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Evaluation of Automatic Irrigation System for Rice Cultivation and Sustainable Agriculture Water Management

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  • Jaenam Lee

    (Rural Research Institute, Korea Rural Community Corporation, Naju 58321, Korea)

Abstract

The water-resource policy of South Korea has been changing from that of securing water to that of saving water through sustainable water management. Moreover, population aging in rural areas is leading to agricultural water-management problems. In this study, an automatic irrigation system for rice crops was investigated and compared with conventional irrigation, and changes in water productivity and required labor power were quantified. The effect of the proposed system on economic feasibility was verified on farmland by monitoring irrigation water and rice yields for three years. Under the automatic irrigation system, on-site water productivity improved by an average of 12.7% and the labor power required for paddy water management decreased by an average of 21.8% compared to the conventional irrigation system. The internal rate of return was 8.6% higher than the discount rate of 4.5%. The net present value was 406,411 KRW, and the benefit-cost ratio was 1.23. The results can serve as a reference for the on-site introduction of irrigation water-supply automation for sustainable water management and are expected to benefit farmers in saving water and reducing labor demands through sustainable agricultural activities.

Suggested Citation

  • Jaenam Lee, 2022. "Evaluation of Automatic Irrigation System for Rice Cultivation and Sustainable Agriculture Water Management," Sustainability, MDPI, vol. 14(17), pages 1-12, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:11044-:d:906592
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    2. Emami, Somayeh & Dehghanisanij, Hossein & Hajimirzajan, Amir, 2024. "Agent-based simulation model to evaluate government policies for farmers’ adoption and synergy in improving irrigation systems: A case study of Lake Urmia basin," Agricultural Water Management, Elsevier, vol. 294(C).
    3. Luis Pastor Sánchez-Fernández & Diego Alberto Flores-Carrillo & Luis Alejandro Sánchez-Pérez, 2024. "Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation," Mathematics, MDPI, vol. 12(1), pages 1-33, January.

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