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Development of an irrigation vulnerability assessment model in agricultural reservoirs utilizing probability theory and reliability analysis

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  • Nam, Won-Ho
  • Choi, Jin-Yong

Abstract

The primary goal of water resource management is to maintain a secure and reliable supply of water that can meet the demands of responsible water resource planning. The development of a sustainable agricultural water management system is necessary to evaluate the capability of the water supply to adapt to changes in environmental conditions in relation to the passage of time. Because each reservoir has specific properties related to its watershed, irrigation district, and changes in inflow, they are essential to improve the current assessment methods. The purpose of this study is to propose an irrigation vulnerability assessment method that considers a probability distribution that uses time-dependent change analyses of the irrigation water requirements by paddy fields and the water supply capacity of agricultural reservoirs. Irrigation vulnerability indices are estimated to evaluate the performance of the water supply on the agricultural reservoir system using a probability theory and reliability analysis as an objective method to evaluate the stability of the water supply. The work presented in this paper addresses the potential impact of environmental changes on water supply and demand, as well as the associated reservoir operation performance, with an emphasis being placed on the probability of the current vulnerability. The environmental impact is particularly marked for irrigated paddy fields that utilize a reservoir agricultural vulnerability evaluation model to classify the relative and quantitative severity of irrigation vulnerabilities. Thus, it is a recommended practice in the development of water supply management strategies to manage the risk of an uncertain future.

Suggested Citation

  • Nam, Won-Ho & Choi, Jin-Yong, 2014. "Development of an irrigation vulnerability assessment model in agricultural reservoirs utilizing probability theory and reliability analysis," Agricultural Water Management, Elsevier, vol. 142(C), pages 115-126.
    • Handle: RePEc:eee:agiwat:v:142:y:2014:i:c:p:115-126
    DOI: 10.1016/j.agwat.2014.05.009
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    References listed on IDEAS

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    1. Suresh, K. R. & Mujumdar, P. P., 2004. "A fuzzy risk approach for performance evaluation of an irrigation reservoir system," Agricultural Water Management, Elsevier, vol. 69(3), pages 159-177, October.
    2. Paydar, Z. & Qureshi, M.E., 2012. "Irrigation water management in uncertain conditions—Application of Modern Portfolio Theory," Agricultural Water Management, Elsevier, vol. 115(C), pages 47-54.
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    4. Baek, C.W. & Coles, N.A., 2013. "An artificial catchment rainfall-runoff collecting system: Design efficiency and reliability potential considering climate change in Western Australia," Agricultural Water Management, Elsevier, vol. 121(C), pages 124-134.
    5. Wu, Yiping & Chen, Ji, 2013. "Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: A case study of the Xinfengjiang reservoir in southern China," Agricultural Water Management, Elsevier, vol. 116(C), pages 110-121.
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    Cited by:

    1. Nam, Won-Ho & Hong, Eun-Mi & Choi, Jin-Yong, 2015. "Has climate change already affected the spatial distribution and temporal trends of reference evapotranspiration in South Korea?," Agricultural Water Management, Elsevier, vol. 150(C), pages 129-138.
    2. Nam, Won-Ho & Hayes, Michael J. & Svoboda, Mark D. & Tadesse, Tsegaye & Wilhite, Donald A., 2015. "Drought hazard assessment in the context of climate change for South Korea," Agricultural Water Management, Elsevier, vol. 160(C), pages 106-117.
    3. Nam, Won-Ho & Choi, Jin-Yong & Hong, Eun-Mi, 2015. "Irrigation vulnerability assessment on agricultural water supply risk for adaptive management of climate change in South Korea," Agricultural Water Management, Elsevier, vol. 152(C), pages 173-187.
    4. Ji-Wan Lee & Chung-Gil Jung & Jee-Hun Chung & Seong-Joon Kim, 2019. "The relationship among meteorological, agricultural, and in situ news-generated big data on droughts," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 765-781, September.

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