A decision tool for optimal irrigated crop planning and water resources sustainability

In the present study, the conjunctive use policies of surface and ground water resources are developed for minimizing water shortage in an irrigation district subject to constraints on groundwater withdrawals and crop planning capacities. An integrated soil water balance algorithm is coupled to a non-linear optimization model in order to carry out water allocation planning in complex deficit agricultural water resources systems based on an economic efficiency criterion. Various options of conjunctive use water resources along with current and proposed cropping patterns have been explored by Koohdasht Irrigation District (KID), a semi-arid region in I.R. Iran. The analysis provides various scenarios, which can help managers in decision-making for the optimum allocation plans of water resources within the irrigation area. The results reveal that the proposed model, as a decision tool for optimal irrigated crop planning and water resources sustainability, may be used for maximizing the overall net benefits and global water productivity of an irrigation district considering an allowable annual recharge of groundwater. Findings indicate the importance of the conjunctive water management modeling, which can be easily implemented and would enhance the overall benefits from cropping activities in the study area.     

MEASURING THE COSTS OF REALLOCATING WATER FROM AGRICULTURE: A MULTI‐MODEL APPROACH

ABSTRACT. Increasing demand for water by environmental interests, coupled with the diminishing prospects for constructing new water diversion projects, is forcing farmers in the western United States to cope with reduced surface water deliveries. The cost of improving instream water quality by reducing agricultural diversions is shown to depend mainly on how the supply reductions are allocated among users and on the extent of water trading. A central contribution of this paper is a methodology for measuring the impacts of water supply policy reforms on irrigated agriculture. The paper nests three empirical models in a general conceptual framework. The models differ in terms of their degree of detail and assumptions about input substitution. By comparing model results, it is possible to place bounds on the consequences of policy changes, and to identify critical factors determining economic impacts. The models are applied to the problem of improving water quality in the San Francisco Bay/Delta estuary.     

Multiobjective Linear Model Optimize Water Distribution in Mexican Valley

A multiobjective optimization model is developed for the Mexican Valley to find optimal water distribution scenarios for three water users: agriculture, industry and domestic. Surface, ground, treated and imported water supplies are considered. The model with three objectives and 15 constraints was solved by the distance based method with distance l ₁. Three scenarios and two priorities were analyzed for this problem. In Scenario 1, actual aquifer overexploitation and treated water usage were allowed. Scenario 2 considered the reduction of water extraction from the aquifer to one billion m³ (59%), and increased usage of treated water in agriculture by 50%. In Scenario 3, we assume aquifer sustainability and increasing surface water usage by 857 mill m³/year. The last scenario is the best because, in the worst case, the farmers can cover one season and also some crops in the second season, and the domestic users can get more water than their minimum demand. In addition, aquifer sustainability is implemented, which can reduce aquifer overexploitation. The waste water disposal problem, which is critical in this area, also can be reduced.     

An inexact rough-interval fuzzy linear programming method for generating conjunctive water-allocation strategies to agricultural irrigation systems

An inexact rough-interval fuzzy linear programming (IRFLP) method is developed for agricultural irrigation systems to generate conjunctive water allocation strategies. The concept of “rough interval” is introduced in the modeling framework to represent dual-uncertain parameters. After the modeling formulation, an agricultural water allocation management system is provided to demonstrate the applicability of the developed method. The results show that reasonable solutions and allocation strategies are obtained. Based on the analysis of alternatives obtained from different scenarios, the significant impact of dual uncertainties existing in the system is specified. Comparisons between the results from IRFLP and interval-valued fuzzy linear programming are also conducted. The obtained rough-interval solutions correspond to the management strategies under both normal and special system conditions, and thus more conveniences would be provided for decision makers. Compared to the previous modeling efforts, the proposed IRFLP shows uniqueness in addressing the interaction between dual intervals of highly uncertain parameters, as well as their joint impact on the system.     

OPTIMIZING THE PERFORMANCE OF IRRIGATED AGRICULTURE IN EASTERN ENGLAND UNDER DIFFERENT WATER PRICING AND REGULATION STRATEGIES

Irrigation water shortage is becoming an increasingly serious problem in agricultural production. Growing pressure on water resources is leading to increasing restrictions on abstraction for irrigation and consideration of the use of economic instruments, such as increased abstraction charges and/or tradable licences, to restrict demand and encourage wiser use of water. We evaluate irrigation using selected economic, social, and environmental indicators of performance, including the value of water used for irrigation. A linear programming model is developed and used to simulate possible responses by irrigators and the impact on irrigation performance of intervention measures, namely abstraction quota restrictions and volumetric pricing that might be used to ration water and/or increase water use efficiency. Through the use of parametric programming a scenario analysis is performed to a case study in eastern England with regard to perturbations of irrigation water under alternative policy instruments.     

Unit commitment in electricity pool markets

We consider an electricity generator making offers of energy into an electricity pool market over a horizon of several trading periods (typically a single trading day). The generator runs a set of generating units with given start-up costs, shut-down costs and operating ranges. At the start of each trading period the generator must submit to the pool system operator a new supply curve defining quantities of offered energy and the prices at which it wants these dispatched. The amount of dispatch depends on the supply curve offered along with the offers of the other generators and market demand, both of which are random, but do not change in response to the actions of the generator we consider. After dispatch the generator determines which units to run in the current trading period to meet the dispatch. The generator seeks a supply function that maximizes its expected profit. We describe an optimization procedure based on dynamic programming that can be used to construct optimal offers in successive time periods over a fixed planning horizon.     

Incorporating market characteristics into physical distribution models

This paper is concerned with incorporating the interactive effects of location, price and demand into mathematical models of distribution systems. Equations for distribution costs, capital investment, demand and gross profit margin are introduced and from these, profit and return on investment equations are derived. For a given number of depots, a search procedure is derived to determine the locations of the depots which maximise the derived profit equation. A similar search procedure is derived to maximise return on investment. The maximum profit and maximum return on investment solutions are compared and it is deduced that for a fixed gross profit margin, these solutions will be almost identical. Finally, the search procedures are applied to real data and observations are made on how the type of location determined by the search procedures varies as the market characteristics vary.     

A Decision Support System for Micro-Watershed Management in India

The improvement of economic conditions in developing countries like India is crucially dependent on improvement in agriculture. Crop production depends on the volume of irrigation water and its temporal distribution, water quality, solar radiation, precipitation and a host of soil properties. All these factors vary from crop to crop. In view of the above it is imperative for increasing agricultural production that scarce water resources should have efficient management. It is necessary to evolve an innovative approach for water distribution and management. This paper presents an integrated DSS model for a Micro-Watershed Management System (MWMS) for generating alternative water allocation and agricultural production scenarios for a semi-arid region. The model is tested with data from the Radharamanpur micro-watershed (364 Ha. area) in the Bankura district of West Bengal state in India.     

夜盘交易对我国农产品期货市场影响的实证研究

随着我国农产品期货与国际市场的联动性进一步加强,为防止相关期货产品的隔夜风险和价格跳水问题,对部分农产品期货实行夜盘交易制度。为测度夜盘交易制度是否有益于农产品期货市场朝着稳定、理性的方向发展,本文采用了适合刻画金融序列波动性的GARCH族模型,实证检验得出GARCH、GARCH-M和EGARCH模型能够高度拟合农产品期货的价格序列并显著衡量夜盘交易对于我国农产品期货市场的影响。研究结论如下:第一、基于GRACH模型实证结果,夜盘交易制度变量的回归结果显著,该制度能减轻农产品期货的价格波动,且其影响是显著的;第二、EGARCH模型的回归结果同样显著,分别对比不同样本期的EGARCH模型实证结果可以得到,夜盘交易的开放减少了农产品期货市场的非对称性,使得市场趋向于理性的方向发展。     

考虑疫情风险与双重时效性的生鲜品供应中断库存控制策略研究

为解决重大疫情引发的供应中断导致生鲜品库存水平振荡,在市场需求随机变化的情形下,建立一个由供应商、配送中心和零售商组成的三级生鲜供应链库存系统,考虑由疫情引起的三种风险情景,引入系统动力学模型对零售商动态库存系统运营进行仿真分析。研究发现：受疫情风险传导系数和变质率两个序参量影响,供应链库存呈现振荡趋势;通过确定不同供应中断时长下的疫情风险情景提出优化保鲜投入策略、安全库存策略、以及共享库存联合提前转运策略有效降低零售端库存水平振荡并使其呈现渐稳趋势,实现产品在交付过程中的双重时效性,达到供需匹配,缓解疫情风险带来的影响,为相关零售企业提供决策支持。     

基于支持向量机的辽宁省粮食产量预测

随着中国经济的不断发展,城市化进程不断推进,总人口逐年增加;农村人口逐年减少,粮食的需求量逐年增加,某些贫困地区已经出现粮食短缺的状况.本文选取了1986年-2016年辽宁省年粮食总产量、有效灌溉面积、农业化肥施用量、农业机械总动力、播种面积以及受灾面积等相关数据.利用支持向量机回归、线性回归,随机森林三种方法,对辽宁省粮食产量进行了预测,并比较了三种方法预测的精准度.     

Fuzzy goal programming for inventory management: A bacterial foraging approach

An efficient inventory planning approach in today’s global trading regime is necessary not only for increasing the profit margin, but also to maintain system flexibility for achieving higher customer satisfaction. Such an approach should hence be comprised of a prudent inventory policy and clear satisfaction of stakeholder’s goals. Relative significance given to various objectives in a supply chain network varies with product as well as time. In this paper, a model is proposed to fill this void for a single product inventory control of a supply chain consisting of three echelons. A generic modification proposed to the membership functions of the fuzzy goal-programming approach is used to mathematically map the aspiration levels of the decision maker. The bacterial foraging algorithm has been modified with enhancement of the algorithms’ capability to map integer solution spaces and utilised to solve resulting fuzzy multi-objective function. An illustrative example comprehensively covers various decision scenarios and highlights the underlying managerial insights.     

IMPACTS OF WATER SUPPLY UNCERTAINTY AND STORAGE ON EFFICIENT IRRIGATION TECHNOLOGY ADOPTION

In the framework of a stochastic dynamic programming model, the paper investigates the impact of water supply uncertainty and storage at farm level on adoption of efficient irrigation technologies under a flexible water price regime. We find that even a flexible water pricing cannot guarantee higher adoption of efficient irrigation technology in all cases. Results of the paper indicate that if a farmer invests in water storage capacity, then the value of efficient usage of water increases, and the rate of adoption of efficient irrigation technology will be higher. It establishes a complementarity relationship between investments in storage capacity and adoption of efficient irrigation technology. The relationship becomes stronger with increasing variance in water supply. In a situation without any option to store water at the farm level, we find a negative relationship between investment in efficient irrigation technology and water variability. However, numerical analysis results suggest that a risk averse farmer may invest more in efficient irrigation only if the variance in water supply is very high.     

GLOBAL WARMING,IMPACT ON AGRICULTURE AND ADAPTATION STRATEGY

Abstract Sensitivity of the Southeastern US agriculture sector to temperature increases will be based largely on accompanying changes in precipitation, extent of the warming, and relative impact on competing crops grown in the area. The impact of climate change in 10 Southeastern US counties was investigated under three different climate scenarios for two different reference years (2030 and 2090). Seven major crops grown in the area were selected to study the impact on crop yield, irrigation acreage, and optimal choice of crops in a representative farm in each of the southeastern states. If warming is moderate and also brings a considerable increase in precipitation—as indicated by the Hadley model—then, the effect on yields, water use, and income will be mostly benign. If warming is moderate without increased precipitation and the water for irrigation is available, then the effects on the agriculture sector are still mostly negligible. If warming is not moderate and no increased precipitation materializes, farmers could realize quite dramatic negative consequences for row crop agriculture in the Southeastern United States.     

Analysis of relationship between forward and spot markets in oligopolies under demand and cost uncertainties

In this paper, we consider interaction between spot and forward trading under demand and cost uncertainties, deriving the equilibrium of the multi-player dynamic games. The stochastic programming and worst-case analysis models based on discrete scenarios are developed to analyze the impact of demand uncertainty and risk aversion on oligopoly (forward and spot) markets’ structure in terms of the forwards and spot pricing, traded quantities and production. A real case of the Iberian electricity market is studied to illustrate performance of the models. The numerical experiments show that cost uncertainty impacts on the strategic decisions more than demand uncertainty.     

The impact of forecasting model selection on the value of information sharing in a supply chain

This paper presents a study on the impact of forecasting model selection on the value of information sharing in a supply chain with one capacitated supplier and multiple retailers. Using a computer simulation model, this study examines demand forecasting and inventory replenishment decisions by the retailers, and production decisions by the supplier under different demand patterns and capacity tightness. Analyses of the simulation output indicate that the selection of the forecasting model significantly influences the performance of the supply chain and the value of information sharing. Furthermore, demand patterns faced by retailers and capacity tightness faced by the supplier also significantly influence the value of information sharing. The result also shows that substantial cost savings can be realized through information sharing and thus help to motivate trading partners to share information in the supply chain. The findings can also help supply chain managers select suitable forecasting models to improve supply chain performance.     

Modeling Optimal Allocation of Deficit Irrigation: Application to Crop Production in Saudi Arabia

We develop an integrated dynamic programming—linear programming (LP) model to solve for optimal land exploitation for a given crop. The model applies deficit irrigation in order to increase the irrigated area at the expense of reducing the crop yield per unit area. The dynamic program guarantees that deficit irrigation is considered only when it is economically efficient. Moreover, it provides the best irrigation level for each growth stage of the crop, accounting for the varying impact of water stress overtime. The LP provides the best tradeoff between expanding the irrigated area and decreasing water share per hectare. The model objective is to maximize the total expected crop yield. The model is particularly applicable for regions suffering from irrigation water scarcity, such as Saudi Arabia. The implementation was made for crops in Al-Jouf Region, north of Saudi Arabia     

零售商风险规避条件下基于期权契约的生鲜农产品供应链协调研究

民以食为天,随着生活水平的不断提高,生鲜农产品在消费结构中的重要性越来越突出,本文将期权思想引入生鲜农产品供应链运作当中,针对由一个零售商和一个供应商组成的二级生鲜农产品供应链,结合生鲜农产品的自然属性,考虑在途损耗对产品数量的影响以及保鲜投入对产品新鲜度的影响,运用CVaR模型研究了零售商的风险规避程度对供应链决策的影响以及期权契约协调机制。研究表明,期权机制可实现风险在供需双方之间共担,可解决随机需求下生鲜农产品供应链的协调问题并合理分配整体利润;仅当零售商的风险规避程度较低时系统协调和帕累托改进才能同时达成。     

Mean-risk optimal decision of a steel company under emission control

We propose a mean-risk decision model for a steel company facing emission limits and trading with emission allowances. The model is calibrated using data of a real-life steel company and is subsequently solved for five different scenarios of demand and different levels of risk aversion. It is found that while the limits are never reached, permit trading influences the decision to a great extent, especially given extremely low or extremely high demand, i.e., when large amounts of permits need to be traded. We demonstrate that the risk caused by emission trading may increase not only with an increasing demand but also when the demand is low and a great amount of allowances must be sold.     

基于模糊综合评价模型的赣州市水资源承载力动态评价

水资源的合理利用对区域经济社会发展以及促进人与自然的可持续发展至关重要.通过构建模糊综合评价模型,选取年降水量、人均水资源量、水资源利用率、万元GDP用水量、万元工业增加值用水量、农田灌溉亩均用水量、生态用水等7个指标对赣州市2009-2018年水资源承载力进行动态评价研究,分析近十年该地区水资源承载力演变趋势以及影响该地区水资源承载力的主要因素.结果表明:1)赣州市水资源综合承载力较高,水资源还有进一步开发利用的空间;2)2009-2018年赣州市水资源承载力整体上呈上升趋势,但上升幅度不大,呈现小幅波动状态,其中GDP、工业用水量以及农业用水量对赣州市水资源承载力的具有显著影响;3)赣州市水资源较丰富,但由于时空分配不均,水资源配置体系也不够完善,且供水的基础设施比较薄弱,所以水资源的开发利用程度比较低.该研究结果可为当地水资源的可持续利用提供决策参考和依据.