• Korean Journal of Hydrosciences
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• v.2
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• pp.99-113
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• 1991

Integrated irrigation management system (IIMS) that is incorporated with a microcomputer-based decision support system (DSS) has been developed and applied to paddy rice irrigation systems management. The system hardwares consist of field data acquisition units, data transmission units, central data processing units, and printing and displaying units. Ridld data to be collected include incremental rainfall, streamflow and reservoir water levels, and water levels at several irrigation canal sections within an irrigation sidtricts. The softwares are to process field data, real-time forecasting, irrigation control data, and decision variables from data-base and simulation model subsystems. And the user-interface subsystems are incorporated to present the water system operators and managers the results from data and model sugsystems. User-friendly menu with animated graphic modules are adopted to help understand irrigation controls for the district. This paper issues the overal descriptions of DSS as applied to Anjuk irrigation district. The details of major model components for the irrigation controls are presented along with real-time data collection systems. The potentials of DSS have been appraised very practical and promising for better irrigation system operation and management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2925-2948
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• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.47-58
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• 1998

This study is to try grading size and economic values in irrigation reservoirs for the purpose to maintenance management valuation technique. This use main irrigation reservoirs which are managed by Farmland Improvement Associations(FIA) to estimate grading of irrigation reservoirs for maintenance and management. In order to make efficient management on irrigation reservoirs, this study will be a basic data at a decision ranking of investment which are followed by conservation and maintenance management.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.161-170
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• 2008

Interest is growing in applying simulation models for the South Texas conditions, to better assess crop water use and production with different crop management practices. The Environmental Policy Integrated Climate (EPIC) model was used to evaluate its application as a decision support tool for irrigation management of com (Zea mays L.) in South Texas of the U.S. We measured actual crop evapotranspiration (ETc) using a weighing lysimeter, soil moisture using a neutron probe, and grain yield by field sampling. The model was then validated using the measured data. Simulated ETc using the Hargreaves-Samani equation was in agreement with the lysimeter measured ETc. Simulated soil moisture generally matched with the measured soil moisture. The EPIC model simulated the variability in grain yield with different irrigation regimes with $r^2$value of 0.69 and root mean square error of $0.5\;ton\;ha^{-1}$. Simulation results with farm data demonstrate that EPIC can be used as a decision support tool for com under irrigated conditions in South Texas. EPIC appears to be effective in making long term and pre-season decisions for irrigation management of crops, while reference ET and phenologically based crop coefficients can be used for inseason irrigation management.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.3
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• pp.67-78
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• 1990

A decision support system, Daily Irrigation Network Operation Simulation model (DINOPS) was developed that can adequately describe the physical behavior of an irrigation system. The model is to depict the physical features of complex water allocation schemes of the irrigation system and to simulate the response of the system to different irrigation schemes. The model was validated on the Banweol irrigation district by comparing the simulated canal discharges and paddy water levels with the field data. The operation of the DINOPS model was demonstrated on the irrigation district where several irrigation management practices were evaluated with computing irrigation efficiencies and rainfall effectiveness respectively. The model sensitivity with respect to heights of bund and block diversion rates were analyzed and discussed.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.67-76
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• 2003

The principal operation rule of irrigation reservoir is to accelerate the water use and supply water actively when water is sufficient, and to restrict water use and supply water deficiently in order not to stop the irrigation activity when water is scarce. In drought seasons. water should be saved in order to keep the reservoir not to be dried up during the irrigation season. It is important to know how much water should be saved, depending on the rice-growing season and water storage volume. For the drought control of irrigation reservoirs. the rotational irrigation scheduling in paddy with the operation rule curve developed in this study could be utilized as a software program to install TM/TC system for irrigation water supply by automation facilities.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.45-53
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• 2013

Efficient water operation and management of an irrigation system plays an important element in the sustainability of irrigated agriculture. An agricultural water is delivered in many open canals of irrigation delivery system by reservoirs. The poor water distribution and management in an irrigation system is a major factor leading to low water efficiency. It is necessary to compare the estimated irrigation demands with the actual water supplies for decision making to maintain the water supply according to demand strategy. Smarter water management, new technologies and improvement of water management system, is essential to solve the problem of water efficiency and availability. In this paper, the irrigation efficiencies according to water delivery performance indicator were measured with automatic water gauge at irrigation canals, and calculated from spatial and temporal distribution of water supply for the lack of planning in water delivery. The analysis of results are obtain an insight into possible improvement methods to develop canal water management policies that enable irrigation planners to optimally manage scarce available water resources.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.39-44
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• 2012

Water supply capacity and operational capability in agricultural reservoirs are expressed differently in the limited storage due to seasonal and local variation of precipitation. Since agricultural water supply and demand basically assumes the uncertainty of hydrological phenomena, it is necessary to improve probabilistic approach for potential risk assessment of water supply capacity in reservoir for enhanced operational storage management. Here, it was introduced the irrigation vulnerability characteristic curves to represent the water supply capacity corresponding to probability distribution of the water demand from the paddy field and water supply in agricultural reservoir. Irrigation vulnerability probability was formulated using reliability analysis method based on water supply and demand probability distribution. The lower duration of irrigation vulnerability probability defined as the time period requiring intensive water management, and it will be considered to assessment tools as a risk mitigated water supply planning in decision making with a limited reservoir storage.

• KCID journal
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• v.12 no.1
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• pp.78-83
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• 2005

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.198-198
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• 2017

Climate change causes unpredictable and erratic climatic patterns which affects crop production in agriculture and threatens public health. To cope with the challenges of climate change, sustainable and sound growth environment for crop production should be secured. Recent attention has been given to the development of smart irrigation system using sensors and wireless network as a solution to achieve water conservation as well as improvement in crop yield and quality with less water and labor. This study developed the smart irrigation technique for farmlands by monitoring the soil moisture contents and real-time climate condition for decision-making support. Central to this design is micro-controller which monitors the farm condition and controls the distribution of water on the farm. In addition, a series of laboratory studies were conducted to determine the optimal irrigation pattern, one time versus plug time. This smart technique allows farmers to reduce water use, improve the efficiency of irrigation systems, produce more yields and better quality of crops, reduce fertilizer and pesticide application, improve crop uniformity, and prevent soil erosion which eventually reduce the nonpoint source pollution discharge into aquatic-environment.