Use of CropSyst as a decision support system for scheduling regulated deficit irrigation in a pear orchard

Prediction of plant water status is necessary for the judicious application of regulated deficit irrigation. CropSyst, a generic crop growth model that is applicable to fruit trees, was used to forecast plant water potential for irrigation management recommendations in a pear orchard. Plant water potential is predicted along with tree transpiration using Ohm’s law analogy. The parameters of the model were adjusted by using field measured data on a lysimeter-grown pear tree. After adjustment, and using the same lysimeter data, a satisfactory agreement was found between simulated and measured tree transpiration, light interception, and stem water potential. Model simulations were also performed for other independent field data. These corresponded to eight different conditions of a deficit-irrigated field experiment in a pear orchard. Each condition differed in soil texture, time of irrigation cut-off, crop load, and tree leaf area. Deficit irrigation was managed first by withholding irrigation until reaching a threshold in midday stem water potential of −1.5 MPa. Subsequently, irrigation was applied at fixed proportions of full irrigation requirements. Simulations with CropSyst were used as decision support system that could work independently of stem water potential measurements. Simulations in all eight sites were satisfactory at providing adequate time without irrigation during the first part of the deficit period. A highly significant relationship (r ²  = 0.71) between predicted and measured stem water potentials was found for a simulation period of 40 days. Simulations for longer periods (i.e. 74 days) decreased the r ² to 0.61, and for this reason after resuming irrigation, slight deviations were found for the average stem water potential in two out of five sites. In conclusion, CropSyst produced relevant information for managing deficit irrigation in simulation periods shorter than 40 days.     

SIMIS: the FAO decision support system for irrigation scheme management

Scheme irrigation management information system (SIMIS) is a decision support system for managing irrigation schemes. It can be used either as a management tool or as a training tool. The data needed for the technical and administrative management of the scheme can be stored, edited and displayed in various forms. They can then be used for helping in water management, calculating irrigation requirements, developing irrigation layouts, scheduling water deliveries, and keeping records of water consumption. The SIMIS approach is based on simple water balance models with capacity constraints. The user can simulate management alternatives, assess the results and try out new alternatives, until a satisfactory solution is found. SIMIS also helps in the administrative aspects of managing irrigation schemes (accounting, calculating water charges, controlling maintenance activities) and in assessing their performance.     

Online decision support for irrigation for farmers

Online decision support for irrigation has been available in Denmark since 1996. This paper describes an Internet implementation of a previous stand-alone PC-program; the Internet version has undergone several modifications and upgrades. The system has a morphological model for crop development based on temperature sums, and a hydrological model for calculating soil water balance. Weather data are supplied automatically from weather databases, precipitation data can be overrode by user inputs. Users can initiate the system with data on fields and crops, and add data on irrigations. Irrigation advice and explanation are provided in tables and graphics. The system had 322 active users in 2004 and 490 in 2005.     

An assessment of project management software as a decision support system for irrigation management in Morocco

The characteristics and potential of project management software as a tool for improved planning and management of on-going irrigation operations are assessed. A commercially available package was tested through use for the simulated planning of the close season maintenance campaign of major pump stations at a large scale irrigation scheme in Morocco. The software was found to be well suited to this planning activity and successfully helped resolve conflicts in terms of time and resources available. Its potential as a tool for sensitivity analysis and for monitoring and control was clearly demonstrated. The exercise had an immediate effect on management decision making and managers concerned have adopted the software for further trials. The approach is recommended as a means to enhance planning, communication and teamwork for suitable irrigation management operations, but will be most effective with the development of supporting databases to enhance the quality of planning data used.     

卷盘式喷灌机选型辅助决策系统的开发

卷盘式喷灌机选型辅助决策系统的研制开发 ,为卷盘式喷灌机田间工程规划中的正确配套选型提供了快捷、准确、高效的方法 ,并能指导卷盘式喷灌机制造者的优化设计 ,以发挥卷盘式喷灌机的最佳工作效益。     

Investment decision model for drip irrigation system

Drip irrigation is becoming popular in India although the decision to shift to drip irrigation from surface irrigation is not backed up by solid economic factors. It is not that the factors do not justify the shift, but that insufficient study has been done to document the conditions under which a change is justified. The investment decision for shifting to drip irrigation will depend upon many factors; including cost of cultivation, productivity, yield gain factor, cost of produce, electricity charges, depth of groundwater and irrigation requirement. These parameters vary from crop to crop, place to place, size of plot, and farmer to farmer. Therefore a sweeping recommendation suitable for all conditions cannot be made. In view of this, a software program has been developed for estimating the threshold economic value of the investment cost of drip irrigation. In addition to the threshold value of investment cost, the software provides information on energy consumption and net return. The software can be used both for annual crops such as sugarcane or seasonal crops such as vegetable rotations (winter–summer). To demonstrate the interdependence of various input parameters, an analysis has been made using local data in this software. The analysis has provided the relationship between the investment cost and the yield gain factor, the returns from the crop, as well as the savings in energy and the size of the prime mover with regard to the size of the farm.     

Management model for decision support when applying low quality water in irrigation

Use of low quality water for irrigation of food crops is an important option to secure crop productivity in dry regions, alleviate water scarcity and recycle nutrients, but it requires assessment of adverse effects on health and environment. In the EU-project “SAFIR¹” a model system was developed that combines irrigation management with risk evaluation, building on research findings from the different research groups in the SAFIR project. The system applies to field scale irrigation management and aims at assisting users in identifying safe modes of irrigation when applying low quality water. The cornerstone in the model system is the deterministic “Plant-Soil-Atmosphere” model DAISY, which simulates crop growth, water and nitrogen dynamics and if required heavy metals and pathogen fate in the soil. The irrigation and fertigation module calculates irrigation and fertigation requirements based on DAISY's water and nitrogen demands. A Water Source Administration module keeps track of water sources available and their water quality, as well as water treatments, storage, and criteria for selection between different sources. At harvest, the soil concentrations of heavy metals and pathogens are evaluated and the risk to consumers and farmers assessed. Crop profits are calculated, considering fixed and variable costs of input and output. The user can run multiple “what-if” scenarios that include access to different water sources (including wastewater), water treatments, irrigation methods and irrigation and fertilization strategies and evaluate model results in terms of crop yield, water use, fertilizer use, heavy metal accumulation, pathogen exposure and expected profit. The management model system can be used for analysis prior to investments or when preparing a strategy for the season.     

I. A decision support system to improve planning and management in large irrigation schemes

This paper describes a decision support system (DSS) that was developed to improve planning and management for the large irrigation schemes in the Alentejo region of Portugal. The system was designed to help in the analysis and evaluation of the crops and crop systems that can potentially be cultivated, together with identification of limitations affecting crop selection and crop yields. It integrates socio-economic and biophysical data at the field level to analyse the performance of an irrigation scheme in terms of the adoption of irrigation by farmers and farmers’ incomes. The final output is given in the form of specific actions and policies for the irrigated areas. The DSS was designed initially to be used in the Alqueva project, a large irrigation scheme that is under construction in Alentejo. Nevertheless, the final framework is generic in nature, being suitable for planning and policy evaluation in other large irrigation schemes.     

Usefulness and limitations of decision support systems for improving irrigation scheme management

SIMIS (the FAO Scheme Irrigation Management Information System) is a decision support system that integrates tools and performance indicators to facilitate the planning and management of irrigation schemes. The authors used SIMIS to compute performance indicators in an irrigation scheme in Southern Spain that were used to identify distribution system constraints affecting the flexibility of water deliveries and to identify scheme sectors where deliveries could not meet the predicted crop water demands. Applying SIMIS, the authors and the irrigation scheme manager evaluated measures to overcome the constraints for future irrigation campaigns, and to refine the water orders made every 2 weeks to the basin authority. On the other hand, SIMIS presented limitations to the evaluation of on-demand delivery schedules. To overcome these limitations, an external model, developed outside SIMIS, showed that the current distribution network of the scheme has the capacity to deliver water on-demand only if a slight water deficit is accepted during the peak demand period. The analysis showed that by relaxing the stringency of the quality of operation of on-demand systems, rotation systems may be transformed into on-demand systems without changing their structures. This analysis could also be done using Clément's hypothesis, but doing so resulted in overestimates of the quality of operation and of the relative irrigation supply.     

Irrigation scheduling and irrigation systems: optimising irrigation efficiency for container ornamental shrubs

Water use and plant growth and quality were compared across different nursery stock beds, different methods of applying irrigation, and different methods of scheduling irrigation. With overhead irrigation, scheduling of irrigation according to plant demand, along with an irrigation system designed to maximise irrigation uniformity, resulted in substantial water savings, without reducing plant quality. This was the case in both wet and dry years. In the dry year, plant quality was particularly good when grown on a sub-irrigated sand bed; this system also used less water than any of the overhead irrigation systems. Two different systems were effective in scheduling overhead irrigation, one based on the volumetric moisture in the growing substrate, and the other based on plant evapotranspiration. The latter was determined with a small sensor with wet and dry artificial “leaves”, the output of which correlated with that obtained following the Penman–Monteith method based on a full set of meteorological data.     

Drip irrigation scheduling for tomatoes in unheated greenhouses

During the last two decades, energy-saving solar greenhouses without heating systems, about 150-800 m² (width: 5-10 m, length: 30-80 m) in size, have been widely used in the North of China for vegetable production during cold seasons. The greenhouse is also suitable for use in other countries located in the temperate or warm-temperate zones, especially in the developing countries, because it is inexpensive with a simple structure, and does not need any additional energy for heating in winter. Drip irrigation has been recognized as a sensible method of supplying water inside the greenhouses, and a simple method for drip irrigation scheduling at low cost is urgently required. Using the water-balance method, the authors studied the water consumption of tomato (Lycopersicon esculentum Mill.) and the relationship between evapotranspiration and water surface evaporation measured with 20 cm pan. Research results show that there is no significant water flux at 0.75 m depth when soil water potential is kept higher than -20 kPa at 15 cm depth, and around -20 kPa at 60 cm depth. The accumulative value of evapotranspiration is approximately equal to the accumulative value of water surface evaporation measured using 20 cm pan. Further analysis found that 20 cm pan can be used to determine the water requirement of tomato drip irrigation scheduling in this type of greenhouse.     

MIRRIG: A decision support system for design and evaluation of microirrigation systems

The decision support system (DSS) MIRRIG has been developed to support the design of microirrigation systems and to advise farmers as a result of field evaluations. It is written in Visual Basic 6.0, runs in a Windows environment, and uses a database with information on emitters and pipes available in the market, as well as on crops, soils and the systems under design. MIRRIG is composed by design and simulation models and a multicriteria analysis model that ranks alternative design solutions based upon an integration of technical, economic and environmental criteria. User friendly windows are adopted for handling the databases and to manage the sub-models. The model allows creating and comparing a set of design alternatives relative to the pipe system and the emitters, either drip or microsprinkling emitters. For each alternative, the pipe system is sized and the irrigation system is simulated to produce performance, environmental and economic indicators. These include uniformity of water application, potential for contamination with agrochemicals due to water percolation, and installation and operation costs. Those indicators are used as attributes of the selected criteria. All alternatives are then compared and ranked through multicriteria analysis where the weights giving the relative importance of the adopted criteria are defined by the user. These procedures allow selecting the best design alternative and solving the complexities involved in the design of microirrigation systems. The model is available from the website www://ceer.isa.utl.pt/cms or by contacting cpedras@ualg.pt.     

Drip Planner Chart: a simple irrigation scheduling tool for smallholder drip farmers

Drip irrigation is widely recognized as potentially one of the most efficient irrigation methods. However, this efficiency is often not achieved because systems are not always well designed or maintained and many farmers lack the tools to assess the crop water requirements and to monitor the soil moisture conditions in the field. There is a vast amount of literature on irrigation scheduling but little literature takes scientific information the next step by preparing practical guidelines for smallholder farmers. There is a large and widening gap between the state of the art irrigation scheduling tools and current on-farm irrigation practices. Most farmers find current irrigation scheduling tools overwhelming and lack the means and skills to install and operate them. It is suggested that farmers need simple, cheap and more comprehensive support tools to achieve improved irrigation management at the farm level. Wageningen University and Research Centre (WUR) developed the Drip Planner Chart (DPC) to provide smallholder farmers with a simple tool to schedule drip irrigation to the crops?? needs. DPC is a manual disk calculator to calculate daily irrigation requirement. Farmers?? feedback was the basis for developing the DPC. Using DPC over a three-year period in Spain resulted in a 14 % water saving and improved irrigation timing. Trials at smallholder farmer fields in Nepal and Zambia showed DPC advice is more adapted to the changing demands of the crop over the different growth stages and responds to the farmer??s quest for practical drip scheduling advice. This paper presents the Drip Planner Chart and the scientific validation of the accuracy of the DPC. Experiments on farmers?? fields show water saving in Nepal and improved yield in Zambia. In both countries an improved scheduling over the growing seasons was found using DPC.     

Evaluating canopy temperature-based indices for irrigation scheduling

Summary Since the development of commercial versions of infrared sensors, they have been increasingly used to determine canopy temperature and schedule irrigations. However, some shortcomings of the technique have been identified, among them the sensitivity of canopy temperature measurements to weather fluctuations. Based on field and computer simulated data, an analysis of the suitability of crop water stress indices (CWSI's) developed from canopy temperature under variable weather conditions was done. Important day to day fluctuations of CWSI values determined using an empirical baseline (empirical CWSI) appeared common for nonstressed crops, particularly under low vapor pressure deficit conditions. These fluctuations generate uncertainty in the use of this empirical index to determine needs for irrigation. The use of an improved index (theoretical CWSI) requiring measurements of net radiation, soil heat flux and wind speed, and estimates of aerodynamic and canopy resistances reduced but did not eliminate these fluctuations. Results using a simulation model showed that the empirical CWSI provided late indication of irrigation needs, after some water stress has developed, which may limit its application for crops sensitive to water stress. These simulations also indicated that the theoretical CWSI was able to track the development of water stress and provide reasonable indication of irrigation needs. However, this result may not be fully realized in field applications where the determination of CWSI may be affected by various sources of variability which are not accounted for by the model.     

A simple irrigation scheduling approach for pecans

Pecans are a major crop in New Mexico's Lower Rio Grande Valley (LRGV). It is estimated that New Mexico is responsible for about 21% of the world's pecan production (Lillywhite et al., 2007). Currently, approximately 12,000 ha of pecan orchards at various stages of growth consume 45% of the area's irrigation water. Pecan evapotranspiration (ET) varies with age, canopy cover, soil type, crop density and method of water management. Intense competition for the LRGV's limited water supply has created a serious need for better water management through improved irrigation scheduling. Annual pecan ET ranges from as low as 500 mm to as high as 1400 mm. Diversity of the pecan crop coefficient (K_c) and ET makes the task of irrigation scheduling for this crop very complicated. Using remote sensing technology and field ET measurements, a simple relationship was developed to relate crop coefficient and ET to canopy cover. This relationship is then used in combination with climate data to calculate daily and weekly water requirements for each orchard. The difference between annual ET values estimated from canopy cover and values measured with an eddy covariance flux tower ranged from 2 to 5%. The average ratio of estimated monthly ET values over measured ET values was 1.03 with the standard error of the estimate ranging from 10 to 20 mm/month. This methodology provides a simple tool that farmers can use to schedule irrigation of pecan orchards. Even though the methodology was developed for irrigation scheduling in the LRGV, it can be used in other locations by transferring the reference crop coefficients using K_c-GDD relationships.     

灌区水资源优化配置决策支持系统

本文利用系统优化理论,将灌区整体水资源的数量作为主要约束条件,构造整个灌区作物总产量最大的目标函数,运用线性规划思想进行求解,优化整个灌区水资源配置.以windows操作系统为开发环境,选用Vb6.0编程语言,Access数据库管理数据,开发整个灌溉区水资源优化配置决策支持系统,实现整个灌区水资源优化配置的自动化及可视化.     

Accounting for slow drainage and hysteresis in irrigation scheduling

Summary Soils continue to drain for several days following irrigation. Water budgeting predictions can be improved by accounting for this, provided hysteresis is recognized in the field capacity condition. Uncertainty in this condition was evident in experiments comparing predicted soil water depletions with neutron probe measurements. Comparisons were made for potato, lettuce and calabrese crops, irrigated by hose-reel machine. Best agreement between measurements and predictions was obtained when excess water storage above a lower field capacity condition was allowed for; corresponding to minimum root mean square errors of 3.2 mm–6.2 mm. These were comparable to the practical limits of uncertainty associated with field depletion measurements.     

PCYield: model-based decision support for soybean production

Soybean farmers make decisions based on diverse information. However, one tool not widely utilized is crop simulation. Perceived barriers are burdensome inputs, user unfriendliness, and hard-to-interpret results. Our approach combines the CROPGRO-Soybean model with a window-based, user interface addressing these problems. The resulting, simple-to-use program, PCYield, contains features of more complex systems including (1) field-specific data management, (2) Internet access to real-time weather data, (3) production risk indicators, and (4) graphical outputs. A unique aspect of this project was the participation of a private weather data corporation and, through them, a national chain of agricultural input and service providers. The paper describes the project history, developmental policy issues, technical problems, market testing and subsequent software privatization. Positive producer reactions have included requests for more advanced features. This suggests that grower acceptance of complex models can be gained over time by beginning with simple aids and enhancing them with user-requested upgrades.     

Higher performance through combined improvements in irrigation methods and scheduling: a discussion

Prior to the discussion on approaches to combine irrigation scheduling and water application practices, several farm irrigation performance indicators are defined and analysed. These indicators concern the uniformity of water distribution along an irrigated field and the efficiency of on-farm water application. Then, the analysis focus is on three main irrigation systems: surface, sprinkler and microirrigation. For each of these systems, the analysis concerns the main characteristics and constraints of the systems, more relevant aspects influencing irrigation performances, and approaches which could lead to a more appropriate coupling of irrigation scheduling and water application methods. Conclusions point out on the need for combined improvements in irrigation scheduling and methods, for expanding field evaluation of irrigation in farmers fields, for improved design of on-farm systems, and for quality control of irrigation equipments and design.     

Genetic algorithms for the sequential irrigation scheduling problem

A sequential irrigation scheduling problem is the problem of preparing a schedule to sequentially service a set of water users. This problem has an analogy with the classical single machine earliness/tardiness scheduling problem in operations research. In previously published work, integer program and heuristics were used to solve sequential irrigation scheduling problems; however, such scheduling problems belong to a class of combinatorial optimization problems known to be computationally demanding (NP-hard). This is widely reported in operations research. Hence, integer program can only be used to solve relatively small problems usually in a research environment where considerable computational resources and time can be allocated to solve a single schedule. For practical applications, metaheuristics such as genetic algorithms (GA), simulated annealing, or tabu search methods need to be used. These need to be formulated carefully and tested thoroughly. The current research is to explore the potential of GA to solve the sequential irrigation scheduling problems. Four GA models are presented that model four different sequential irrigation scenarios. The GA models are tested extensively for a range of problem sizes, and the solution quality is compared against solutions from integer programs and heuristics. The GA is applied to the practical engineering problem of scheduling water scheduling to 94 water users.