Multiplicative seasonal Arima model for longterm forecasting of inflows

This paper deals with stochastic modelling of monthly inflows into a reservoir system in the monsoon climatic coditions using a multiplicative seasonal ARIMA model based on 25 years of data with logarithmic transformation. The developed model was applied to forecast the monthly inflows for 27 years. The comparison of these forecasted flows with the actual flows reveals that the ARIMA family models are adequate for longterm forecasting of inflows. The parameter uncertainity was also evaluated and found to be minimal thus avoiding the frequent updating of the model for forecasting. The use of the model in evolving optimal cropping patterns and optimal operational policies is also highlighted.     

A Novel Hybrid Method for River Discharge Prediction

Accurate prediction of river discharge is essential for the planning and management of water resources. This study proposes a novel hybrid method named HD-SKA by integrating two decomposition techniques (termed as HD) with support vector regression (SVR), K-nearest neighbor (KNN) and ARIMA models (combined as SKA) respectively. Firstly, the proposed method utilizes local mean decomposition (LMD) to decompose the original river discharge series into sub-series. Next, ensemble empirical mode decomposition (EEMD) is employed to further decompose the LMD-based sub-series into intrinsic mode functions. Further, the EEMD decomposed components are used as inputs in three data-driven models to predict river discharge respectively. The prediction of all components is then aggregated to obtain the results of HD-SVR, HD-KNN and HD-ARIMA models. The final prediction is obtained by taking the average prediction of these models. The proposed method is illustrated using five rivers in Indus Basin System. In five case studies, six models were built to compare the performance of the proposed HD-SKA model. The data analysis results show that the HD-SKA model performs better than all other considered models. The Diebold-Mariano test confirms the superiority of the proposed HD-SKA model over ARIMA, SVR, KNN, EEMD-ARIMA, EEMD-KNN, and EEMD-SVR models.

     

ARIMA-SVR组合方法在水质预测中的应用

针对复杂水域水质变化机理难以掌握、水质预测建模困难且预测精度低的问题,将时间序列分析方法与机器学习方法引入水质预测领域,提出了基于差分自回归移动平均(ARIMA)与支持向量回归(SVR)组合模型的水质预测方法。数据经过预处理后先由ARIMA模型对其进行线性拟合,然后通过SVR模型预测残差以补偿其中的非线性变化。选择巢湖水域2004—2015年间的pH和溶解氧监测数据作为试验样本,通过Hodrick-Prescott(HP)滤波方法分析,结果表明2组数据具有不同的趋势特性和波动特性。根据精度评价指标对比分析模型的预测效果,结果表明组合模型预测精度显著提高,pH和溶解氧预测值与观测值间的相关系数均达到了0.99,均方根误差分别为0.20和0.61,平均绝对百分比误差分别为2.2%和6.6%。本研究所建立的组合预测方法具有较高的预测精度和较强的泛化能力,适用于复杂水域的水质预测。     

应用人工神经网络推算洪水流量的计算方法

天然河道洪水期的水位－流量关系，因受洪水涨落率和回水顶托等因素的影响，一般成为非线性绳套状曲线，洪水流量过程的计算往往根据大量实测水位，流量资料，采用定性判断和实践经验手工绘制水位与流量的时序列关系曲线，由水位过程插补求得。本文运用人工神经以向传播模型，引入与流量变化密切相关的水位，涨率，落差等因子，建立多因素相关的人工神经网络推流模型。     

黄河天桥水电站面流消能问题探讨

天桥水电站采用面流消能，原设计洪水标准为１００ａ一遇，经本次水工整体模型试验，对１００ａ一遇设计洪水、５００ａ一遇校核洪水和１９８９年实测洪水均作了定床和动床试验研究。成果显示，１００ａ一遇洪水和１９８９年洪水在建筑物下游可保持面流流态，无严重冲刷；５００ａ一遇校核洪水则出现底流，冲坑较深，应考虑采取工程措施以改善流态，降低单宽流量。     

Application of the Distributed Hydrological Model,TOPNET, to the Big Darby Creek Watershed,Ohio, USA

Evaluation of the applicability and utility of watershed hydrologic models in different hydro-geologic and soil conditions is necessary for a range of spatial scales and to assess the utility of these models as watershed water resources management tools. This study presents the application of the hydrological model TOPNET to the Big Darby Creek watershed, Ohio, United States. It focuses on the simulation modeling of stream flow in the watershed based on meteorological data for the eight year period of 1992–1999. Visual comparison of time series plots and statistical measures namely, Nash-Sutcliffe efficiency (NS), coefficient of correlation (R²), and the percent bias (PBIAS) were used to assess the model performance. The statistical model evaluation results indicated that the model has a relatively high confidence and can give a good representation of the flow hydrographs for the watershed. For the calibration period simulations of annual stream flow were accurate with a mean R² and NS of 86% and 85% for the Big Darby at Darbyville gaging station. For the little Darby at West Jefferson gaging station a mean R² of 81% was obtained while the NS averaged 78%. Further analysis based on the aggregation of the water years into wet seasons and dry seasons, the model was also able to adequately simulate stream flow for both gaging stations and for both low flow periods and high flow periods. Statistical analysis for the validation period also yielded high R² values of 88% and 83% for the Darby at Big Darby at Darbyville gaging station and Little Darby at West Jefferson gaging station respectively. The worst PBIAS obtained for both calibration and validation period was 18% and this is better than recommended values for satisfactory daily simulations of ±25% for PBIAS. The encouraging simulation results obtained in this study shows the utility and usefulness of the TOPNET model in hydrological modeling and ultimately as a water resources management tool.     

大单宽流量低傅汝德数收缩墩底流消力池的试验研究

为解决大单宽流量、低傅汝德数底流消能中存在振荡水跃,进而导致消力池内流态不稳定、水面波动大、消能率低等问题,采用模型试验的方法,对在消力池前设置收缩墩后的收缩扩散与底流复合消力池进行了研究。结果表明:设置Y型收缩墩后消力池内呈较为稳定的收缩射流与淹没水跃的三元复合流态,水流更为稳定,振荡水跃消失,可有效解决池内的水流间歇性振荡和水面大幅波动等问题。同时,设置收缩墩后,可有效降低池内最大临底流速,由近30 m/s降至约20 m/s。消能率由60.93%提升至66.61%,消能效果显著。此外,下游河道冲刷大大减小。最不利冲刷工况下的2年一遇洪水时,基岩最大冲深由近32.0 m降为5.6 m。消力池前设置收缩墩,对于因受地形地质等客观条件限制,无法通过改变池长池深来解决大单宽低傅汝德数的底流消能问题,提供了一种新思路。     

Multi-Objective Optimization for Flood Interval Prediction Based on Orthogonal Chaotic NSGA-II and Kernel Extreme Learning Machine

Deterministic flood prediction methods can only provide future point prediction results of the target variable. The intrinsic uncertainties and the fluctuation range of the prediction results cannot be evaluated. This study proposes a flood interval prediction method based on orthogonal chaotic non-dominated sorting genetic algorithm-II (OCNSGA-II) and kernel extreme learning machine (KELM) to estimate the uncertainty of the flood prediction results. The dual-output KELM model is exploited to predict the upper and lower bounds of the possible flood prediction result. The OCNSGA-II algorithm is employed to adjust the hidden layer output weights of the KELM model to minimize the prediction interval normalized average width (PINAW) and maximize the prediction interval coverage probability (PICP). The target variable with a disturbance of ±10% are taken as the initial upper and lower bounds. The superiority of the proposed method has been validated on one a real-world data set collected from the upper reaches of the Yangtze River in China. Results have shown that the proposed model can obtain prediction intervals with higher quality than the conventional single-objective interval prediction models and the other multi-objective benchmark models.

     

ARIMA与ANN组合预测模型在中长期径流预报中的应用

基于时间序列预测模型及BP神经网络,提出了新的组合预测方法.该方法采用三层结构的BP神经网络来构造组合预测模型,运用时间序列模型预测方法得出的预测结果,采用历史滚动法将前5年的预测结果数据作为BP网络的输入,以当前年份的预测结果为网络期望输入,建立了ARIMA-ANN组合预报模型.利用Matlab7神经网络工具箱对塔里木河上游源流卡群水文站的年径流量进行了预报及验证.结果表明:组合模型的预报结果精度高,容错能力强,是中长期径流预报的有效方法.     

基于时间序列模型的济南趵突泉地下水位预测

本文对2012年5月至2017年12月济南泉域趵突泉的地下水位波动规律进行了分析,并采用3种灰色时间序列模型,评价了保泉形势,通过模型的拟合效果检验可知:对于存在周期性波动趋势的地下水位观测值,GM(1,1)模型优势未能得到充分体现,ARIMA与Holt-Winters模型的预测结果较为接近,整体精度较高,表现出明显的预测优势。深入比选ARIMA与Holt-Winters模型的8项拟合优度指标,最终确定利用预测效果最优的Holt-Winters模型,从时间序列的角度对趵突泉地下水位进行分析,并预测2018—2019年趵突泉的年平均水位分别为27.734m和27.605m,泉水位波动的峰值为28.215 m,谷值将出现于2019年的6月份,数值仅为27.124m,逼近27.01m的泉水停喷线,为近7年来的最低水位。预测结果表明:现状降雨与开采条件下,2019年6月趵突泉将面临潜在的停喷的危机,保泉形势不容乐观。     

万州申明坝污水处理厂事故排放的影响分析

由于自然灾害和污水处理系统发生故障等原因,万州申明坝污水处理厂存在一定的事故排放可能性。通过对万州申明坝污水处理厂的厂址、设施进行调查,对其受纳水体苎溪河和入长江口的水质、水文进行实地监测,分析其事故排放的风险性。分别选用一维模型和二维模型对万州申明坝污水处理厂事故排放对苎溪河和长江水质的影响进行模拟分析,并引用涪陵污水处理厂排放口对长江影响的实测数据来验证所选模型,结果证实了模型的可行性:在长江175m水位,万州申明坝污水处理厂事故排放时污染带的长度是正常排放的20倍,宽度是正常排放的4倍;在长江145m水位,万州申明坝污水处理厂事故排放时污染带的长度是正常排放的3倍,宽度是正常排放的2倍。     

非均匀沙卵石推移质输移随机特性研究

使用天然尺度的实验室渠道观测了在恒定流的条件下非均匀卵石床面的推移质运动变化过程,采集到了更高精度、更长时间序列的输沙率变化过程,分析了输沙率统计变化对采样时间的依赖性。实测推移质输沙率的脉动现象十分剧烈,且当采样时间越小时,这种脉动现象越剧烈。来流为4300L/s,采样间隔分别为2、5与10min情况下,输沙率脉动值较平均值分别大约4.8倍、3.3倍与2.7倍;来流为5500L/s,采样间隔分别为2、5与10min情况下,输沙率脉动值较平均值分别大约3.2倍、2.1倍与1.9倍。卵石推移质单宽输沙率的离差系数、无量纲脉动强度以及无量纲极差值均随采样历时与无量纲希尔兹切应力的增大而减小。利用本次试验成果,通过多元线性回归得到的卵石推移质单宽输沙率的离差系数、无量纲脉动强度以及无量纲极差值与采样历时以及无量纲希尔兹切应力的关系式可为工程应用提供参考。     

Comparison of performance of statistical models in forecasting monthly streamflow of Kizil River,China

This paper presents the application of autoregressive integrated moving average(ARIMA),seasonal ARIMA(SARIMA),and Jordan-Elman artificial neural networks(ANN)models in forecasting the monthly streamflow of the Kizil River in Xinjiang,China.Two different types of monthly streamflow data(original and deseasonalized data)were used to develop time series and Jordan-Elman ANN models using previous flow conditions as predictors.The one-month-ahead forecasting performances of all models for the testing period(1998-2005)were compared using the average monthly flow data from the Kalabeili gaging station on the Kizil River.The Jordan-Elman ANN models,using previous flow conditions as inputs,resulted in no significant improvement over time series models in one-month-ahead forecasting.The results suggest that the simple time series models(ARIMA and SARIMA)can be used in one-month-ahead streamflow forecasting at the study site with a simple and explicit model structure and a model performance similar to the Jordan-Elman ANN models.     

Long-term effects of navigation dams on a segment of the upper Mississippi River

Navigation dams on the upper Mississippi River have altered the long-term relationship of river stage to river discharge. Analysis of the 34-year pre-dam and 74-year post-dam data sets indicated that the completion of Lock and Dam 19 in 1913 increased river width and volume behind the dam. The immediate impact was a higher mean river stage less influenced by changes in river discharge. The dam's long-term impact was to increase sedimentation causing a steady loss of both river width and volume that resulted in stage/discharge relationships approaching those of the pre-dam era. The present condition of higher mean river stage coupled with greater stage fluctuation is a major factor in the increased recurrence and duration of floods on the upper Mississippi River in recent decades.     

The Development of Rating Curve Considering Variance Function Using Pseudo-likelihood Estimation Method

This paper employs a new estimation method for estimating stage–discharge rating curve parameters. In typical practical applications, the original non-linear rating curve is transformed into a simple linear regression model by log-transforming the measurement without examining the effect of heteroscedasticity of residuals. Therefore, the model with pseudo-likelihood estimation is developed in this study to deal with heteroscedasticity of residuals in the original non-linear model. The parameters of rating curves and variance functions of errors are simultaneously estimated by the pseudo-likelihood estimation (P-LE) method. Also simulated annealing, a sort of global optimization techniques, is adapted to minimize the log likelihood of the weighted residuals. At first, the developed P-LE model was applied to a hypothetical site where stage–discharge data were generated by incorporating various errors for statistical test. Also, the limit of stages for segmentation is estimated in the process of P-LE using the Heaviside function. For the validation of effects of the developed P-LE model, the results of the conventional log-transformed linear regression (LT-LR) model and the P-LE model are estimated and compared. After statistical simulation, the developed P-LE model is then applied to the real data sets from six gauge stations in the Geum River basin. It can be suggested that this new estimation method is applied to real river sites to successfully determine the weights taking into account error distributions from observed discharge data.     

钱塘江斜坡式海塘遭遇超强台风渗流特性研究

钱塘江河口潮汐以非正规浅海半日潮为主,一日两涨两落,最高潮位主要受台风暴潮控制,当风暴潮来临时,会带来大量潮水入河口区,潮水位短时内升高较快。采用有限元方法模拟潮水骤升骤降状态对斜坡式海塘进行不稳定渗流分析。模型计算结果表明,采用有限元模型能够模拟海塘内浸润线随潮水的升降而适时的变化情况,与稳定渗流相比,其渗流浸润线前、后坡都较低。将50 a一遇设计潮位工况与超强台风工况下的非稳定渗流进行比对得出,相同的涨落潮时刻海塘后坡的浸润线基本相同。     

Streamflow and Hydrological Drought Trend Analysis and Forecasting in Cyprus

The persistent water shortage in Cyprus has been alleviated by importing freshwater from neighbouring countries, and severe droughts have been met with financial reimbursement from the EU at least twice. The goal of this research is to investigate and perform short-term forecasting of both streamflow and hydrological drought trends over the island. Eleven hydrometric stations with a 34-year common record length of the mean daily discharge from 10/1979 to 09/2013 are used for this purpose, with the relevant upstream catchments considered to represent pristine conditions. The Streamflow Drought Index (SDI) successfully captures the hydrological drought conditions over the island, and the performance of the index is validated based on both the historic drought archives and results from other drought indices for the island. The Mann–Kendall (M-K) test reveals that the annual and seasonal time series of the discharge volumes always illustrate a decreasing but insignificant trend at a significance level of a?=?0.05; additionally, the decrease per decade in the average annual streamflow volume based on Sen’s slope statistic is approximately ?9.4%. The M-K test on the SDI reveals that drought conditions intensified with time. Ten autoregressive integrated moving average (ARIMA) models are built and used to forecast the mean monthly streamflow values with moderate accuracy; the best ARIMA forecast model in each catchment is derived by comparing two model-performance statistical measures for the different (p,d,q) model parameters. The predicted discharge values are processed by the SDI-3 index, revealing that non-drought conditions are expected in most catchments in the upcoming three months, although mild-drought conditions are anticipated for catchments 7, 8 and 9.     

水力学模型试验两种参数的测量不确定度评定

将测量不确定度与水工模型试验结合起来,对水工模型试验测量中常见的2种检测参数(流量、流速)进行不确定度评定。评定结果表明:①对流量检测不确定度影响最大的参数是堰上水头,其次是堰宽、堰高。因此,在堰上水头的测量过程中应注意各操作步骤精度的控制,量水堰制作过程中应特别注意堰宽的控制。②对流速检测不确定度影响最大的是水体脉动及位置误差,由于水体脉动无法人为控制,因此应特别注意每次测量时测点位置的控制。     

非均匀沙卵石推移质输移随机特性研究

使用天然尺度的实验室渠道观测了在恒定流的条件下非均匀卵石床面的推移质运动变化过程，采集到了更高精度、更长时间序列的输沙率变化过程，分析描述了输沙率统计变化对采样时间的依赖性。实测推移质输沙率的脉动现象十分剧烈，且当采样时间越小时，这种脉动现象越剧烈。来流为4300l/s，采样间隔分别为2min、5min与10min情况下，输沙率脉动值较平均值分别大约4.8倍、3.3倍与2.7倍；来流为5500l/s，采样间隔分别为2min、5min与10min情况下，输沙率脉动值较平均值分别大约3.2倍、2.1倍与1.9倍。卵石推移质单宽输沙率的离差系数、无量纲脉动强度以及无量纲极差值均随采样历时与无量纲希尔兹切应力的增大而减小。利用本次试验成果，通过多元线性回归得到的卵石推移质单宽输沙率的离差系数、无量纲脉动强度以及无量纲极差值与采样历时以及无量纲希尔兹切应力的关系式可为工程应用提供参考。     

复式河道一维洪水演进数值模拟

针对复式河道的特点,建立复式河道一维非恒定流数学模型,采用四点线性隐格式离散圣维南方程组,在动量方程中通过对主槽宽度进行修正,很好地解决了漫滩瞬间流量波动问题。通过2006年汛期调水调沙期间的实测资料对黄河下游白鹤—孙口河段洪水演进过程进行验证,结果表明,计算的洪峰变化过程比较符合实测情况,洪水传播时间的计算值与实测值基本吻合。