Performance Assessment of a Coupled Particle Swarm Optimization and Network Flow Programming Model for Optimum Water Allocation

Water resources allocation problems are mainly categorized in two classes of simulation and optimization. In most cases, optimization problems due to the number of variables, constraints and nonlinear feasible search space are known as a challenging subject in the literature. In this research, by coupling particle swarm optimization (PSO) algorithm and a network flow programming (NFP) based river basin simulation model, a PSO-NFP hybrid structure is constructed for optimum water allocation planning. In the PSO-NFP model, the NFP core roles as the fast inner simulation engine for finding optimum values for a large number of water discharges in the network links (rivers and canals) and nodes (reservoirs and demands) while the heuristic PSO algorithm forms the outer optimization cover to search for the optimum values of reservoirs capacities and their storage priorities. In order to assess the performance of the PSO-NFP model, three hypothetical test problems are defined, and their equivalent nonlinear mathematical programs are developed in LINGO and the results are compared. Finally, the PSO-NFP model is applied in solving a real river basin water allocation problem. Results indicate that the applied method of coupling PSO and NFP has an efficient ability for handling river basin-scale water resources optimization problems.     

Determination of the Optimal River Basin-Wide Agricultural Water Demand Quantities Meeting Satisfactory Reliability Levels

Water Resources Management - The unbridled increase in water demands and beyond-sustainable water withdrawals have led to decrease reliable supply levels, particularly for agricultural purposes in...     

Optimal Reservoir Operation with Water Supply Enhancement and Flood Mitigation Objectives Using an Optimization-Simulation Approach

Floods are one of the most destructive natural disasters which compensation of their effects inflicts immense costs especially in areas with human developments such as cities. Moreover, supplying water for demands particularly during the drought period is a challenging issue in water resource planning. The aim of this study is to propose a model for optimal operation of a reservoir with enhancing downstream demands supply and flood damage mitigation objectives. The model is developed by coupling MODSIM, river network simulation DSS with the imperialist competitive optimization algorithm (ICA). Gotvand Dam in southwestern Iran is the case of study and amounts of water storage in the reservoir in daily time-steps are the decision variable. Results indicate efficiency of the proposed optimization-simulation approach, suggesting that flood damages can be controlled with proper planning while ensuring that downstream water demands are satisfied. As an instance of results, the optimum reservoir rule curve obtained by the proposed model is able to manage a flood entering to the reservoir 11 times greater than the safe flow in the downstream reach and release it lower than the safe flow rate.     

Evaluation of the Bankruptcy Approach for Water Resources Allocation Conflict Resolution at Basin Scale,Iran’s Lake Urmia Experience

Water conflicts appear when there are insufficient and less available water resources than water demands claimed by different agents. In this study, a new bankruptcy approach is investigated to resolve water conflicts in the Zarrinehroud River Basin, the largest and most important sub-basin of Lake Urmia’s Basin in the northwest of Iran. The new bankruptcy method is compared with the proportional rule (PRO) and another alternative based on the cessation of irrigated agriculture in the region proposed to supply and save environmentally in danger Lake Urmia. Four scenarios consisting of the current situation, optimistic, average and pessimistic scenarios regarding the future of water resources of the basin and agricultural developments were considered. According to the results, both bankruptcy rules helped Lake Urmia to receive more water, but neither could utterly overcome the water shortage of the Lake, so can be used as supplementary actions alongside other solutions. The cessation of irrigated agriculture throughout the basin overcame the average annual shortage of Lake Urmia in the first and second scenarios equal to 137 and 148 million cubic meters respectively. It showed disability to fully supply the lake in the third and fourth scenarios. These three methods must be combined with a social-economic policy like the purchase of decreased water allocations to farmers to be socially acceptable.     

Comparative Application of Model Predictive Control and Particle Swarm Optimization in Optimum Operation of a Large-Scale Water Transfer System

Water Resources Management - This research evaluates the application and performance of two methods of Model Predictive Control (MPC) and Particle Swarm Optimization (PSO) in real time control and...     

Optimum Pumping Well Placement and Capacity Design for a Groundwater Lowering System in Urban Areas with the Minimum Cost Objective

High level of groundwater in urban areas may cause major problems in construction and mining projects. One effective solution is to implement drainage wells to lower the water table into the desired level through an appropriate pumping strategy. In this paper, placement and capacity of the dewatering wells are optimized by minimizing the total costs of a groundwater lowering system (GLS) through a simulation-optimization approach. For this purpose, MODFLOW, the groundwater simulation software, is coupled with the Firefly Optimization Algorithm (FOA) to find the optimal solution. The proposed FOA-MODFLOW model is tested in an urban area in east southern part of Iran, Kerman city’s ancient Mosque region. Results show that the obtained cost-effective design noticeably outperforms the consulting engineers’ proposal in terms of both the number of drilled wells and the associated costs with justifiable constraints. Optimal strategy satisfies the constraints by suggesting construction of two wells with totally pumping rate of 5503 m³/day while the water table is dropped 1.5 m with a ground subsidence less than 80 mm in the region. Additionally, an investigation on the value of various design parameters emphasizes on the sensitivity of the solutions to the permissible groundwater level and the well’s maximum pumping rates among the others.     

A Comparative Study of MLR,KNN, ANN and ANFIS Models with Wavelet Transform in Monthly Stream Flow Prediction

Water Resources Management - Reliable and precise prediction of the rivers flow is a major concern in hydrologic and water resources analysis. In this study, multi-linear regression (MLR) as a...     

Performance Assessment of the Linear,Nonlinear and Nonparametric Data Driven Models in River Flow Forecasting

In recent years, the data-driven modeling techniques have gained more attention in hydrology and water resources studies. River runoff estimation and forecasting are one of the research fields that these techniques have several applications in them. In the current study, four common data-driven modeling techniques including multiple linear regression, K-nearest neighbors, artificial neural networks and adaptive neuro-fuzzy inference systems have been used to form runoff forecasting models and then their results have been evaluated. Also, effects of using of some different scenarios for selecting predictor variables have been studied. It is evident from the results that using flow data of one or two month ago in the predictor variables dataset can improve accuracy of results. In addition, comparison of general performances of the modeling techniques shows superiority of results of KNN models among the studied models. Among selected models of the different techniques, the selected KNN model presented best performance with a linear correlation coefficient equal to 0.84 between observed flow data and predicted values and a RMSE equal to 2.64.     

Basin-wide Water Resources Planning by Integrating PSO Algorithm and MODSIM

Water resources planning and management at basin scale is such a large and complex problem that makes it essential to use effective modeling tools in order to obtain an optimum plan for river basins development. In this paper, a methodology is presented for optimized design and operation of the upstream Sirvan basin in Iran. The model proposed integrates MODSIM generalized river basin network flow model, with the capability of simulating various characteristics and features of water resources in a river basin, and Particle Swarm Optimization (PSO) algorithm. In the developed PSO-MODSIM model, the size of planned dams and water transfer systems, as design variables, and the relative priorities for meeting reservoir target storages, as operational variables, are varied and evolved using PSO algorithm. MODSIM is called to simulate the system performance and to evaluate the fitness of each set of those design and operational variables with respect to the model’s objective function. The PSO objective function is to maximize the total net benefit consisting of benefits due to supplying water to different types of water uses and construction costs of dams and water transfer and/or pumping systems. Varying the design and operational variables in MODSIM 8 is done using the MODSIM’s custom coding feature in VB.NET routine. The PSO-MODSIM model is used to size the planed water storage and transfer components of a river basin system and to allocate water resources optimally over time and space among competing demands, considering coordinated operation of the system components. The model results has been analyzed for different scenarios of water transfer from Sirvan to neighboring basins.     

A Demand Management Based Crop and Irrigation Planning Using the Simulation-Optimization Approach

Coupled simulation-optimization models are useful tools for solving optimum water allocation and crop planning problems. In this study, the optimum crops pattern in the Arayez plain in the Karkheh river basin in Iran is determined by integration of a network flow programming (NFP) based simulation model and the shuffle frog leaping optimization algorithm (SFLA) in the form of a simulation-optimization approach. MODSIM applies NFP for finding water allocations which by use of its customization ability, the benefit of water supply for the agricultural crops is calculated based on the agronomic equations. The objective function is to maximize the total net benefit gained from crops production where the decision variables which are the irrigation depths and the cultivation areas are optimized by SFLA. Results show that by use of the coupled SFLA-NFP model, the net benefit increases 12% comparing the present situation in the plain. Also, the sensitivity analyses on effective parameters indicate that the potential maximum yield and the net price of the crops yield in the market have a direct impact on the crops optimum cultivation area.