Evaluation of Optimal River Training Work Using GA Based Linked Simulation-Optimization Approach

Use of structural measures for controlling a river to minimize its devastating effect and to utilize it for the benefit of mankind is a common practice all over the world. Because of high investment, such measures require prior investigation through model study. As lab based physical model study is very expensive and time consuming, mathematical modeling is generally used for investigating different alternatives of river training works. In this study, a new approach is proposed for deciding appropriate river training measure in a particular reach of a river or channel. In this methodology, an optimization model is linked with the hydrodynamic model for obtaining cost effective combination of groynes which will maintain a user defined flow speed in a pre-decided portion of a river reach. The optimization model is developed using binary coded Genetic Algorithm (GA) and the flow simulation model uses the Beam and Warming scheme for solving the two dimensional (2D) hydrodynamic equations of unsteady flow. The performance of the model is tested by applying the methodology in a rectangular channel for attaining different target speed values at a pre-defined portion of the channel and logical results have been obtained for all the tested scenarios.     

Conjunctive Operation of Reservoirs and Ponds Using a Simulation-Optimization Model of Irrigation Systems

Water resource management in arid agricultural irrigation regions is a great challenge for managers and decision makers. In some of those regions, many ponds have been built to ensure an adequate water supply for irrigation. Therefore, reservoirs and ponds should be managed conjunctively to minimize shortages of water. In this study, a new integrated mathematical model of conjunctive, or integrated, operation of reservoirs and ponds to maximize the water supply has been proposed for a reservoir-pond irrigation system. This objective has been achieved via the use of two models: an optimal model, which is used to determine the optimal discharge of reservoirs, and a simulation model, which considers the regulatory role of ponds and reservoirs and simulates their water supply to the irrigation system. An adaptive genetic algorithm has been employed in this study to solve the nonlinear and multi-dimensional reservoirs optimization problem. This methodology has been applied to the Yarkant River Basin to demonstrate its applicability, and three scenarios are presented. The main objective of the simulation-optimization model in the Yarkant River Basin is to minimize shortages in meeting irrigation demands for nine sub-irrigation systems subject to the constraint of ecological water transfer to the Tarim River. The optimizing effect of the model was particularly prominent under the third scenario, i.e., the XBD, MMK, and ART Reservoirs and 16 ponds conjunctively operated to meet the water demand of the YKB. The frequency of success (FS) in meeting agricultural water demands reaches up to 75%, and the value for ecological demand is 50.98%. The results demonstrate the importance of the conjunctive combined use approach for management of water resources in irrigation system of arid regions.     

Multi Objective Simulation-Optimization Approach in Pollution Spill Response Management Model in Reservoirs

In this study, a Pollution Spill Response Management Model (PSRMM) is developed to provide an emergency response on reservoir operation during accidental injection of hazardous material to reservoirs. PSRMM consist of spatial system analyzing (SSA) model, 2D hydrodynamic and water quality simulation model (CE-QUAL-W2), and multi-objective particle swarm optimization (MOPSO) algorithm. CE-QUAL-W2 model is applied for spatial and temporal analysis of water body in simulation routine of PSRMM. Also, in an advanced modeling framework, CE-QUAL-W2 is coupled with MOPSO algorithm to obtain desirable near optimal reservoir operation strategy and/or emergency planning in selective withdrawal framework. The simulation-optimization (SO) routine of PSRMM provides pareto optimum reservoir operation strategy in selective scheme to minimize reservoir cleanup time and to reduce the magnitude and frequency of water quality standard violations. The proposed tool is applied in Ilam reservoir in Iran, as a multipurpose hydraulic project providing water for drinking, irrigation, and flood control during an accident spill of conservative hazardous material. Different scenarios are defined and tested employing the proposed PSRMM for managing accidental spill of conservative pollutant into the reservoir.     

Irrigation Planning and Management Through Optimization Modelling

Proper planning and management of irrigation is vital in achieving food security for the burgeoning global population and sustaining livelihoods. Because irrigated agriculture is expected to provide more food, if managed properly. The comprehensive reviews on the use of various programming techniques used for planning and management of irrigation have been provided in this paper. The literature review revealed that the management models used in the past mainly considered the objectives of maximization of net farm income, minimization of waterlogging, and minimization of groundwater depletion. These objectives were achieved by optimizing the allocation of available land and water resources. The past reviews are grouped into four sections based on the programming techniques adopted. The sections include: linear programming, nonlinear programming, dynamic programming, and genetic algorithms. This review provides the basis for the selection of appropriate methodology for the planning and management of irrigation.     

Integrated Sustainable Irrigation Planning with Multiobjective Fuzzy Optimization Approach

Multiobjective fuzzy methodology is applied to a case study of Khadakwasla complex irrigation project located near Pune city of Maharashtra State, India. Three objectives, namely, maximization of net benefits, crop production and labour employment are considered. Effect of reuse of wastewater on the planning scenario is also studied. Three membership functions, namely, nonlinear, hyperbolic and exponential are analyzed for multiobjective fuzzy optimization. In the present study, objective functions are considered as fuzzy in nature whereas inflows are considered as dependable. It is concluded that exponential and hyperbolic membership functions provided similar cropping pattern for most of the situations whereas nonlinear membership functions provided different cropping pattern. However, in all the three cases, irrigation intensities are more than the existing irrigation intensity.     

Pond and Irrigation Model (PIM): a Tool for Simultaneously Evaluating Pond Water Availability and Crop Irrigation Demand

Agricultural ponds are an important alternative source of water for crop irrigation to conserve surface and ground water resources. In recent years more such ponds have been constructed in Mississippi and around the world. There is currently, however, a lack of a tool to simultaneously estimate crop irrigation demand and pond water availability. In this study, a Pond-Irrigation Model (PIM) was developed to meet this need using STELLA (Structural Thinking, Experiential Learning Laboratory with Animation) software. PIM simulated crop land and agricultural pond hydrological processes such as surface runoff, soil drainage, and evapotranspiration as well as crop irrigation demand and pond water availability. More importantly, PIM was able to decide when to conduct crop irrigation based on management allowable depletion (MAD) root zone soil water content and to determine optimal ratios of agricultural pond size to crop land with sufficient pond water available for crop irrigation. As a case demonstration, the model was applied to concomitantly estimate row crops (i.e., corn, cotton, and soybeans) water irrigation demand and pond water availability in a farm located at East-central Mississippi. Simulations revealed that corn used more soil water for growth than soybeans, whereas soybeans needed more irrigation water than corn and occurred due to less rainwater available for soybeans growth. We also found that there was one time for corn, zero time for cotton, and two times for soybeans when the pond water level was drawn to near zero for irrigation from 2005 to 2014. PIM developed in this study is a useful tool for estimating crop irrigation demand and pond water availability simultaneously.     

Ranking Irrigation Planning Alternatives Using Data Envelopment Analysis

Application of Data Envelopment Analysis (DEA) as a Multicriterion Decision Making (MCDM) methodology is tested for Sri Ram Sagar Project, Andhra Pradesh, India to select the suitable irrigation planning alternative. Three different criterion functions of DEA, namely minimizing deviation variable D_j (Min,D_Dj), minimizing maximum deviation (Minmax), and minimizing the sum of deviations ∑D_j (Minsum) are applied for the same DEA constraint set. These criterion functions are evaluated under the framework of Multi Objective Linear Programming (MOLP). Highest efficiency rated irrigation planning alternative is chosen to be the best for each of the above criterion functions. The results are compared with those obtained by discrete MCDM methods, PROMETHEE and EXPROM. It is found that ranks obtained by DEA are reasonably close to those obtained by the above mentioned MCDM methods, PROMETHEE and EXPROM.     

Analysis of Irrigation Needs Using an Approach Based on a Bivariate Copula Methodology

The problem of drought probability has been investigated by several authors, who have usually analysed droughts using various drought indices such as the Standard Precipitation Index. Various aspects of time series of such indices (intensity, severity and duration) were investigated by several authors using a copula method. Because such analysis is based on only one basic climatic variable, this paper addresses a different approach, i.e., joint analysis of the severity and duration of the most demanding potential annual irrigation periods by a bivariate copula method. Characteristics of these periods are derived from both temperature and precipitation. Maximum annual duration of the potential irrigation period and corresponding rainfall deficit were inferred from these basic variables as inputs to two-dimensional probability analysis by the copula method, because this offers more direct answers to questions of irrigation needs. Results indicate the suitability of the proposed method for analysis of irrigation needs, with greater benefits than the typical one-dimensional analysis of individual climatic variables. A case study for testing the method was done for southwestern Slovakia, for which the frequency of irrigation needs was estimated. Example results indicate that every second year, a one-month period can be expected in which temperatures are >25^°C and there is a moisture deficit of ～30 mm. Even more significant periods of drought can be expected, for example, with a 5 or 10-year return period. These phenomena significantly damage agriculture yields, so requirements for irrigation structures in the study area are indicated by the proposed method.     

Development of an Improved Pollution Source Identification Model Using Numerical and ANN Based Simulation-Optimization Model

The identification of unknown pollution sources is an important and challenging task for the engineers working on pollution management of a groundwater aquifer. The locations and transient magnitude of unknown contaminant sources can be identified using inverse optimization technique. In this approach, the absolute difference between the simulated and the observed contaminant concentration at the observation locations of the aquifer is minimized by using an optimization algorithm. The simulated concentrations is calculated using the aquifer simulation model. As such, there is a need to incorporate the aquifer simulation model with the optimization model. Thus the performance of the model is highly related to the aquifer simulation model. The incorporation of the sophisticated numerical simulation model will give better performance, but the model will be computationally expensive. On the other hand, the model will be computationally less expensive if an approximate simulation model is used in place of the numerical simulation model. However, in this case, the predictive performance of the model will decline. For achieving efficiency in both computational time as well as in predicting the performance, this study presents a new genetic algorithms based simulation-optimization method incorporating both the numerical and the approximate simulation models. The efficiency and field applicability of the model is demonstrated using illustrative study areas. The performance evaluation of the model shows that the proposed model has the potential for real-world field applications.     

Integrated Approach for Supporting Sustainable Water Resources Management of Irrigation Based on the WEFN Framework

Irrigated agriculture plays a vital role for the socio-economic development of the Mediterranean area, although it has significant impacts on both water and energy resources. Therefore, in a context in which water resources are also experiencing increasing pressures, there is an urgent need for supporting their sustainable management. This may be an extremely challenging task, especially at the local scale, due to the several interconnected dynamics affecting the state of a complex irrigation system. In fact, multiple actors are involved in decision-making processes, and the use of natural resources (and their mutual interactions) strongly depends on their behaviors, which affect the system as a whole. In this context, the present study proposes an integrated methodology, based on the Water Energy Food Nexus (WEFN), specifically focused on the sustainable management of water resources for irrigation. Firstly, a model based on Causal Loop Diagrams (CLD) is developed in order to get a deep insight into the key dynamics behind a complex irrigation system. Secondly, three indices based on the “footprint” concept are identified, in order to synthesize such dynamics. The integration of these two approaches support investigating the whole system and, particularly, understanding the influence of multiple decisional actors on it, as well as the role of a set of key drivers and constraints. This might also allow drawing some relevant conclusions, useful for supporting effective decisions oriented to a sustainable water resources management. Specific reference is made to a case study, the Capitanata irrigation system, located in the Southern Italy.

     

Fuzzy Stress-based Modeling for Probabilistic Irrigation Planning Using Copula-NSPSO

Hydrological uncertainties are the main components of a sustainable framework in agricultural water management. Prediction of drought as a meteorological phenomenon should be considered to define the groundwater exploitation strategies. This study was conducted to develop a multiobjective-bivariate structure for reducing the soil moisture deficit and groundwater withdrawal in the Qazvin Irrigation District, Qazvin province, Iran. Therefore, non-dominated sorting theory, self-organizing particle swarm optimization and bivariate copula functions were incorporated under fuzzy uncertainty analysis. The results showed that the generalized extreme values and log-normal distribution functions had the best fitness on the drought peak and severity with Kolmogorov Smirnov amounts of 0.08 and 0.17, respectively. Furthermore, the goodness-of-fit tests were indicated the Joe joint function (MLE = 11) is the appropriate function for estimating the probabilistic values of drought characteristics. Proposed plans were to increase the water use efficiency for improving the expected yield production by an average of 20%. Furthermore, the standardized groundwater index was decreased from 1.1 to –4.3 for winter crops.

     

Simulation-Optimization Modeling of Conjunctive Operation of Reservoirs and Ponds for Irrigation of Multiple Crops Using an Improved Artificial Bee Colony Algorithm

Seasonal drought has become an important factor in agricultural production in humid and semi-humid areas. In this study, to mitigate the impact of seasonal drought, a new integrated mathematical model is proposed for optimal multi-crop irrigation scheduling, which is associated with conjunctive operation of reservoirs and ponds to maximize the annual returns for a reservoir-pond irrigation system. This objective is achieved via the use of two models: an operating policy model, which considers the regulatory role of ponds and optimizes reservoirs and ponds releases in one third of a month, and an allocation model, which optimizes irrigation allocations across crops by addressing water production function. The uneven distribution of ponds is also considered by dividing the irrigation district into many sub-districts. Artificial bee colony algorithm is innovatively improved by incorporating differential evolution algorithm and particle swarm optimization algorithm to solve this nonlinear, high-dimensional and complex optimization problem. The methodology is applied to the Zhanghe Irrigation Distict, which is located in Hubei Province of China, to demonstrate its applicability, and three additional models are simulated to demonstrate the validity of the integrated model. The results indicate that the integrated model can alleviate the impact of the seasonal drought and has remarkable optimization effect, especially for drought years. The average annual return calculated by the integrated model is 7.9, 7.0 and 3.1 % higher than that of the remaining three models, respectively. And in the special dry year, in which the frequency of rainfall is 95 %, the annual return calculated by the integrated model is 24.5, 21.8 and 10.1 % higher than that of the remaining three models, respectively.     

Crop Calendar Adjustment Study for Sathanur Irrigation System in India Using Genetic Algorithm

The multiple objectives and interests of various stack holders’ in reservoir operation bring forward many solutions to the problem. Possibly due to this complexity, in practice, the operating rules to be derived not only from heuristic approaches such as rules of thumb, rule curve, operator experience and engineering judgments but also through well defined mathematical models. An attempt is made to study the possibility of changing the crop (paddy crop instead of groundnut) and crop starting period for Sathanur irrigation system, India. This system is considered as one of the water-deficit irrigation system where the water is collected in the reservoir during north-east monsoon (Oct–Dec) and crops are cultivated after the rainfall season. Even though the first priority is to supply drinking water to Tiruvanamalai town and nearby villages, the quantity required for drinking water is very meagre when compared to irrigation demands. Genetic algorithm (GA) has been used to find the optimal crop-starting period that can give maximum performance and net benefit from the system. The results of the model study indicate that starting the cultivation of paddy crop between 1st and 10th of October every year provides maximum net benefit than starting the cultivation between 11th and 20th of December as practiced now.     

作物需水量与灌溉制度模拟

从作物需水量的基本概念出发，以水量平衡原理为基础，建立了模拟农田根层土壤水循环的计算机模型-ISAREG.这一模型具有多种功能，可模拟根层土壤水分变化，评价给定的灌溉制度，计算作物需水量和灌溉需水量，也可用以制订多种供水限制条件下的优化灌溉制度．用望都灌溉试验站的小麦、玉米、棉花3种作物两年的试验观测资料对上述模型进行了验证．     

A Planning Model for the Fuerte-Carrizo Irrigation System, Mexico

A methodology is presented for planning the operation of the Fuerte-Carrizo irrigation system in northwest Mexico. The system has two storage dams, two irrigation districts, and water transfer capabilities between both dams. The methodology uses a combination of linear programming (LP) and simulation. The LP model maximizes the net return of the farmers, subject to restrictions of the system, availability of water and land, and water transfer relationships. The simulation model is programmed as a microcomputer interactive package simulating the performance of the system. The methodology has proven to be a useful tool to assist those responsible for the operation of the irrigation system.     

A Comprehensive Approach for Spatial and Temporal Water Demand Profiling to Improve Management in Network Areas

The aim of this paper is to present a comprehensive approach for spatial and temporal demand profiling in water distribution systems. Multiple linear regression models for estimating network design parameters and decision trees for predicting daily demand patterns are presented. Proposed approach is a four-step procedure: data collection, data processing, data characterization, and spatial and temporal demand profiling. Continuous flow measurements and infrastructure and billing data were collected from a large set of water network areas and combined with census data. Main results indicate that family structures (i.e., families with elderly or adolescents), individuals’ mobility (i.e., people employed in the tertiary sector and university graduates) and public consumption (i.e., public spaces’ irrigation) are key-variables to profile water demand. Profiling models are of the utmost importance to describe water demand in areas with no monitoring but with similar socio-demographic characteristics to the ones analyzed, to improve network operation and to support network planning and design in new areas. Obtained models have been tested for new areas, showing good prediction performances.     

灌溉用水需求分析与节水灌溉发展研究

随着新的灌溉技术以及节水技术的不断发展,为了适应新时期的发展,实施灌溉用水总量控制和定额管理成为现代农业发展中的重中之重,同时也是水资源合理配置、节约使用在灌溉用水管理上的具体体现,也是分配灌溉用水使用权的基本依据。因此,仔细的分析灌溉用水需求,发展节水灌溉技术,从不同视角、不同层面进行逐步深入的探讨是有必要的。文章针对灌溉用水需求进行分析,并对灌溉技术的发展进行探讨。     

Coupled Simulation-Optimization Model for the Management of Groundwater Resources by Considering Uncertainty and Conflict Resolution

Water Resources Management - Determining the optimized policies in the exploitation of groundwater water resources is a complicated issue, especially when there are several different managers with...     

Optimal Size of Auxiliary Storage Reservoir for Rain Water Harvesting and Better Crop Planning in a Minor Irrigation Project

The scope and feasibility of auxiliary storage reservoir in the outlet command of a flow based minor irrigation project was studied to overcome the inadequate irrigation water availability during the dry season. A multi objective optimization model was developed to determine the optimal size of auxiliary storage reservoir and optimal cropping pattern. Assuming that about 50% main reservoir capacity water will be available for irrigating dry season crops and fixing the first priority level of the objective function as maximization of net seasonal benefit and maximization of cropped area, the optimal surface area for auxiliary storage reservoir as the percentage of the command area was obtained as 17.40% and 10.92%, respectively. The performance of the minor irrigation project significantly increased due to provision of auxiliary storage reservoir. The economic analysis also revealed that the intervention is economically viable.     

A Socioeconomic Valuation of an Irrigation System Project Based on Real Option Analysis Approach

Traditional net present value methods used to evaluate potential projects make no allowance for flexibility and assume a static environment. The concept of real options has extended into irrigation systems to model design flexibility in the realistically uncertain environment. In particular, this article extends the evaluation techniques of an irrigation dam by combining the real options approach along with the traditional on (Discount Cash Flow). However, whereas financial options are well-defined traded contracts, real options in irrigation systems are a priori undefined, complex and interdependent. Moreover, irrigation systems involve many more options than designers could consider. Therefore designers need to identify the real options most likely to offer good flexibility and the most value. This paper demonstrates the ease that irrigation systems economic analysis with risk analysis and real options can be valued by simulation software that is readily available to owners of personal computers. Sequentially, Discount Cash Flow analysis accompanied with real options approach facilitates decision making and encourages more sophisticated and realistic economic analysis of irrigation systems.