Analysis of dynamic wave model for flood routing in natural rivers

Flooding is a common natural disaster that causes enormous economic, social, and human losses. Of various flood routing methods, the dynamic wave model is one of the best approaches for the prediction of the characteristics of floods during their propagations in natural rivers because all of the terms of the momentum equation are considered in the model. However, no significant research has been conducted on how the model sensitivity affects the accuracy of the downstream hydrograph. In this study, a comprehensive analysis of the input parameters of the dynamic wave model was performed through field applications in natural rivers and routing experiments in artificial channels using the graphical multi-parametric sensitivity analysis (GMPSA). The results indicate that the effects of input parameter errors on the output results are more significant in special situations, such as lower values of Manning’s roughness coefficient and/or a steeper bed slope on the characteristics of a design hydrograph, larger values of the skewness factor and/or time to peak on the channel characteristics, larger values of Manning’s roughness coefficient and/or the bed slope on the space step, and lower values of Manning’s roughness coefficient and/or a steeper bed slope on the time step and weighting factor.     

Rainfall-runoff simulation and flood forecasting for Huaihe Basin

The main purpose of this study was to forecast the inflow to Hongze Lake using the Xin＇anjiang rainfall-runoff model. The upper area of Hongze Lake in the Huaihe Basin was divided into 23 sub-basins, including the surface of Hongze Lake. The influence of reservoirs and gates on flood forecasting was considered in a practical and simple way. With a one-day time step, the linear and non-linear Muskingum method was used for channel flood routing, and the least-square regression model was used for real-time correction in flood forecasting. Representative historical data were collected for the model calibration. The hydrological model parameters for each sub-basin were calibrated individually, so the parameters of the Xin＇anjiang model were different for different sub-basins. This flood forecasting system was used in the real-time simulation of the large flood in 2005 and the results are satisfactory when compared with measured data from the flood.     

Test of newly developed conceptual hydrological model for simulation of rain-on-snow events in forested watershed

A conceptual hydrological model that links the Xin’anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating rain-on-snow events that commonly occur in the Pacific Northwest of the United States. The resultant model was applied to the Lookout Creek Watershed in the H. J. Andrews Experimental Forest in the western Cascade Mountains of Oregon, and its ability to simulate streamflow was evaluated. The simulation was conducted at 24-hour and one-hour time scales for the period of 1996 to 2005. The results indicated that runoff and peak discharge could be underestimated if snowpack accumulation and snowmelt under rain-on-snow conditions were not taken into account. The average deterministic coefficient of the hourly model in streamflow simulation in the calibration stage was 0.837, which was significantly improved over the value of 0.762 when the Xin’anjiang model was used alone. Good simulation performance of the XINSNOBAL model in the WS10 catchment, using the calibrated parameter of the Lookout Creek Watershed for proxy-basin testing, demonstrates that transplanting model parameters between similar watersheds can provide a useful tool for discharge forecasting in ungauged basins.     

θ-improved limited tolerance relation model of incomplete information system for evaluation of water conservancy project management modernization

The modernization of water conservancy project management is a complicated engineering system involving a management system, a management method, management personnel, the exertion of social, economic, and ecological effects, and so on. However, indices for evaluating the modernization of water conservancy project management are usually unobtainable in practical applications. Conducting appropriate extension of the classical rough set theory and then applying it to an incomplete information system are the key to the application of the rough set theory Based on analysis of some extended rough set models in incomplete information systems, a rough set model based on the θ-improved limited tolerance relation is put forward. At the same time, upper approximation and lower approximation are defined under this improved relation. According to the evaluation index system and management practices, the threshold for θ is defined. An example study indicates the practicability and maneuverability of the model.     

Parameter estimation in channel network flow simulation

Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the parameter calibration workload is substantial and a high level of uncertainty in estimated roughness cannot be avoided. In this study, all the individual channel segments are graded according to the factors determining the value of roughness. It is assumed that channel segments with the same grade have the same value of roughness. Based on observed hydrological data, an optimal model for roughness estimation is built. The procedure of solving the optimal problem using the optimal model is described. In a test of its efficacy, this estimation method was applied successfully in the simulation of tidal water flow in a large complicated channel network in the lower reach of the Yangtze River in China.     

Risk analysis of slope instability of levees under river sand mining conditions

Levees are affected by over-exploitation of river sand and river adjustments after the formation of sand pits. The slope stability is seriously threatened, drawing wide concern among experts and scholars in the area of water conservancy. This study analyzed the uncertainties of slope stability of levees under river sand mining conditions, including uncertainty caused by interest- driven over-exploitation by sand mining contractors, and uncertainty of the distance from the slope or sand pit to the bottom of the levee under the action of cross-flow force after the sand pit forms. Based on the results of uncertainty analysis, the distribution and related parameters of these uncertainties were estimated according to the Yangtze River sand mining practice. A risk model of the slope instability of a levee under river sand mining conditions was built, and the possibility of slope instability under different slope gradients in a certain reach of the Yangtze River was calculated with the Monte Carlo method and probability combination method. The results indicated that the probability of instability risk rose from 2.38% to 4.74% as the pits came into being.     

Impact of climate change on hydropower generation in Rio Jubones Basin,Ecuador

This study attempted to use the soil and water assessment tool(SWAT), integrated with geographic information systems(GIS), for assessment of climate change impacts on hydropower generation. This methodology of climate change impact modeling was developed and demonstrated through application to a hydropower plant in the Rio Jubones Basin in Ecuador. ArcSWAT 2012 was used to develop a model for simulating the river flow. The model parameters were calibrated and validated on a monthly scale with respect to the hydro-meteorological inputs observed from 1985 to 1991 and from 1992 to 1998, respectively. Statistical analyses produced Nash-Sutcliffe efficiencies(NSEs) of 0.66 and 0.61 for model calibration and validation, respectively, which were considered acceptable. Numerical simulation with the model indicated that climate change could alter the seasonal flow regime of the basin, and the hydropower potential could change due to the changing climate in the future.Scenario analysis indicates that, though the hydropower generation will increase in the wet season, the plant will face a significant power shortage during the dry season, up to 13.14% from the reference scenario, as a consequence of a 17% reduction of streamflow under an assumption of a 2.9℃ increase in temperature and a 15% decrease in rainfall. Overall, this study showed that hydrological processes are realistically modeled with SWAT and the model can be a useful tool for predicting the impact of climate change.     

THE SIMILAR STRUCTURE OF SOLUTIONS IN FRACTAL MUITILAYER RESERVOIR INCLUDING A QUADRATIC GRADIENT TERM

When the classical nonlinear partial differential equations are used to model the fractal reservoir, based on the assumption of low compressibility fluids, the effects of the quadratic gradient term are ignored, which would be questionable for mixed gas reservoirs and low permeability reservoirs. To consider the influence of the wellbore storage, the nonlinear mathematical flow model of the fractal multilayer reservoir is built in this paper, with three kinds of outer boundaries (infinite boundaries, constant pressure boundaries and closed boundaries). Using the Laplace transform method, the solutions for the dimensionless reservoir pressure and the bottom hole pressure in the Laplace space are obtained. An analysis shows that the solutions involve similar structures even for three different kinds of outer boundaries, and can be unified as a continuous fraction. The unified expression would make it more convenient to analyze the formation parameters, which greatly facilitates the development of the well test analysis software.     

Hydraulic metal structure health diagnosis based on data mining technology

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.     

水文模型参数敏感性分析方法评述

针对水文模型敏感性分析中存在的诸多问题,分析水文模型参数敏感性分析在模型构建及应用过程中的主要作用及其与不确定性分析和参数优化之间的联系,总结敏感性分析方法的3种分类,并探讨水文模型中常用的筛选法、回归分析法、基于方差的分析方法及基于代理模型技术的分析方法等4种关键技术方法,剖析水文模型参数敏感性分析方法的适用条件及优缺点,回顾各种方法在水文模型中的研究现状,提出水文模型参数敏感性分析的研究框架与步骤,指出水文模型参数敏感性分析的计算效率、可靠性和参数的相关性是未来的主要研究方向。     

一种SWAT模型参数识别的改进方法

参数的敏感性分析和不确定性分析是分布式水文模型构建的先决条件。在辽河流域建立SWAT模型,利用SWAT-CUP中的SUFI-2算法进行参数的率定,在此基础上提出一种更为简便的参数识别方法。将研究区域辽河干流的主要支流分别进行参数识别,再将SWAT-CUP中率定的最佳参数的从TXINOUT文件中提取出来,分别覆盖到SWAT模型中各对应支流子流域的TXINOUT文件中,即可得到按主要支流经过参数识别后的SWAT模型,避免了SWAT-CUP调参工具涉及众多子流域导致参数识别过于复杂的问题。结果表明,辽河干流主要支流招苏台河、清河、柴河等子流域主要水文断面率定期的平均纳什效率系数分别为0.60、0.65、0.68,验证期分别为0.60、0.72、0.77,参数率定的结果相对于全局调参有较大的改进。采用本文提出的参数识别方法,可以解决SWAT-CUP全局调参时上下游断面结果难以同时匹配或伪匹配的问题,又可以避免分区参数识别时对不同子流域的土地利用类型、土壤类型以及坡度等参数的繁琐设定,同时降低了SWAT模型手动调参的复杂程度,可较好地应用到SWAT模型参数识别过程中。     

基于LH-OAT分布式水文模型参数敏感性分析

为了有效进行分布式水文模型参数的优选,消除模型计算过程中的不确定性,更好地理解参数对水文模拟的影响,开展了模型参数敏感性分析。使用LH-OAT方法,对比分析了3个不同的流域中多个目标函数下的分布式物理水文模型——流溪河模型的参数敏感性,将其参数敏感性归为：极敏感,敏感,一般敏感和不敏感4类。研究表明,模型参数的敏感性并不是一成不变的,在不同流域,不同评价目标下,会发生一定程度的改变。     

Toward Improved Calibration of SWAT Using Season-Based Multi-Objective Optimization: a Case Study in the Jinjiang Basin in Southeastern China

Calibration is an important step in most hydrological modeling processes because it helps produce reasonable results. This study aims to investigate the seasonal sensitivity of streamflow parameters and to evaluate the ability of a season-based multi-objective approach to calibrate the Soil and Water Assessment Tool (SWAT) model. The primary goal was achieved through an integrated approach. A variance-based global sensitivity technique, Sobol’ method, was used to evaluate the seasonal sensitivity of streamflow parameters. For the multi-objective approach, three objective functions were considered: the Nash–Sutcliffe efficiency, Nash–Sutcliffe efficiency of logarithmic transformed discharge, and relative bias. The model performances of the season-based multi-objective approach MOO(II), based on these functions and flow duration curves during wet and dry seasons, were compared to three other methods: SOO(I), a conventional single-objective approach to the entire series; SOO(II), a season-based single-objective approach; and MOO(I), a multi-objective approach for the entire series. The four methods were assessed using the SWAT model to predict daily discharge in the Jinjiang basin in southeastern China. The results showed that sensitivity of model parameters varied between the wet and dry seasons. The seasonal calibration approaches, MOO(II) and SOO(II), showed significantly better simulation performances during the dry season while the multi-objective approaches produced more accurate simulations of different aspects of the hydrograph, including peak and low flows and overall water balance, compared to the single-objective methods. MOO(II) captured the seasonal variation of hydrological processes best, compared to the other methods, and the parameter values it identified demonstrated significant seasonal variations.     

Predictive Analysis and Simulation Uncertainty of a Distributed Hydrological Model

Distributed hydrological models should pass through a careful calibration procedure backed by sensitivity, uncertainty and predictive analysis before they are utilized as a decision making aid in watershed management and scenario studies. This paper examines whether the uncertainty of the parameters of the spatially distributed hydrologic model WetSpa causes significant uncertainty in the model predictions. The WetSpa model is applied to the Torysa river basin, a rather large catchment located in Slovakia. Parameter estimation, sensitivity and predictive analysis of the model parameters are performed using a model-independent parameter estimator, PEST. It is found that the correction factor for measured evaporation data has the highest relative sensitivity. Parameter uncertainty and predictive analysis give an insight of a proper parameter set and parameter uncertainty intervals and prove that the parameter uncertainty of the model does not result in a significant level of predictive uncertainty.     

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。     

GIS-based applications of sensitivity analysis for sewer models

Sensitivity analysis (SA) evaluates the impact of changes in model parameters on model predictions. Such an analysis is commonly used when developing or applying environmental models to improve the understanding of underlying system behaviours and the impact and interactions of model parameters. The novelty of this paper is a geo-referenced visualization of sensitivity indices for model parameters in a combined sewer model using geographic information system (GIS) software. The result is a collection of maps for each analysis, where sensitivity indices (calculated for model parameters of interest) are illustrated according to a predefined symbology. In this paper, four types of maps (an uncertainty map, calibration map, vulnerability map, and design map) are created for an example case study. This article highlights the advantages and limitations of GIS-based SA of sewer models. The conclusion shows that for all analyzed applications, GIS-based SA is useful for analyzing, discussing and interpreting the model parameter sensitivity and its spatial dimension. The method can lead to a comprehensive view of the sewer system.     

目标函数对滦河流域SWAT模型径流模拟不确定性的影响

针对水文模型参数和径流模拟结果不确定性问题,选取2Nash-Sutcliffe效率系数(NSE)、改进的决定系数(R_m²)、相对误差(PBIAS)、Kling-Gupta效率系数(KGE)4种目标函数,对构建的滦河流域潘家口水库上游SWAT模型进行参数率定及验证,分析了不同目标函数下模型参数的敏感性差异及径流模拟的不确定性。结果表明：参数敏感性会随迭代次数增加和抽样范围变化发生改变,不同目标函数下率定的参数范围和最优值显著不同;NSE和KGE作为目标函数在各站点径流模拟中更稳健,分别表现出较高的模拟精度和较低的模拟不确定性。     

基于信息熵对新安江水文模型参数及预报结果不确定性的量化分析

将GLUE方法与信息熵结合,分析新安江水文模型参数及预报结果的不确定性。首先用信息熵公式初步判断参数的敏感程度,根据GLUE方法求出90％置信度下流量的不确定范围;其次应用信息熵和U不确定公式共同量化分析模型预报结果的不确定性。以资水水系的新宁站集水区为研究区域,得出结论：①GLUE方法能够用来分析新安江水文模型参数的不确定性;②信息熵公式能够初步判断模型参数的敏感程度;③模型预报结果的不确定性随着实测资料的增加而降低。     

基于GPU加速的水文模型参数率定

针对水文模型参数率定问题,为显著提升计算效率,选择SCE-UA算法和新安江模型为研究对象,围绕SCE-UA算法并行化与程序化实现、并行SCE-UA算法在图形处理器(GPU)上的加速效果这两个关键科学问题,以GPU硬件平台和通用计算设备架构(CUDA)软件平台为工具,采用时空复杂度分析、算法并行性挖掘、代码深度优化、数值模拟实验等多种手段相结合的方法,进行了水文模型参数率定提速研究。内容包括:①搭建基于CUDA和GPU的并行计算软硬件平台,进行配置与调优;②并行SCE-UA算法及其程序化实现;③并行SCE-UA算法在GPU上的加速效果。研究结果表明:所提出的方法显著提升了参数率定效率,能够促进水文模拟、最优化方法、计算机科学与技术等多学科的交叉、融合与发展,对水文模拟与预报、防洪快速应急响应具有科学意义和实用价值。