Monthly Water Resources and Irrigation Planning: Case Study of Conjunctive Use of Surface and Groundwater Resources

The Tehran metropolitan area is one of the mega cities of the world and has an annual domestic water consumption close to one billion cubic meters. The sewer system mainly consists of traditional absorption wells. Therefore, the return flow from the domestic consumption has been one of the main sources of groundwater recharge. Some part of this sewage is drained into local rivers and drainage channels and partially contaminates the surface runoff and local flows. These polluted surface waters are used in conjunction with groundwater for irrigation purposes in the southern part of the Tehran. In this paper, a systematic approach to surface and groundwater resources modeling in the study area, with its complex system of water supply, groundwater recharge, and discharge, is discussed. A dynamic programming optimization model is developed for conjunctive use planning. The objective function of this model is developed to supply the agricultural water demands, to reduce pumping costs, and to control groundwater table fluctuations. To develop the response function of the aquifers located in the study area, a mathematical model for simulation of the Tehran aquifer water table fluctuations has been developed and calibrated with the available data. Different scenarios are defined to study the long-term impacts of the development projects on conjunctive use policies and water table fluctuations. Comparison of the results showed how significant is the effects of an integrated approach to the surface and groundwater resources allocation in Tehran metropolitan area. The proposed model is a useful tool for irrigation planning in this region.     

Optimal Retailer Load Estimates Using Stochastic Dynamic Programming

In this paper, we describe a stochastic dynamic programming methodology for determining optimal forward load estimates for electric power retailers to their suppliers. This work describes both a model as well as results based on real data for the Electric Reliability Council of Texas market and provides insights useful for planning purposes for electric power retailers in the face of uncertain market prices and end-user loads.     

Dynamic Site Layout Planning Using Approximate Dynamic Programming

Dynamic site layout planning requires identifying and updating the positions of all temporary construction facilities such as offices, storage areas, and workshops over the entire project duration. Existing models do not guarantee global optimal solutions because they focus on optimizing the planning and layout of successive construction stages in a chronological order, without considering the future implications of layout decisions made in early stages. This paper presents the development of an approximate dynamic programming model that is capable of searching for and identifying global optimal dynamic site layout plans. The model applies the concepts of approximate dynamic programming to estimate the future effects of layout decisions in early stages on future decisions in later stages. The model is developed in three main phases: (1) formulating the decision variables, geometric constraints, and objective function of the dynamic site layout planning problem; (2) modeling the problem using approximate dynamic programming; and (3) implementing and evaluating the performance of the model. An evaluation example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating global optimal solution for dynamic site layout planning of construction projects.     

Minimum Cost Irrigation Network Design Using Interactive Fuzzy Integer Programming

Minimum cost irrigation network design has been conventionally based on crisp pressure requirements at the hydrants of the network. In order to incorporate obscure knowledge on these pressure requirements at the design stage, an interactive fuzzy integer programming methodology is proposed. In the integer linear programming, formulation membership functions are adopted for expressing pressure constraints. Also, the interactive character of the proposed methodology enables the designer to select a less demanding range of pressures at some “critical” hydrants. By using the proposed methodology significant economic gains may be achieved reducing the cost of the network, since the energy line is adapted more satisfactorily to the ranging pressure requirements. Finally, an application of the methodology to an irrigation network is presented.     

Fuzzy Inexact Mixed-Integer Semiinfinite Programming for Municipal Solid Waste Management Planning

Based on the concept of functional intervals, fuzzy inexact mixed-integer semiinfinite programming (FIMISIP) method is developed for municipal solid waste management planning. The method allows the uncertainties in parameters expressed as fuzzy, interval, and functional interval numbers to be directly communicated into the programming problem. The FIMISIP problem is solved by dividing it into two interactive semiinfinite programming (SIP) subproblems. Solutions reflecting the inherent uncertainties can then be generated by combining the SIP solutions into a set of decision intervals. The method is applied to a municipal solid waste management planning system for demonstrating its effectiveness in dealing with uncertain and dynamic complexities. Compared to the previous inexact programming methods, FIMISIP has the advantages as follows: (1) the dynamic complexity can be addressed by introducing the functional-interval parameters associated with time into the programming problem; (2) the FIMISIP solutions provide a set of flexible waste-management schemes to the decision makers; and (3) the FIMISIP solutions are more reliable than those from the previous ILP ones since they can be “really” optimal regardless of how the parameters vary with time within the time period. While this study is a first attempt to solve solid waste management issues under complex uncertainties, the method can be extended to other environmental management planning problems.     

Optimization of Water Distribution Networks Using Integer Linear Programming

In this study optimum design of municipal water distribution networks for a single loading condition is determined by the branch and bound integer linear programming technique. The hydraulic and optimization analyses are linked through an iterative procedure. This procedure enables us to design a water distribution system that satisfies all required constraints with a minimum total cost. The constraints include pipe sizes, which are limited to the commercially available sizes, reservoir levels, pipe flow velocities, and nodal pressures. Accuracy of the developed model has been assessed using a network with limited solution alternatives, the optimal solution of which can be determined without employing optimization techniques. The proposed model has also been applied to a network solved by others. Comparison of the results indicates that the accuracy and convergence of the proposed method is quite satisfactory.     

Performance-Based Optimization of Land and Water Resources within Irrigation Schemes. I: Method

Optimum land and water allocation to different crops grown in different regions of an irrigation scheme is a complex process, especially when these irrigation schemes are characterized by different soils and environment and by a large network of canals. At the same time if the water supply in the irrigation schemes is limited, there is a need to allocate water both efficiently and equitably. This paper describes the approach to include both productivity (efficiency) and equity in the allocation process and to develop the allocation plans for optimum productivity and/or maximum equity for such irrigation schemes. The approach presented in this paper considers the different dimensions of equity such as water distribution over the season, water distribution during each irrigation, and benefits generated. It also includes distribution and conveyance losses while allocating water equitably to different allocation units. This paper explains the approach with the help of the area and water allocation model which uses the simulation–optimization technique for optimum allocation of land and water resources to different crops grown in different allocation units of the irrigation scheme.     

Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning

The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near-optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables.     

Optimization Model for Allocating Water in a River Basin during a Drought

Optimization of water use is a complex problem in a large scale river basin. One of the most important approaches in optimizing water use in a river basin is to find the relationship between water demand and water supply. The parameters that affect demand, supply, and the methods of evaluation of such elements are discussed in this study. Also, a method is presented for providing objective and constraint functions from considering these effects. Fuzzy logic theory is used to modify the stochastic dynamic programming (SDP) method such that an optimization model is developed for allocating water and can be defined as the “stochastic fuzzy dynamic programming (SFDP)” method. This method is applied to optimize water use in the Kor and Seevand river basins, located in the Bakhtegan watershed, Fars, Iran. The primary water resources management consisted of the variability ranges of decision variables such as release from Doroodzan Dam and reservoir storage and was also used for allocating water in these river basins based on the SDP method. Therefore, in the present study, these variability ranges are obtained based on historical data, and divided into several record classes. Optimum class of release, a case of the record classes, was obtained from the optimization model for each month during the past 4 out of 25 years. Although, the SFDP method can be used in optimizing water allocation during each period, the method is structured and discussed only during the drought periods (4 years). Later, a comparison was made between optimum classes and record classes that were operated during the primary water resources management. During this period, the SFDP method reduced the difference between the release from the dam and the total water demand of the river basin. Therefore, approximately a 27% improvement in adaptation between release and demand could be attained. Finally, if the decision maker makes the decision for the release from the dam that is optimal according to our objective function, the reliability of reservoir operating can be increased by 51% during future droughts.     

Performance-Based Optimization of Land and Water Resources within Irrigation Schemes. II: Application

The area and water allocation model which uses simulation–optimization technique for optimum allocation of land and water resources to different crops cultivated in different allocation units of the irrigation scheme was modified to include both productivity and equity in the process of developing the allocation plans for optimum productivity and/or maximum equity. This paper illustrates the potential of this approach with the help of a case study on Nazare medium irrigation scheme in India. The allocation plans were developed for optimization of different performance parameters (productivity and equity) for different management strategies based on irrigation amount and irrigation interval and cropping distribution strategies of free and fixed cropping. The results indicated that the two performance objectives productivity and equity conflict with each other and in this case, equitable water distribution may be preferred over free water distribution at the cost of a small loss in productivity. Though these results relate to one case study, they show the value of the approach of incorporating productivity and equity in the allocation process with the help of the simulation-optimization model described in the companion paper.     

Fuzzy Active Control of Flexible Structures by Using Electromagnetic Actuators

Numerical and experimental investigations are carried out to assess the possibility of controlling a flexible beam by using an electromagnetic actuator (EMA). The advantage of EMAs is that they do not require contact with the structure so they can be applied to light and small mechanisms. Nevertheless, their open-loop instability and nonlinear dynamic behavior relating to excitation frequency can limit their fields of application. The EMA is designed and dimensioned as a function of the structure to be controlled. The effect of the EMA is considered a restoring force; consequently, the structure is still linear, which enables the calculation of the modal matrices of the structure. Moreover, an inverse model of the EMA is proposed to implement a linear action block for the frequency range used. The gap distance is estimated by using a modal approximation of the displacements resulting from the measurements. The control strategy is a fuzzy controller with displacements and velocities as inputs. Fuzzy controllers are used for their effectiveness in the presence of nonlinearities and uncertainties. The system is modeled and the characteristics of the model are identified experimentally. Several control configurations are assessed by using numerical simulations, and then the controller is tested experimentally in the context of impact perturbations. The results show the effectiveness and robustness of the developed control.     

Dual-Interval Fuzzy Stochastic Programming Method for Long-Term Planning of Municipal Solid Waste Management

In many real-world problems, quality of the available information is generally poor and uncertainties presented as multiple formats may exist in various system components. In this study, a dual-interval fuzzy stochastic programming (DIFSP) method is developed for tackling uncertainties presented as dual intervals and random variables within a multistage context. The developed method is applied to a case study of long-term planning of a municipal solid waste-management system. It has been demonstrated that DIFSP has advantages in addressing the dynamic, interactive, and uncertain characteristics. Moreover, it can reflect dynamics in terms of both waste-flow allocation and facility-capacity expansion through constructing a multilayer scenario tree. With the aid of an interactive algorithm woven with a vertex analysis, solutions for waste-flow allocation and facility-capacity expansion under various uncertainty levels in decision making may be illuminated in support of solid waste-management system planning in urban regions. They can help decision makers to identify desired waste-management policies with minimized system cost and maximized environmental efficiency.     

Stochastic Time-Cost-Resource Utilization Optimization Using Nondominated Sorting Genetic Algorithm and Discrete Fuzzy Sets

In a construction project, the cost and duration of activities could change due to different uncertain variables such as weather, resource availability, etc. Resource leveling and allocation strategies also influence total time and costs of projects. In this paper, two concepts of time-cost trade-off and resource leveling and allocation have been embedded in a stochastic multiobjective optimization model which minimizes the total project time, cost, and resource moments. In the proposed time-cost-resource utilization optimization (TCRO) model, time and cost variables are considered to be fuzzy, to increase the flexibility for decision makers when using the model outputs. Application of fuzzy set theory in this study helps managers/planners to take these uncertainties into account and provide an optimal balance of time, cost, and resource utilization during the project execution. The fuzzy variables are discretized to represent different options for each activity. Nondominated sorting genetic algorithm (NSGA-II) has been used to solve the optimization problem. Results of the TCRO model for two different case studies of construction projects are presented in the paper. Total time and costs of the two case studies in the Pareto front solutions of the TCRO model cover more than 85% of the ranges of total time and costs of solutions of the biobjective time-cost optimization (TCO) model. The results show that adding the resource leveling capability to the previously developed TCO models provides more practical solutions in terms of resource allocation and utilization, which makes this research relevant to both industry practitioners and researchers.     

Operational Monitoring of Daily Crop Water Requirements at the Regional Scale with Time Series of Satellite Data

This work presents a simple, cost-effective, and operational approach to monitor crop water requirements at the regional scale for water management and monitoring purposes. The recommended Food and Agricultural Organization of the United Nations methodology (FAO-56) calculates crop evapotranspiration using crop-specific coefficients (Kc), which vary according to the crop type, health, and phenological stage. This approach, though widely applied for irrigation planning, cannot always match the appropriate crop coefficient with the actual crop phenological stage and health condition, especially in anomalous situations. Previous research demonstrated that crop coefficients and spectral vegetation indexes are correlated. Recent studies have used this relationship with high-resolution satellite data from different sensors to provide information to irrigation advisory services. However, high-resolution data are not feasible for an operational and routine monitoring of water consumption and needs. This paper tests the usefulness of time series of coarse resolution satellite data such as those collected by the moderate-resolution imaging spectroradiometer (MODIS) sensor, to monitor crop coefficients temporal and spatial variability and therefore crop water needs at the regional scale taking advantage of the peculiar characteristics offered by MODIS in terms of high temporal resolution and preprocessed products availability. The outlined methodology takes into account the actual growing stage of the crops and nearly real-time vegetation variations, overcoming some limitations of the traditional FAO approach while preserving the maximum operability. The analysis was carried out in the South Milan agricultural area on data referring to 2003 and 2004. The results agreed with those of other studies and proved to be able to account for the anomalous conditions of the summer in 2003. These results were then compared with those obtained using the traditional FAO crop coefficient curves built with data collected during field campaigns in the same years in rice fields. Constraints, limitations, and possible uses are discussed.     

Tank Simulation for the Optimization of Water Distribution Networks

In this paper an original approach to the simulation of floating-on-the-system tanks as decision variables for water distribution system design optimization is presented, aiming to bridge the gap between traditional engineering practice and mathematical considerations needed for genetic algorithms (GAs). The paper includes a systematic and detailed critical overview of various mathematical approaches in literature, as well as a novel, more “engineering oriented” approach to the simulation of tanks as decision variables for water distribution system design optimization, describing in detail assumptions and impacts to the evaluation of potential solutions. Tank simulation is based on two decision variables: capacity and minimum normal operational level, omitting risers. Shape and ratio between emergency/total capacities are taken into consideration as design parameters. Assessment of tank performance is carried out by four criteria for the normal daily operational cycle, differentiating between operational and filling capacity, as well as two further criteria for emergency flows. The original design and operational mathematical assumptions are implemented in a fuzzy multiobjective GA model, which is applied to the well-known example from literature “Anytown” water distribution network to benchmark the results.     

模糊控制水泵变频调速技术的应用

介绍了重钢动力厂４~#泵站采用模糊控制技术对水泵进行变频调速的情况。重点叙述了模糊控制器结构、原理及应用该技术后的节能效果。     

Modeling the Behavior of Flow Regulating Devices in Water Distribution Systems Using Constrained Nonlinear Programming

Currently the modeling of check valves and flow control valves in water distribution systems is based on heuristics intermixed with solving the set of nonlinear equations governing flow in the network. At the beginning of a simulation, the operating status of these valves is not known and must be assumed. The system is then solved. The status of the check valves and flow control valves are then changed to try to determine their correct operating status, at times leading to incorrect solutions even for simple systems. This paper proposes an entirely different approach. Content and co-content theory is used to define conditions that guarantee the existence and uniqueness of the solution. The work here focuses solely on flow control devices with a defined head discharge versus head loss relationship. A new modeling approach for water distribution systems based on subdifferential analysis that deals with the nondifferentiable flow versus head relationships is proposed in this paper. The water distribution equations are solved as a constrained nonlinear programming problem based on the content model where the Lagrangian multipliers have important physical meanings. This new method gives correct solutions by dealing appropriately with inequality and equality constraints imposed by the presence of the flow regulating devices (check valves, flow control valves, and temporarily closed isolating valves). An example network is used to illustrate the concepts.     

Analysis of Nighttime Driver Behavior and Pavement Marking Effects Using Fuzzy Inference System

Nighttime driving behavior differs from that during the day because of differences in the driver’s field of view. At night, drivers must rely on their vehicle headlamps to illuminate the roadway. It is essential then that the roadway delineation system provide the appropriate lane guidance to motorists when navigating a roadway, particularly one that is curvilinear. A nighttime driving experiment was conducted to collect user perception data of various pavement markings and markers applied to horizontal curves. The effectiveness of each pavement marking was rated using a subjective scale. A fuzzy inference system was used to analyze the subjective pavement marking and marker evaluation ratings provided by the research participants. Pavement marking effectiveness, horizontal curve sharpness, and driver age were used to develop a fuzzy index for nighttime driving condition (FIND). Based on the FIND, the results indicate that drivers prefer that a combination of treatments be applied to horizontal curves rather than only a single treatment. A bright centerline, bright edgeline, and bright retroreflective raised pavement maker combination treatment, and a bright centerline and bright edgeline combination treatment, resulted in the highest FIND score. A bright, 8-in. (20.3 cm) edgeline, applied alone to a horizontal curve, scored the lowest FIND.     

Dynamic Modeling of Bentazon Removal by Pseudo-Moving-Bed Granular Activated Carbon Filtration Applied to Full-Scale Water Treatment

A model for the removal of pesticides by granular activated carbon (GAC) filtration in full-scale water treatment is presented. The model describes GAC filtration in a pseudo-moving-bed configuration, where two filters are operated in series and after breakthrough the first filter is regenerated and becomes the second filter. The influent of the second filter is changing due to gradual breakthrough of the first filter. Therefore, a dynamic model is developed based on kinetics, equilibrium, and mass balance equations. The model is calibrated and validated on data of full-scale and pilot plants. Operational strategies are evaluated of two different cases. From this study it can be concluded that a dynamic mathematical model can be successfully used to evaluate the performance and operation of full-scale GAC filters for pesticide removal and can be used for operational decision support. Data obtained from practice can be used for calibration without additional laboratory work.     

Development and Evaluation of Soil Moisture-Based Seepage Irrigation Management for Water Use and Quality

A 2-year study was conducted at a seepage-irrigated vegetable farm in south Florida to develop and evaluate an improved, soil moisture-based irrigation management practice that could potentially reduce irrigation water use, prevent water quality impairment, and maintain or improve crop yield. The improved practice reduced irrigation water use by 36% compared to the conventional irrigation management. Moreover, the improved practice also increased rainfall retention and decreased runoff events by lowering the water table 13?cm compared to the conventional practice. Total dissolved phosphorus (P) concentrations in groundwater were higher (p<0.01) for the improved practice compared with the conventional practice in two of the three fields where ground water quality was monitored. Higher P concentrations for the improved practice were likely due to the dilution effect. Statistically, no differences (p>0.05) were observed in groundwater nitrogen (N) (NOx–N, NH4–N, and total dissolved N) concentrations between the improved and the conventional practices. Similarly, no statistical difference was observed in crop yield between the improved and the conventional practices, although the average total yield was higher for the improved practice. The improved practice also reduced the incidence of plant disease compared to the conventional practice which resulted in crop failure in some fields. Thus, use of the improved practice reduced irrigation water use without impacting crop yield.