Environmental indices in irrigation management

Irrigation management calls for objective criteria capable of representing the economy, reliability, and productivity of irrigation systems. These criteria must be compatible with long-term sustainability and conservation goals. The criteria representing the above goals are the economic effect of management on yield reduction, economic effect, and reliability referring to plant growth and operation of the network. In this study environmental indices are introduced to express the above criteria in quantitative terms. The inclusion of these indices at the farm and network level create a multicriteria framework for decision-making based on composite programming. An experimental study was conducted during the irrigation periods of 1989 and 1990 in Chania, Greece, concerning water delivered to 40 experimental plots, soil moisture content at the rootzone, and irrigation system operational failures. The data collected in real time were used for the calculation of the corresponding environmental indices. The variation in time and space is high and resulted in up to 62% of yield loss and low system performance (up to 7% of system temporal reliability). The study indicated that environmental indices could be incorporated to select alternatives and also to develop policies on water delivery. The final decision involves a trade-off analysis between cost of application and desired system performance. Measures of both primary objectives can be obtained using environmental indices that represent system operation aggregation at its basic levels (on farm and network).     

多目标规划在产业结构优化中的应用——以秦皇岛市为例

秦皇岛是缺水城市，水资源短缺已成为制约经济发展的瓶颈。合理利用水资源对经济发展意义重大。本文采用多目标规划方法，构建了秦皇岛市水资源约束条件下的产业结构优化模型，提出了秦皇岛市产业结构优化方案。     

Global factors shaping the future of food aid: the implications for WFP

Food aid is a key component of a humanitarian response but its use in other programming contexts is subject to numerous criticisms. Even in humanitarian emergencies food aid is often late, unreliable and out of proportion to other elements of the response. Three major factors will shape the future of food aid. First, mechanisms of food aid governance are being reviewed and may undergo major changes—particularly the Food Aid Convention now that hopes have diminished for an Agreement on Agriculture at the World Trade Organisation. The second significant factor is donor agency trends. Overall levels of food aid have dropped fairly steadily in recent decades and there are several discernible trends in resource allocation, procurement and the use of food aid. The third factor is an emerging body of best practice that will define acceptable standards of food aid programming in the future.     

Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization

Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.     

Integrated model for renewable energy planning in Turkey

All economic sectors are associated with energy use; therefore, government organizations aim to supply sustainable energy for human needs and economic growth. In particular, increased environmental concerns of the public in Turkey have impacted policymaking for renewable energy (RE) management in Turkey. The primary objective for RE sources of the Turkish Ministry of Energy is to ensure that 30% of the share of electricity production is from RE resources in 2023. In this paper, the integrated multi-objective, multi-period linear programming model is presented to determine effective allocation of RE supply for seven different geographical regions in Turkey for the period of 2017 to 2024. The integrated model consists of two different stages. The first stage involves qualitative evaluations of RE sources for seven geographical regions. Analytical Hierarchy Process (AHP) is applied to determine criteria priorities and overall ratings of geographical regions across determined criteria for RE sources are computed. The second stage of the integrated model consists of a multi-objective, multi-period linear programming model. The proposed multi-objective linear programming model is coded in MPL (Mathematical Programming Language) and solved using the GUROBI 5.1.0 solver. The output of the integrated model presents the total supply amount of RE sources for geographical regions in planning period. The ε-constraints method is applied to compute the total supply amount of RE from geographical regions for the period of 2017 to 2024. In this study, a systematic decision-making model is generated to allocate renewable energy sources to the geographical regions. The presented model integrates qualitative evaluations and quantitative parameters of different geographical regions to determine the optimal supply amount of RE. The obtained results are consistent with the potential quantities of RE alternatives in geographical regions, regional specifications, and social requirements.     

A MULTIOBJECTIVE MODEL FOR REGIONAL WATER QUALITY MANAGEMENT1

ABSTRACT: Linear programming is the simplest of all the optimization techniques used in regional water quality management studies; but the technique can optimize only one goal. When there are multiple goals with the same or different priorities, goal programming is a useful decisionmaking tool. This paper illustrates the application of goal programming to a regional water quality management problem where the following two goals are considered: (1) minimize the total cost of waste treatment, and (2) maintain the water quality goals (dissolved oxygen) close to the minimum level stated in the stream standards.     

MANY RESOURCES,MANY USES: A SYSTEM ANALYSIS APPROACH TO RENEWABLE RESOURCE DEVELOPMENT1

ABSTRACT: Decisionmaking associated with the Nation's 1.7 billion acres of forest and range land has become increasingly complicated because of the rise in competition for resource use and in the awareness of environmental and social effects. This system analysis approach uses four models to synthesize pertinent masses of information into measures of economic, environmental, and social impacts. The system results can be used to help evaluate alternative national programs. The models are:

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OPTIMAL RESERVOIR MANAGEMENT AND CROP PLANNING UNDER DETERMINISTIC AND STOCHASTIC INFLOWS1

ABSTRACT: This study analyzes planning under deterministic and stochastic inflows for the Mayurakshi project in India. Models are developed to indicate the optimal storage of reservoir water, the transfer of water to the producing regions, and the spillage of water from the reservoir, if needed. A deterministic programming model was first formulated to represent the existing situation. A chance-constrained model then was constructed to evaluate potential violations of the deterministic model. Both models were quantified for the command area. Data were collected from surveys of the area and from government agencies. Both the deterministic and change-constrained models suggest a more intensive cropping program in the region. Both emphasize more dependence on rabi and less on kharif crops. The chance-constrained especially suggests use of more water in the rabi season. Important chances in cropping programs and labor use take place under the chance-constrained model.     

UNIT HYDROGRAPHS – A COMPARATIVE STUDY1

ABSTRACT. Unit hydrographs derived by using two methods, linear programming and least squares, are compared. Test data comprise rainfall and runoff information from four storms over the North Branch Potomac River near Cumberland, Maryland. The mathematical bases of these methods for unit-hydrograph derivation are explained. The linear programming method minimizes the sum of absolute deviations, and the least squares method minimizes the sum of the squares of deviations. Computer subroutines are readily available for application of these methods. The unit hydrographs derived with the two methods are practically the same for storms 2 and 3, but differ somewhat for storms 1 and 4. However, the reconstituted direct surface runoff hydrographs are similar to those observed with the exception of the hydrograph for storm 4 which had a relatively more non-uniform rainfall excess of a considerably larger duration.     

A CODED ALGORITHM FOR CAPACITY EXPANSION OF A WATER QUALITY MANAGEMENT SYSTEM1

ABSTRACT: This paper describes a mathematical model, an algorithm and a computer program that were specially developed to study the problem of a water quality management system undergoing a rapidly increasing environmental stress. The model output will determine the locations, sizes and the timing of construction of new treatment plants plus an overall treatment plant operating policy so that environmental standards are maintained at a minimum cost. The model, as formulated, is a 0-1 mixed integer programming problem which is solved by decomposing it into a capital budgeting problem (solved by Little's branch and bound algorithm) and an operational policy problem (solved by linear programming). The coded algorithm (in FORTRAN 10) has been tested with a semi-realistic example.