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     

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.     

Simulation and optimization for crop water allocation based on crop water production functions and climate factor under uncertainty

In this paper, the uncertainty methods of interval and functional interval are introduced in the research of the uncertainty of crop water production function itself and optimal allocation of water resources in the irrigation area. The crop water production functions in the whole growth period under uncertainty and the optimal allocation of water resources model in the irrigation area under uncertainty are established, and the meteorological factor is considered in the model. It can promote the practical application of the uncertain methods, reflect the complexity and uncertainty of the actual situation, and provide more reliable scientific basis for using water resources economically, fully improving irrigation efficiency, and keeping the sustainable development of the irrigated area. This approach has important value on theoretical and practical for the optimal irrigation schedule, and has very broad prospects for research and development to other related agriculture water management.     

DEVELOPMENT OF AN OPTIMAL WATER ALLOCATION DECISION TOOL FOR THE MAJOR CROPS DURING THE WATER DEFICIT PERIOD IN THE SOUTHEAST UNITED STATES

ABSTRACT. We developed a dynamic economic model to optimize irrigation water allocations during water deficit periods for three major crops grown in the humid southeastern United States. Analysis involved the use of crop simulation models to capture (a) the yield water relationship and (b) soil moisture dynamics from one week to another week. A hy‐drological model was used to find the water supply; combinations of hydrological and simulation models were used to find the optimal water allocation during each week in corn, cotton and peanuts. Results indicated that farmers should irrigate the most valuable crop first (peanuts) before applying water to other crops (corn and cotton). Results also showed that, because of restriction on total water supply, an increase in crop acreage did not increase the net revenue of the farm in a proportionate amount. Results should provide guidelines to water managers, engineers, policy makers, and farmers regarding an optimal amount of water allocation that will maximize net returns when water shortage is a serious concern.     

USING A SYSTEM DYNAMICS APPROACH TO MODEL SUSTAINABILITY INDICATORS FOR IRRIGATION SYSTEMS IN AUSTRALIA

ABSTRACT. An indicator defined as a function of the total water diversion through the Coleambally canal and the potential irrigation demand is selected to represent the sustainability of the irrigation water system in the Coleambally irrigation area, Australia. A simulation procedure using a system dynamics approach was developed to evaluate the indicator. The procedure includes water diversion assessment, potential crop water demand and total gross margin. Three cases of water supply options (surface water, ground water pumping and water trading), two cases of changes in the total agricultural area and three cropping pattern scenarios were simulated to better understand their impact on sustainability. The simulated results indicate that increasing the agricultural area reduces the sustainability of the irrigation system because the demand of water increased despite increase in the gross margin. The scenarios show that imposed water trading and ground water pumping would considerably increase the supply system having a positive impact on the sustainability. The paper concludes that a multi‐objective sustainability indicator taking account of economic and environmental issues could be more useful.     

MODELING CLIMATE CHANGE AND THE EFFECT ON THE NORWEGIAN SALMON FARMING INDUSTRY

Abstract Global warming is expected to affect the ecosystem in the Northeast Atlantic, and substantial changes will also affect the aquaculture industry. Farming of salmon and trout is the biggest aquaculture industry in Norway, with an export value of about 3 billion US dollars in 2007. The objective of the paper is to analyze the potential economic effect a general increase in sea temperature can have on the Norwegian salmon aquaculture industry. The assessment of the economic impact of global warming is made possible by estimating a growth function, which explicitly includes sea water temperature. The analysis compares the economic effect of a climate change on fish farming plants in the south and the north of Norway. The scenarios are based on a model with monthly seasonal variation in temperature.     

Optimal cropping patterns under water deficits

A mathematical programming model is proposed for optimal cropping patterns under water deficits in dry regions. Crops may be deliberately under-irrigated in order to increase the total irrigated area and possibly the profit. An operating policy will identify both the total area and the irrigation level allocated to a given selected crop taking into account the possible successors and predecessors of this crop. Both annual and seasonal crops are examined in the same study. The model starts by identifying the optimal operating policy for each grower in the region having a given stock of irrigation water. Then, in order to allocate water efficiently among growers, the model determines the global optimal cropping plan of the entire region. To solve efficiently the problem, a decomposition algorithm is developed. Also some useful economic interpretations are given.     

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.     

多元统计在海南农业区域经济分析中的应用

利用多元统计中的主成分和聚类分析对海南各市县的农业产量进行研究,得出代表海南的传统农业产量区及热带作物产量区,并对上述产量区进行分类.此外,还对各市县农业现状进行对应分析,得出各市县农业产业结构特征和主导产业,结论较为合理.     

A mathematical programming model applied to the study of water markets within the Spanish agricultural sector

Spanish irrigated agriculture uses about 80% of all the nation's available water resources. The need to increase the economic efficiency of current uses of water in the agricultural sector is perceived as the top priority of the country's national water policy. In Spain surface water is centrally allocated among competing users based on allocation criteria dictated by the Water Law. The complete absence of price or market signals is a major obstacle to induce irrigators to use water more efficiently. Water markets within the agricultural sector is a promising, though scarcely analyzed in Spain, solution to increase its economic efficiency. This research is an attempt to evaluate probable water transfers among farmers and irrigation districts as well as water price equilibria resulting from different water market arrangements. Three interconnected mathematical programming models permit the simulation of water use at the farm level and water market arrangements in the Guadalquivir Valley (Spain). Results show that water markets would be highly dependent on the level of transaction costs and on the relative reductions of water allotments due to nonoverlapping drought cycles among water districts.     

A MODEL FOR ESTIMATING PREMIUMS TO REDUCE IRRIGATION ON FARMS

Abstract This paper aims to determine the minimum agri‐environmental premium per hectare that farmers should receive to reduce crop irrigation. To this end, the authors develop a mixed‐integer quadratic model using a new methodology based on traditional positive mathematical programming, which allows the inclusion in the model of crop variants that are not present in the baseline situation of the farms. What is shown is that the results obtained with this new methodology, using the cost average approach of calibration, are the same as those obtained with an empirical method, when there is no change of crop distribution after the changeover from irrigated to nonirrigated farms. The theoretical results are compared with those obtained using the calibration with exogenous elasticities and are illustrated numerically for a representative farm of an area around Spain's Tablas de Daimiel in which the use of groundwater for crop irrigation has led to the ongoing deterioration of wetlands that depend on the same source of water, endangering the region's environmental sustainability.     

Crop planning optimization model: the validation and verification processes

Each optimization problem in the area of natural resources claims for a specific validation and verification (V&V) procedures which, for overwhelming majority of the models, have not been developed so far. In this paper we develop V&V procedures for the crop planning optimization models in agriculture when the randomness of harvests is considered and complex crop rotation restrictions must hold. We list the criteria for developing V&V processes in this particular case, discuss the restrictions given by the data availability and suggest the V&V procedures. To show its relevance, they are applied to recently constructed stochastic programming model aiming to serve as a decision support tool for crop plan optimization in South Moravian farm. We find that the model is verified and valid and if applied in practice—it thus offers a plausible alternative to standard decision making routine on farms which often leads to breaking the crop rotation rules.     

基于小波随机耦合模型的三江平原年降水量预测

近些年来,由于水田面积迅速增加,导致三江平原井灌水稻区地下水位普遍下降,"吊泵"、局部超采现象时有发生.为解决上述问题,以853农场为例,对实测年降水资料进行差分和标准化处理,采用小波理论和随机水文学方法进行耦合分析,建立了年降小波随机耦合模型,精度检验结果表明,模型有效性和可靠性较高.该模型揭示了区域年降水量的时间变化规律,为853农场乃至整个三江平原充分利用天然降水、合理制定水稻灌溉制度以及地下水资源的恢复和可持续利用提供了科学依据.     

可交易的水权安排对农户灌溉用水行为的影响——基于农户行为模型的理论分析

水资源用水总量控制与定额管理相结合的制度已成为我国水法的重要制度.但目前我国用水定额管理工作仅强调了通过用水定额管理并结合价格机制实行超定额累进加价征收水资源费和水费的办法来激励人们节约用水,没有明确界定这些用水定额的产权归属问题及用水定额的可交易性问题.将通过建立农户灌溉用水行为模型,利用边际分析方法分析可交易的农业用水定额对农户行为的影响.分析表明,当水权可交易时,水价政策与水市场的存在将激励农户节约用水,减少灌溉用水量.农户将通过采用灌溉效率更高的灌溉技术来节约单位面积的灌溉用水量或通过改变种植面积或种植结构的方式来节约总的灌溉用水量,而种植面积或种植结构的变化将进一步促进农地流转市场的发展.但水权交易成本的增加可能削弱出售水权农户的节水积极性并影响农户参与水市场的积极性从而影响水市场的形成与发展.     

MANAGING THE CLIMATE RENT: HOW CAN REGULATORS IMPLEMENT INTERTEMPORALLY EFFICIENT MITIGATION POLICIES?

This paper provides a formal framework to analyze informational and commitment requirements of several intertemporal price and quantity instruments for mitigating global warming. We ask under what conditions and to what extend the regulator can shift the complex and daunting intertemporal optimization of fossil resource use to markets. Mitigation always generates an intertemporal climate rent which reflects the stock‐dependent damages and emerging scarcities of the atmospheric carbon deposit. In order to calculate and to manage this climate rent appropriately, common policy instruments like Pigouvian taxes or emissions trading presume perfect information about resource demand, extraction costs, reserve sizes, and damages for the entire planning horizon. To reduce these informational requirements we develop an alternative policy approach—a state dependent tax rule—that relies only on current observations of cumulative extraction (or atmospheric carbon concentration). Within a cost–benefit analysis, this instrument is capable to shift the complex intertemporal optimization problem completely to the resource sector when resource owners are homogeneous. Under a cost‐effective carbon budget approach, emissions trading with banking and borrowing can also unburden the regulator from solving the intertemporal social planner optimization problem. Additionally, we discuss which instruments can obtain an optimal allocation even if resource owners employ discount rate mark‐ups (i.e., due to imperfect commitment or insecure property rights). While an emissions trading scheme without banking and borrowing is robust against discount rate mark‐ups, resource taxes have to be modified in order to achieve an optimal allocation.     

CLIMATE CHANGE AND FISHERIES: ASSESSING THE ECONOMIC IMPACT IN ICELAND AND GREENLAND

ABSTRACT. . Climate changes in the 21st century are expected to significantly increase ocean temperatures and modify other oceanographic conditions in the North Atlantic. Marine biological research suggests that the impacts on the commercially most important fish stocks in the Icelandic‐Greenland ecosystem may well be quite substantial. This will obviously lead to a corresponding impact on the economies of these two countries. However, the timing, extent and biological impact of global warming is quite uncertain. As a result the economic impact is similarly uncertain. This paper attempts to provide estimates of the impact of altered fish stocks due to global warming on the Icelandic and Greenland economies. The approach is one of stochastic simulations. This involves essentially three steps. The first is to obtain predictions of the impact of global warming on fish stocks and the associated probability distribution. For this we rely on recent marine biological predictions. The second step is to estimate the role of the fisheries sector in the two economies. This is done with the help of modern econometric techniques based on economic growth theory and historical data. Obviously these estimates are also subject to stochastic errors and uncertainty. The third step is to carry out Monte Carlo simulations on the basis of the above model and the associated uncertainties. The result of the Monte Carlo simulations consists of a set of dynamic paths for GDP over time with an expected value and a probability distribution for each future year. On this basis it is possible to calculate confidence intervals for the most likely path of GDP over time. The results indicate that the fisheries impact of global warming on the Icelandic GDP is more likely to be positive than negative but unlikely to be of significant magnitude compared to historical economic growth rates and fluctuations. The uncertainty of this prediction, however, is large. For Greenland, the impact on fish stocks and the GDP is highly likely to be positive and quite substantial relative to the current GDP. Due to less knowledge of the relationship between the fisheries sector and the Greenland economy, however, the confidence interval of this prediction is even wider than in the case of Iceland.     

Stochastic vs deterministic programming in water management: the value of flexibility

In the paper we develop a two stage scenario-based stochastic programming model for water management in the Indus Basin Irrigation System (IBIS). We present a comparison between the deterministic and scenario-based stochastic programming model. Our model takes stochastic inputs on hydrologic data i.e. inflow and rainfall. We divide the basin into three rainfall zones which overlap on 44 canal commands. Data on crop characteristics are taken on canal command levels. We then use ten-daily and monthly time intervals to analyze the policies. This system has two major reservoirs and a complex network of rivers, canal head works, canals, sub canals and distributaries. All the decisions on hydrologic aspects are governed by irrigation and agricultural development policies. Storage levels are maintained within the minimum and maximum bounds for every time interval according to a power generation policy. The objective function is to maximize the expected revenue from crops production. We discuss the flexibility of two stochastic optimization models with varying time horizon.     

春小麦水分敏感指数与有限水量生育期的最优分配

通过不同的受旱处理，确定了Jensen模型中的春小麦水分敏感指数。介绍了运用生态规划模型实现有限水量生育期最优分配的方法与步骤，并以辽西地区春小麦为例，确定了不同初始含水量和生育期可利用灌溉水量下的最优分配决策。     

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.     

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.