Impact of Normalization and Input on ARMAX-ANN Model Performance in Suspended Sediment Load Prediction

The suspended sediment load in rivers is an important parameter in watershed planning and management. Since daily suspended sediment time series contain linear and nonlinear components, existing prediction models are associated with limitations. Therefore, this study introduces a new hybrid model comprising two commonly used stochastic and nonlinear models. The sediment load is first modeled by an autoregressive-moving average with exogenous terms (ARMAX) model. Subsequently, the ARMAX residuals are modeled with an artificial neural network (ANN). For this purpose, discharge (Q) and sediment (S) are considered as model input parameters. Three modeling scenarios are defined to investigate the impact of data normalization on the hybrid model. The exponential and Box-Cox transformation methods are combined into a new data normalization method called mixed transformation. The performance of these methods is then compared. In addition, the impact of the type and number of input combinations on ARMAX-ANN model accuracy is evaluated. To this end, 12 input combinations and 1331 ARMAX and ANN models are verified. The ARMAX model inputs include S, Q and the white noise disturbance term (e), while the ANN model inputs include the ARMAX model results and residuals. Moreover, the hybrid model’s accuracy is compared with the ARMAX and ANN models.     

新疆尼雅河悬移质泥沙分析

尼雅河是新疆和田地区民丰县境内的主要河流,文章采用3个水文站的实测资料对尼雅河悬移质含沙量和输沙量的年内及年际变化进行分析。结果表明,河流含沙量年内分配与径流同时集中在春季和夏季,含沙量分布与径流相一致,最大年与最小年含沙量极值变化较大;泥沙输移与径流的变化关系密切,输沙量季节变化极大。     

Principle Component Analysis in Conjuction with Data Driven Methods for Sediment Load Prediction

This study investigates sediment load prediction and generalization from laboratory scale to field scale using principle component analysis (PCA) in conjunction with data driven methods of artificial neural networks (ANNs) and genetic algorithms (GAs). Five main dimensionless parameters for total load are identified by using PCA. These parameters are used in the input vector of ANN for predicting total sediment loads. In addition, nonlinear equations are constructed, based upon the same identified dimensionless parameters. The optimal values of exponents and constants of the equations are obtained by the GA method. The performance of the so-developed ANN and GA based methods is evaluated using laboratory and field data. Results show that the expert methods (ANN and GA), calibrated with laboratory data, are capable of predicting total sediment load in field, thus showing their transferability. In addition, this study shows that the expert methods are not transferable for suspended load, perhaps due to insufficient laboratory data. Yet, these methods are able to predict suspended load in field, when trained with respective field data.     

Regional Flood Frequency Analysis Using L-Moments for the West Mediterranean Region of Turkey

The aim of this study is to investigate and determine hydrologically homogeneous regions and to derive regional flood frequency estimates for 47 gauged sites in the West Mediterranean River Basins in Turkey, using an index flood method with L-moments parameter estimation. Screening of the data of the gauged site is carried out based on a discordancy measure in terms of the L-moments. Initial candidate regions are established by the cluster analysis of first five L-moment statistics, using k-means method. Homogeneity of the basins is tested using simulation with a four-parameter Kappa distribution and an L-moments based heterogeneity measure. Three subregions are defined, namely the Antalya subregion, the Lower West Mediterranean subregion, and the Upper West Mediterranean subregion. Comparative regional flood frequency estimates are made for each subregion using various distributions, namely the generalized logistic, general extreme value, generalized normal, Pearson type III, generalized Pareto, kappa, and Wakeby distributions. Based on an L-moments goodness-of-fit statistic, the Pearson type III distribution is identified as the best-fit distribution for the Antalya and Lower-West Mediterranean subregions, and the Generalized Logistic for the Upper-West Mediterranean subregion. Monte Carlo simulation is used to evaluate the accuracy of the quantile estimates on the basis of the relative root-mean-square error and relative bias.     

黄河下游悬浮颗粒物和沉积物对磷的吸附

选取黄河口、济南及花园口3个断面,在其沉积物表层5 cm处取样,进行了吸光度和吸附量试验,研究了黄河下游悬浮物和沉积物对磷的吸附作用.结果表明:①黄河下游对磷的吸附等温线数据符合Langmuir方程,临界平衡磷浓度为0.005～0.08mg/L;②pH值对沉积物磷吸附有影响,当pH=3~5时为慢吸附(包括负吸附),当pH=5～9时为稳定区,当pH=9~11时为快吸附;③沉积物中磷的吸附量随盐度升高逐渐降低,解吸量随盐度升高而逐渐增加.     

Uncertainty Analysis in Sediment Load Modeling Using ANN and SWAT Model

Sediment load estimation is essential in many water resources projects. In this study, the capability of two different types of model including SWAT as a process-based model and ANNs as a data-driven model in simulating sediment load were evaluated. The issue of uncertainty in the simulated outputs of the two models which stems from different sources was also investigated. Calibration and uncertainty analysis of SWAT were performed using monthly observed discharge and sediment load values and through the application of SUFI-2 procedure. The issue of uncertainty in the ANN model was also accounted for by training a network several times with different initial weights and bias values as well as randomly-selected training and validation sets, each time a network trained. Trying different input variables to find the best and most efficient network structure, it was found that in the forested watershed of Kasilian, adding average daily rainfall or previous values of discharge dose not change the performance of the ANN model significantly. Comparing the results of SWAT and ANN, it was found that SWAT model has a superior performance in estimating high values of sediment load, whereas ANN model estimated low and medium values more accurately. Moreover, prediction interval for the results of ANN was narrower than that of SWAT which suggests that ANN outputs are with less uncertainty.     

珠江三角洲河网悬沙数学模型分析

物理模型对于复杂多变的河网河道的水力因素变化不易描述,数学模型已成为研究其河道水力、泥沙问题的重要手段。在线性化的Pressmann四点隐式差分法基础上,应用汊点分组思想求解河网流场,采用节点悬沙控制方法对珠江三角洲河网悬沙进行了数值模拟,利用实测资料对模型进行率定与验证,并分析了珠江三角洲流域河网悬沙输移特征。结果表明,数值模拟结果真实、可靠,与实测资料基本吻合,从而再次证明珠江三角洲河网是以径流输沙为主的平原河网。建立悬沙节点控制方法进行河网悬沙的数值模拟,实现了泥沙方程组的分级解法,提高了计算效率与精度。     

悬移质模型沙级配的模拟计算方法探讨

对于研究泥沙问题的动床模型试验，模型沙的选择是模型设计的关键。模型沙的选择是指综合考虑所研究问题的性质，已知条件，模型几何比尺，以满足模型与原型的水沙运动相似为目的，选定，设计模型沙的材料，比重和粒径级配，作者主要阐述悬移质模型沙级配的模拟方法，并提出利用沙玉清公式计算，设计模型沙级配的另一种方法，以尽可能严格满足模型相似条件。克服老方法的不足和缺陷。     

云南省三江干流水电开发与区域经济

云南省水力资源丰富,经济可开发量为97950MW,居全国第二。大型水电站主要分布在金沙江、澜沧江和怒江干流上,占全省经济可开发量的86%;三江干流涉及了云南省大部分地区,涉及人口占全省总人口的77.45%,国内生产总值占全省的76.37%。三江干流上大型电站的开发,将对全省经济发展有着极其重要的影响,可促进区域第三产业、运输业及与水电相关行业的发展。只有开发三江干流上的水电站才能加快培育云南省以水电为主的电力支柱产业,逐步形成"西电东送"和"云电外送"的能源基地。三江干流的开发必将对云南省实现国内生产总值翻两番及全面建设小康社会和受电区域的经济发展作出重要贡献。     

渭河下游悬移质全沙水流挟沙力公式研究

为寻求有效的渭河下游水流挟沙力公式,参考相关研究成果,依据渭河下游275组实测近似冲淤平衡洪水的水力泥沙资料,对挟沙力判数、浑水相对黏度系数、浑水阻力系数、浑水中泥沙有效重度的倒数、浑水卡门常数这5个挟沙力影响因子之间的相关性进行了分析,发现浑水相对黏度系数与泥沙有效重度的倒数近乎直接相关,且这二者与浑水卡门常数有一定相关性;在5因子、4因子、3因子、2因子的各种组合模式与断面平均含沙量的拟合关系式中,相关性和精度均较好,而且自变量因子具独立性的是包含挟沙力判数和浑水相对黏度系数的2因子关系式,该关系式与张红武挟沙力公式进行的对比表明,二者的系数和指数略有出入;结合数学模型的计算要求,提出了直接代入浑水平均沉速并结合浑水相对黏度系数拟合式进行挟沙力试算,从而得到悬移质全沙挟沙力的计算方案。     

长江源区河流地貌及水沙特性

长江源区河网密布,多数河流仍处于自然演变过程中,河谷地貌保存完整。基于实地踏勘资料,结合 SRTM3 DEM 对长江源区部分河流河谷地貌及水沙特性进行了分析。研究河流涵盖长江北源楚玛尔河、正源沱沱河、南源当曲、干流通天河及支流布曲、尕尔曲。根据河谷形态及河流地貌,可将这些河段归纳为3类:高原冲积型、丘陵坦谷型和高山峡谷型。其中:高原冲积型河道平面多呈游荡或多股分汊;丘陵坦谷型河道平面呈单一或分汊态势;高山峡谷型河道则为单一河道。研究时段内,长江源3个源头中,当曲流量最大,沱沱河流量大于楚玛尔河;输沙量则表现为沱沱河最大、楚玛尔河其次,当曲最小。泥沙分析发现:平面呈游荡状态的河流,其泥沙特征与其他河型有明显不同,具有悬移质含沙量大、粒径粗且均匀,床沙粒径较细的特点。相关分析显示河道宽度与水流含沙量呈正相关关系,初步说明了游荡河型产生的原因。     

冲积河流堤线改线影响数学模型计算

为适应沿江城市发展，对冲积平原河流的河漫滩地进行了堤线改线。采用平面二维水流泥沙数学型进行堤线改线影响计算，模型考虑了悬移质及推移质泥沙运动，桥渡及料场的阻力变化，应用模型计算了赣江南昌河段喻家湾堤线改线工程前后的洪水水位壅高，断面流速分布变化，取土料场回淤情况，并对改线工程进行了评价。     

潮汐河口悬移质动床实物模型的理论与实践

河口泥沙一般较细，其河床变形多取决于悬移质的运动。文章论证了悬移、起动与河床变形相似为潮汐河口悬移质动床实物模型泥沙运动的主要相似条件，模型沙主要按悬移与起动相似条件选择；提出并介绍了采用轻质沙后挟沙相似的满足、时间变态的处理原则与经验；此外还讨论了模型选沙中的一些理论与技术问题。     

秃尾河 窟野河 孤山川产流输沙模型研究

依据秃尾河、窟野河、孤山川三条河流域降雨时空分布极不均匀及产流输沙多集中汛期的特点,将流域分为若干单元,以各单元面积内的时段最大降雨、雨强、地貌参数为影响产流输沙综合指标,最后叠加成总指标的方法,建立了产流输沙次和年经验模型。统计结果表明,模型计算与实测值相比,平均相对误差分别为:年清水模数0.69％～4.5％;年浑水模数0.2％～8.4％;年输沙模数0.05％～11.5％。     

一种区域地下水位预报的时间序列分析组合模型

根据地下水位动态变化的特征 ,建立提取水文趋势项的时间序列分析组合模型 ,并用逆函数法对地下水位进行预报。经典型实例验证 ,模型精度较高 ,具有一定的实用价值     

Suitability of the SWAT Model for Simulating Water Discharge and Sediment Load in a Karst Watershed of the Semiarid Mediterranean Basin

Water Resources Management - This paper presents a case study conducted in the Upper Argos River, in southeast Spain, to verify the applicability of the SWAT model for prediction of the water...     

对《悬移质变态动床模型试验中掺混相似条件的剖析》一文的商榷

根据对水流泥沙运动相似规律的一些认识，讨论了《对悬移质变态动床模型试验中掺混相似条件剖析》一文中论定悬沙水流相似中只存在一个相似条件等问题。指出原文在推导过程中存在的不合理假定后，循原文的途径导出了两个相似条件。认为相似条件λu*=λΩ不是不能成立，而是须满足条件λu*=λH^1/6才能成立，在物理上是须满足流速垂线分布相似。试验资料表明，在模型变率不是很大时，相似条件λu*=λΩ是可以应用的。     

天津蓟县泥石流区域预报模型

为了对天津蓟县泥石流区域进行预报,以天津蓟县部分乡镇作为研究区域,并进行网格自动划分,得到了网格的节点-单元-通道信息。通过分析泥石流形成条件选取了泥石流发生频率、24 h雨量、1 h雨量、地质岩性、平均坡度、植被覆盖类型、人口密度7个危险因子,并应用模糊赋权法计算各个危险因子权重,从而建立了泥石流区域预报模型,最后根据计算出的各个网格危险等级对2012年在蓟县双安地区发生的泥石流进行了模拟。结果表明:北部山区泥石流危险度R_d在0.4~0.8之间,属于中度、高度危度险区,双安泥石流灾害点处于高度危险区内,模拟结果与实际情况一致。由此可见该模型具有一定可靠性,可以用于天津蓟县北部山区泥石流的预报。     

长兴县平原河道回淤速度与成因的调查分析

河道清淤是一项环境效益明显、社会效益突出的民生工程.由于种种原因导致河道前面清后面淤,为了更好地掌握淤积情况,对河道的回淤速度和成因进行了调查分析,并提出了做好河道清淤工作的建议对策.