Irrigation Decision Support System Research Articles

A decision support system for managing irrigation in agriculture

In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.

Decision Support System for Runoff Water Harvesting and Irrigation

Decision Support System for Runoff Water Harvesting and Irrigation

A Fuzzy Decision Support System for irrigation and water conservation in agriculture

Since agriculture is the major water consumer, web services have been developed to provide the farmers with considerate irrigation suggestions. This study improves an existing irrigation web service, based on the IRRINET model, by describing a protocol for the field implementation of a fully automated irrigation system. We demonstrate a Fuzzy Decision Support System to improve the irrigation, given the information on the crop and site characteristics. It combines a predictive model of soil moisture and an inference system computing the most appropriate irrigation action to keep this above a prescribed “safe” level. Three crops were used for testing the system: corn, kiwi, and potato. This Fuzzy Decision Support System (FDSS) favourably compared with an existing agricultural model and data-base (IRRINET). The sensitivity of the FDSS was tested with random rainfall and also in this extended case the water saving was confirmed.

Drip vs. surface irrigation: A comparison focussing on water saving and economic returns using multicriteria analysis applied to cotton

This study explores the use of drip and surface irrigation decision support systems to select among furrow, border and drip irrigation systems for cotton, considering water saving and economic priorities. Data refers to farm field observations in Northeast of Syria. Simulation of drip irrigation was performed with MIRRIG model for various alternatives: double and single row per lateral, emitter spacing of 0.5 and 0.7 m, six alternative pipe layouts and five self-compensating and non-compensating emitters. Furrow and border irrigation alternatives were designed and ranked with the SADREG model, considering lasered and non-lasered land levelling, field lengths of 50–200 m and various inflow discharges. A multicriteria analysis approach was used to analyse and compare the alternatives based upon economic and water saving criteria. Results for surface irrigation indicate a slight advantage for long non-lasered graded furrows; non-lasered alternatives were selected due to economic considerations. For drip irrigation, the best ranking is for systems having lower costs, mainly with double rows per lateral and larger emitter spacing. Comparing surface and drip irrigation systems, despite low cost, drip alternatives may lead to 28–35% water saving relative to improved graded furrows, and increase water productivity from 0.43 kg m−3 to 0.61 kg m−3, surface irrigation provides higher farm returns. Drip irrigation is selected only when high priority is assigned to water saving. Deficit irrigation does not change this pattern of results. Apparently, adopting drip irrigation requires appropriate economic incentives to farmers, changes in the structure of production costs and increased value of production.

Enorasis

Under the influence of the Water Framework Directive and the EU Common Agricultural Policy, and considering the fact that agriculture is globally the largest consumer of water, the efficient and sustainable management of irrigation water has become an issue of foremost priority in the EU environmental agenda. In this context this study presents the ENORASIS Platform, which offers an intelligent Decision Support System (ENORASIS Service Platform and Components) for sustainable irrigation and water management based upon advanced, state of the art technologies, methodologies and models from various scientific fields. Real life pilot cases were deployed in different climate regimes and with different crop types in order to prove and demonstrate the effectiveness and the benefits of the proposed platform.

Design and Implementation of an Irrigation Decision Support System for Cotton in Xinjiang, China

Design and Implementation of an Irrigation Decision Support System for Cotton in Xinjiang, China

Decision Support System for Irrigation based on WebGIS in Arid area

Decision Support System for Irrigation based on WebGIS in Arid area

SOA-based precision irrigation decision support system

At present, irrigation decision-making systems applied to the field of agriculture were mostly aimed at a given area and specific crops. It was difficult to be applied in different areas and different crops. In this paper, a precision irrigation decision-making system has done something to solve this problem. The paper, on the one hand, has synthesized multi-areas and multi-crops in one decision; on the other hand, the key was that it used an advanced design idea, which quickly builds a system by using SOA architecture and fully meets different needs of users based on the maximum reuse of services. The paper arranges services in BPM. First of all, user programmed areas, crop types and the water supply. Secondly, the system selects optimum services from the BPM based on different inputs, and then quickly builds a suitable model. Moreover, it gave precise guidance for crop irrigation processes. The precision irrigation decision support system provides an on-demand decision-making model for agricultural production. Applied results show that, through the test on Xiao Tangshan winter wheat, Da Xing vegetables and rice in central China, the system can quickly build a decision-making model to meet the needs of irrigation for different users. In addition, it shows a good reflection and wide use.

Pilot study for irrigation modelling of a pear plantation

Our investigation was carried out in the area of Fruit growing Research and Consultant non-profit company, at Újfehértó. The pear requires large water quantity, but this pear plantation hasn’t irrigation system not yet. This study reviews the drainage conditions of the area based on digital elevation model, and examined the canopy cover of pear trees by evaluating of the hyperspectral image. Our aims were to determine the exact watershed based irrigation modelling and determining of the canopy% of the pear orchard to facilitate a precision irrigation decision support system.

EVALUATION OF THE ´FERTIGATION MODEL´, A DECISION SUPPORT SYSTEM FOR WATER AND NUTRIENT SUPPLY FOR SOIL GROWN GREENHOUSE CROPS

Soil grown greenhouse crops require high fertilisation rates. Combined with the common practice of over-irrigation, leaching of nutrients is a serious problem. In order to reduce the environmental impact, a `fertigation? model was developed as a decision support system for irrigation and fertiliser supply. The applicability in growers practice was evaluated during two years on commercial nurseries, growing chrysanthemum (Dendranthema grandiflorum). The evaluation was performed by comparison of the actual water and irrigation strategy of the growers with the strategy recommended by the model in a specific section within the same greenhouse. At one chrysanthemum grower a lysimeter was installed to measure water and nutrient leaching. The model performed well in general, without any yield or quality decline by using the model. The irrigation and the nitrogen surplus were decreased significantly compared to the growers standard and consequently reduced the environmental impact. The results indicate also that application of this model depends highly on the growers? attitude towards the environmental impact of irrigation and fertilisation at one hand and the avoidance of risks at the other

An integrated decision support system for irrigation and water policy design: DSIRR

The Decision Support System for Irrigation (DSIRR) is a DSS for the economic-environmental assessment of agricultural activity focusing on irrigation, designed to answer both public and private needs. The program simulates the economically driven decision processes of farmers, permitting an accurate description of production and irrigation in terms of technology and agronomics. Distinct farm models can be constructed to describe the relevant production system in the catchment. Short and long term analyses can be conducted, the latter with endogenous investment choices. Solutions are found by applying multicriterial mathematical programming techniques. Farm models run under a graphical interface, which allows the user to quantify, by farm type, the utilization of water, labour and machinery, considering different types of soils, irrigation systems, water-yield functions and seasonality. Data are aggregated at catchment scale. Richness of information produced, flexibility and simplicity of use make DSIRR a useful tool for more sustainable agriculture and the definition of a sound water policy.

A Decision Support System for the Irrigation and Nutrition Management of Tomatoes Cultivated in Low-technology, Plastic-covered Greenhouses

Vegetable production in low-technology (low-tech) plastic-covered greenhouses depends on low investment and cheap production methods that prohibit the adoption of expensive technologies. Nevertheless, advanced technology can be developed for this low-tech situation provided that a personal computer (PC) is available and the software is of low cost and specially designed to function without the need for additional expensive hardware. This will encourage the adoption of computer technology in an industry where computer illiteracy is still high. In the present paper, a decision support system for irrigation and fertilizer management of tomatoes [Lycopersicon esculentum (L.) Mill.] is described. The system is comprised of two modules: 1) an irrigation-fertilization consultation module for the management of water and fertilizer supply and 2) a diagnostic expert system module for the identification and rectification of nutritional disorders. Irrigation requirements are defined on the basis of daily evaporimeter readings. Fertilizer schedules are derived from the literature, but modified on the basis of experience gained during previous cultivations. The urgent need for such a management system is indicated by the relatively low quality of vegetable produce currently grown in low-tech greenhouses and the waste of precious water and fertilizer due to over-application by growers, with concomitant damage to the environment. During tests, irrigation was reduced by as much as 30% in comparison with empirical methods. To enable more widespread assessment and to increase its range of application, the software of this system is offered free of charge for evaluation by interested users.