Refinement of predictive reaeration equations for a typical Indian river

Dissolved oxygen mass balance has been computed for different reaches of River Kali in western Uttar Pradesh (India) to obtain the reaeration coefficient (K₂). A total of 270 field data sets have been collected during the period from March 1999 to February 2000. Eleven most popular predictive equations, used for reaeration prediction and utilizing mean stream velocity, bed slope, flow depth, friction velocity and Froude number, have been tested for their applicability in the River Kali using data generated during field survey. The K₂ values computed from these predictive equations have been compared with the K₂ values observed from dissolved oxygen balance measurements in the field. The performance of predictive equations have been evaluated using error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and correlation statistics. The equations developed by Smoot and by Cadwallader and McDonnell showed comparatively better results. Moreover, a refined predictive equation has been developed using a least‐squares algorithm for the River Kali that minimizes error estimates and improves correlation between observed and computed reaeration coefficients. Copyright © 2001 John Wiley & Sons, Ltd.     

Evaluation of various relationships of reaeration rate coefficient for modeling dissolved oxygen in a river with extreme flow variations in Pakistan

Mathematical relationships have been developed for reaeration rate coefficient (K_a) by various researchers. These relationships have a number of variables such as depth, velocity, width, slope, Froud number, molecular diffusion coefficient, kinematic viscosity and the gas‐transfer Reynolds number. From these variables, 29 relations have been developed and divided into four groups. To evaluate their predictive capability for highly variable flow rivers receiving high pollution loads form large cities, these relationships have been used to model dissolved oxygen (DO) in the River Ravi. Such rivers are either saturated with DO during high flows or anaerobic during critical low‐flow conditions. The evaluation is based on the agreement between model DO values calculated using K_a obtained from the available equations and the measured DO concentrations in the river samples in terms of sum of square of residuals (SSR) and coefficient of determination (R²). It has been found that in general, the group of equations containing depth and velocity as the only two variables affecting K_a performed better than the equations in other groups as reflected by lower SSR and higher R² values. The study results also reveal that the turbulence‐based reaeration rate coefficient equation containing additional variables also resulted in close agreement between DO model results and the measured values. The study results identify the most important parameters affecting the reaeration rate coefficient and the suitability of various K_a relationships as well for rivers with highly variable flows. Copyright © 2012 John Wiley & Sons, Ltd.     

Determination of reaeration‐rate coefficient by modified tracer gas technique

The modified tracer gas technique is used to determine the reaeration coefficient in six different water bodies of the Itajaí River basin, three with rural land use and three in urban areas. Propane was used as the tracer gas and Rhodamine WT as the conservative tracer, providing information on dilution, mixing and dispersion. Liquefied petroleum gas was used instead of high purity propane, aimed at reducing the costs associated with the field trials. Reaeration‐rate coefficients observed in the field ranged from 25.8 to 367.7 d^?1. Two data sets could be observed where smaller streams had substantially larger coefficients of between 133.1 and 367.7 d^?1, while the larger streams had values ??ranging from 25.8 to 54.5 d^?1. Five empirical equations were evaluated by comparing the values ??obtained in the field. The equations proposed by Tsivolgou and Wallace and Tsivoglou and Neal showed greater adherence to the values ??determined in the tests. Reaeration‐rate coefficients obtained in the field were correlated with the hydrodynamic characteristics of the watercourses, thus establishing a mathematical function through which to obtain estimates for future evaluations. The R² value obtained using this equation was 0.959, indicating a high correlation between the calculated values ??and those estimated in the field. Copyright © 2012 John Wiley & Sons, Ltd.     

冰封期湖泊溶解氧变化特征及代谢速率

冰封期湖泊与大气的气体交换受冰盖阻碍,影响湖泊溶解氧含量,进而影响湖泊水质.为探究冰封期湖泊溶解氧和新陈代谢速率变化特征及影响因素,本研究通过监测典型季节性冰封湖泊不同深度的溶解氧(DO)、水温和光合有效辐射(PAR),结合水质检测结果,分析冰封期湖泊DO变化及代谢速率影响因素,对湖泊日新陈代谢速率计算方法进行改进并估算冰封期湖泊新陈代谢速率.结果表明：2021年1—3月间,岱海DO浓度平均值为15.49 mg/L,并出现昼夜变化和分层现象.DO在冰封期变化趋势呈现出先逐渐升高,然后保持稳定,进入消融期(2021年3月2—11日)分层现象逐渐消失的规律.岱海冰封期净初级生产力和生态系统呼吸速率平均值分别为0.11和0.10 mg/(L·d),在水温未出现分层时净初级生产力呈现较高水平;之后水温沿水深方向出现分层,净初级生产力明显下降;当冰层融化后,PAR显著上升,净初级生产力又逐渐恢复至0.10 mg/(L·d).统计分析表明,岱海冰封期DO与水温、PAR、总氮等变化具有一定相关关系,且由于湖泊流域生态环境条件及冰封期物候特征不同,岱海与内蒙古其他湖泊相比,冰封期DO变化趋势存在一定差...     

Use of mixed bivariate distributions for deriving inter‐station correlation coefficients of rain rate

Even though rain rate is notorious for its spatial and temporal intermittency, its effect on the second‐order statistics of rain rate, especially the inter‐station correlation coefficients, has not been intensively evaluated before. This study has derived and compared the inter‐station correlation coefficient of rain rate for three cases of data: (1) only the positive measurements at both locations; (2) the positive measurements at either one or both locations; (3) all the measurements including zero measurement at both locations. For these three cases, the inter‐station correlation coefficients are analytically derived by applying the mixed bivariate log‐normal distribution. As an application example, the model parameters are estimated using the rain rate data collected at the Geum River basin, Korea, and the resulting inter‐station correlation coefficients are evaluated and compared with those estimated by applying the Gaussian distribution. We could find that highly biased inter‐station correlation coefficients are unavoidable when simply estimating them under the assumption of Gaussian distribution, or even when using the log‐transformed rain rate data. Copyright © 2007 John Wiley & Sons, Ltd.     

A new fuzzy linear regression approach for dissolved oxygen prediction

Abstract

A new method for fuzzy linear regression is proposed to predict dissolved oxygen using abiotic factors in a riverine environment, in Calgary, Canada. The proposed method is designed to accommodate fuzzy regressors, regressand and coefficients, i.e. representing full system uncertainty. The regression equation is built to minimize the distance between fuzzy numbers, and generalizes to crisp regression when crisp parameters are used. The method is compared to two existing fuzzy linear regression techniques: the Tanaka method and the Diamond method. The proposed new method outperforms the existing methods with higher Nash-Sutcliffe efficiency, and lower RMSE, AIC and total fuzzy distance. The new method demonstrates that nonlinear membership functions are more suitable for representing uncertain environmental data than the typical triangular representations. A result of this research is that low DO prediction is improved and consequently the approach can be used for risk analysis by water resource managers.

Editor D. Koutsoyiannis; Associate editor T. Okruszko     

Non‐point source pollution estimation using a modified approach

Non‐point source (NPS) pollution from agricultural land is increasing exponentially in many countries of the world, including India. A modified approach based on the conservation of mass and reaction kinetics has been derived to estimate the inflow of non‐point source pollutants from a river reach. Two water quality variables, namely, nitrate (NO₃) and ortho‐phosphate (o‐PO₄), which are main contributors as non‐point source pollution, were monitored at four locations of River Kali, western Uttar Pradesh, India, and used for calibration and validation of the model. Extensive water quality sampling was done with a total of 576 field data sets collected during the period from March 1999 to February 2000. Remote sensing and geographical information system (GIS) techniques were used to obtain land use/land cover of the region, digital elevation model (DEM), delineation of basin area contributing to non‐point source pollution at each sampling location and drainage map. The results obtained from a modified approach were compared with the existing mass‐balance equations and distributed modelling, and the performances of different equations were evaluated using error estimation viz. standard error, normal mean error, mean multiplicative error and correlation statistics. The developed model for the River Kali minimizes error estimates and improves correlation between observed and computed NPS loads. Copyright © 2007 John Wiley & Sons, Ltd.     

地震震级预测的相关向量机模型

为了借助容易获取的地震相关因素间接预测地震震级,提出基于相关向量机（Relevance Vector Machine,RVM）方法的地震震级预测模型。通过样本学习建立地震震级与地震累积频度、累积释放能量、平均震级、b值、η值和相关区震级等6个主要影响因素之间的非线性映射关系,利用已知影响因素预测地震震级。结果表明:RVM模型预测结果均优于BP神经网络及SOM-BP神经网络预测结果;通过敏感因子分析比较各因素的敏感程度,b值和η值最为突出,在震级研究中应重点分析。综合分析,RVM模型具有精度高和离散性小等优点,对地震震级预测有较好的推广价值。     

A methodological approach for estimating turbidity in a river

During the operations of purging and disposal of sediments of a reservoir it is necessary to know the values of turbidity in the river downstream in natural condition,in the absence of dams or river training works.The paper shows that under these conditions the ratio of the average values of sediment discharge to the annual maximum value of water discharge is a function of the average annual turbidity.Turbidity can be considered as representative synthetic index of the climatic conditions,the lithological features and the land cover of the basin,and the geometric characteristics of the river network.The proposed relationship of sediment discharge as a function of water discharge were validated on the basis of data collected from different Italian regions that have very different morphological,geo-lithological and rainfall features and that are characterised by a basin area changing between a few dozen and thousands of square kilometres.The results can be considered satisfying.     

热分层对水库水质的季节性影响——以西安黑河水库为例

深水水库作为城市的重要供水水源,通常由于热量在垂向水体上的不均匀分配形成热分层.热分层会阻碍垂向上水体交换引发水质分层现象,在冬季水库发生“翻库”之后,水体混合导致水库的整体水质下降.结合热分层指数可以客观、直接地表达水库热分层的稳定程度.综合水库的气温、水体更新率和水质参数(溶解氧、pH、总磷、氨氮)的年度变化,对陕西黑河水库2008-2010年的热分层状况进行研究.研究表明:水库的热分层形成会直接恶化底部水质尤其会加速底部水体中溶解氧的消耗;热分层的年度变化主要受气温控制,但在特定时期较大的水体更新率可以在一定程度上弱化水体热分层,减缓底部水质恶化.该结果可使水库管理者在水库分层最稳定、水质恶化最严重时期以人工调节水体更新率的方式弱化热分层,为保证水质安全提供参考.     

A simple method for the determination of ionic diffusion coefficients in flooded soils

Soil cores from river marginal wetlands from the Torridge and Severn catchments in the UK were collected to study rates of soil denitrification at different sites and at two stations (levee and backplain depression) at the river margin. Half the cores were sterilized prior to flooding to destroy the denitrifying bacteria. After flooding and equilibration, monitoring the concentration of amended nitrate in the supernatant of the sterile cores over a period of 7 days provided a simple procedure for the estimation of the diffusion coefficient of the nitrate ion in the flooded soils. An expression was developed that permitted this diffusion coefficient to be extracted from the slope of a plot of supernatant concentration versus (time)^1/2. The values obtained, at 15 °C, varied from 2·4 to 6·8 × 10^?10m²s^?1. Sterile cores are usually treated as controls in denitrification experiments; this work develops a procedure whereby they may yield useful soil process information. Copyright © 2001 John Wiley & Sons, Ltd.     

A new approach for estimating seismic damage of buried water supply pipelines

Conventional damage prediction methods for lifeline structures are primarily based on peak ground motion measurements. However, line structures such as lifelines suffer damage that is mainly induced by the strain of the ground and therefore are likely to be vulnerable to sharp spatial changes in the ground motion. In this study, we propose a measure for evaluating the damage incurred by underground water supply pipelines based on the spatial gradient of the peak ground velocity (PGV), in an attempt to quantify the effects of the geospatial variabilities in the ground motion on pipeline damage. We investigated the spatial distribution of the damage caused to water pipelines during the Niigata‐ken Chuetsu earthquake on October 10, 2004 (Japan Meteorological Agency magnitude (M_JMA) of 6.8) and the Kobe earthquake on January 17, 1995 (M_JMA7.3) and compared the surveyed damage with the PGV distribution as well as with the gradients of the PGV calculated around the damage areas. For the Kobe earthquake, we used the PGV distribution obtained by the strong‐motion simulation performed by Matsushima and Kawase 1 . In case of the Chuetsu earthquake, we estimated the ground motion using a broadband‐frequency‐based strong‐ground‐motion simulation method based on a multiasperity source model. In both cases, we calculated the gradients of the PGV along the geographical coordinates, with the amplitude of the PGV gradient vector being employed as the damage estimator. Our results show that the distribution of damage to underground water supply pipelines exhibits a greater correlation with the gradients of the PGV than with the PGV itself. Thus, the gradient of the PGV is a useful index for preparing initial‐screening hazard maps of underground facilities. Copyright © 2017 John Wiley & Sons, Ltd.     

A modelling approach for estimating suspended sediment concentrations for multiple rivers influenced by agriculture

A data-driven model based on an adaptive neuro-fuzzy inference system (ANFIS) was tested for the estimation of suspended sediment concentrations within watersheds influenced by agriculture. ANFIS models were developed using different combinations of inputs such as precipitation, streamflow, surface runoff and the watershed vulnerability index. A multi-watershed ANFIS model was also developed combining the datasets from all studied watersheds. The best results were obtained from a combination of precipitation, streamflow and watershed vulnerability index as input variables. Nash-Sutcliffe coefficients were improved for the multi-watershed ANFIS compared to watershed-specific ANFIS models. The introduction of the erosion vulnerability index significantly improved the ability of the ANFIS model to estimate suspended sediment concentrations within the watersheds. Furthermore, the inclusion of this index opens the possibility of using the ANFIS model to investigate the impact of land-use changes on sediment delivery.     

有色可溶性有机物(CDOM)吸收作为湖库化学需氧量监测替代指标的探讨

化学需氧量是衡量水体中有机物量及污染程度的综合性指标,也是我国《地表水环境质量标准(GB 3838—2002)》的重要评价指标.然而,由于测定过程缓慢和使用了有毒有害试剂易于形成二次污染,现行标准的高锰酸钾和重铬酸钾化学需氧量测定方法无法做到环境友好,也不能反映当前快速和实时监测的技术需求.因此,迫切需要发展操作简便、快速高效、灵敏可靠、环境友好和环保绿色的化学需氧量替代检测方法.本文首先从文献计量学视角比较我国与世界上发达国家化学需氧量研究主题论文发文量,剖析了我国发展化学需氧量替代检测方法的迫切性.基于全国大范围65个湖库706个样本有色可溶性有机物吸收系数、化学需氧量和其他水质参数同步调查数据,构建广覆盖范围的有色可溶性有机物特征波长吸收系数和化学需氧量间高精度线性关系模型,确定了地表水环境质量评价的吸收系数阈值,模型可以广泛应用于不同类型(深水、浅水、大型、中型、小型)和不同营养状态(贫、中、富营养)湖库水体有机物浓度的定量表征,具有一定普适性.通过对比有色可溶性有机物吸收系数和传统的高锰酸钾、重铬酸钾法优势和不足,明确了有色可溶性有机物吸收系数替代化学需氧量用于湖库水体开展有...     

A River Water Quality Model for Chlorophyll and Dissolved Oxygen that Accommodates Zebra Mussel Metabolism

The development, testing and application of a dynamic two-dimensional (longitudinal-vertical) mass balance model for dissolved oxygen (DO) and chlorophyll (Chl) for rivers is documented that for the first time accommodates both the oxygen demand and filtering effects of zebra mussels. The test system is a phytoplankton-rich section ( 15 km long) of the Seneca River, NY, that is believed to represent an upper bound of the impact of this exotic invader. Changes in common measures of water quality of the river brought about by the zebra mussel invasion are reviewed and related longitudinal patterns in DO, Chl, and Secchi disc transparency are documented. Model testing is supported by comprehensive measurements of DO, Chl, and various forcing conditions over a three-month period, and independent determinations of several model coefficients. Wide variations in the areal consumption rate of DO (ZOD; g·m^–2·d^–1) and filtering rate (m³·m^–2·d^–1) of zebra mussels, as determined through model calibration, occurred over the study period. Values of ZOD in areas with dense zebra mussel populations at times (e.g., > 50 g·m^–2·d^–1) were an order of magnitude greater than the sediment oxygen demand associated with organically enriched deposits. The value of determinations of these fluxes from model calibration procedures is evaluated within the context of the limitations of protocols presently available to support independent specification of these rates. Model analyses are conducted to evaluate the relative magnitude of source and sink processes for DO and Chl, the potential operation and implications of feedback from low DO levels on oxygen consumption by zebra mussels, and the sensitivity of model simulations to selected sources of uncertainty and variability. Model projections of oxygen resources of the river are presented in a probabilistic format in evaluating reductions in zebra mussel biomass that would be necessary to eliminate violations of standards and regain assimilative capacity.     

A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows

Abstract

A wavelet-neural network (WNN) hybrid modelling approach for monthly river flow estimation and prediction is developed. This approach integrates discrete wavelet multi-resolution decomposition and a back-propagation (BP) feed-forward multilayer perceptron (FFML) artificial neural network (ANN). The Levenberg-Marquardt (LM) algorithm and the Bayesian regularization (BR) algorithm were employed to perform the network modelling. Monthly flow data from three gauges in the Weihe River in China were used for network training and testing for 48-month-ahead prediction. The comparison of results of the WNN hybrid model with those of the single ANN model show that the former is able to significantly increase the prediction accuracy.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Wei, S., Yang, H., Song, J.X., Abbaspour, K., and Xu, Z.X., 2013. A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows. Hydrological Sciences Journal, 58 (2), 374–389.     

A probabilistic approach for estimating the seismic response of elasto‐plastic SDOF systems

The seismic response of elasto‐plastic structures to both recorded and generated accelerograms is characterized by a large scattering of the results, even for accelerograms with similar peak ground acceleration values and frequency content. According to current code recommendations a design value of the seismic response of an elasto‐plastic structure can be computed as the mean of the responses to a certain number of spectrum‐fitting generated accelerograms. A more effective probabilistic approach is presented herein. It allows the analyst to calculate a design value of the seismic response characterized by a predefined non‐exceedance probability using a limited number of generated accelerograms. The results of the performed analyses are presented in diagrams that can be used for structural design applications. The applicability of the proposed method is demonstrated in the case of an elasto‐plastic structural system and the results are compared with those obtained applying current code recommendations. Copyright © 2005 John Wiley & Sons, Ltd.     

计算结构首次穿越时间概率密度函数的新方法

本文在M adsen等提出的积分方程方法基础上,采用单点FORM方法计算结构首次穿越问题中的条件穿越率、联合穿越率及首次穿越时间概率密度。提出的新方法计算简单,结果精确,适于进行脆性结构的首次穿越破坏分析。     

A novel approach for estimating karst groundwater recharge in mountainous regions and its application in Switzerland

A pragmatic and simple approach for estimating the groundwater recharge of karst aquifers in mountainous regions by extrapolation of the hydrological regimes of gauged and well‐documented systems is presented. Specific discharge rates are derived using annual precipitation and spring measurements by taking into account catchment size and elevation, which are assumed to be the dominant factors. Reference sites with high data reliability are used for calibration and regional extrapolation. This is performed with normalized values employing spatial precipitation deviations and correlation with the elevation of the catchment areas. A tiered step procedure provides minimum and maximum normalized gradients for the relationship between recharge quantity and elevation for karst regions. The normalized recharge can therefore be obtained and extrapolated for any location using the spatial precipitation variability to provide an estimate of annual groundwater recharge. The approach was applied to Switzerland (approximately 7500 km² of karst terrain situated between 200 and over 4000 m a.s.l.) using annual precipitation data from meteorological stations for the years 2000 to 2011. Results show that the average recharge rates of different Swiss karst domains range from 20 to 46 L/km²s, which corresponds to an infiltration ratio between 0.6 and 0.9 of total precipitation. Despite uncertainties inherent in the approach, these results provide a benchmark for renewable karst groundwater resources in Switzerland of about 8.4 km³/year. The approach can be applied to any other mountainous karst region, that is, where a clear relationship between elevation, precipitation and recharge can be assumed. Copyright © 2015 John Wiley & Sons, Ltd.