径流过程动态广义单位响应函数模型的数字仿真试验

通过径流过程的数字仿真试验,初步证明了动态广义响应函数模型的可行性,并初步探索出卡尔曼滤波环节中确定模型误差协方差距阵(Q*阵)的结构形式以及初始状态向量X%(初始广义单位响应函数)的假定值为模型的推广应用提供了参考.     

基于物理成因概念的水文系统模型及其应用

本文依据等流时线概念，通过将某时刻流域出口断面流量组成表达式与该时刻流域蓄水量表达式联解，得到形状类似多输入单输出的响应函数模型(简称为SMG模型)，它的输入组成具有成因概念，在一定条件下，它可简化为线性变换函数模型和总线性响应函数模型。该模型的参数分析表明，其响应函数值有负数是合理的，这从成因概念上说明了响应函数不同于单位线。将SMG模型应用于龙羊峡水库汛期(5～10月)旬入库流量实际作业预报表明，其预报精度优于人工神经网络，更明显优于自回归模型和多元回归模型。     

基于Volterra级数的水轮机调速器液压系统故障诊断

针对现有水轮机调速器液压系统故障诊断存在诸如诊断精度不高、泛化能力不强、在线检测能力不足等问题,根据Volterra级数的非线性模型高辨识能力以及可实时在线计算等优点,本文提出了一种基于Volterra级数的水轮机调速器液压系统故障诊断的新方法。该方法利用递推最小二乘法辨识出系统Volterra核,经多维广义离散Fourier变换得到系统广义频域响应函数(GFRF)模型,最后利用主元分析法(PCA)进行特征提取及分类,从而实现系统故障的高效诊断。仿真结果表明,该方法具有较高辨识精度,能准确分辨出系统的不同状态。     

渠江巴河流域实时洪水预报方法研究

本文根据大流域雨洪径流的具体特性，将概念性模型与系统模型结合起来制作预报方案，较好地解决了分散人流和响应函数识别问题。采用自适应卡尔曼滤彼方法实时刷新模型参数，以此来提高模型计算精度。对巴河流域的实例验证表明，应用效果良好。     

水电站水库群与地下水资源系统联合运行多目标管理模型及计算方法

本文探讨了水电站水库群与地下水资源系统联合运行多目标管理问题，建立起联合运行多目标管理模型，提出一种模糊带权改进目标协调法。理论分析和实例计算表明，所建立的模型和提出的计算方法具有较强的实用性和通用性，为解决水电站水库群与地下水资源系统联合运行管理问题提供了一条有效途径。     

九台市水资源管理模型

九台市水资源管理模型九台市水资源管理办公室王珊林，杨明，安宇，杨维国１水资源联合管理模型的建立１．１水资源管理问题目前九台市水资源供需矛盾较为突出，无论是城区供水，还是灌区需水均不能满足要求，为此，特拟九台市水资源联合调度总体方案是＂开发地下水，合理...     

多输入／单输出线性函数模型在河道流量演算中的应用初探

在河道流量演算中常常遇到多输入／单输出的情况，常用的流量演算方法处理较为困难，为此本文采用多输入／单输出线性函数模型进行河道流量演算，每个输入的线性响应函数为切比雪夫多项式，系统的记忆长度及线性响应函数多项式的展开阶数通过试错法确定，各个输入与输出的互相关系数可为系统记忆长度的确定提供初解。本文用两输入／单输出线性函数模型对岷江上游干流姜射坝站至于流皂用湾站的河道流量进行演算，并考虑支流杂谷脑河桑坪站的流量汇入，在实际计算中同时采用自回归模型进行实时校正，其计算结果是今人满意的。     

水文系统模型在大流域汇流演进计算中的应用

在大流域汇流水语言演进计算当中应用系统模型（ＴＬＲ、ＣＬＳ、ＬＰＭ等）较之概念性模型具有使用资料少，求解简便，可用严格的数字方法优化出多个输入的脉冲响应，其输入可为流域内的降雨，上游流量过程，输出为流域出口断面流量过程，安康流域汇流演进计算采用（ＣＬＳ，ＬＰＭ，ＴＬＲ）系统模型对洪水及径流进行了模拟，较好地处理了分散入流及响应函数的识别问题。     

给水管网非线性规划的新模型

本文发展了一个确定了给水管网道道直径，水泵扬程，水塔尺寸的最优设计非线性规划模型，提出了将管网不等式约束非线性规划转换为无约束规划问题的变量代换法，求解目标函数广义简约梯度的广义节点法，并采用ＰＲＰ共轭梯度法求解管网非线性规划问题，计算结果表明模型的求解速度比现有同类型非线性管网模型快数十倍。占用计算机内存较少，程序较简单，适用于各种给水管网。     

基于时间响应函数修正的GM(1,1)模型及变形预测应用

针对GM(1,1)模型中拟合所得的时间响应函数与实测累加曲线不重合这一情形,提出分别以时间和累加变形量为横纵坐标建立平面直角坐标系,在坐标系中,将原模型时间响应函数进行纵向平移,然后对平移后函数进行绕点旋转,从而构建新的时间响应函数,使其更接近实测累加曲线;将对应横坐标代入并求解非线性函数,再累减还原为预测值,且将其应用于其他改进GM(1,1)模型中。采用实测变形数据进行验证可知,其预测精度有所提高,具有实践参考价值。     

Mitigating Socio-Economic-Environmental Impacts During Drought Periods by Optimizing the Conjunctive Management of Water Resources

Multi-period optimization of conjunctive water management can utilize reservoirs and aquifer carry-over to alleviate drought impacts. Stakeholders’ socio-economic and environmental indices can be used to minimize the socio-economic and environmental costs associated with water shortages in drought periods. The knowledge gap here is the evaluation and inclusion of the socio-economic and environmental value of conjunctive water management in terms of its drought mitigation capability. In this paper, an integrated water quantity-quality optimization model that considers socio-economic and environmental indices is developed. The model considers and integrates reservoir and aquifer carry-over, river-aquifer interaction and water quality with stakeholders’ socio-economic indices of production, net income and labor force employment to evaluate the socio-economic and environmental value of conjunctive water management. Total dissolved solid (TDS) is used as the water quality index for environmental assessments. The model is formulated as a multi-period nonlinear optimization model, with analysis determining the optimal decisions for reservoir release and withdrawal from the river and aquifer in different months to maximize the socio-economic indices of stakeholders within the environmental constraints. The proposed model is used in Zayandehrood water resource system in Iran, which suffers from water supply and pollution problems. Model analysis results show that conjunctive water use in the Zayandehrood water basin reduces salinity by 50 % in the wetland and keeps water supply reduction during a drought under 10 % of irrigation demand.     

Development of Priority-Based Policies for Conjunctive Use of Surface and Groundwater

Abstract

A combined optimization-simulation approach was used to develop and evaluate the alternate priority-based policies for operation of surface and groundwater systems and is demonstrated with a case study. An optimization model was used to find optimal cropping pattern with and without the conjunctive use of surface and groundwater, as well as with and without socio-economic constraints. The optimization model, based on linear programming, maximizes the net benefit from irrigation activities subject to various physical, economical, and social constraints. A simulation model was used to evaluate the conjunctive operation of the system using the optimal cropping pattern derived from the optimization model. The developed policies have been verified with long-generated stream flow sequences. Three alternate priority-based policies differing in level of groundwater pumping and area of cultivation of rice crop have been evaluated: (1) irrigation with surface water only (Policy-1); (2) irrigation with conjunctive use of surface and groundwater, without socio-economic constraints (Policy-2); and (3) irrigation with conjunctive use operation and with socio-economic constraints (Policy-3). It was found that the use of available groundwater within three meters below ground level (Policy-2) to be optimal, and these results were used in simulation for further evaluation of policies. It was also found that the policy-3 of conjunctive use operation with a priority of 75 percent of maximum possible rice area (using groundwater available within four meters below ground level) resulted in a better scenario. Thus the conjunctive use Policy-2 and Policy-3 with 75 percent of maximum possible rice crop area can be used as better policies for the system studied.     

Distributed Simulation‐optimization Model for Conjunctive Use of Groundwater and Surface Water Under Environmental and Sustainability Restrictions

Evolving optimal management strategies are essential for the sustainable development of water resources. A coupled simulation-optimization model that links the simulation and optimization models internally through a response matrix approach is developed for the conjunctive use of groundwater and surface water in meeting irrigation water demand and municipal water supply, while ensuring groundwater sustainability and maintaining environmental flow in river. It incorporates the stream-aquifer interactions, and the aquifer response matrix is generated from a numerical groundwater model. The optimization model is solved by using MATLAB. The developed model has been applied to the Hormat-Golina valley alluvial stream-aquifer system, Ethiopia, and the optimal pumping schedules were obtained for the existing 43 wells under two different scenarios representing with and without restrictions on stream flow depletion, and satisfying the physical, operational and managerial constraints arising due to hydrological configuration, sustainability and ecological services. The study reveals that the total annual optimal pumping is reduced by 19.75?% due to restrictions on stream flow depletion. It is observed that the groundwater pumping from the aquifer has a significant effect on the stream flow depletion and the optimal conjunctive water use plays a great role in preventing groundwater depletion caused by the extensive pumping for various purposes. The groundwater contribution in optimal conjunctive water use is very high having a value of 92?% because of limited capacity of canal. The findings would be useful to the planners and decision makers for ensuring long-term water sustainability.

     

Application of Genetic Algorithms and Artificial Neural Networks in Conjunctive Use of Surface and Groundwater Resources

Abstract

In this paper, a methodology for conjunctive use of surface and groundwater resources is developed using the combination of the Genetic Algorithms (GAs) and the Artificial Neural Networks (ANN). Water supply to agricultural demands, reduction of pumping costs and control of groundwater table fluctuations are considered in the objective function of the model. In the proposed model, the results of MODFLOW groundwater simulation model are used to train an ANN. The ANN as groundwater response functions is then linked to the GA based optimization model to develop the monthly conjunctive use operating policies. The model is applied to the surface and groundwater allocation for irrigation purposes in the southern part of Tehran. A new ANN is also trained and checked for developing the real-time conjunctive use operating rules.

The results show the significance of an integrated approach to surface and groundwater allocation in the study area. A simulation of the optimal policies shows that the cumulative groundwater table variation can be reduced to less than 4 meters from the current devastating condition. The results also show that the proposed model can effectively reduce the run time of the conjunctive use models through the composition of a GA-based optimization and a ANN-based simulation model.     

Simulation-Optimization Modeling of Conjunctive Use of Surface Water and Groundwater

Water resources management in semiarid regions with low precipitation and high potential of evapotranspiration is a great challenge for managers and decision makers. In those regions, both sources of water should be managed conjunctively so as to minimize shortages of water in dry seasons. In conjunctive use, the difficulty increases as one must represent the response of both systems interactions, and develop management strategies that simultaneously address surface water and aquifer regulation. This paper focuses on the simulation-optimization for conjunctive use of surface water and groundwater on a basin-wide scale, the Najafabad plain in west-central Iran. A trained artificial neural network model is developed as a simulator of surface water and groundwater interaction while a genetic algorithm is developed as the optimization model. The main goal of the simulation-optimization model is to minimize shortages in meeting irrigation demands for three irrigation systems subject to constraints on the control of cumulative drawdown of the underlying water table and maximum capacity of surface irrigation systems. To achieve the main goal, three scenarios are presented. Results of the proposed model demonstrate the importance of the conjunctive use approach for planning the management of water resources in semiarid regions.     

Modeling Water Resources and River-Aquifer Interaction in the Júcar River Basin,Spain

The paper presents how to solve some practical problems of water planning in a medium/large river basin, such as: the water resources assessment and its spatial-temporal variability over the long-short term, the impact of human activities on the water cycle, due to groundwater pumping and water returns into aquifers, the river-aquifer interactions and the aquifer depletion. It is based on the use of a new monthly conceptual distributed water balance model -PATRICAL- that includes the surface water (SW), groundwater (GW) behavior and the river-aquifer interaction. The model is applied to the Júcar River Basin District (RBD) in Spain (43,000 km²), with more than 250 aquifers, including catchments with humid climates (Júcar RBD northern), semiarid and arid catchments (southern). The model has a small number of parameters and obtains a satisfactory performance in SW and GW behavior. It has been calibrated/validated using monthly streamflows and two additional elements not generally used in models for large river basins, GW levels and river-aquifer interactions. In the hydrological time series of the Júcar RBD headers a statistical change point in the year 1979/80 is detected. It is due to changes in precipitation patterns and represents a 40 % of reduction in streamflows in relation with the previous period. The impact of GW pumping in all aquifers is determined, the ‘Mancha Oriental’ aquifer produces a significant reduction in streamflows of the Júcar river –around 200–250 hm³/year. The GW level in the ‘Villena-Benejama’ aquifer -Vinalopo Valley- has declined more than 200 m in last 30 years.     

Assessing Adaptability of Cyclic and Non-Cyclic Approach to Conjunctive use of Groundwater and Surface water for Sustainable Management Plans under Climate Change

Groundwater overdraft in many regions throughout the world has been threatening the sustainability of this valuable resource. It has been argued that climate change may contribute to the severity of the issue; hence “impact assessment” is being replaced by “adaptation,” which explores more adapting scenarios and approaches. This study explores the adaptability of the proposed cyclic and non-cyclic conjunctive use of groundwater and surface water resources in increasing groundwater sustainability while increasing the sustainability of water allocation to the agricultural sector under possible climate change scenarios. To simulate climate change in the study area, precipitation and temperature variables are extracted from the results of three global atmospheric circulation models (Ensemble, CMCC-CMS, MRI-CGCM3) under RCP2.6 and RCP8.5 greenhouse gas emission scenarios in the period of 2021–2031. Spatial downscaling is performed using the M5 decision tree algorithm. The Wavelet-M5 hybrid model is used to predict runoff values as a rainfall-runoff model. Also, the Kharrufa method is applied to calculate evaporation in the future seasons. The system's adaptability to climate change is examined using the multi-objective cyclic and non-cyclic conjunctive use of surface and groundwater models. The study reveals that cyclic operation strategy improves the conjunctive use system adaptability compared to the optimal operation strategy that employs the non-cyclic approach. In this study's case study, the improvement in groundwater sustainability index exceeds 27 percent over the non-cyclic conjunctive use strategy.

     

Multi-Objective Optimal Model for Conjunctive Use Management Using SGAs and NSGA-II Models

The widespread investigations on water resources management has become an essential issue because due to lack of sufficient research and inattention to planning and management of conjunctive use of surface and groundwater. The conjunctive management is a suitable alternative for imbalanced water resources distribution and related constraints in using of surface water. In this paper, a multi-objective model is developed to maximize the minimum reliability of system as well as minimize the costs due to water supply, aquifer reclamation and violation of the reservoir capacity in operation and allocation priority. The non-dominated sorting genetic algorithm (NSGA-II) is used to present the optimal trade-off between the objectives. The sequential genetic algorithms is also applied (SGA) in order to be compared with the NSGA-II model. The results show that the NSGA-II model can considerably reduce the computation burden of the conjunctive use models in comparison with the SGA optimization model. The obtained trade-off curve shows that a little increase in reliability leads to much more system costs. The weighted single objective SGA model results verify optimal trade-off obtained from NSGA-II model and show the optimality of allocated discharges.     

Applying Genetic Algorithm and Neural Network to the Conjunctive Use of Surface and Subsurface Water

The conjunctive use of surface and subsurface water is one of the most effective ways to increase water supply reliability with minimal cost and environmental impact. This study presents a novel stepwise optimization model for optimizing the conjunctive use of surface and subsurface water resource management. At each time step, the proposed model decomposes the nonlinear conjunctive use problem into a linear surface water allocation sub-problem and a nonlinear groundwater simulation sub-problem. Instead of using a nonlinear algorithm to solve the entire problem, this decomposition approach integrates a linear algorithm with greater computational efficiency. Specifically, this study proposes a hybrid approach consisting of Genetic Algorithm (GA), Artificial Neural Network (ANN), and Linear Programming (LP) to solve the decomposed two-level problem. The top level uses GA to determine the optimal pumping rates and link the lower level sub-problem, while LP determines the optimal surface water allocation, and ANN performs the groundwater simulation. Because the optimization computation requires many groundwater simulations, the ANN instead of traditional numerical simulation greatly reduces the computational burden. The high computing performance of both LP and ANN significantly increase the computational efficiency of entire model. This study examines four case studies to determine the supply efficiencies under different operation models. Unlike the high interaction between climate conditions and surface water resource, groundwater resources are more stable than the surface water resources for water supply. First, results indicate that adding an groundwater system whose supply productivity is just 8.67 % of the entire water requirement with a surface water supply first (SWSF) policy can significantly decrease the shortage index (SI) from 2.93 to 1.54. Second, the proposed model provides a more efficient conjunctive use policy than the SWSF policy, achieving further decrease from 1.54 to 1.13 or 0.79, depending on the groundwater rule curves. Finally, because of the usage of the hybrid framework, GA, LP, and ANN, the computational efficiency of proposed model is higher than other models with a purebred architecture or traditional groundwater numerical simulations. Therefore, the proposed model can be used to solve complicated large field problems. The proposed model is a valuable tool for conjunctive use operation planning.     

Conjunctive Water Use Optimization for Watershed-Lake Water Distribution System under Uncertainty: a Case Study

Water Resources Management - In this research, a large-scale inexact optimization method was developed for the conjunctive use management of a watershed-lake water distribution system. The modeling...