A New Approach for Trend Assessment of Annual Streamflows: a Case Study of Hydropower Plants in Serbia

The authors propose a new approach for trend assessment that takes into account long-term periodicity of annual flows. In particular, analysis is performed of annual flows recorded at the locations of 30 operating and designed hydropower plants (HPPs) in Serbia, in order to assess the current and future water availability for hydropower generation. The composite annual trend is determined by sliding a fixed time window of 30 years along the observed time series with a one-year time step. Such a linear moving window (LMW) approach enables the identification of the flow trend as a median of all values for each time step. Significant trend harmonics are determined using discrete spectral analysis. The results show an alternation of upward and downward trend phases of different durations, namely: 67–87, 33–43 and 21–29 years. On the other hand, the results of the Mann-Kendall test indicate a monotonic downward trend at the studied sites in the Drina River Basin, while statistically insignificant trends are noted at other river basins. The Mann-Kendall test with the Theil-Sen estimator also implies a downward and statistically insignificant flow trend after the observed period, whereas the LMW approach indicates a probable trend increase at all the examined sites. The proposed approach can be used to predict annual flows in order to establish long-term water management plans at hydropower plants.     

日月尺度耦合解集方法在降水模拟中的应用

应用一阶马尔可夫链描述干湿变化,以伽玛分布表征降水量分布,采用修正方法调整小尺度序列值,消除小尺度合成值与大尺度对应值之间的误差,进行日、月降水序列模拟。耦合模型模拟序列能够保持各尺度的统计特性和合计值与实测序列严格相等。渭河流域长武、武功、天水和渭源四站降水模拟实例表明,建立的耦合模型在降水模拟中取得了较为满意的效果。通过选择合适的基本模型,耦合模型也可以应用于其他水文随机模拟。     

日月尺度耦合解集方法在降水模拟中的应用

应用一阶马尔可夫链描述干湿变化,以伽玛分布表征降水量分布,采用修正方法调整小尺度序列值,消除小尺度合成值与大尺度对应值之间的误差,进行日、月降水序列模拟.耦合模型模拟序列能够保持各尺度的统计特性和合计值与实测序列严格相等.渭河流域长武、武功、天水和渭源四站降水模拟实例表明,建立的耦合模型在降水模拟中取得了较为满意的效果.通过选择合适的基本模型,耦合模型也可以应用于其他水文随机模拟.     

A Daily Water Balance Modelling Approach for Simulating Performance of Tank-Based Irrigation Systems

Tanks are small reservoirs, which are widely distributed in South India and Sri Lanka, where they represent an important water resource for people, crops, livestock and fish. Considerable efforts have been made to rehabilitate tank irrigation systems in recent decades, but there have been few studies carried out to improve understanding of their hydrology. This paper presents a daily water balance approach, which aims to simulate the dynamic behaviour of tank storage. The model was validated over four seasons for two representative tanks within Mahaweli System H, a major irrigation system in the dry zone of Sri Lanka. Use of the model to evaluate current performance and scope for improvement is demonstrated.     

Estimating Sediment Budget at a River Basin Scale Using a Process-Based Distributed Modelling Approach

The paper presents a process-based distributed modelling approach for estimating sediment budget at a river basin scale with partitions of suspended and bed loads by simulating sediment loads and their interactions. In this approach, a river basin is represented by hillslopes and a network of channels. Hillslopes are divided into an array of homogeneous grid cells for modelling surface runoff and suspended sediments. Channels are defined by incorporating flow hydraulic properties into the respective hillslope grids as sub-grid attributes for modelling both suspended and bed loads. Suspended sediment transport is modelled using one dimensional kinematic wave approximation of Saint-Venant’s principles of conservation of mass and momentum. Transport capacity of runoff or streamflow is used to set the limit of suspended sediment transport rate. Bed load in channels is estimated based on the instantaneous water and hydraulic parameters. Fractional interchange between suspended load and bed load is then back calculated. The performance of the model was evaluated through a case study application in a large river basin in Japan. The model satisfactorily calculated the sediment transport and total sediment budget in the basin. The simulated bed load was found to be reasonable and consistent with the water flow and suspended sediment flux. The results showed the bed load can be expressed as a linear function of the suspended load. The fractions of different sediment loads also exhibit linear relationships with water discharge for the rising and recession limbs of the flood hydrographs. The case study has demonstrated that the process-based distributed modelling approach can efficiently describe the basin-scale sediment budgets with due consideration of the suspended and bed loads and their interactions in the hillslopes and channels.     

无资料地区计算年径流均值的幂函数法

针对无实测资料地区水文分析计算之需,提出了以幂函数法计算设计年径流均值的方法。研究了幂函数法的模型建立、参数率定、模型检验与应用等方法。以山西省水文分区的中区为例,引入幂函数模型,计算了该区设计年径流的均值。与实测资料相比,按参数一般值验算误差统计,误差在±20%以内的站点占72.5%,误差在±30%以内的站点占90.0%;按单站参数验算误差统计,误差在±20%以内的站点占92.5%,误差在±30%以内的站点高达97.5%,说明幂函数模型解决无资料地区设计年径流均值定量化计算的方法可靠,简单实用,且具有较高的精度,可以满足工程规划中水文分析计算的要求。     

累积流量坐标法在水环境污染带计算中的应用

以汉江旬阳库区安康段的月河为例,将月河视为连续点源,考虑河道的不规则性并采用二维水质模型累积流量坐标法计算月河污染带,结果表明,河道的不规则性对污染带分布有较大影响,使污染物浓度分布沿程起伏变化,污染带长度和宽度与规则河道解析解结果相差不大.     

Estimation of the Parameters of Wakeby Distribution by a Numerical Least Squares Method and Applying it to the Annual Peak Flows of Turkish Rivers

In this study, a numerical least squares (NLS) method for estimating the parameters of five-parameter Wakeby distribution was introduced. To asses the right tail estimate performances of the method, Monte Carlo simulated data and annual peak flows of 50 stations on Turkish rivers were used. Its results were compared to those by L-moments (LM) and curve fitting method of MATLAB. The biases from the LM for non-exceedence probability (F) of 0.999 mostly were less than those by the NLS. However, the values of relative root mean square error (rrmse) statistics from the NLS were better than those by the LM. In addition, the statistic of average deviation from the observed annual peak flows showed that NLS method exhibited mostly better results than those by LM for right tail predictions. Lastly, except the convergence problem of MATLAB, while both of the NLS and MATLAB produced the same determination coefficient (r ²) for the majority of data set, the NLS produced lower rrmse values than MATLAB.     

Evaluation of Sediment Transport Capacity Equations Using Basin Scale Process-Based Sediment Dynamic Modelling Approach

Most process-based sediment dynamic models are based on the concept of sediment transport capacity (TC) of flow. Relationships between sediment TC and its characterized variables are found to vary widely, depending on the characteristics of a watershed and the underlying hydrological processes. This study has aimed to incorporate various widely used sediment transport capacity equations (TCEs) in a process-based sediment dynamic model, and to evaluate their relative performances in estimating suspended sediment dynamics at a river basin scale. The paper describes the modelling approaches and their application to a case study area (Abukuma River Basin, Japan), and then elaborates various parameters used in different TCEs with their useful impacts on modelling outcomes. The results of the case study have demonstrated that some of the TCEs are not suitable for simulating basin scale sediment dynamics. The TCEs that consist of more hydraulic parameters representing the flow and sediment transport processes have produced better outcomes.     

分解模型与贝叶斯方法在枯水分析中的应用

本文把随机分解模型应用到枯水径流分析与设计,用贝叶斯统计推断其中的偏态参数C_s。运用结果表明:分解模型能很好地模拟枯水过程,贝叶斯估计能利用区域信息推求模型参数,提高参数估计的稳健性和降低抽样误差。     

Analysis of Bed Load Equations and River Bed Level Variations Using Basin-Scale Process-Based Modelling Approach

Bed load transport is a key process in maintaining the dynamically stable channel geometry for restoring the form and function of river ecosystems. Bed load consists of relatively large sediment particles that are moved along the streambed by rolling, sliding or saltation. Currently, various empirical correlations are used to estimate bed load transport rates since no single procedure, whether theoretical or empirical, has yet to be universally accepted as completely satisfactory in this aspect. Bed load particles are primarily sourced from river bed materials or banks. The amount of bed load and its spatial distribution contributes significantly to river bed level changes. Hillslope sediment contribution, mostly available to the river in the form of suspended load, also plays an important role in river bed level changes. This study aims to analyse different bed load equations and the resultant computations of river bed level variations using a process-based sediment dynamic model. Analyses have revealed that different bed load equations were mainly deduced from the concept of relating bed shear stresses to their critical values which are highly factored by the slope gradient, water discharge and particle sizes. In this study, river bed level variations are calculated by estimating total surplus or deficit sediment loads (suspended loads and bed loads) in a channel section. This paper describes the application of different widely used bed load equations, and evaluation of their various parameters and relative performances for a case study area (Abukuma River Basin, Japan) using a basin-scale process-based modelling approach. Relative performances of river bed level simulations obtained by using different bed load equations are also presented. This paper elaborates on the modelling approaches for river bed load and bed level simulations. Although verifications were not done due to unavailability of field data for bed load, qualitative evaluations were conducted vis-à-vis field data on flow and suspended sediment loads as well as the bed loads presented in different past studies.     

Modelling Impacts of Climate Change on a River Basin: Analysis of Uncertainty Using REA & Possibilistic Approach

In the context of climate change, the uncertainty associated with Global Climate Models (GCM) and scenarios needs to be assessed for effective management practices and decision-making. The present study focuses on modelling the GCM and scenario uncertainty using Reliability Ensemble Averaging (REA) and possibility theory in projecting streamflows over Wainganga river basin. A macro scale, semi-distributed, grid-based hydrological model is used to project the streamflows from 2020 to 2094. The observed meteorological data are collected from the India Meteorological Department (IMD) and the streamflow data is obtained from Central Water Commission (CWC) Hyderabad. In REA, meteorological data are weighted based on the performance and convergence criteria (GCM uncertainty). Whereas in possibility theory, based on the projection of different GCMs and scenarios during recent past (2006–2015) possibility values are assigned. Based on the possibility values most probable experiment and weighted mean possible CDF for the future periods are obtained. The result shows that there is no significant difference in the outcomes is observed between REA and possibility theory. The uncertainty associated with GCM is more significant than the scenario uncertainty. An increasing trend in the low and medium flows is predicted in annual and monsoon period. However, flows during the non-monsoon season are projected to increase significantly. Moreover, it is observed that streamflow generation not only depends on the change in precipitation but also depends on the previous state of physical characteristics of the region.     

Quantitative Assessment of Agricultural Practices on Farmland Evapotranspiration Using EddyCovariance Method and Numerical Modelling

While low cost eddy covariance (EC) techniques based on the open-path laser analyzers have been widely used, they are not very accurate and are restricted to use in non-rainy days. As an alternative, and relevant to promoting precision agriculture where water availability is proving key, the application of the EC technique based on closed-path QCLAS-EC Analyzer is described, in a study of cabbage farmland evapotranspiration (ET). This study uses the advantages of the closed-path EC method to quantitatively assess the impact of agricultural activities on farmland ET and compared with RZWQM2 (Root Zone Water Quality Model) model. The cumulative ET is shown to have increased by 1.5–3.6 mm over ten-days after planting, and decreased by 3.5–8.1 mm over 10 days, following harvesting. While irrigation contributed to ET, the cumulative ten-day ET increase is between 0.6–2.3 mm which is significantly lower than the effects due to planting and harvesting. The RZWQM2 model was used to quantify the effects of four agricultural practices. Simulation of ET attained R² and RMSE as 0.79 and 0.013 mm/d, respectively. In addition, the RZWQM2 model successfully simulated groundwater levels, Leaf area index, and crop height (R² values of 0.71, 0.98 and 0.97, respectively). The RZWQM2 model simulates the effects of planting, harvesting, and irrigation on ET, indicating the same directional changes of magnitude with measured data. The results provide a comprehensive and direct study based on the closed-path EC method and RZWQM2 model to assess the impact of multiple agricultural activities on farmland ET and to improve precision agriculture.

     

An Assimilation Simulation Approach for the Suspended Sediment Concentration in Inland Lakes Using a Hybrid Perturbation Generation Method

Suspended sediments, one of the most important factors affecting the water environments of inland lakes, are closely related to the migration and interaction of various pollutants. Existing studies show that the suspended sediment concentration can be accurately predicted based on assimilation methods coupled with hydrodynamic models. However, in the hydrological assimilation simulation process, the existing perturbation generation methods consider the perturbation error to follow a random Gaussian distribution, which does not consider the spatial variation characteristics of errors. Thus, in this paper, we proposed a new method that generates a hybrid perturbation field for the assimilation simulation instead of using random error. The proposed approach was validated through assimilation simulations of the suspended sediment concentration of Taihu Lake, China, and five assimilation experiments were conducted. The proposed method was compared with the existing methods for generating the perturbation field. After three days and 72 time steps of assimilation simulation based on the hybrid perturbation field, the proposed assimilation method provided results that were more consistent with the buoy-measured data. These findings demonstrate that the proposed method for generating a hybrid perturbation field has a higher simulation accuracy than other methods and is therefore effective and provides a new idea for the assimilation simulation of suspended sediment concentrations in inland lakes.

     

三峡工程日调节二维非恒定流数值模型研究

本文用插值元法对任意边界的河道流场采用非矩形网格剖分,然后进行交替方向隐式求解,可以使用C_r数较大的时间步长。在对边界条件进行适当处理后,用正规网格替代了交替网格。并将此方法用于几个问题的数值求解,实践证明本方法是成功的。     

用新分层方法研究功能梯度材料平面断裂问题

针对材料参数在厚度方向按任意函数形式连续变化的功能梯度材料薄板,利用新的分层方法,求出各向异性、正交异性功能梯度材料板平面断裂基本方程并结合各向同性功能梯度材料及各向同性、各向异性、正交异性复合材料对方程作了全面讨论．结果表明复合材料和功能梯度材料以及各向同性、各向异性、正交异性之间既有区别又有密切联系,新的分层方法非常有效．     

Optimization of Reservoir Operation with a New Approach in Evolutionary Computation Using TLBO Algorithm and Jaya Algorithm

Reservoir operation and management are complex engineering problems, due to the stochastic nature of inflow, various demands and as well as tailwater in the downstream. The complexity increases when the number of reservoirs gets increased such as multi-reservoir system or chain system. To obtain optimal operation in such condition become more difficult. It requires powerful optimization algorithm to solve aforesaid problems. Teaching Learning Based Optimization (TLBO) algorithm and Jaya Algorithm (JA) are recently developed advanced optimization techniques a novel approach comparatively simple, easy, and robust. The main advantages of these algorithms are it only requires the common control parameters such as number of iterations and population size. In the present study, three different benchmark problems were evaluated to check the applicability and performance of TLBO and JA in multi-reservoir operation problems. The benchmark problems are the discrete time four-reservoir operation (DFRO), the continuous time four-reservoir operation (CFRO), and the ten-reservoir operation (TRO). The results from the TLBO and JA are compared with different approaches from the literature. The optimal net benefits obtained from JA for DFRO, CFRO and TRO problems are 401.44, 308.40 and 1194.59, respectively, and that of TLBO algorithm are 401.33, 308.30 and 1194.44, respectively. It is found that both JA and TLBO algorithms provided a satisfactory solution as other optimization techniques, from literature. In conclusion, JA outperformed over TLBO.     

Development of a Predictive Equation for Modelling the Infiltration Process Using Gene Expression Programming

In this study, the soft computing technique of Gene expression programming (GEP) has been employed to generate a predictive equation of infiltration rate (f_p). Infiltration experiments were conducted at 124 different sites and soil samples were collected to assess various soil properties throughout the Himalayan lake catchment. Parameters determined from observed data using nonlinear-Levenberg Marquardt algorithm were substituted in Horton, Kostiakov and Philip infiltration models and f_p were predicted. Using soil data generated by laboratory investigation of soil samples, the GEP model was developed. Training and testing of the GEP model was performed using 70% and 30% of data respectively. Performance of GEP developed functional relationship was evaluated by comparing predictions from it and aforementioned infiltration models with field observed f_p, and by applying overall performance index (OPI) computed using Coefficient of Determination (R²), Nash–Sutcliffe Efficiency (E_NS), Willmott’s Index of Agreement (W), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). Expression developed using GEP indicated feasibility of developed equation with E_NS, R², W, RMSE and MAE of 0.84, 0.84, 0.96, 1.9, and 0.8, respectively for training data-set and 0.84, 0.85, 0.95, 1.2, and 0.95, respectively for testing data-set. Comparative analysis revealed that though with a slightly higher OPI value (0.7–0.8), the performance of conventional models is better compared to the GEP model (0.66) but the GEP model having satisfactory performance may be used for f_p prediction particularly in absence of observed data.

     

Rehabilitation of Urban Drainage Systems Using a Resilience-Based Approach

Highly efficient methods are needed to mitigate negative impacts of urban storms such as flooded roads and damage to properties and infrastructures. A rehabilitation approach based on resiliency is proposed in this paper for urban drainage systems using structural improvement of bottlenecks. The resilience-based approach enhances system capability to act very flexible against exceptional loads such as bridge/culvert blockage during the floods. The approach integrates a multi-objective evolutionary algorithm (MOEA) and EPA-SWMM simulation model to find cost-effective rehabilitation measures under structural failure of critical elements in the network. It is applied to the western part of Tehran Stormwater Drainage System (TSDS) to attain optimal measures by minimizing the costs and flood volumes. The approach outperforms the conventional methods (particularly compared to a previous rehabilitation proposal for the study area) when the system encounters unexpected blockage conditions. Results show that the optimal design obtained by the proposed approach can decrease network flooding from 3.5 × 10⁶ m³ to near zero with at most 23% lower investment costs relative to the traditional design.