at different temporal resolutions; and (2) the quantitative relationship equations have been verified to have good capacity for model simulation when the model parameters are transformed from other temporal resolution.     

广州天河智慧城SWMM参数敏感性分析

为研究城市雨水模拟中参数对SWMM模拟结果的影响,构建了广州天河智慧城SWMM水文模型,开展降雨径流水量水质同步监测,对模型参数进行率定与验证,并使用Morris方法分析水文水力参数和水质参数的敏感性。结果表明:水文水力参数中最大下渗速率对总径流量敏感性最高,地表曼宁系数对峰值流量敏感性最高,下渗参数为影响水文水力模拟结果的主要参数;水质参数中冲刷指数对污染物模拟结果敏感性最高,前期干旱天数对污染物模拟结果敏感性比总径流量模拟的敏感性高。     

Separation of the Impact of Landuse/Landcover Change and Climate Change on Runoff in the Upstream Area of the Yangtze River,China

Landuse/landcover change (LULCC) and climate change (CC) impacts on streamflow in high elevated catchments are very important for sustainable management of water resources and ecological developments. In this research, a statistical technique was used in combination with the Soil and Water Assessment Tool (SWAT) to the Upstream Area of the Yangtze River (UAYR). Different performance criteria (e.g., R², NSE, and PBIAS) were used to evaluate the acceptability of the model simulation results. The model provided satisfactory results for monthly simulations in the calibration (R²; 0.80, NSE; 0.78 and PBIAS; 22.3%) and the validation period (R²; 0.89, NSE; 0.75 and PBIAS; 19.1%). Major landuse/landcover transformations from 1990 to 2005 have occurred from low grassland to medium grassland (2%) and wetlands (0.9%), bare land to medium grassland (0.2%), glaciers to wetland (16.8%), and high grassland to medium grassland (5.8%). The results show that there is an increase in average annual runoff at the Zhimenda station in UAYR by 15 mm of, which approximately 98% is caused by climate change and only 2% by landuse/landcover change. The changes evapotranspiration are larger due to climate change as compared to landuse/landcover change, particularly from August to October. Precipitation and temperature have increased during these months. On the contrary, there has been a decrease in evapotranspiration and runoff from October to March which depicts the intra-annual variations in the vegetation in the study area.